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Download date: 01 Aug 2018
Hemodynamics and maternal characteristics prior to hypertensive disorders of pregnancy
The printing of this thesis was sponsored by:
Department of Obstetrics and Gynecology, AMC, Amsterdam, The Netherlands
BMEYE, Amsterdam, The Netherlands
Hemodynamics and maternal characteristics prior to hypertensive disorders of pregnancy
Thesis, University of Amsterdam, The Netherlands
Copyright© 2010. K.C. Vollebregt, Amsterdam, The Netherlands. All rights reserved.
No parts of this thesis may be reproduced or transmitted in any form or by any means,
without prior permission of the author.
Cover: Kees Boer “Het relatieve belang van spiralen voor de zwangerschap”
Lay-Out: Chris Bor, Medische Fotografie en Illustratie, AMC, Amsterdam,
The Netherlands
Printed by: Buijten & Schipperheijn, Amsterdam, The Netherlands
ISBN: 978-90-9025939-0
Hemodynamics and maternal characteristics prior to hypertensive disorders of pregnancy
ACADEMISCH PROEFSCHRIFT
ter verkrijging van de graad van doctor
aan de Universiteit van Amsterdam
op gezag van de Rector Magnificus
prof. dr. D.C. van den Boom
ten overstaan van een door het college
voor promoties ingestelde commissie,
in het openbaar te verdedigen
in de Agnietenkapel op
vrijdag 4 maart 2011
te 12:00 uur
door
Karlijn Corien VollebregtGeboren te Bussum
Promotiecommissie
Promotor: Prof. dr. J.A.M. van der Post
Co-promotores: Dr. K. Boer
Dr. H. Wolf
Overige leden: Prof. dr. E.T. van Bavel
Dr. J.M. Karemaker
Prof. dr. B.W.J. Mol
Prof. dr. B.J.M. Mulder
Dr. M.E.A. Spaanderman
Prof. dr. E.A.P. Steegers
Faculteit der Geneeskunde
CONTENTS
Chapter 1 General introduction and outline of the thesis 7
Chapter 2 Accuracy of mean arterial pressure and blood pressure measurements in predicting preeclampsia: systematic review and meta-analysis. BMJ 2008;336(7653):1117-20
19
Chapter 3 Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia.Journal of Hypertension 2010;28(1):127-134
53
Chapter 4 The association of three different techniques to measure blood pressure in the first trimester of pregnancy with later preeclampsia.Submitted
69
Chapter 5 Arterial stiffness at 8 0/7-11 0/7 weeks of pregnancy and the association with later preeclampsia.Submitted
85
Chapter 6 Is psychosocial stress in first ongoing pregnancies associated with preeclampsia and gestational hypertension?BJOG 2008;115(5):607-615
99
Chapter 7 Does physical activity in leisure time early in pregnancy reduce the incidence of preeclampsia or gestational hypertension?Acta Obstetricia et Gynecologica Scandinavica 2010;89(2):261-269
117
Chapter 8 Sensitivity of spontaneous baroreflex control of the heart and hemodynamic parameters are not influenced by the menstrual cycle.Hypertension in Pregnancy 2006;25(3):159-167
131
Chapter 9 Summary, conclusion and recommendations for future researchSamenvatting, conclusies en aanbevelingen
143161
Appendices Authors’affiliations 179
Bibliography 183
Dankwoord 185
Curriculum vitae 191
11 Introduction
Chapter 1
9
General Introduction
INTRODUCTION
Preeclampsia and gestational hypertension are major causes of maternal and fetal
morbidity as well as mortality worldwide.1;2 In the Netherlands 8.3% of all pregnancies in
2006 was affected by preeclampsia or gestational hypertension.3 The majority of these
women were pregnant with their first child. During pregnancy or postpartum, women
with hypertensive disorders of pregnancy and their babies are at risk of complications
like elective preterm birth, fetal growth retardation, perinatal death, HELLP syndrome,
eclampsia, renal insufficiency, cerebral bleeding or maternal mortality.4 Additionally
women with previous preeclampsia have an elevated risk for cardiovascular disease in
later life.5;6 Being small for gestational age at birth is associated with future cardiovascular
and metabolic disorders.7
Hypertensive disorders of pregnancy present a large variation in phenotype and severity
of disease. These vary from gestational hypertension with moderate hypertension after
20 weeks of gestation in a previously normotensive woman, to preeclampsia (gestational
hypertension with proteinuria), hemolysis, elevated liver enzymes, low platelets (HELLP)
syndrome to eclampsia.8 Generally the disease is more severe if it occurs early in
pregnancy and if it is combined with physical signs and symptoms that are associated
with preeclampsia.4 At present preeclampsia is unpredictable in onset and progression.
The only effective treatment is termination of pregnancy.4 If preeclampsia starts early in
pregnancy, maternal risks have to be balanced against neonatal risks caused by elective
preterm birth.
Despite extensive research the pathogenesis of preeclampsia remains unclear. A widely
accepted hypothesis is that a disturbed placental function early in pregnancy causes a
systemic inflammatory response characterized by generalized endothelial dysfunction
leading to the maternal syndrome in the second half of pregnancy.9 Inadequate placentation
may be the result of vascular, immunological, genetic or environmental factors.
Prevention of preeclampsia is hardly possible. Based on large meta-analyses there is
evidence that low-dose aspirin reduces the risk by approximately 10%.10;11 This treatment
is recommended in women with moderate to high risk for preeclampsia.12 In women with
low baseline calcium intake calcium supplementation reduces the risk of preeclampsia.13
Trials investigating possible strategies to reduce the incidence of severe preeclampsia and
gestational hypertension are hampered by the low incidence of the disease. Predictive
tests identifying high risk women could facilitate such research. Because placentation
10
starts early in pregnancy it seems likely that early interventions will be the most effective.
Identification of a high risk group early in pregnancy is therefore relevant. Up to now
there is no early validated predictive test with sufficient accuracy, that is useful in daily
clinical practice.14
Several risk factors have been identified with respect to preeclampsia. These risk factors
can be pregnancy specific, like parity or multiple pregnancy, or not pregnancy specific
and are shared with risk factors of adult cardiovascular disease. Among these are
maternal physical characteristics like obesity, age and pre-existing vascular diseases like
hypertension and diabetes.4 Other known risk factors for cardiovascular disease like
psychosocial stress might also influence the incidence of preeclampsia.15;16 It is assumed
that psychosocial stress causes excessive sympathetic nervous system activation.17Several
studies describe a higher sympathetic activity in women with preeclampsia, compared
to women with an uncomplicated pregnancy.18;19 However, it is not clear if sympathetic
hyperactivity in preeclampsia is influenced by psychosocial stress.20-22
Protective or disease modifying interventions that reduce the risk of cardiovascular disease
might be useful for the prevention of hypertensive disorders in pregnancy. Physical activity
is one such potential factor, known to prevent non-pregnant cardiovascular disease and
to reduce its symptoms. Its precise mechanism is unclear. An acceptable hypothesis
is that it reduces oxidative stress, which in turn influences the immune response and
improves endothelial function.23-26 These processes are also involved in the development
of preeclampsia and gestational hypertension.4 Literature regarding physical activity and
preeclampsia shows conflicting results.27-29
By studying the maternal cardiovascular system in pregnancy, one understands why factors
that regulate blood pressure might be predictive of preeclampsia. Already in the very
beginning of pregnancy, before 12 weeks gestational age, the maternal cardiovascular
system changes. Cardiac output increases and peripheral vascular resistance decreases.
Total circulating plasma volume increases by 40% compared with non-pregnant
controls. Blood pressure decreases until mid-pregnancy and rises again till the end of
pregnancy.30;31 Women with severe preeclampsia not only have hypertension but also a
reduced cardiac output, an increased vascular resistance, an increased arterial stiffness
and a diminished circulating plasma volume.32;33
Together with proteinuria an increased blood pressure is the obligatory symptom of the
syndrome preeclampsia. Women predisposed to develop preeclampsia already have an
increased blood pressure early in pregnancy compared to women who do not develop
preeclampsia or gestational hypertension, long before clinical symptoms arise. Although
Chapter 1
11
General Introduction
they do not meet the criteria for hypertension yet, their blood pressure measured in the
beginning of pregnancy can be used to predict preeclampsia.34-36 Blood pressure can be
measured using different methods and devices. In the first half of the eighteenth century
blood pressure was measured for the first time invasively in a mare by Stephan Hales. Until
1905 it was not possible to measure blood pressure non-invasively with a simple device
suitable for daily clinical practice. It was Nicolai Korotkoff who combined the mercury
manometer developed by Riva-Rocci and a stethoscope to register the occurrence and
disappearance of vascular sounds on the pressure release in an occluding upper arm
cuff.37 This method is considered as golden standard for non-invasive blood pressure
measurements and criteria have been described to standardize the procedure.38 Mercury
sphygmomanometry is used to diagnose preeclampsia and gestational hypertension.8
In the Netherlands the use of mercury sphygmomanometers in hospitals is not allowed
because of mercury toxicity. They are replaced by aneroid sphygmomanometers.
Nowadays several automated devices can be used to measure blood pressure, based
on registration of vascular oscillations or vascular sounds during cuff pressure release or
peripheral vascular pressure. However, many of these devices have not been validated
for the use in pregnancy.
Sphygmomanometry as described by Korotkoff and oscillometry register vascular
oscillations during the gradual relaxation of vascular occlusion in the upper arm. The
appearance and disappearance of vascular sounds determine systolic and diastolic
blood pressure and the mean arterial pressure is calculated as ((2x DBP) + SBP)/3.
In oscillometry the mean arterial pressure is estimated primarily by the pressure where
oscillations are largest. Systolic and diastolic blood pressures are derived from this
point. Sphygmomanometry registers systolic from one and diastolic blood pressure
from another heart beat cycle. In oscillometry the envelope of all oscillations during cuff
pressure release is registered, but the single maximum oscillation denotes mean arterial
pressure.39 Both techniques are influenced by arm diameter and vascular deformability.
Oscillometry is often used in automated devices suitable for ambulatory blood pressure
measurement (ABPM). In this way information about out of office blood pressure and
heart rate can be obtained. A more sophisticated approach is the calculation of the
Hyperbaric Index (HBI) using ABPM of at least 24 hours. The HBI is the individual amount
of blood pressure excess during the measurement period above a 90% tolerance limit.40
Non-invasive finger arterial waveform registration enables continuous blood pressure
registration. One of the advantages of this method is that not only blood pressure
but also heart rate, cardiac output, total peripheral resistance, arterial stiffness and
autonomic cardiovascular control can be estimated. It is not clear if there are differences
in predictive capacity between the different techniques and devices.
12
The outcome of studies using blood pressure for the prediction of hypertensive disorders
is generally disappointing. Addition of maternal characteristics and other variables like
arterial stiffness seems to improve the predictive accuracy for preeclampsia.41-43 Of
these maternal characteristics, the most predictive variable is the outcome of a former
pregnancy. Nearly half of all pregnant women are nulliparous and 2/3 of all cases of
preeclampsia occur in nulliparous women. Therefore this parameter cannot be used to
predict preeclampsia in these women.
AIM OF THIS THESIS
To investigate if differences in cardiovascular parameters can be observed early in
pregnancy between women, who will develop preeclampsia or gestational hypertension
later in pregnancy and women with an uncomplicated pregnancy. Moreover, if these
differences could be used to develop a screening strategy with a focus on nulliparous
women. Additionally we wanted to establish if modifiable risk factors for cardiovascular
disease like psychosocial stress and physical activity are also associated with preeclampsia.
Specifically we wanted to answer the following questions:
l Can blood pressure measured in the beginning of pregnancy be used as a screening
test for preeclampsia?
l Is there a difference in predictive capacity between different methods of measuring
blood pressure?
l Is arterial stiffness increased in the beginning of pregnancy in women who will develop
preeclampsia later in pregnancy and is this associated with the disease?
l Is psychosocial stress in the first half of pregnancy associated with later preeclampsia?
l Can physical exercise in leisure time in the first half of pregnancy reduce the incidence
of preeclampsia?
l Does the menstrual cycle influence blood pressure and the spontaneous baroreflex
control of the heart?
Chapter 1
13
General Introduction
OUTLINE OF THE THESIS
Part 1. Blood pressure measurement as a screening test
A meta-analysis of the value of blood pressure measurements as a screening test for
preeclampsia is presented (Chapter 2). The two following chapters explore if automated
blood pressure measurements have a stronger association with later hypertensive
disorders of pregnancy than conventional sphygmomanometry measurement. In a
prospective cohort of healthy nulliparous women and women with a previous pregnancy
complicated by preeclampsia blood pressure is measured in the first trimester with 3
different techniques; conventional sphygmomanometry, non-invasive continuous finger
arterial pressure waveform registration and ABPM. In chapter 3 we prospectively evaluate
the Hyperbaric Index, calculated from a 48 hour ABPM as a possible screening test in
the first trimester for preeclampsia or gestational hypertension. In addition we compare
the predictive capacity of the HBI with conventional sphygmomanometry and a 48 hour
ABPM. In chapter 4 the associations between blood pressure and later preeclampsia or
gestational hypertension are estimated for the three measurement techniques.
Part 2. Association of preeclampsia with arterial stiffness
Using the same cohort as in chapter 3, arterial stiffness was measured in healthy
nulliparous women and multiparous former preeclamptic women with continuous finger
arterial pressure waveform analysis. We analyze if this could enable the selection of
women at risk for developing preeclampsia later in pregnancy (Chapter 5).
Part 3. Maternal characteristics and their association with preeclampsia
Between January 2003 and March 2004 all pregnant women who received their
antenatal care by a midwife or gynecologist in Amsterdam were asked to participate
in the Amsterdam Born Children and their Development Study (ABCD-study). All
participants filled in a questionnaire on sociodemographic characteristics, medical
history, psychosocial stress and lifestyle. We explore data of all nulliparous women with
a singleton pregnancy in this cohort, to assess the association of psychosocial stress
(chapter 6) or physical activity in leisure time (chapter 7) with preeclampsia. Calculations
are adjusted for a number of well known risk factors like age, body mass index, smoking
and pre-existing medical conditions.
14
Part 4. The influence of the menstrual cycle on hemodynamics and cardiovascular control
Although differences in hemodynamics and cardiovascular regulation in pregnancy are
found between uncomplicated pregnancies and pregnancies with hypertensive disorders
not much is known about measurements before pregnancy and the individual alterations
in women. The influence of the menstrual cycle on the spontaneous baroreflex control of
the heart and hemodynamic parameters is investigated (Chapter 8).
Chapter 1
15
General Introduction
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death: a systematic review. Lancet 2006;367:1066-74. 2. Schutte JM, Steegers EA, Schuitemaker NW, Santema JG, de BK, Pel M et al. Rise in maternal
mortality in the Netherlands. BJOG. 2010;117:399-406. 3. Stichting Perinatale Registratie Nederland. Perinatale zorg in Nederland 2006. Utrecht: Stichting
Perinatale Regsitratie Nederland, 2008. 4. Steegers EA, von DP, Duvekot JJ, Pijnenborg R. Pre-eclampsia. Lancet 2010;376:631-44. 5. Manten GT, Sikkema MJ, Voorbij HA, Visser GH, Bruinse HW, Franx A. Risk factors for
cardiovascular disease in women with a history of pregnancy complicated by preeclampsia or intrauterine growth restriction. Hypertens.Pregnancy. 2007;26:39-50.
6. Lykke JA, Langhoff-Roos J, Sibai BM, Funai EF, Triche EW, Paidas MJ. Hypertensive pregnancy disorders and subsequent cardiovascular morbidity and type 2 diabetes mellitus in the mother. Hypertension 2009;53:944-51.
7. Barker DJ. Maternal nutrition, fetal nutrition, and disease in later life. Nutrition 1997;13:807-13.
8. Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens.Pregnancy. 2001;20:IX-XIV.
9. Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005;365:785-99. 10. Askie LM, Duley L, Henderson-Smart DJ, Stewart LA. Antiplatelet agents for prevention of
pre-eclampsia: a meta-analysis of individual patient data. Lancet 2007;369:1791-98. 11. Duley L, Henderson-Smart DJ, Meher S, King JF. Antiplatelet agents for preventing pre-eclampsia
and its complications. Cochrane.Database.Syst.Rev. 2007;CD004659. 12. NICE clinical guideline. Hypertension in pregnancy: the management of hypertensive disorders
during pregnancy. National Collaborating Centre for Women’s and Children’s Health 2010. 13. Hofmeyr GJ, Lawrie TA, Atallah AN, Duley L. Calcium supplementation during pregnancy
for preventing hypertensive disorders and related problems. Cochrane.Database.Syst.Rev. 2010;CD001059.
14. Cnossen JS, Ter RG, Mol BW, van der Post JA, Leeflang MM, Meads CA et al. Are tests for predicting pre-eclampsia good enough to make screening viable? A review of reviews and critical appraisal. Acta Obstet.Gynecol.Scand. 2009;88:758-65.
15. Rozanski A, Blumenthal JA, Kaplan J. Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation 1999;99:2192-217.
16. Anand SS, Islam S, Rosengren A, Franzosi MG, Steyn K, Yusufali AH et al. Risk factors for myocardial infarction in women and men: insights from the INTERHEART study. Eur.Heart J. 2008;29:932-40.
17. Lucini D, Di FG, Parati G, Pagani M. Impact of chronic psychosocial stress on autonomic cardiovascular regulation in otherwise healthy subjects. Hypertension 2005;46:1201-06.
18. Schobel HP, Fischer T, Heuszer K, Geiger H, Schmieder RE. Preeclampsia -- a state of sympathetic overactivity. N.Engl.J.Med. 1996;335:1480-85.
19. Greenwood JP, Stoker JB, Walker JJ, Mary DA. Sympathetic nerve discharge in normal pregnancy and pregnancy-induced hypertension. J.Hypertens. 1998;16:617-24.
20. Paarlberg KM, Vingerhoets AJ, Passchier J, Dekker GA, van Geijn HP. Psychosocial factors and pregnancy outcome: a review with emphasis on methodological issues. J.Psychosom.Res. 1995;39:563-95.
21. Klonoff-Cohen HS, Cross JL, Pieper CF. Job stress and preeclampsia. Epidemiology 1996;7:245-49. 22. Marcoux S, Berube S, Brisson C, Mondor M. Job strain and pregnancy-induced hypertension.
Epidemiology 1999;10:376-82.
16
23. Mora S, Cook N, Buring JE, Ridker PM, Lee IM. Physical activity and reduced risk of cardiovascular events: potential mediating mechanisms. Circulation 2007;116:2110-18.
24. Dickinson HO, Mason JM, Nicolson DJ, Campbell F, Beyer FR, Cook JV et al. Lifestyle interventions to reduce raised blood pressure: a systematic review of randomized controlled trials. J.Hypertens. 2006;24:215-33.
25. Kojda G, Hambrecht R. Molecular mechanisms of vascular adaptations to exercise. Physical activity as an effective antioxidant therapy? Cardiovasc.Res. 2005;67:187-97.
26. Moyna NM, Thompson PD. The effect of physical activity on endothelial function in man. Acta Physiol Scand. 2004;180:113-23.
27. Sorensen TK, Williams MA, Lee IM, Dashow EE, Thompson ML, Luthy DA. Recreational physical activity during pregnancy and risk of preeclampsia. Hypertension 2003;41:1273-80.
28. Magnus P, Trogstad L, Owe KM, Olsen SF, Nystad W. Recreational physical activity and the risk of preeclampsia: a prospective cohort of Norwegian women. Am.J.Epidemiol. 2008;168:952-57.
29. Osterdal ML, Strom M, Klemmensen AK, Knudsen VK, Juhl M, Halldorsson TI et al. Does leisure time physical activity in early pregnancy protect against pre-eclampsia? Prospective cohort in Danish women. BJOG. 2009;116:98-107.
30. Duvekot JJ, Peeters LL. Maternal cardiovascular hemodynamic adaptation to pregnancy. Obstet.Gynecol.Surv. 1994;49:S1-14.
31. Spaanderman ME, Meertens M, van BM, Ekhart TH, Peeters LL. Cardiac output increases independently of basal metabolic rate in early human pregnancy. Am.J.Physiol Heart Circ.Physiol 2000;278:H1585-H1588.
32. Visser W, Wallenburg HC. Central hemodynamic observations in untreated preeclamptic patients. Hypertension 1991;17:1072-77.
33. Spasojevic M, Smith SA, Morris JM, Gallery ED. Peripheral arterial pulse wave analysis in women with pre-eclampsia and gestational hypertension. BJOG. 2005;112:1475-78.
34. Moutquin JM, Rainville C, Giroux L, Raynauld P, Amyot G, Bilodeau R et al. A prospective study of blood pressure in pregnancy: prediction of preeclampsia. Am.J.Obstet.Gynecol. 1985;151:191-96.
35. Hermida RC, Ayala DE, Mojon A, Fernandez JR, Silva I, Ucieda R et al. Blood pressure excess for the early identification of gestational hypertension and preeclampsia. Hypertension 1998;31:83-89.
36. Sibai BM, Ewell M, Levine RJ, Klebanoff MA, Esterlitz J, Catalano PM et al. Risk factors associated with preeclampsia in healthy nulliparous women. The Calcium for Preeclampsia Prevention (CPEP) Study Group. Am.J.Obstet Gynecol. 1997;177:1003-10.
37. Booth J. A short history of blood pressure measurement. Proc.R.Soc.Med. 1977;70:793-99. 38. O’Brien E, Asmar R, Beilin L, Imai Y, Mallion JM, Mancia G et al. European Society of
Hypertension recommendations for conventional, ambulatory and home blood pressure measurement. J.Hypertens. 2003;21:821-48.
39. Ramsey M, III. Noninvasive automatic determination of mean arterial pressure. Med.Biol.Eng Comput. 1979;17:11-18.
40. Halberg F, Ahlgren A, Haus E. Circadian systolic and diastolic hyperbaric indices of high school and college students. Chronobiologia 1984;11:299-309.
41. Duckitt K, Harrington D. Risk factors for pre-eclampsia at antenatal booking: systematic review of controlled studies. BMJ 2005;330:565.
42. Poon LC, Karagiannis G, Leal A, Romero XC, Nicolaides KH. Hypertensive disorders in pregnancy: screening by uterine artery Doppler imaging and blood pressure at 11-13 weeks. Ultrasound Obstet Gynecol. 2009;34:497-502.
43. Khalil A, Cowans NJ, Spencer K, Goichman S, Meiri H, Harrington K. First-trimester markers for the prediction of pre-eclampsia in women with a-priori high risk. Ultrasound Obstet.Gynecol. 2010;35:671-79.
12Jeltsje S. Cnossen Karlijn C. Vollebregt Nynke de Vrieze Gerben ter Riet Ben W.J. Mol Arie FranxKhalid S. Khan Joris A.M. van der Post
BMJ. 2008; 336(7653):1117-20
Accuracy of mean arterial pressure and blood pressure measurements in predicting preeclampsia: systematic review and meta-analysis
20
ABSTRACT
Objective To determine the accuracy of using systolic and diastolic blood pressure, mean arterial
pressure, and increase of blood pressure to predict preeclampsia.
Design
Systematic review with meta-analysis of data on test accuracy.
Data sources
Medline, Embase, Cochrane Library, MEDION, reference list checking of included articles
and reviews, contact with authors.
Review methods
Without language restrictions, two reviewers independently selected the articles in
which the accuracy of blood pressure measurement during pregnancy was evaluated to
predict preeclampsia. Data were extracted on study characteristics, quality and results
to construct 2x2 tables. Summary receiver operating characteristic curves and likelihood
ratios were generated for the various levels and their thresholds.
Results
34 studies, testing 60,599 women (3341 cases of preeclampsia) were included. In
women at low risk for preeclampsia, the areas under the summary receiver operating
characteristic curves for blood pressure measurement in the second trimester were
0.68 (95% confidence interval 0.64 to 0.72) for systolic blood pressure, 0.66 (0.59 to
0.72) for diastolic blood pressure, and 0.76 (0.70 to 0.82) for mean arterial pressure.
Findings for the first trimester showed a similar pattern. Second trimester mean arterial
pressure of 90 mmHg or more showed a positive likelihood ratio of 3.5 (95% confidence
interval 2.0 to 5.0) and a negative likelihood ratio of 0.46 (0.16 to 0.75). In women
deemed to be at high risk, a diastolic blood pressure of 75 mmHg or more at 13 to 20
weeks’ gestation best predicted preeclampsia: positive likelihood ratio 2.8 (1.8 to 3.6),
negative likelihood ratio 0.39 (0.18 to 0.71). Additional subgroup analyses did not show
improved predictive accuracy.
Conclusion
When blood pressure is measured in the first or second trimester of pregnancy, the
mean arterial pressure is a better predictor for preeclampsia than systolic blood pressure,
diastolic blood pressure or an increase of blood pressure.
Chapter 2
21
Blood pressure and preeclampsia; a m
eta-analysis
INTRODUCTION
Preeclampsia is an important disorder of pregnancy, with potentially severe consequences
for mother and child.1;2 The frequency of preeclampsia varies between 2% and 7% in
healthy nulliparous women.3-5 In preeclampsia, the interaction between the placenta
and maternal constitution is influenced by genetic and environmental factors, causing a
hypertensive inflammatory response.6 The gestosis is associated with low birth weight and
preterm delivery but can also develop at term, during labour, or even postpartum.2 It has
been shown that women destined to develop preeclampsia have higher mean arterial
pressures in the first and second trimester and even before pregnancy than women with
normal pregnancies.7;8
Blood pressure measurement is a screening test that is routinely used in antenatal
care to detect or predict hypertensive disease.2 Accurate prediction of women at risk
for preeclampsia is crucial to judicious allocation of monitoring resources and use of
preventive treatment9, with the prospect of improving maternal and neonatal outcome.
Studies investigating the predictive accuracy of blood pressure measurement report
conflicting results. In view of these conflicting reports, it is uncertain whether blood
pressure measurement should be used routinely as a predictive test or used only to
diagnose hypertensive disorders in pregnancy once they are suspected. We carried
out a systematic review to investigate the accuracy of blood pressure measurement for
prediction of preeclampsia in pregnant women.
METHODS
This review was based on our previously published protocol.10 Librarians carried out
two electronic searches covering Medline, Embase, Cochrane Library (2006;4), and
Medion (www.mediondatabase.nl/) from inception to February 2007. The search strategy
(Appendix 1) consisted of MeSH or key terms related to the disease (preeclampsia) and
population (pregnant women) combined with methodological filters for identification
of studies on diagnostic tests and causal factors.11-13 A second search strategy was
done to ascertain retrieval of relevant papers because ‘blood pressure’ is a term both
related to our index test blood pressure measurement and the outcome preeclampsia.
We checked reference lists of relevant studies to identify cited articles not captured by
electronic searches and contacted authors of primary studies who had e-mail addresses
available. No language restrictions were applied. We included studies that reported on
any technique to measure blood pressure in pregnant women in any healthcare setting
22
and of any level of risk for preeclampsia. We included test accuracy studies allowing
generation of 2x2 tables.
Trained reviewers independently screened titles and abstracts for relevance (J.S.C. and
K.C.V.), and full papers for inclusion and data extraction (JSC and NdV). An explanation
of extracted clinical, methodological and statistical data has been published.10 Studies
were assessed by one reviewer (J.S.C.) for methodological quality against the quality
assessment of diagnostic accuracy studies (QUADAS) criteria14 and randomly checked
by a second reviewer (NdV). How we assessed items is summarised in Appendix 2. We
also assessed application of preventive treatment. For multiple publication of one data
set we included only the most recent or complete study. Disagreements were resolved by
consensus or a third reviewer.
Reference standards for preeclampsia were a persistent systolic blood pressure of 140
mmHg or more or diastolic blood pressure of 90 mmHg or more, or both, with proteinuria
of 0.3 g/ day or more or a dipstick result of + or more (30 mg/dl in a single urine
sample), or both, new after 20 weeks of gestation. Severe preeclampsia was defined as
systolic blood pressure of 160 mmHg or more or diastolic blood pressure of 110 mmHg
or more, or both, with proteinuria of 2.0 g/ day or more or a dipstick result of +++ or
more, or both, or of early onset (< 34 weeks) gestation. Superimposed preeclampsia
was defined as the development of proteinuria of 0.3 g/ day or more or a dipstick result
of + or more after 20 weeks of gestation in chronically hypertensive patients. Chronic
hypertension was defined as hypertension present before pregnancy or detected before
20 weeks gestation and not resolving within three months after delivery.15
Data synthesis
From the 2x2 tables we calculated sensitivity and specificity and plotted their results
in receiver operating characteristics plots. We pooled results among groups of studies
measuring similar blood pressure variables (systolic, diastolic, mean arterial, or increase)
and similar outcome. We used a bivariate regression model that takes into account the
negative correlation between sensitivity and specificity. This method has been extensively
described elsewhere and is recently recommended for meta-analysis of diagnostic
tests.16;17 Briefly, rather than using a single outcome measure per study, such as the
diagnostic odds ratio, the bivariate model preserves the two-dimensional nature of
diagnostic data in a single model. This model incorporates the correlation that may exist
between sensitivity and specificity within studies owing to possible differences in threshold
between studies. When necessary, the bivariate model uses a random effects approach for
both sensitivity and specificity, allowing for heterogeneity beyond chance due to clinical
or methodological differences between studies. In addition the model acknowledges the
Chapter 2
23
Blood pressure and preeclampsia; a m
eta-analysis
difference in precision by which sensitivity and specificity have been measured in each
study. This means that studies with a larger number of women with preeclampsia receive
more weight in the calculation of the pooled estimate of sensitivity, whereas studies with
more women without preeclampsia are more influential in the pooling of specificity.
To estimate a summary receiver operating characteristic curve and an area under that
curve, we used the results of the model with the smallest Akaike’s Information Criterion
(a measure of the goodness of fit of an estimated statistical model).18 This model best
accounts for heterogeneity between studies. We calculated areas under the curves in the
first trimester for the complete summary receiver operating characteristic curve, which
meant extension beyond the available data. We also calculated pooled sensitivities and
specificities and derived likelihood ratios thereof.19
We carried out the following subgroup analyses, defined a priori: outcome (severe
preeclampsia), sample (low-risk sample v high-risk sample), number of readings (multiple
measurements v single measurement, and gestational age at testing (first trimester v
second trimester). Sensitivity analyses were done for application of preventive treatment
and study quality. We considered studies of high quality when they scored positive on
at least four of the following items: prospective design with consecutive recruitment,
appropriate reference standard, follow-up greater than 90%, adequate description of the
index test, and reporting of preventive treatment.
All statistical analyses were done using SAS 9.1 for Windows (Proc NLMixed in the bivariate
model). We used STATA/SE 9.0 0 for drawing the receiver operating characteristic plots.
RESULTS
Figure 1 summarises the flow of studies through the review. Overall, 34 studiesw1-w34
screening 60,599 women (3341 preeclamptic women) were included, which comprised
28 cohorts, three randomised controlled trials and three case-control studies resulting in
135 2x2 tables. None of 12 authors contacted about unclear information in their articles
provided additional information. The main reason given was “data not available”.
Twenty-eight studies were prospective and six retrospective. The risk profiles of the women
included in the studies are shown in Appendix 3. Sample sizes ranged from 22 to 22,582
women. The incidence rates for preeclampsia ranged from 0.8 to 40.8% (median
incidence 6.3%; case control studies excluded). Seven studies reported on “high risk”
women (range for incidence rates 2.0 to 28.7%). Since the criteria for high risk varied
from women with an abnormal uterine artery detected by Doppler ultrasonography to
women with chronic hypertension or diabetes, this may have caused the great variation
24
in incidence. Fourteen studies explicitly reported exclusion of chronic hypertension and
four studies reported inclusion of chronic hypertension (women at high risk). Twenty
eight studies reported on blood pressure measurement in the second trimester. Eighteen
studies reported on mean arterial pressure, defined as (diastolic blood pressure + one
third x (systolic blood pressure – diastolic blood pressure)) or automated mean arterial
pressure readings. Six studies reported on systolic blood pressure, 11 on diastolic blood
pressure, and three on increase of systolic blood pressure or increase of diastolic blood
pressure, or both. One studyw33 reported on diastolic midline estimating statistic of rhythm
(MESOR) and two studiesw28;w31 reported on absolute blood pressure levels. Since both
randomised controlled trials in women at low risk investigated calcium supplementation,
which has not been proved effective,20 and one only included the placebo group, we
analysed the trials together with the cohort studies. Four studies were excluded from the
final meta-analysis (three case control studiesw2;w15;w20 to further enhance validity and
one study without threshold for the index testw26).
Quality assessment
Figure 2 summarises the results of quality assessment. Over 70% of studies met the
following items for quality assessment: period between tests, avoidance of partial and
Primary articles retrieved for detailed evaluation (n= 186) - from electronic searches (n= 182) - from reference lists (n= 4)
Articles excluded (n= 152) - not prediction (n= 32) - reviews, letters, comments, or editorials (n= 16) - pre-eclampsia not separate outcome or pregnancy induced
hypertension only (n= 49) - no test accuracy (n= 19) - insufficient data to construct 2x2 table (n= 31) - data duplication (n= 1) - other (n= 4)
Primary articles in cluded in systematic review (n= 34)
Potentially relevant citations identified from electronic searches to capture primary articles on all tests used in prediction of pre-eclampsia (n= 19 548)
Potentially relevant citations on blood pressure measurement (n= 4 000)
References excluded after screening titles or abstracts (n= 3 818)
Figure 1. Literature identification and study selection
Chapter 2
25
Blood pressure and preeclampsia; a m
eta-analysis
differential verification, independent reference test, blind assessment of index test,
and clinical data available. Less than 30% of studies scored positive on the items for
adequate patient spectrum, adequate descriptions of selection criteria, index test, and
reference test, and blind assessment of reference test. Seven publications reported on the
application of preventive treatment.
3
13
12
34
3
30
5
8
28
34
34
31
15
9
7
4
3
2
1
16
11
12
2
15
27
18
20
30
4
13
15
6
2
7
23
12
0% 20% 40% 60% 80% 100%
Preventive treatment
Withdrawals explained
Uninterpretable results reported
Clinical data available
Blinding of reference test
Blinding of index test
Adequate description reference test
Adequate description index test
Independent reference test
Differential verification bias
Partial verification bias
Time period between tests
Appropriate reference test
Selection criteria described
Representative patient spectrum
Compliance to quality item
Yes; N/A No Unclear
Figure 2. Summary of quality assessment
Data analysis
Figure 3 shows the receiver operating characteristic plots for the results for systolic blood
pressure, diastolic blood pressure, mean arterial pressure and increases of systolic
blood pressure or diastolic blood pressure according to risk and trimester. Some studies
are shown several times with several thresholds. Figure 4 shows the summary receiver
operating characteristic curves for systolic blood pressure, diastolic blood pressure, and
mean arterial pressure in low-risk populations in the second trimester. The area under
26
the curve was 0.68 (95% confidence interval 0.64 to 0.72) for systolic blood pressure,
0.66 (0.59 to 0.72) for diastolic blood pressure, and 0.76 (0.70 to 0.82) for mean
arterial pressure. For a specificity of 90%, the sensitivities of diastolic blood pressure
and mean arterial pressure were both 35%, whereas for systolic blood pressure the
sensitivity was only 24%. For the six studies with a mean arterial pressure of 85 mmHg
or more the pooled sensitivity was 52% (95% confidence interval 28% to 75%) and the
pooled specificity 84% (95% confidence interval 75% to 94%); derived positive likelihood
ratio 3.3 (95% confidence interval 2.2 to 4.3) and negative likelihood ratio 0.57 (95%
confidence interval 0.35 to 0.80). A mean arterial pressure of 90 mmHg or more showed
a pooled sensitivity of 62% (35% to 89%) and a pooled specificity of 82% (72% to 92%);
020
4060
8010
0se
nsiti
vity
(%)
020406080100specificity
SBP
020
4060
8010
0se
nsiti
vity
(%)
020406080100specificity
DBP
020
4060
8010
0se
nsiti
vity
(%)
020406080100specificity
MAP0
2040
6080
100
sens
itivi
ty (%
)
020406080100specificity
increase SBP/DBP
Figure 3. Receiver operating characteristic plots for all results according to timing of test during gestation. Hollow circles represent 2nd trimester testing in low risk populations; solid circles 2nd trimester in high risk populations; and hollow triangles 1st trimester in low risk populations.
Chapter 2
27
Blood pressure and preeclampsia; a m
eta-analysis
derived positive likelihood ratio 3.5 (CI 2.0 to 5.0) and negative likelihood ratio 0.46
(0.16 to 0.75). The three studies on increase of systolic blood pressure or diastolic
blood pressure, or both, showed poor predictive accuracy (figure 3.3). Poor predictive
accuracy was shown for an increase of systolic blood pressure or diastolic blood pressure
compared with baselinew16;w27 and an increase of blood pressure compared with later
gestational ages.w32
Subgroup and sensitivity analysis
Severe preeclampsia was reported by only one cohort study w25 (first trimester: positive
likelihood ratio 2.9, 1.9 to 4.2; negative likelihood ratio 0.74, 0.59 to 0.88) and one
case control study w2 (positive likelihood ratio 4.3, 2.2 to 8.9; negative likelihood ratio
0.54, 0.45 to 0.70).
In high-risk populations a diastolic blood pressure of 75 mmHg or more at 13 to 20
weeks’ gestation best predicted preeclampsia: (positive likelihood ratio 2.8, 1.8 to
3.6, negative likelihood ratio 0.39, 0.18 to 0.71).w26 Another study showed a positive
likelihood ratio 2.8 and negative likelihood ratio of 0.00, but this study had only one
case of preeclampsia (sensitivity 100%).
In 24 studies it was unclear whether single (in doctor’s surgery) or multiple (ambulatory
blood pressure monitoring during the daytime) readings were reported. When it was
assumed that these studies carried out single measurements, the areas under the curves
for testing in low risk populations in the second trimester remained 0.68 for systolic
0
0,2
0,4
0,6
0,8
1
0 0,2 0,4 0,6 0,8 1
1-specificity
sensitivity
SBP
DBP
MAP
Figure 4. Summary receiver operating characteristic curves with 95% confidence intervals for systolic blood pressure, diastolic blood pressure and mean arterial pressure in population of women at low risk of pre-eclampsia tested in second trimester
28
blood pressure, 0.66 for diastolic blood pressure, and 0.76 for mean arterial pressure.
Areas under the curves for blood pressure measurement in the first trimester were 0.66
for systolic blood pressure, 0.67 for diastolic blood pressure, and 0.79 for mean arterial
pressure.
Studies that excluded women with chronic hypertension showed positive likelihood ratios
for systolic blood pressure of 1.9 (95% confidence interval 0.0 to 3.7), diastolic blood
pressure 2.7 (0.0 to 5.5), and mean arterial pressure 2.6 (1.5 to 3.7). Negative likelihood
ratios were, respectively, 0.6 (0.4 to 0.6), 0.6 (0.4 to 0.7), and 0.5 (0.3 to 0.8).
Sensitivity analysis on preventive treatment was considered impractical because 25
studies (80%) did not report on it. None of the studies met the criteria for high quality.
DISCUSSION
We reviewed the literature on the accuracy of blood pressure measurement during
pregnancy to predict preeclampsia. The mean arterial pressure predicted preeclampsia
fairly well (area under the curve between 0.70 and 0.80) whereas systolic blood pressure,
diastolic blood pressure, and an increase of systolic blood pressure or increase of diastolic
blood pressure, or both, predicted preeclampsia poorly (area under the curve < 0.70).
In low-risk populations a mean arterial pressure in the second trimester best predicted
preeclampsia, with an area under the curve of 0.76. An increased mean arterial pressure
of 90 mmHg or more in the second trimester, however, showed a small increase of the
likelihood of developing preeclampsia (positive likelihood ratio 3.5; negative likelihood
ratio 0.46). In high-risk populations a diastolic blood pressure of 75 mmHg or more
at 13 to 20 weeks’ gestation best predicted preeclampsia, although the accuracy of
prediction was modest (positive likelihood ratio 2.8, negative likelihood ratio 0.39).
Subgroup analyses were limited and did not improve predictive accuracy.
Strengths and weaknesses of the review
We carried out extensive literature searches without language restrictions, assessed the
quality of the studies and the reporting, and used contemporary statistical methods.
Many studies did not distinguish between preeclampsia and other hypertensive disorders
in pregnancy (figure 3.1), nor did many report sufficient information to construct a 2x2
table. Contacting authors did not increase the number of included studies, resulting
in a potential loss of relevant data. Quality assessment and subgroup analyses were
hindered by unclear reporting in many studies, which is a common problem in diagnostic
reviews. Previous studies reported that poor study design and conduct can affect
estimates of diagnostic accuracy21;22 but it is not entirely clear how individual aspects
Chapter 2
29
Blood pressure and preeclampsia; a m
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of quality may effect this and to what magnitude in this particular area. Many strategies
to account for differences in quality have been applied but none led to estimates that
were systematically less optimistic than ignoring quality in meta-analyses of test accuracy
studies.23;24 As a result of unclear reporting it was not possible to carry out multivariate
subgroup analysis on the basis of individual quality criteria, therefore we reported the
overall results. Poor reporting occurred in details of the index test and reference standard,
patient selection criteria, and blinding. Definitions of preeclampsia have changed over
time, with previous definitions including oedema and increases in blood pressure. The
measurement of blood pressure was poorly reported, underestimating the importance
of recording diastolic blood pressure with Korotkoff phase V as this is more reliably
recorded and more closely reflects direct measurement of diastolic blood pressure.25-27
Poor reporting of the device used underestimates the importance of its validation for
blood pressure measurement during pregnancy.28;29 Poor reporting of patient selection
criteria may partly explain the great variability of incidence rates of preeclampsia not
only between but also within the categories of populations considered high risk or low
risk. In some of the studies the population that was intended to be recruited differed from
the population enrolled. The selection criteria for high risk varied from abnormal uterine
artery detected by Doppler ultrasonography to pre-existent disease or mixtures thereof,
such as chronic hypertension or diabetes. Large cohort studies (> 300,000 women)
reflecting unselected populations however showed incidence rates of preeclampsia
between 0.8 and 5.1%.30-32 This suggests that small studies of low risk or unselected
populations within this review may have been prone to selection bias. Studies that tested
in mid-trimester should have taken into account that the predictive accuracy at 14 weeks
may differ from that at 27 weeks because by definition no one develops preeclampsia
in the first half of pregnancy.
Strengths and weaknesses in relation to other studies
A published review in this area was restricted to evaluating risk factors for preeclampsia
at the first antenatal visit.33 This review included four studies on blood pressure and
concluded that the risk of preeclampsia was increased in women with a raised diastolic
blood pressure (> 80 mmHg) at the first antenatal visit (relative risk 1.48, 95% confidence
interval 1.0 to 1.9). Other published reviews did not apply appropriate methods for
systematic reviews of screening tests or did not distinguish between different hypertensive
disorders.34-39 Some of these reviews concluded that an increased mean arterial pressure
(≥ 85 or ≥ 90 mmHg) predicted transient hypertension rather than preeclampsia 34-36 and that pregnant women with diastolic blood pressures of 70 mmHg or less, or
30
mean arterial pressure of 80 mmHg or less in the second trimester have a small risk of
developing preeclampsia.38
Unanswered questions, future research and implications
When deciding on whether a predictive test should be applied in clinical practice several
things need to be considered: the prevalence of the disease and the predictive accuracy of
the test, the cost of the test and the acceptability to patients, and the treatments available
for the disease in question. Preeclampsia is a disease with relatively low prevalence. A
clinically useful test would need to have a great area under the curve (preferably > 0.80)
or high positive likelihood ratio (> 10) and low negative likelihood ratio (< 0.10).40 From
the results of this review mean arterial pressure shows the greatest predictive accuracy in
both first and second trimesters, with a relatively small likelihood ratio (positive likelihood
ratio 3.5; negative likelihood ratio 0.46). In clinical practice measurement of mean
arterial pressure at the first antenatal visit may improve the accuracy for estimating risk
of preeclampsia. Although it will probably not make a clinical impact in isolation, it is
highly likely that the prediction of preeclampsia will evolve through the development of
algorithms that possibly include clinical, biophysical and biochemical markers. Recently,
the authors of a large prospective study concluded that maternal variables, together
with mean arterial pressure at 11+0 to 13+6 weeks, identify a group at high risk for
preeclampsia.41 Our data cannot rationalise current obstetrical practice of repeated
blood pressure measurements during the first and second trimester in healthy women
with a normal blood pressure at the first antenatal visit. A formal cost utility analysis is
needed.
Women can experience unnecessary anxiety when being identified at risk of preeclampsia
after an antenatal test. At present no pharmacological treatment or management strategy
(for example, regular ultrasound scanning, early delivery) has been shown to effectively
prevent the development of preeclampsia. Early antihypertensive treatment has been
shown to only prevent severe hypertension, not any other complication. Research into
aspirin as a treatment has, however, shown a modest preventive effect (relative risks of
0.9 for preeclampsia and 0.9 for fetal growth restriction42) in the absence of any serious
side effects. Aspirin is a cheap and readily available preventive treatment. In this instance
a false negative test result is potentially more harmful than a false positive test result.
It is imperative to differentiate between mild and severe disease, because early or severe
preeclampsia is associated with raised rates of maternal morbidity and mortality and with
pronounced risks for the fetus, such as severe fetal growth restriction.2;43 Future research
should also concentrate on the development of algorithms that combine biochemical
and biophysical markers, including blood pressure measurement – a diagnostic process
Chapter 2
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Blood pressure and preeclampsia; a m
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used in clinical care. These may help improve the predictive accuracy of the tests to
clinically important values.
Acknowledgements
We thank Faridi van Etten for help with the searches, Kees Boer and Hans Wolf for
comments on the project and manuscript, and Koos Zwinderman for help with statistical
analyses.
32
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death: a systematic review. Lancet 2006; 367:1066-1074. (2) Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005; 365(9461):785-799. (3) Vatten LJ, Skjaerven R. Is Preeclampsia More Than One Disease? Obstet Gynecol Surv 2004;
59(9):645-646. (4) Sibai BM. Diagnosis and management of gestational hypertension and preeclampsia. Obstet
Gynecol 2003; 102(1):181-192. (5) Hauth JC, Ewell MG, Levine RJ, Esterlitz JR, Sibai B, Curet LB et al. Pregnancy outcomes in
healthy nulliparas who developed hypertension. Calcium for Preeclampsia Prevention Study Group. Obstet Gynecol 2000; 95(1):24-28.
(6) Redman CW, Sargent IL. Latest advances in understanding preeclampsia. Science 2005; 308(5728):1592-1594.
(7) Easterling TR, Benedetti TJ, Schmucker BC, Millard SP. Maternal hemodynamics in normal and preeclamptic pregnancies: a longitudinal study. Obstet Gynecol 1990; 76(6):1061-1069.
(8) Rang S, Wolf H, Van Montfrans GA, Karemaker JM. Serial assessment of cardiovascular control shows early signs of developing pre-eclampsia. J Hypertens 2004; 22(2):369-376.
(9) Duley L, Henderson-Smart DJ, Knight M, King JF. Antiplatelet agents for preventing pre-eclampsia and its complications. Cochrane Database Syst Rev 2004;(1):CD004659.
(10) Cnossen JS, van der Post JA, Mol BW, Khan KS, Meads CA, Ter RG. Prediction of pre-eclampsia: a protocol for systematic reviews of test accuracy. BMC Pregnancy Childbirth 2006; 6:29.
(11) Yale University School of Medicine: Finding the evidence on PubMed. http://info med yale edu/library/reference/publications/pubmed/ [cited 2003 Dec. 10]
(12) Bachmann LM, Coray R, Estermann P, Ter Riet G. Identifying diagnostic studies in MEDLINE: reducing the number needed to read. J Am Med Inform Assoc 2002; 9(6):653-658.
(13) Haynes RB, Wilczynski N, McKibbon KA, Walker CJ, Sinclair JC. Developing optimal search strategies for detecting clinically sound studies in MEDLINE. J Am Med Inform Assoc 1994; 1(6):447-458.
(14) Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 2003; 3(1):25.
(15) Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001; 20(1):IX-XIV.
(16) Harbord RM, Deeks JJ, Egger M, Whiting P, Sterne JA. A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics 2007; 8(2):239-251.
(17) Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH. Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 2005; 58(10):982-990.
(18) Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974; 19(6):716-723.
(19) Zwinderman AH, Bossuyt PM. We should not pool diagnostic likelihood ratios in systematic reviews. Stat Med 2008; 27(5):687-697.
(20) Meads CA, Cnossen JS, Meher S, Juarez_Garcia A, ter Riet G, Duley L et al. Methods of prediction and prevention of pre-eclampsia - systematic reviews of accuracy and effectiveness literature with economic modelling. 12. 2008. Health Technology Assessment.
(21) Lijmer JG, Mol BW, Heisterkamp S, Bonsel GJ, Prins MH, van der Meulen JH et al. Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 1999; 282(11):1061-1066.
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(22) Rutjes AW, Reitsma JB, Di Nisio M, Smidt N, van Rijn JC, Bossuyt PM. Evidence of bias and variation in diagnostic accuracy studies. CMAJ 2006; 174(4):469-476.
(23) Leeflang M, Reitsma J, Scholten R, Rutjes A, Dinisio M, Deeks J et al. Impact of Adjustment for Quality on Results of Metaanalyses of Diagnostic Accuracy. Clin Chem 2007; 53(2):164-172.
(24) Whiting P, Harbord R, Kleijnen J. No role for quality scores in systematic reviews of diagnostic accuracy studies. BMC Med Res Methodol 2005; 5:19.
(25) Brown MA, Reiter L, Smith B, Buddle ML, Morris R, Whitworth JA. Measuring blood pressure in pregnant women - a comparison of direct and indirect methods. Am J Obstet Gynecol 1994; 171(3):661-667.
(26) Brown MA, Hague WM, Higgins J, Lowe S, McCowan L, Oats J et al. The detection, investigation and management of hypertension in pregnancy: full consensus statement. Aust N Z J Obstet Gynaecol 2000; 40(2):139-155.
(27) Shennan A, Gupta M, Halligan A, Taylor DJ, deSwiet M. Lack of reproducibility in pregnancy of Korotkoff phase IV as measured by mercury sphygmomanometry. Lancet 1996; 347(8995):139-142.
(28) Brown MA, Robinson A, Buddle ML. Accuracy of automated blood pressure recorders in pregnancy. Aust N Z J Obstet Gynaecol 1998; 38(3):262-265.
(29) Pomini F, Scavo M, Ferrazzani S, De Carolis S, Caruso A, Mancuso S. There is poor agreement between manual auscultatory and automated oscillometric methods for the measurement of blood pressure in normotensive pregnant women. J Matern Fetal Med 2001; 10(6):398-403.
(30) Conde-Agudelo A, Althabe F, Belizan JM, Kafury-Goeta AC. Cigarette smoking during pregnancy and risk of preeclampsia: a systematic review. Am J Obstet Gynecol 1999; 181(4):1026-1035.
(31) Sebire NJ, Jolly M, Harris JP, Wadsworth J, Joffe M, Beard RW et al. Maternal obesity and pregnancy outcome: a study of 287,213 pregnancies in London. Int J Obes Relat Metab Disord 2001; 25(8):1175-1182.
(32) Sebire NJ, Jolly M, Harris J, Regan L, Robinson S. Is maternal underweight really a risk factor for adverse pregnancy outcome? A population-based study in London. BJOG 2001; 108(1):61-66.
(33) Duckitt K, Harrington D. Risk factors for pre-eclampsia at antenatal booking: systematic review of controlled studies. BMJ 2005; 330(7491):565.
(34) Chesley LC, Sibai BM. Clinical significance of elevated mean arterial pressure in the second trimester. Am J Obstet Gynecol 1988; 159(2):275-279.
(35) Conde-Agudelo A, Lede R, Belizan J. Evaluation of methods used in the prediction of hypertensive disorders of pregnancy. Obstet Gynecol Surv 1994; 49(3):210-222.
(36) Dekker GA, Sibai BM. Early detection of preeclampsia. Am J Obstet Gynecol 1991; 165(1):160-172.
(37) O’Brien WF. Predicting preeclampsia. Obstet Gynecol 1990; 75(3 Pt 1):445-452. (38) O’Brien WF. The prediction of preeclampsia. Clin Obstet Gynecol 1992; 35(2):351-364. (39) Visser W, Wallenburg HC. Prediction and prevention of pregnancy-induced hypertensive
disorders. Baillieres Best Pract Res Clin Obstet Gynaecol 1999; 13(1):131-156. (40) Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ 2004; 329(7458):168-169. (41) Poon LCY, Kametas NA, Pandeva I, Valencia C, Nicolaides KH. Mean arterial pressure at 11+0
to 13+6 weeks in the prediction of preeclampsia. Hypertension 2008; 51:1-7. (42) Askie LM, Duley L, Henderson-Smart DJ, Stewart LA. Antiplatelet agents for prevention of
pre-eclampsia: a meta-analysis of individual patient data. Lancet 2007; 369:1791-1798. (43) Report of the National High Blood Pressure Education Program Working Group on High Blood
Pressure in Pregnancy. Am J Obstet Gynecol 2000; 183(1):S1-S22.
34
Appendix 1
Search strategies to identify articles on blood pressure measurement used to predict preeclampsiaThe overall search strategy on prediction of preeclampsia is previously published in a
protocol.1 For this review we identified citations on blood pressure measurement in the
established Reference Manager 11.0 database using the following terms in keywords,
titles, and abstract: {dinamap} OR {dynamap} OR OR {mercury} OR {oscill\*} OR {Auscultat\*} OR {Automat\*}
OR {Sphygmomanom\*} OR {Mercury} OR {Ambulatory Monitoring} OR OR OR {finapres}
OR {finger arterial pressure waveform} OR {Blood Pressure Determination} OR {Blood Pressure
Measurement} OR {Blood Pressure Monitoring\*} OR {Blood Pressure Monitor}
Additional search in PubMED
1. (((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) AND (predict*[tiab] OR predictive value of tests[mh] OR scor*[tiab] OR observ*[tiab] OR observer variation[mh])
2. Search (((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) NOT (((((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) AND Letter[ptyp]) OR ((((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination ”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) AND Editorial[ptyp]) OR ((((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) AND Review[ptyp]) OR ((((“Sphygmomanometers”[MeSH]) OR (“Blood Pressure Determination”[MeSH]) OR (“Blood Pressure”[MeSH:noexp])) AND ((“Hypertension, Pregnancy-Induced”[MeSH]) OR (“Pregnancy Complications, Cardiovascular”[MeSH] AND Humans[Mesh]))) AND Practice Guideline[ptyp]))
3. #2 NOT #1
Reference List
(1) Cnossen JS, van der Post JA, Mol BW, Khan KS, Meads CA, Ter RG. Prediction of pre-eclampsia:
a protocol for systematic reviews of test accuracy. BMC Pregnancy Childbirth 2006; 6:29.
Chapter 2
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Appendix 2
QUADAS (quality assessment of diagnostic accuracy studies) criteria used to assess the methodological quality of studies of blood pressure measurement used to predict pre-eclampsiaQUADAS question Study characteristics and methods required to
meet criterion
1. Was the spectrum of patients representative of the patients who will receive the test in practice? (spectrum bias)
Pregnant women, consecutively recruited; study has prospective design. Patients with chronic hypertension, insulin dependent diabetes mellitus, chronic renal disease, autoimmune disorders (AID), multiple pregnancies, or history of pre-eclampsia; so called ‘high risk’ patients
2. Were patient selection criteria clearly described? (selection bias)
Information is available on at least 5 of the following factors: chronic hypertension, insulin dependent diabetes mellitus, chronic renal disease, parity, singleton/ multiple pregnancies, previous pre-eclampsia, and age
3. Is the reference standard likely to correctly classify the target condition?
lPre-eclampsia: systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg plus proteinuria measured as ≥ 0.3 g of protein in a 24-hour urine collection or dipstick test result ≥ 1+ (equivalent to 30 mg/dL in a single urine sample)
lSuperimposed pre-eclampsia: proteinuria measured as ≥ 0.3 g of protein in a 24-hour urine collection or dipstick test result ≥ 1+ after 20 weeks of gestation in patients with chronic hypertension
lSevere pre-eclampsia: systolic blood pressure ≥ 160 mmHg or diastolic blood pressure ≥ 110 mmHg plus proteinuria measured as ≥ 2.0 g of protein in a 24-hour urine collection or dipstick test result ≥ 3+
4. Is the time period between reference standard and index test short enough to be reasonably sure that the target condition did not change between the 2 tests? (disease progression bias)
Not applicable
5. Did the whole sample, or a random selection of the sample receive verification using a reference standard of diagnosis? (partial verification bias)
All patients or a random selection received verification with reference standard (even if reference standard not the same for all patients)
6. Did patients receive the same reference standard regardless of the index test result? (differential verification bias)
All patients received same reference test (this is likely because the index test is non-invasive).
7. Was the reference standard independent of the index test (i.e. the index test did not form part of the reference standard)? (incorporation bias)
The results of the index test are not incorporated in the definition of pre-eclampsia
8. Was the execution of the index test described in sufficient detail to permit its replication?
Description includes at least seven of the following: linstrument used, (manufacturer), calibration of
instrument, appropriate cuff, position of patient, left or right arm, state of mind (rest), Korotkoff sound (IV or V) for DBP, number of measurements (single or serial), measurement parameter/ cutoff level
9. Was the execution of the reference standard described in sufficient detail to permit its replication?
Description includes:lBlood pressure: instrument, position of patient,
Korotkoff sound for diastolic blood pressure lProteinuria: 24-hour urine collection or use of
dipstick with cutoff point
36
10a. Were the index test results interpreted without knowledge of the results of the reference standard? (review bias)
Always fulfilled, reference test results not yet available when index test is performed (prediction)
10b. Were the reference standard results interpreted without knowledge of the results of the index test? (review bias)
Relevant statement is included in text (e.g., “Assessors were blind to index test results”)
11. Were the same clinical data available when tests results were interpreted as would be available when the test is used in practice?
Any information to the patient obtained by direct observation (age, symptoms, body mass index) normally available when test is interpreted in practice was also available when the test was interpreted in the study, or data unavailable in practice also unavailable during interpretation
12. Were uninterpretable/ intermediate test results reported?
All test results are reported, including uninterpretable/ intermediate results
13. Were withdrawals from the study explained? It is clear what happened to all patients in study (e.g., flow diagram [follow-up])
Supplementary question
14. Was there any preventive intervention? After blood pressure measuerment, patients received any of the following: acetylsalicylic acid, low-molecular-weight heparin, vitamin C or E, antihypertensive medication, saline infusion, oxygen
38
Table 1. Characteristics of studies of blood pressure measurement used to predict preeclampsia in pregnant women at low or unspecified riskFirst author (year) Country
Gestation(weeks)
N(% preeclampsia)
SensitivityTP/(TP+FN)
Specificity TN/(FP+TN)
Index test Threshold(mmHg)
Details index test Reference standard preeclampsia
Population (study design)*
Ales1
(1989)USA
2nd trimester 730 (0.8) 4/6 589/724 MAP ≥ 85 Automated ultrasound device with digital readout, seated, average both arms, 5min rest, K5
RR ≥ 140/90 mmHg, MAP ≥ 107 mmHg or increase > 30/15 mmHg, twice 6h apart after 24 weeks; proteinuria ++ dipstick or > 0.3g/24h
IN: all pregnant women
Atterbury2 (1996)USA
2nd trimester 114 (50.0) 30/57 50/57 MAP ≥ 85 Sphygmomanometer, Baumonometer, seated, K5
Severe preeclampsia: SBP > 170 or DBP > 110 mmHg, twice 6h apart; proteinuria ++ dipstick; (oliguria, cerebral or visual disturbances, pulmonary oedema, epigastric or right upper quadrant pain, HELLP)
IN (cases): gestational age over 24 weeks, complete records, midtrimester blood pressure, protein assay 18-22 weeks, severe preeclampsia; IN (controls): normotensive, delivery after 37 weeks; EX: from control group for any medical, obstetrical or fetal complications.(case control)
Conde-Agudelo3 (1993)Argentina
202631
580 (4.0) 11/2310/239/23
334/557434/557479/557
MAP > 81MAP > 85MAP > 89
4 random-zero sphygmomanometers rotating among centers, calibrated every 3 weeks seated, left arm, 10 min rest, mean of 5 measurements, K5
SBP ≥ 140 or DBP ≥ 90 mmHg, twice 6h apart; proteinuria 0.3g/L
IN: placebogroup of trial on calcium supplementation (same population as Lopez et al.) EX: chronic medical illnesses
Fallis4
(1963) USA2nd trimester 113 (34.5) 32/39 65/74 MAP > 90 Hypertension + proteinuria IN: primigravid women
Friedman5 (1977)USA
17-26 22,582 (3.9) 571/888 13458/21694 MAP ≥ 90 Indirect sphygmomanometer, K4 or K5
Hypertension + proteinuria IN: unselected population (Collaborative Perinatal Project)
Higgins6 (1997)Ireland
18-24 984 (2.3) 4/233/234/235/234/232/231/232/235/235/234/236/23
920/961940/961914/961916/961919/961924/961934/961926/961933/961923/961931/961919/961
MAP > 86 (ABPM)MAP > 86 (clinic)
MAP > 86 (nighttime)MAP > 86 (daytime)SBP > 119 (ABPM)
SBP > 119 (nighttime)SBP > 119 (clinic)
SBP > 119 (daytime)DBP > 71 (ABPM)
DBP > 71 (nighttime)DBP > 71 (clinic)
DBP > 71 (daytime)
ABPM, SpaceLabs 90207, every 30 min, non-dominant armOffice blood pressure: appropriate cuff, seated, relaxed, arm at heart level, non-dominant arm
DBP > 90 mmHg twice 4h apart or DBP > 110 mmHg once; ≥ + dipstick twice 4h apart, no urinary tract infection
IN: healthy primigravid women; EX: history of hypertension, renal and cardiac disease, diabetes mellitus
Iwasaki7
(2002)Japan
1st trimester 1599 (2.8) 44/4541/4540/4529/45
300/1554621/1554951/15541253/1554
MAP ≥ 74MAP ≥ 80MAP ≥ 86MAP ≥ 92
Non-invasive automated measurements (BP-203RV, Nippon Colin Co, Tokyo), seated, right arm held at heart level
SBP ≥ 140 or DBP ≥ 90 mmHg after second trimester; proteinuria ≥ 0.3g/24h
IN: singleton pregnancies
Knuist8
(1998)Netherlands
at booking 2413 (1.4) 16/3425/34
1684/23791107/2379
SBP > 120DBP > 70
SBP at bookingDBP at booking
DBP > 90 mmHg twice 4h apart, after 20 weeks; ≥ ++ dipstick twice 4h apart without urinary tract infection
IN: all nulliparous, singleton pregnancies; EX: pre-existing disease (such as diabetes, severe hypertension, renal disease) or obstetric abnormality (such as multiple gestation)
Appendix 3
Chapter 2
39
Blood pressure and preeclampsia; a m
eta-analysis
Table 1. Characteristics of studies of blood pressure measurement used to predict preeclampsia in pregnant women at low or unspecified riskFirst author (year) Country
Gestation(weeks)
N(% preeclampsia)
SensitivityTP/(TP+FN)
Specificity TN/(FP+TN)
Index test Threshold(mmHg)
Details index test Reference standard preeclampsia
Population (study design)*
Ales1
(1989)USA
2nd trimester 730 (0.8) 4/6 589/724 MAP ≥ 85 Automated ultrasound device with digital readout, seated, average both arms, 5min rest, K5
RR ≥ 140/90 mmHg, MAP ≥ 107 mmHg or increase > 30/15 mmHg, twice 6h apart after 24 weeks; proteinuria ++ dipstick or > 0.3g/24h
IN: all pregnant women
Atterbury2 (1996)USA
2nd trimester 114 (50.0) 30/57 50/57 MAP ≥ 85 Sphygmomanometer, Baumonometer, seated, K5
Severe preeclampsia: SBP > 170 or DBP > 110 mmHg, twice 6h apart; proteinuria ++ dipstick; (oliguria, cerebral or visual disturbances, pulmonary oedema, epigastric or right upper quadrant pain, HELLP)
IN (cases): gestational age over 24 weeks, complete records, midtrimester blood pressure, protein assay 18-22 weeks, severe preeclampsia; IN (controls): normotensive, delivery after 37 weeks; EX: from control group for any medical, obstetrical or fetal complications.(case control)
Conde-Agudelo3 (1993)Argentina
202631
580 (4.0) 11/2310/239/23
334/557434/557479/557
MAP > 81MAP > 85MAP > 89
4 random-zero sphygmomanometers rotating among centers, calibrated every 3 weeks seated, left arm, 10 min rest, mean of 5 measurements, K5
SBP ≥ 140 or DBP ≥ 90 mmHg, twice 6h apart; proteinuria 0.3g/L
IN: placebogroup of trial on calcium supplementation (same population as Lopez et al.) EX: chronic medical illnesses
Fallis4
(1963) USA2nd trimester 113 (34.5) 32/39 65/74 MAP > 90 Hypertension + proteinuria IN: primigravid women
Friedman5 (1977)USA
17-26 22,582 (3.9) 571/888 13458/21694 MAP ≥ 90 Indirect sphygmomanometer, K4 or K5
Hypertension + proteinuria IN: unselected population (Collaborative Perinatal Project)
Higgins6 (1997)Ireland
18-24 984 (2.3) 4/233/234/235/234/232/231/232/235/235/234/236/23
920/961940/961914/961916/961919/961924/961934/961926/961933/961923/961931/961919/961
MAP > 86 (ABPM)MAP > 86 (clinic)
MAP > 86 (nighttime)MAP > 86 (daytime)SBP > 119 (ABPM)
SBP > 119 (nighttime)SBP > 119 (clinic)
SBP > 119 (daytime)DBP > 71 (ABPM)
DBP > 71 (nighttime)DBP > 71 (clinic)
DBP > 71 (daytime)
ABPM, SpaceLabs 90207, every 30 min, non-dominant armOffice blood pressure: appropriate cuff, seated, relaxed, arm at heart level, non-dominant arm
DBP > 90 mmHg twice 4h apart or DBP > 110 mmHg once; ≥ + dipstick twice 4h apart, no urinary tract infection
IN: healthy primigravid women; EX: history of hypertension, renal and cardiac disease, diabetes mellitus
Iwasaki7
(2002)Japan
1st trimester 1599 (2.8) 44/4541/4540/4529/45
300/1554621/1554951/15541253/1554
MAP ≥ 74MAP ≥ 80MAP ≥ 86MAP ≥ 92
Non-invasive automated measurements (BP-203RV, Nippon Colin Co, Tokyo), seated, right arm held at heart level
SBP ≥ 140 or DBP ≥ 90 mmHg after second trimester; proteinuria ≥ 0.3g/24h
IN: singleton pregnancies
Knuist8
(1998)Netherlands
at booking 2413 (1.4) 16/3425/34
1684/23791107/2379
SBP > 120DBP > 70
SBP at bookingDBP at booking
DBP > 90 mmHg twice 4h apart, after 20 weeks; ≥ ++ dipstick twice 4h apart without urinary tract infection
IN: all nulliparous, singleton pregnancies; EX: pre-existing disease (such as diabetes, severe hypertension, renal disease) or obstetric abnormality (such as multiple gestation)
40
Kyle9
(1993)UK
181828282828
145 (11.7) 11/174/1715/1711/176/172/17
65/128115/12854/128104/128115/128125/128
MAP ≥ 80MAP ≥ 85MAP ≥ 80MAP ≥ 85DBP ≥ 75DBP ≥ 80
ABPM: TM2420 (Japan), cuff size determined by upper arm circumference each visit, seated, left arm, every 15 min awake/ every 30min asleep, at least 20/ 8 valid readings
increase DBP ≥ 25 mmHg to a maximum of DBP ≥ 90 mmHg or more; proteinuria ≥ + dipstick twice
IN: normotensive, no renal disease and not taking medication
Lopez10
(1994)Argentina
3434
1167 (3.3) 16/3810/38
926/11291039/1129
DBP K4DBP K5
4 random-zero sphygmomanometers rotating monthly among centers, calibration every 3 weeks, 10 min rest, lateral position, 5 measurements in each position (lateral/ supine/ seated), K4 and K5, standardised
DBP ≥ 90 mmHg twice 6h apart; proteinuria ≥ 0.3g/L twice 6h apart, random urine specimens
IN: nulliparous, singleton pregnancies, free of clinical/ laboratory evidence of current/previous diseases, not taking any treatment, no history of diabetes mellitus, chronic renal disease, and normal oral glucose tolerance test results (RCT)
Mahanna11 (1983)Italy
17-25 210 (4.8) 9/10 185/200 MAP > 90 Twice n.r. IN: unselected; EX: chronic hypertension
Moutquin12 (1986)Canada
9-1213-1617-2021-2425-289-1213-1617-2021-2425-289-1213-1617-2021-2425-289-1213-1617-2021-2425-28
983 (5.0) 23/4922/4916/4919/4922/4915/4915/498/4910/499/4923/4928/4921/4920/4921/4915/4921/499/4914/4914/49
786/934839/934850/934872/934856/934869/934902/934910/934914/934915/934704/934758/934797/934805/934772/934814/934842/934873/934867/934854/934
DBP > 80DBP > 80DBP > 80DBP > 80DBP > 80DBP > 85DBP > 85DBP > 85DBP > 85DBP > 85SBP > 130SBP > 130SBP > 130SBP > 130SBP > 130SBP > 135SBP > 135SBP > 135SBP > 135SBP > 135
Automated random-zero sphygmomanometer (Dinamap 845), right arm, seated, 5 min rest, at least twice, calibration daily, oscillometric, K4
RR ≥ 140/90 mmHg twice ≥ 6h apart; proteinuria ≥ + albustix twice 6h apart or oedema or serum urate levels (>4.6 mg/dL); RR < 120/80 mmHg 6 weeks postpartum
IN: patients of 3 private obstetricians
Moutquin13 (1992)Canada
9-1213-1617-2021-2425-28
224 (6.3) 6/146/145/141/144/14
200/210202/210206/210206/210208/210
DBP ≥ 89DBP ≥ 89DBP ≥ 89DBP ≥ 89DBP ≥ 89
Automated sphygmomanometer (Dinamap 845*, USA), calibrated, digital, seated, 5 min rest, twice 2 min. interval, K4
RR > 140/90 mmHg or increase 30/15 mmHg twice 6h apart after 20 weeks; proteinuria 0.3g/L twice 6h apart
IN: patients of 3 private obstetricians; singleton, primi/multiparity
Chapter 2
41
Blood pressure and preeclampsia; a m
eta-analysis
Kyle9
(1993)UK
181828282828
145 (11.7) 11/174/1715/1711/176/172/17
65/128115/12854/128104/128115/128125/128
MAP ≥ 80MAP ≥ 85MAP ≥ 80MAP ≥ 85DBP ≥ 75DBP ≥ 80
ABPM: TM2420 (Japan), cuff size determined by upper arm circumference each visit, seated, left arm, every 15 min awake/ every 30min asleep, at least 20/ 8 valid readings
increase DBP ≥ 25 mmHg to a maximum of DBP ≥ 90 mmHg or more; proteinuria ≥ + dipstick twice
IN: normotensive, no renal disease and not taking medication
Lopez10
(1994)Argentina
3434
1167 (3.3) 16/3810/38
926/11291039/1129
DBP K4DBP K5
4 random-zero sphygmomanometers rotating monthly among centers, calibration every 3 weeks, 10 min rest, lateral position, 5 measurements in each position (lateral/ supine/ seated), K4 and K5, standardised
DBP ≥ 90 mmHg twice 6h apart; proteinuria ≥ 0.3g/L twice 6h apart, random urine specimens
IN: nulliparous, singleton pregnancies, free of clinical/ laboratory evidence of current/previous diseases, not taking any treatment, no history of diabetes mellitus, chronic renal disease, and normal oral glucose tolerance test results (RCT)
Mahanna11 (1983)Italy
17-25 210 (4.8) 9/10 185/200 MAP > 90 Twice n.r. IN: unselected; EX: chronic hypertension
Moutquin12 (1986)Canada
9-1213-1617-2021-2425-289-1213-1617-2021-2425-289-1213-1617-2021-2425-289-1213-1617-2021-2425-28
983 (5.0) 23/4922/4916/4919/4922/4915/4915/498/4910/499/4923/4928/4921/4920/4921/4915/4921/499/4914/4914/49
786/934839/934850/934872/934856/934869/934902/934910/934914/934915/934704/934758/934797/934805/934772/934814/934842/934873/934867/934854/934
DBP > 80DBP > 80DBP > 80DBP > 80DBP > 80DBP > 85DBP > 85DBP > 85DBP > 85DBP > 85SBP > 130SBP > 130SBP > 130SBP > 130SBP > 130SBP > 135SBP > 135SBP > 135SBP > 135SBP > 135
Automated random-zero sphygmomanometer (Dinamap 845), right arm, seated, 5 min rest, at least twice, calibration daily, oscillometric, K4
RR ≥ 140/90 mmHg twice ≥ 6h apart; proteinuria ≥ + albustix twice 6h apart or oedema or serum urate levels (>4.6 mg/dL); RR < 120/80 mmHg 6 weeks postpartum
IN: patients of 3 private obstetricians
Moutquin13 (1992)Canada
9-1213-1617-2021-2425-28
224 (6.3) 6/146/145/141/144/14
200/210202/210206/210206/210208/210
DBP ≥ 89DBP ≥ 89DBP ≥ 89DBP ≥ 89DBP ≥ 89
Automated sphygmomanometer (Dinamap 845*, USA), calibrated, digital, seated, 5 min rest, twice 2 min. interval, K4
RR > 140/90 mmHg or increase 30/15 mmHg twice 6h apart after 20 weeks; proteinuria 0.3g/L twice 6h apart
IN: patients of 3 private obstetricians; singleton, primi/multiparity
42
Moutquin14 (1990)Canada
9-12
13-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-36
751 (5.9) 12/44
27/4430/4427/4428/4429/4415/449/4419/4424/4423/4421/4424/448/448/4416/4423/4417/4416/4416/447/443/4410/448/445/447/448/443/44
625/707
449/707365/707363/707304/707467/707535/707658/707558/707491/707531/707532/707590/707637/707677/707598/707559/707591/707602/707626/707655/707703/707679/707670/707680/707687/707692/707693/707
increase DBP > 10(every 4 weeks reference
period)increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30Increase SBP > 30
Automated random-zero sphygmomanometer with digital dysplay (Dinamap 845, USA), oscillometric, daily calibration, seated, 5 min rest, twice 2 min. intervals, K4
RR > 140/90 mmHg twice 6h apart; proteinuria ≥ + dipstick twice 6h apart or generalised oedema; RR < 120/80 mmHg 6 weeks postpartum
IN:primiparae; EX: gestational hypertension, chronic hypertension, liver disease and hypertension,
Odegard15 (2000)Norway
first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)
906 (34.2) 274/310201/31085/310304/311237/31193/311
125/596323/596527/59632/596387/596455/596
SBP > 110SBP > 120SBP > 130DBP > 60DBP > 70DBP > 80
SBP/ DBP DBP > 90 mmHg in addition to increase > 25 mmHg or when baseline DBP > 90 mmHg then increase > 15 mmHg; proteinuria ≥ + dipstick (= 0.3g/L)
IN: Norwegian Medical Birth Registry, delivered in Rogaland Central Hospital (nested case control)
Ohkuchi16 (2003)Japan
1st trimester 1498 (7.3) 36/110 1155/1388 Increase SBP/DBP >30/15 Noninvasive automated measurement (BP-203RV II, Japan), seated, right arm at heart level, K5
SBP ≥ 140 or DBP ≥ 90 mmHg twice; proteinuria + dipstick twice or ++ dipstick once or > 0.3g/24h
IN: normotensive, non-proteinuric
Oney17 (1983)Germany
18-26 200 (10.5) 19/21 113/179 MAP ≥ 90 Auscultatory blood pressure mearsurements, 10 min rest
SBP ≥ 140 or DBP ≥ 90 mmHg twice 6h apart after 24 weeks gestation; proteinuria ≥ 0.3g/24h
IN: normotensive, nulliparous women; EX: cardiovascular disease, urinary infection
Oney18 (1982)Germany
18-26 108 (13.9) 14/15 46/93 MAP > 90 n.r. Gestose index n.r.
Page19
(1976)2nd trimester2nd trimester2nd trimester2nd trimester2nd trimester
14833 (2.7) 375/399337/399265/399174/399100/399
3353/144346500/1443410008/1443412594/1443413848/14434
MAP ≥ 75MAP ≥ 80MAP ≥85MAP ≥ 90MAP ≥ 95
n.r. Hypertension; proteinuria ≥ ++ dipstick or oedema
IN: patients of Child Health and Development Studies (California)
Reiss20
(1987)USA
2nd trimester2nd trimester
60 (50.0) 6/304/30
28/3028/30
MAP > 75MAP > 80
Right arm, resting in left lateral recumbent position, K4
rise DBP > 15 mmHg; proteinuria ≥ + dipstick
IN: hypertensive cases, controls matched for age, race gravidity, parity, an approximate delivery date (case control)
Robrecht21 (1980)Germany
14-2814-28
285 (19.6) 50/5635/56
156/229204/229
MAP ≥ 85MAP > 90
n.r. Gestose index ≥ 1: RR > 140/90 mmHg, proteinuria ≥ 0.5g/24h, pretibial oedema
n.r.
Chapter 2
43
Blood pressure and preeclampsia; a m
eta-analysis
Moutquin14 (1990)Canada
9-12
13-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-369-1213-1617-2021-2425-2829-3233-36
751 (5.9) 12/44
27/4430/4427/4428/4429/4415/449/4419/4424/4423/4421/4424/448/448/4416/4423/4417/4416/4416/447/443/4410/448/445/447/448/443/44
625/707
449/707365/707363/707304/707467/707535/707658/707558/707491/707531/707532/707590/707637/707677/707598/707559/707591/707602/707626/707655/707703/707679/707670/707680/707687/707692/707693/707
increase DBP > 10(every 4 weeks reference
period)increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 10increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase DBP > 15increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 20increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30increase SBP > 30Increase SBP > 30
Automated random-zero sphygmomanometer with digital dysplay (Dinamap 845, USA), oscillometric, daily calibration, seated, 5 min rest, twice 2 min. intervals, K4
RR > 140/90 mmHg twice 6h apart; proteinuria ≥ + dipstick twice 6h apart or generalised oedema; RR < 120/80 mmHg 6 weeks postpartum
IN:primiparae; EX: gestational hypertension, chronic hypertension, liver disease and hypertension,
Odegard15 (2000)Norway
first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)first visit (< 18)
906 (34.2) 274/310201/31085/310304/311237/31193/311
125/596323/596527/59632/596387/596455/596
SBP > 110SBP > 120SBP > 130DBP > 60DBP > 70DBP > 80
SBP/ DBP DBP > 90 mmHg in addition to increase > 25 mmHg or when baseline DBP > 90 mmHg then increase > 15 mmHg; proteinuria ≥ + dipstick (= 0.3g/L)
IN: Norwegian Medical Birth Registry, delivered in Rogaland Central Hospital (nested case control)
Ohkuchi16 (2003)Japan
1st trimester 1498 (7.3) 36/110 1155/1388 Increase SBP/DBP >30/15 Noninvasive automated measurement (BP-203RV II, Japan), seated, right arm at heart level, K5
SBP ≥ 140 or DBP ≥ 90 mmHg twice; proteinuria + dipstick twice or ++ dipstick once or > 0.3g/24h
IN: normotensive, non-proteinuric
Oney17 (1983)Germany
18-26 200 (10.5) 19/21 113/179 MAP ≥ 90 Auscultatory blood pressure mearsurements, 10 min rest
SBP ≥ 140 or DBP ≥ 90 mmHg twice 6h apart after 24 weeks gestation; proteinuria ≥ 0.3g/24h
IN: normotensive, nulliparous women; EX: cardiovascular disease, urinary infection
Oney18 (1982)Germany
18-26 108 (13.9) 14/15 46/93 MAP > 90 n.r. Gestose index n.r.
Page19
(1976)2nd trimester2nd trimester2nd trimester2nd trimester2nd trimester
14833 (2.7) 375/399337/399265/399174/399100/399
3353/144346500/1443410008/1443412594/1443413848/14434
MAP ≥ 75MAP ≥ 80MAP ≥85MAP ≥ 90MAP ≥ 95
n.r. Hypertension; proteinuria ≥ ++ dipstick or oedema
IN: patients of Child Health and Development Studies (California)
Reiss20
(1987)USA
2nd trimester2nd trimester
60 (50.0) 6/304/30
28/3028/30
MAP > 75MAP > 80
Right arm, resting in left lateral recumbent position, K4
rise DBP > 15 mmHg; proteinuria ≥ + dipstick
IN: hypertensive cases, controls matched for age, race gravidity, parity, an approximate delivery date (case control)
Robrecht21 (1980)Germany
14-2814-28
285 (19.6) 50/5635/56
156/229204/229
MAP ≥ 85MAP > 90
n.r. Gestose index ≥ 1: RR > 140/90 mmHg, proteinuria ≥ 0.5g/24h, pretibial oedema
n.r.
44
Rogers22 (1994)HongKong
18-26 220 (6.8) 14/15 125/205 MAP > 68 Dinamap 845A (Critikon Inc), 5-10 min rest in left lateral recumbent position, SBP, DBP and MAP were measured in right arm, resting on patients side, 1 min. intervals until stabilisation of blood pressure
RR ≥ 140/90 mmHg twice 4h apart; proteinuria ≥ ++ dipstick twice (=0.3g/L)
IN: normotensive, primigravid women. EX: congenital malformations
Shaarawy23 (2000)Egypt
2nd trimester 76 (40.8) 16/31 22/45 MAP > 80 Mild preeclampsia: SBP ≥ 140 or increase ≥ 30 mmHg systolic or DBP ≥ 90 or increase > 15 mmHg over baseline in first 20 weeks, proteinuria ≥ 0.3g/24h. Severe preeclampsia: SBP ≥ 160 or DBP ≥ 110 mmHg, proteinuria ≥ 5.0g/24h (oliguria, cerebral or visual disturbances, epigastric pain, pulmonary oedema)
IN: random selection; EX: history of chronic hypertension, diabetes, renal disease, RR > 140/90 mmHg at time of registration, evidence of proteinuria
Sibai24
(1997)USA
13-2113-2113-2113-2113-2113-2113-2113-2113-2113-2113-21
4314 (7.6) 315/326281/326230/326147/32675/32634/326291/326264/326189/326122/32637/326
451/39881116/39881937/39882847/39883385/39883797/3988675/39881148/39882416/39883121/39883714/3988
SBP > 95SBP > 100SBP > 105SBP > 110SBP > 115SBP > 120DBP > 50DBP > 55DBP > 60DBP > 65DBP > 70
Mercury sphygmomanometer, seated, 2 measurements, 1 min apart, mainly K5
DBP ≥ 90 mmHg; proteinuria ≥ + dipstick or ≥ 0.3g/24h
IN: healthy nulliparous women, no medical or obstetrical complications (RCT)
Stamilio25 (2000)USA
1st trimester24-28
1998 (2.5) 17/4914/49
1717/19491731/1949
MAP > 90MAP > 90
Screening Severe preeclampsia: SBP > 160 or DBP < 110 mmHg; proteinuria ≥ +++ dipstick or ≥ 0.3g/24h (oliguria, cerebral or visual disturbances, epigastric pain, pulmonary oedema/ cyanosis)
IN: all singleton pregnancies who underwent 2nd trimester triple screening
Tranquilli26 (2000)Italy
24-30 75 (18.7) 14/14 27/61 ABPM positive SpaceLabs 90207 (USA), 24h, oscillometric, every 30 minutes
RR > 140/90 mmHg; significant proteinuria
IN: primigravid women, normotensive; EX: history of chronic hypertension, fetal/ chromosomal abnormalities
Villar27 (1989)USA
13-2713-2713-2713-27
700 (19.6)700
554 (18.1)700
53/13730/13723/10011/137
450/563503/563422/563527/563
increase DBP ≥ 15increase SBP ≥ 30
increase SBP/DBP ≥ 30/15MAP ≥ 90
n.r. RR ≥ 140/90 mmHg twice ≥ 6h apart or increase 30/15 mmHg; proteinuria.
IN: young normotensive primigravid women
* Studies are cohort studies unless otherwise stated (case control or randomised controlled trial (RCT)). TP true positives; FP false positives; FN false negatives; TN true negatives; SBP systolic blood pressure; DBP diastolic blood pressure; MAP mean arterial pressure (calculated as (SBP+2*DBP)/3); ABPM ambulatory blood pressure monitoring; h hour; IN included; EX excluded.
Chapter 2
45
Blood pressure and preeclampsia; a m
eta-analysis
Rogers22 (1994)HongKong
18-26 220 (6.8) 14/15 125/205 MAP > 68 Dinamap 845A (Critikon Inc), 5-10 min rest in left lateral recumbent position, SBP, DBP and MAP were measured in right arm, resting on patients side, 1 min. intervals until stabilisation of blood pressure
RR ≥ 140/90 mmHg twice 4h apart; proteinuria ≥ ++ dipstick twice (=0.3g/L)
IN: normotensive, primigravid women. EX: congenital malformations
Shaarawy23 (2000)Egypt
2nd trimester 76 (40.8) 16/31 22/45 MAP > 80 Mild preeclampsia: SBP ≥ 140 or increase ≥ 30 mmHg systolic or DBP ≥ 90 or increase > 15 mmHg over baseline in first 20 weeks, proteinuria ≥ 0.3g/24h. Severe preeclampsia: SBP ≥ 160 or DBP ≥ 110 mmHg, proteinuria ≥ 5.0g/24h (oliguria, cerebral or visual disturbances, epigastric pain, pulmonary oedema)
IN: random selection; EX: history of chronic hypertension, diabetes, renal disease, RR > 140/90 mmHg at time of registration, evidence of proteinuria
Sibai24
(1997)USA
13-2113-2113-2113-2113-2113-2113-2113-2113-2113-2113-21
4314 (7.6) 315/326281/326230/326147/32675/32634/326291/326264/326189/326122/32637/326
451/39881116/39881937/39882847/39883385/39883797/3988675/39881148/39882416/39883121/39883714/3988
SBP > 95SBP > 100SBP > 105SBP > 110SBP > 115SBP > 120DBP > 50DBP > 55DBP > 60DBP > 65DBP > 70
Mercury sphygmomanometer, seated, 2 measurements, 1 min apart, mainly K5
DBP ≥ 90 mmHg; proteinuria ≥ + dipstick or ≥ 0.3g/24h
IN: healthy nulliparous women, no medical or obstetrical complications (RCT)
Stamilio25 (2000)USA
1st trimester24-28
1998 (2.5) 17/4914/49
1717/19491731/1949
MAP > 90MAP > 90
Screening Severe preeclampsia: SBP > 160 or DBP < 110 mmHg; proteinuria ≥ +++ dipstick or ≥ 0.3g/24h (oliguria, cerebral or visual disturbances, epigastric pain, pulmonary oedema/ cyanosis)
IN: all singleton pregnancies who underwent 2nd trimester triple screening
Tranquilli26 (2000)Italy
24-30 75 (18.7) 14/14 27/61 ABPM positive SpaceLabs 90207 (USA), 24h, oscillometric, every 30 minutes
RR > 140/90 mmHg; significant proteinuria
IN: primigravid women, normotensive; EX: history of chronic hypertension, fetal/ chromosomal abnormalities
Villar27 (1989)USA
13-2713-2713-2713-27
700 (19.6)700
554 (18.1)700
53/13730/13723/10011/137
450/563503/563422/563527/563
increase DBP ≥ 15increase SBP ≥ 30
increase SBP/DBP ≥ 30/15MAP ≥ 90
n.r. RR ≥ 140/90 mmHg twice ≥ 6h apart or increase 30/15 mmHg; proteinuria.
IN: young normotensive primigravid women
* Studies are cohort studies unless otherwise stated (case control or randomised controlled trial (RCT)). TP true positives; FP false positives; FN false negatives; TN true negatives; SBP systolic blood pressure; DBP diastolic blood pressure; MAP mean arterial pressure (calculated as (SBP+2*DBP)/3); ABPM ambulatory blood pressure monitoring; h hour; IN included; EX excluded.
46
Table 2 Characteristics of studies of blood pressure measurement used to predict preeclampsia in pregnant women at high risk First author (year) Country
Gestation(weeks)
N(% preeclampsia)
SensitivityTP/(TP+FN)
Specificity TN/(FP+TN)
Index test Threshold (mmHg)
Details index test Reference standard preeclampsia
Population (study design)*
Bar28
(1999)Israel
14-28 60 (26.7) 13/16 34/44 ABPM RR ≥135/85
(mean daytime)
ABPM: SpaceLabs 90202 (USA), non-dominant arm, every 30 min;White coat hypertension: standard mercury sphygmomanometer, seated, larger bladder for arms larger than 32 cm, mean of 3 measurements, right arm, being supine for 10min, K5
Increase > 25 mmHg with a maximum value of DBP > 90 mmHg; proteinuria ≥ 0.3g/24h
IN: women with high blood pressure were referred from community clinics; EX: women with normal blood pressure levels
Caritis29 (1998)USA
13-2613-26
2503 (19.8) 445/495319/485
459/20181154/2018
MAP > 75 (baseline)MAP > 85(baseline)
Seated, K5 SBP ≥ 140 or DBP ≥ 90 mmHg twice > 4h apart; ≥ ++ dipstick twice or ≥ 0.3g/24h without urinary tract infection
IN: type 1 diabetes, chronic hypertension, multiple pregnancies, previous preeclampsia (RCT)
Konijnenberg30 (1997)Netherlands
13-20 244 (7.0) 12/17 170/227 DBP ≥ 75 first antenatal DBP, standard sphygmomanometer
DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: women with increased risk: multiple pregnancies, known pre-existing diseases such as hypertension, diabetes mellitus, vasculitis, history of preeclampsia or fetal growth restriction not caused by congenital malformations or infectious fetal diseases
Lauszus31 (2001)Denmark
1st trimester 87 (28.7) 17/25 43/62 RR >122/74 SpaceLabs 90207 (Redmond USA) oscillometry, cuff insufflation every 20 min from 6-23 hrs and every hour during night, non-dominant arm, average of 3 oscillometric and 3 auscultatory (random-zero sphygmomanometer (Haweeksley, Lancing UK)) measurements. Mean of day- and nighttime measurements
DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: pregestational type 1 diabetes patients
Penny32
(1998)UK
> 20 (median 36)> 20 (median 36)> 20 (median 36)> 20 (median 36)
347 (3.7)270 (3.3)347 (3.7)270 (3.3)
4/134/95/135/9
260/334176/261234/334156/261
SBP > 140SBP > 135DBP > 90DBP > 85
Standardised obstetric day unit (ODU) assessment with up to 5 measurements, trained observer, 30 min intervals, conventional mercury sphygmomanometer, K5, seated, encouraged to rest. ABPM: SpaceLabs 90207, 24hr, every 30 min ODU ABPM
RR > 140/90 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR> 135/85 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR > 140/90 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR > 135/85 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24h
IN: chronic hypertensive patients without antihypertensive treatment (proteinuria >2 weeks after index test measurement)
Perini33 (2004)Italy
21-35,4 22 (27.3) 5/6 9/16 MESOR diastolic ≥ 68
24h, every 30 min, diastolic midline estimating statistic of rhythm (MESOR)
SBP ≥ 140 or DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: 17 patients with increased resistance index (> 0.62); 5 patients with history of preeclampsia
Valensise34 (1995)Italy
21-29 (mean 24,6)
48 (2.0) 1/1 30/47 DBP > 68 ABPM, Space labs 90207 (USA), appriopriate cuff, oscillometric, self-calibrating, every 15 min 8-22h/ every 30min 20-8h, mean diastolic blood pressure (M24h DBP)
DBP > 90 mmHg twice consecutive 4h apart; proteinuria ≥ 0.3g/24h
IN: healthy at recruitment, normotensive, high uterine artery resistance index; EX: chronic hypertension, diabetes, renal disease, fetal abnormality, fetal growth restriction, oligohydramnios
* Studies are cohort studies unless otherwise stated (case control or randomised controlled trial (RCT)). TP true positives; FP false positives; FN false negatives; TN true negatives; SBP systolic blood pressure; DBP diastolic blood pressure; MAP mean arterial pressure (calculated as (SBP+2*DBP)/3); ABPM ambulatory blood pressure monitoring; h hour; IN included; EX excluded.
Chapter 2
47
Blood pressure and preeclampsia; a m
eta-analysis
Table 2 Characteristics of studies of blood pressure measurement used to predict preeclampsia in pregnant women at high risk First author (year) Country
Gestation(weeks)
N(% preeclampsia)
SensitivityTP/(TP+FN)
Specificity TN/(FP+TN)
Index test Threshold (mmHg)
Details index test Reference standard preeclampsia
Population (study design)*
Bar28
(1999)Israel
14-28 60 (26.7) 13/16 34/44 ABPM RR ≥135/85
(mean daytime)
ABPM: SpaceLabs 90202 (USA), non-dominant arm, every 30 min;White coat hypertension: standard mercury sphygmomanometer, seated, larger bladder for arms larger than 32 cm, mean of 3 measurements, right arm, being supine for 10min, K5
Increase > 25 mmHg with a maximum value of DBP > 90 mmHg; proteinuria ≥ 0.3g/24h
IN: women with high blood pressure were referred from community clinics; EX: women with normal blood pressure levels
Caritis29 (1998)USA
13-2613-26
2503 (19.8) 445/495319/485
459/20181154/2018
MAP > 75 (baseline)MAP > 85(baseline)
Seated, K5 SBP ≥ 140 or DBP ≥ 90 mmHg twice > 4h apart; ≥ ++ dipstick twice or ≥ 0.3g/24h without urinary tract infection
IN: type 1 diabetes, chronic hypertension, multiple pregnancies, previous preeclampsia (RCT)
Konijnenberg30 (1997)Netherlands
13-20 244 (7.0) 12/17 170/227 DBP ≥ 75 first antenatal DBP, standard sphygmomanometer
DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: women with increased risk: multiple pregnancies, known pre-existing diseases such as hypertension, diabetes mellitus, vasculitis, history of preeclampsia or fetal growth restriction not caused by congenital malformations or infectious fetal diseases
Lauszus31 (2001)Denmark
1st trimester 87 (28.7) 17/25 43/62 RR >122/74 SpaceLabs 90207 (Redmond USA) oscillometry, cuff insufflation every 20 min from 6-23 hrs and every hour during night, non-dominant arm, average of 3 oscillometric and 3 auscultatory (random-zero sphygmomanometer (Haweeksley, Lancing UK)) measurements. Mean of day- and nighttime measurements
DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: pregestational type 1 diabetes patients
Penny32
(1998)UK
> 20 (median 36)> 20 (median 36)> 20 (median 36)> 20 (median 36)
347 (3.7)270 (3.3)347 (3.7)270 (3.3)
4/134/95/135/9
260/334176/261234/334156/261
SBP > 140SBP > 135DBP > 90DBP > 85
Standardised obstetric day unit (ODU) assessment with up to 5 measurements, trained observer, 30 min intervals, conventional mercury sphygmomanometer, K5, seated, encouraged to rest. ABPM: SpaceLabs 90207, 24hr, every 30 min ODU ABPM
RR > 140/90 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR> 135/85 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR > 140/90 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24hRR > 135/85 mmHg; proteinuria ≥ ++ dipstick or ≥ 0.5g/24h
IN: chronic hypertensive patients without antihypertensive treatment (proteinuria >2 weeks after index test measurement)
Perini33 (2004)Italy
21-35,4 22 (27.3) 5/6 9/16 MESOR diastolic ≥ 68
24h, every 30 min, diastolic midline estimating statistic of rhythm (MESOR)
SBP ≥ 140 or DBP ≥ 90 mmHg; proteinuria ≥ 0.3g/24h
IN: 17 patients with increased resistance index (> 0.62); 5 patients with history of preeclampsia
Valensise34 (1995)Italy
21-29 (mean 24,6)
48 (2.0) 1/1 30/47 DBP > 68 ABPM, Space labs 90207 (USA), appriopriate cuff, oscillometric, self-calibrating, every 15 min 8-22h/ every 30min 20-8h, mean diastolic blood pressure (M24h DBP)
DBP > 90 mmHg twice consecutive 4h apart; proteinuria ≥ 0.3g/24h
IN: healthy at recruitment, normotensive, high uterine artery resistance index; EX: chronic hypertension, diabetes, renal disease, fetal abnormality, fetal growth restriction, oligohydramnios
* Studies are cohort studies unless otherwise stated (case control or randomised controlled trial (RCT)). TP true positives; FP false positives; FN false negatives; TN true negatives; SBP systolic blood pressure; DBP diastolic blood pressure; MAP mean arterial pressure (calculated as (SBP+2*DBP)/3); ABPM ambulatory blood pressure monitoring; h hour; IN included; EX excluded.
48
Reference List (1) Ales KL, Norton ME, Druzin ML. Early prediction of antepartum hypertension. Obstet Gynecol
1989; 73(6):928-933. (2) Atterbury JL, Groome LJ, Baker SL. Elevated midtrimester mean arterial blood pressure in
women with severe preeclampsia. Appl Nurs Res 1996; 9(4):161-166. (3) Conde-Agudelo A, Belizan JM, Lede R, Bergel EF. What does an elevated mean arterial pressure
in the second half of pregnancy predict--gestational hypertension or preeclampsia? Am J Obstet Gynecol 1993; 169(3):509-514.
(4) Fallis NE, Langford HG. Relation of second trimester blood pressure to toxemia of pregnancy in the primigravid patient. Am J Obstet Gynecol 1963; 87(1):123-125.
(5) Friedman EA, Neff RK. Systolic and mean arterial blood pressure. In: Friedman EA, Neff RK, editors. Pregnancy Hypertension. A systematic evaluation of clinical diagnostic criteria. Littleton, Massachusetts: PSG Publishing Company Inc; 1977. 212-219.
(6) Higgins JR, Walshe JJ, Halligan A, O’Brien E, Conroy R, Darling MR. Can 24-hour ambulatory blood pressure measurement predict the development of hypertension in primigravidae? Br J Obstet Gynaecol 1997; 104(3):356-362.
(7) Iwasaki R, Ohkuchi A, Furuta I, Ojima T, Matsubara S, Sato I et al. Relationship between blood pressure level in early pregnancy and subsequent changes in blood pressure during pregnancy. Acta Obstet Gynecol Scand 2002; 81(10):918-925.
(8) Knuist M, Bonsel GJ, Zondervan HA, Treffers PE. Risk factors for preeclampsia in nulliparous women in distinct ethnic groups: a prospective cohort study. Obstet Gynecol 1998; 92(2):174-178.
(9) Kyle PM, Clark SJ, Buckley D, Kissane J, Coats AJ, de Swiet M et al. Second trimester ambulatory blood pressure in nulliparous pregnancy: a useful screening test for pre-eclampsia? Br J Obstet Gynaecol 1993; 100(10):914-919.
(10) Lopez MC, Belizan JM, Villar J, Bergel E. The measurement of diastolic blood pressure during pregnancy: which Korotkoff phase should be used? Am J Obstet Gynecol 1994; 170(2):574-578.
(11) Mahanna I, Algeri T, Cigarini C, Zinelli G. [Arterial pressure, MAP and dynamic tests in the monitoring of pregnancy]. Ann Ostet Ginecol Med Perinat 1983; 104(4):248-255.
(12) Moutquin JM, Rainville C, Giroux L, Raynauld P, Amyot G, Bilodeau R et al. A prospective study of blood pressure in pregnancy: prediction of preeclampsia. Am J Obstet Gynecol 1985; 151(2):191-196.
(13) Moutquin JM, Bilodeau R, Raynault P, Amyot G, Blair JF, Labelle L et al. [Prospective study of arterial pressure during pregnancy. Prediction of hypertensive complications]. J Gynecol Obstet Biol Reprod (Paris) 1982; 11(7):833-837.
(14) Moutquin JM, Rainville C, Giroux L, Raynauld P, Bilodeau R, Amyot G et al. Is a threshold increase in blood pressure predictive of preeclampsia? A prospective cohort study. Clin Exp Hypertens B 1990; 9(2):225-235.
(15) Odegard RA, Vatten LJ, Nilsen ST, Salvesen KA, Austgulen R. Risk factors and clinical manifestations of pre-eclampsia. BJOG 2000; 107(11):1410-1416.
(16) Ohkuchi A, Iwasaki R, Ojima T, Matsubara S, Sato I, Suzuki M et al. Increase in systolic blood pressure of > or = 30 mm Hg and/or diastolic blood pressure of > or = 15 mm Hg during pregnancy: is it pathologic? Hypertens Pregnancy 2003; 22(3):275-285.
(17) Oney T, Kaulhausen H. The value of the mean arterial blood pressure in the second trimester (MAP-2 value) as a predictor of pregnancy-induced hypertension and preeclampsia. A preliminary report. Clin Exp Hypertens B 1983; 2(2):211-216.
(18) Oney T, Balogh A, Kaulhausen H. The predictive value of blood pressure and weight gain during pregnancy for the early diagnosis of gestosis/preeclampsia. Preliminary report. [German]. Fortschritte der Medizin 1982; 100(7):277-280.
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Blood pressure and preeclampsia; a m
eta-analysis
(19) Page EW, Christianson R. The impact of mean arterial pressure in the middle trimester upon the outcome of pregnancy. Am J Obstet Gynecol 1976; 125(6):740-746.
(20) Reiss RE, O’Shaughnessy RW, Quilligan TJ, Zuspan FP. Retrospective comparison of blood pressure course during preeclamptic and matched control pregnancies. Am J Obstet Gynecol 1987; 156(4):894-898.
(21) Robrecht D, Schriever M, Rasenack R, Steiner H, Kaltenbach FJ. [The mean blood pressure in the second trimester (map-2) as a valuable aid in the early recognition of the pregnancies with a risk of hypertension (author’s transl)]. Geburtshilfe Frauenheilkd 1980; 40(2):121-124.
(22) Rogers MS, Chung T, Baldwin S. A reappraisal of second trimester mean arterial pressure as a predictor of pregnancy induced hypertension. J Obstet Gynaecol 1994; 14(4):232-236.
(23) Shaarawy M, Abdel-Magid AM. Plasma endothelin-1 and mean arterial pressure in the prediction of pre-eclampsia. Int J Gynaecol Obstet 2000; 68(2):105-111.
(24) Sibai BM, Ewell M, Levine RJ, Klebanoff MA, Esterlitz J, Catalano PM et al. Risk factors associated with preeclampsia in healthy nulliparous women. The Calcium for Preeclampsia Prevention (CPEP) Study Group. Am J Obstet Gynecol 1997; 177(5):1003-1010.
(25) Stamilio DM, Sehdev HM, Morgan MA, Propert K, Macones GA. Can antenatal clinical and biochemical markers predict the development of severe preeclampsia? Am J Obstet Gynecol 2000; 182(3):589-594.
(26) Tranquilli AL, Giannubilo SR, Bezzeccheri V, Garbati E. [The relative weight of Doppler of the uterine artery and 24-h ambulatory blood pressure monitoring in predicting hypertension in pregnancy and preeclampsia]. Acta Biomed Ateneo Parmense 2000; 71 Suppl 1:351-355.
(27) Villar MA, Sibai BM. Clinical significance of elevated mean arterial blood pressure in second trimester and threshold increase in systolic or diastolic blood pressure during third trimester. Am J Obstet Gynecol 1989; 160(2):419-423.
(28) Bar J, Maymon R, Padoa A, Wittenberg C, Boner G, Ben Rafael Z et al. White coat hypertension and pregnancy outcome. J Hum Hypertens 1999; 13(8):541-545.
(29) Caritis S, Sibai B, Hauth J, Lindheimer M, Vandorsten P, Klebanoff M et al. Predictors of pre-eclampsia in women at high risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units. Am J Obstet Gynecol 1998; 179(4):946-951.
(30) Konijnenberg A, van der Post JA, Mol BW, Schaap MC, Lazarov R, Bleker OP et al. Can flow cytometric detection of platelet activation early in pregnancy predict the occurrence of preeclampsia? A prospective study. Am J Obstet Gynecol 1997; 177(2):434-442.
(31) Lauszus FF, Rasmussen OW, Lousen T, Klebe TM, Klebe JG. Ambulatory blood pressure as predictor of preeclampsia in diabetic pregnancies with respect to urinary albumin excretion rate and glycemic regulation. Acta Obstet Gynecol Scand 2001; 80(12):1096-1103.
(32) Penny JA, Halligan AW, Shennan AH, Lambert PC, Jones DR, de Swiet M et al. Automated, ambulatory, or conventional blood pressure measurement in pregnancy: which is the better predictor of severe hypertension? Am J Obstet Gynecol 1998; 178(3):521-526.
(33) Perini R, Fisogni C, Bonera R, Rovetto B, Frusca T, Lojacono A et al. [Role of Doppler velocimetry of uterine arteries and ambulatory blood pressure monitoring in detecting pregnancies at risk for preeclampsia]. Minerva Ginecol 2004; 56(2):117-123.
(34) Valensise H, Tranquilli AL, Arduini D, Garzetti GG, Romanini C. Screening pregnant women at 22-24 weeks for gestational hypertension or intrauterine growth retardation by Doppler ultrasound followed by 24-hour blood pressure recording. Hypertens Pregnancy 1995; 14(3):351-359.
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Chapter 2
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eta-analysis
13Karlijn C. VollebregtJanneke GisolfIlja GuelenKees BoerGert A. van MontfransHans Wolf
Journal of Hypertension 2010;28(1):127-134
Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia
54
ABSTRACT
Objective The aim of this study was to validate the hyperbaric index (HBI) for first trimester prediction
of preeclampsia and gestational hypertension.
Methods
Participants were low-risk and high-risk nulliparous women and high-risk multiparous
women, and were recruited between April 2004 and June 2006. At a gestational age of
9 weeks (range 8 – 11 weeks), blood pressure was measured first by sphygmomanometry
and thereafter by ambulatory blood pressure measurement (ABPM) for 48 h. The first
90 low-risk women who had an uneventful pregnancy formed the reference group for
calculation of a time-specified tolerance interval with 90% confidence limits. In the
validation group, consisting of the remaining women, the HBI was calculated as the
time-specified blood pressure excess over this tolerance limit for SBP, DBP and mean
arterial pressure.
Results
The validation group contained 101 women. Fifteen developed preeclampsia and 13
gestational hypertension. For preeclampsia the maximum HBI had the best predictive
capacity with a sensitivity of 73 % and a specificity of 86 %. However, the difference
with standard ABPM measurement or sphygmomanometry was small with a sensitivity
between 75 % and 73 % and a specificity between 86 % and 95 %. The predictive efficacy
for gestational hypertension predictive capacity was poor with all methods (sensitivity
between 54 % and 77 %, specificity between 41 % and 78 %).
Conclusion
Standardized sphygmomanometry, ABPM measurement and the hyperbaric index
calculated from 48 h ABPM had a comparable, restricted predictive efficacy. The
high predictive value of hyperbaric index as observed in earlier studies could not be
reproduced.
Chapter 3
55
The Hyperbaric Index
INTRODUCTION
Preeclampsia is one of the main causes of maternal and fetal morbidity and mortality
worldwide. 1 The exact pathophysiology is unknown despite extensive research. Many
hypotheses have been proposed and rejected. Although preeclampsia is usually
diagnosed in the second half of pregnancy, it is hypothesized that the disease originates
early in pregnancy with defective placentation.2 Early selection of women at high risk
for this condition could offer the opportunity to target care at those most likely to benefit
and to evaluate or design preventive strategies. However, currently available diagnostic
tests have limited predictive efficacy with likelihood ratio’s for a positive test of 2-5 and
likelihood ratio for a negative test of 0.2–0.8.2-4
Blood pressure measurement as a predictive tool has been the focus of research for many
years. Although women who will develop preeclampsia later in pregnancy have a slightly
higher blood pressure in the beginning of pregnancy5-7 the discriminative capacity of blood
pressure is disappointing, irrespective of blood pressure measurement technique. 4;6;7
Ambulatory blood pressure measurement (APBM) is a well known technique for the
diagnosis and treatment evaluation of hypertension in nonpregnant women. ABPM
correlates better with hypertension-related organ damage and cardiovascular events
than office blood pressure.8 Using ABPM, a higher blood pressure was observed in
mid-pregnancy in women who later experienced the development of preeclampsia or
gestational hypertension. Although the predictive efficacy of ABPM was higher than
standard blood pressure measurement the predictive capacity appeared to low to be
useful in daily clinical practice.6;9-11
Most studies regarding the prediction of preeclampsia or gestational hypertension
present 24-h means. Although some studies report that diurnal differences can be used
for assessing disease severity, usefulness for prediction has not been reported.12;13 A
more sophisticated technique for evaluation of ABPM was presented by Hallberg et al.,
using the hyperbaric index (HBI).14 HBI was calculated as the amount of blood pressure
excess during the measurement period above a 90% tolerance limit expressed as mmHg
multiplied by hour. Studies by Hermida et al. evaluated HBI as a test for prediction
of preeclampsia and gestational hypertension.15-18 These studies observed a sensitivity
of 94% and a specificity of 100% using HBI calculation from 48-h ABPM. Another
group studied HBI, calculated in a different way, in a hospital-based research setting
and observed a sensitivity of 80% and specificity of 77% at 8-16 weeks for gestational
hypertension and preeclampsia.19
56
Because the results from the studies by Hermida et al. seemed promising and the research
setting between all studies differed we decided to perform a validation study in our own
population.15-19
METHODS
Subjects This research is part of a prospective study, which investigates cardiovascular parameters
in the beginning of pregnancy for the prediction of preeclampsia and fetal growth
restriction. Healthy nulliparous women at low risk and women with elevated risk for
preeclampsia or fetal growth restriction were included between April 2004 and June
2006. Low-risk participants were recruited by advertisements in local newspapers and
flyers at midwife practices near our hospital. Women having diabetes, renal disease,
clotting disorders or a previous pregnancy complicated by preeclampsia were defined
as high risk. They were recruited from our antenatal clinic (Academic Medical Center,
Amsterdam, The Netherlands) and by advertisements in local newspapers. At inclusion,
all women had normal blood pressure (less than 140 mmHg SBP and 90 mmHg DBP,
measured auscultatory) and none used antihypertensive medication. Only women with
a singleton pregnancy were included. Three women who delivered an infant with major
congenital malformation were excluded.
After written informed consent was obtained, all participants underwent identical
study protocols. At 8-11 weeks, blood pressure was measured first by conventional
sphygmomanometry and thereafter for 48 h using an ambulatory blood pressure device
(see below). Gestational age was defined by first trimester ultrasound. The results of
the ambulatory blood pressure measurements were not available for the clinicians/
midwives responsible for prenatal care. Pregnancy outcome was classified as ‘gestational
hypertension’, ‘preeclampsia’ or ’normal’ using blood pressure measurements that
were obtained during routine clinical care. Two obstetricians (H.W. and K.B.) who were
unaware of the results of the early gestational blood pressure measurements reviewed
medical files for classification.
The Medical Ethical Committee of the Academic Medical Center approved the study.
Definitions
Gestational hypertension was defined as a systolic blood pressure (SBP) of at least
140, diastolic blood pressure (DBP) of at least 90 mmHg or both after 20 weeks in a
previously normotensive woman, measured twice with an interval of at least 6 h. Blood
pressure was measured under routine clinical conditions. Preeclampsia was defined as
Chapter 3
57
The Hyperbaric Index
the combination of gestational hypertension and proteinuria of at least 0.3 g/ 24 h or
dipstick of at least ++ after 20 weeks gestation according to the International Society for
the Study of Hypertension in Pregnancy (ISSHP) guidelines.20
Instruments
Blood pressure was measured by aired sphygmomanometry in supine position at the
nondominant arm after at least 15 minutes of rest in a quiet room with an ambient
temperature between 20-22° C between 0700 and 1200 h. Korotkoff V was used to
determine DBP. The average of three measurements with an interval of at least 1 minute
was used for calculations. The mean arterial pressure (MAP) was calculated as ((2x DBP)
+ SBP)/3. ABPM was performed by oscillometry (Spacelab 90207, Redmond, Wasington,
USA). An appropriately sized cuff was placed on the non-dominant arm. Blood pressure
was measured every 30 minutes between 06:00 h till midnight and every 60 minutes
between midnight and 0600 h. All women started the measurements between 0700 and
1200 h and continued for 48 consecutive hours. If blood pressure results were missing
for more than 2 h the participant was excluded from further analysis.21 The participants
were instructed to maintain their daily routine and to complete a diary to identify time of
sleeping and awakening. Mean 24-h blood pressure, daytime blood pressure and, night-
time blood pressure using fixed intervals (between 0600 h till midnight and between
midnight and 0600 h) and night to day ratio were calculated.22 Women were defined as
‘dippers’ when their night to day ratio SBP was 0.90 or less.23All women were instructed
and measured by two trained researchers.
Computation of time-specified tolerance interval of blood pressure and hyperbaric index
The calculation of nonparametric tolerance intervals for hybrid time series and HBI was
performed according to the method described by Hermida et al.17;18 Measurement data
from the first 90 nulliparous women who had an uneventful pregnancy and delivered
at term of an infant with normal birthweight24 were used for calculation of the time-
specified tolerance limits (reference group). The remaining 101 women, including those
with gestational hypertension or preeclampsia, constituted the validation group.
On the basis of self-reported sleeping and waking times, data were synchronized at
mid-sleep. Because the time of blood pressure registration differed between participants,
2-hour time classes were defined at each complete hour of day (running from one before
to one hour after each complete hour), resulting in overlapping time classes. Individual
data were averaged per time class, producing one blood pressure result per individual
per time class. For each time class, the 90% confidence limits were calculated across all
participants. Because the reference group was small and normality and symmetry of the
58
data could not be assumed, a nonparametric approach was chosen using bootstrapping,
as described by Hermida et al.17 The tolerance interval was calculated to include at least
a specified proportion of the population (1-β) with a stated confidence (1-α). We chose
to compute for given time class a tolerance interval which included at least 90% of the
population with a confidence of 90% (β= 0.1 and α = 0.1). The assumption was that the
sample was a reasonable representation of the underlying population. Data in each time
class was bootstrapped (resampled with replacement); the bootstrapped data contained
the same number of records as the original sample. Bootstrapping was repeated until
the standard error of the mean (SEM) was less than 1% of the mean (the Monte Carlo
stopping rule).
For computing tolerance intervals, the mean and variance of the sample and of each
of the bootstrapped resample were calculated. For each resample a lower (ß/2, e.g.
5%) and upper (1- ß/2, e.g. 95%) percentile was determined, thus creating a large
number of upper and lower limits for each time class (one for each bootstrap resample).
Because we were interested in the proportion of the population with confidence 1- α,
from all the (bootstrap) lower percentiles, the 1-√(1- α) percentile was determined: the
lower tolerance limit. From the upper percentiles, the √(1- α) percentile was determined:
the upper tolerance limit. There is √(1- α) probability that a sample from the specified
population lies over the upper tolerance limit; there is also √(1- α) probability that the
130
120
110
100
90
0 500 1000 1500
100
90
80
70
600 500 1000 1500
110
100
90
80
70
60
500 500 1000 1500
80
70
60
50
0 500 1000 1500
SBP
(mm
Hg)
MAP
(mm
Hg)
Relative time of day [min] Relative time of day [min]
Relative time of day [min] Relative time of day [min]
DBP
(mm
Hg)
Hea
rt ra
te (b
pm)
Figure 1. Time-specified tolerance intervals with 90% confidence limits for SBP, DBP, mean arterial pressure and heart rate in the reference population (n=90) synchronized at midsleep.
Chapter 3
59
The Hyperbaric Index
sample lies under the lower tolerance limit: the probability that the sample lies between
both tolerance limits is therefore 1- α (rule of conditional probability). Upper and lower
tolerance intervals were computed for all time classes, see figure 1.
The size of the reference population was determined by stepwise increment of the
reference population by 10 women and calculation of the standard error (SE) of the
90th percentile tolerance limit. After a group size of 70, further increase resulted in a
variation of the SE of less than 2 mmHg. Therefore calculations of the tolerance limits
were discontinued at a group size of 90.
The HBI was calculated for the SBP, DBP and MAP as the individual excess above the
reference threshold (the upper limit of the tolerance interval) using numerical integration
(for an example see figure 2). HBImax was defined as the maximum value of either the HBI
90
80
70
MAP
(mm
Hg)
100
0 500 1000 1500Relative time of day (min)
Figure 2. Plot of the mean arterial pressure of a women with elevated hyperbaric index. The dashed line is the upper 90th percentile tolerance limit of the MAP. The curve starts at midsleep. The continious line is the individual pressure. Marked area is the hyperbaric index.
of SBP, DBP or MAP for each individual. Time-specified tolerance intervals and HBI were
calculated using Matlab® R2007b (The Mathworks, Inc, Natick, Massachusetts, USA).
One-way analysis of variance was used to determine differences between the outcome
groups and multiple post hoc comparisons were performed by Bonferroni t-test or
Kruskal -Wallis test as appropriate. Receiver Operator Characteristics (ROC) curves
were constructed to test the discriminate value of sphygmomanometry measurements,
chronobiological blood pressure parameters and the HBI in predicting gestational
hypertension, preeclampsia or both. We considered an area under the curve less than
0.75 as poor discriminative capacity. Between 0.75-0.90 was considered as fair and
between 0.90-0.97 was considered as good. The optimal cut-off value was chosen using
the maximum Youden index (sensitivity + specificity - 1).25 Statistical calculations were
performed with SPSS 16.0.2(SPSS Inc.Chicago, Illinois, USA). The level of significance
used was a P value of les than 0.05.
Study size calculation was based on the test characteristics observed by Hermida et
al.16;17 We expected that HBI could predict preeclampsia with a sensitivity and specificity
60
of 0.9 or higher. One hundred women with an incidence of preeclampsia of 7 % would
be necessary to determine a statistically significant predictive effect with an α equal to
0.05 and a β equal to 0.8, calculated by chi square test, tested two-sided. Exclusion of
the first 90 women with uneventful pregnancies, who were selected for calculation of
tolerance limits, was expected to increase the incidence of preeclampsia, which would
elevate the power of our analysis. Sensitivity, specificity and area under the ROC curve
are independent of incidence and therefore not influenced by this selection.
Table 1.Characteristics of the reference group and study populationReference population
n=90
Normotensive women n=73
Gestational hypertension
n=13Preeclampsia
n=15
Age(years) 30.2 ± 3.7 30.5 ± 4.1 32.4 ± 2.9 29.1 ± 4.5
BMI(kg/m2) 23.7 ± 3.2 23.8 ± 3.9 25.6 ± 3.0 27.3 ± 4.2*
High risk women(%) 0% 37% 31% 53%
History of preeclampsia(%) 0% 26% 23 % 47 %
Nulliparous(%) 100% 67 % 69 % 47 %
Sphygmomanometry
SBP(mmHg) 104 ± 9 103 ± 10 110 ± 9 114 ± 15*
DBP(mmHg) 61 ± 7 61 ± 7 66 ± 7 69 ± 12*
MAP(mmHg) 76 ± 7 75 ± 7 81 ± 8‡ 84 ± 13*
Mean ABPM
SBP(mmHg) 110 ± 12 111 ± 7 114 ± 8 119 ± 14*
DBP(mmHg) 65 ± 4 65 ± 5 69 ± 6 72 ± 9*
MAP(mmHg) 80 ± 5 83 ± 5 86 ± 7 90 ± 10*
HBI
SBP(mmH x hour) 4.1 ± 17 6.0 ± 22 4.9 ± 9 43.0 ± 54*†
DBP(mmH x hour) 2.9 ± 9 8.0 ± 40 26.2 ± 54 46.7 ± 52*
MAP(mmH x hour) 2.8 ± 9 7.3 ± 36 20.6 ± 41 49.0 ± 57*
Dippers 56% 48% 54% 60%
Gestational age at delivery(weeks) 40.1 ± 1.1 38.7 ± 2.6 39.4 ± 1.6 34.6 ± 3.6*†
Delivery < 37 weeks 0% 16,4% 7.7% 53.3% *†
Birthweight (g) 3616 ± 420 3122 ± 607 3316 ± 602 1959 ± 828*†
Small for gestational age(%) 0 24.7 30.8 73.3*†
Variables are expressed as mean ± SD or percentage. All measurements were in the first trimester of pregnancy except pregnancy outcome GH: gestational hypertension. PE: preeclampsia, SBP: systolic blood pressure, DBP: diastolic blood pressure, MAP: mean arterial pressure, Mean ABPM: mean 24h blood pressure measured with ambulatory blood pressure monitoring.*uncomplicated vs. preeclampsia P<0.05, † gestational hypertension vs. preeclampsia P<0.05, ‡ uncomplicated vs. gestational hypertension P<0.05
Chapter 3
61
The Hyperbaric Index
RESULTS
Two hundred and nineteen women participated in the study. The mean gestational age
at the beginning of the measurements was 9 weeks and 3 days (SD 6 days). Data of
28 women were not usable because of missing measurements or failure of the device.
The main reason for missing measurements was discontinuation of wearing the device
because women could not sleep with the device. After calculation of the time specified
tolerance intervals with 90% confidence limits using measurements in the first 90
nulliparous women the data of the remaining 101 women were available for evaluation
of the method. Patient characteristics of the study population are given in table 1. In
the validation group 38 high risk women were included; 36 women had preeclampsia
in a previous pregnancy, 1 woman had diabetes mellitus, and 1 woman had severe
fetal growth retardation in a previous pregnancy. Seventy-three women had normal
blood pressure throughout pregnancy, 13 developed gestational hypertension and 15
preeclampsia (Table 1).
30 40 50 60 70 80 90 100
HBI max
HBI MAP
HBI DBP
HBI SBP
ABPM MAP
ABPM DBP
ABPM SBP
MAP
DBP
SBP
20
Sensitivity 95% Cl
Specificity 95% Cl
40 60 80 100
HBI max
HBI MAP
HBI DBP
HBI SBP
ABPM MAP
ABPM DBP
ABPM SBP
MAP
DBP
SBP
Preeclampsia(a) (b) Gestational Hypertention
Figure 3. (a) Sensitivity and specificity of sphygmomanometry, ambulatory blood pressure monitoring and Hyperbaric index for predicting preeclampsia with 95% confidence interval. (b) Sensitivity and specificity of sphygmomanometry, ABPM and HBI for predicting gestational hypertension with 95% CI. ABPM, ambulatory blood pressure monitoring; CI, confidence interval; DBP, diastolic blood pressure; HBI, hyperbaric index; MAP, mean arterial pressure; SBP, systolic blood pressure.
62
BMI, blood pressure measurements with sphygmomanometry and ABPM, and HBI differed
significantly between normotensive women and women who developed preeclampsia
(Table 1). Only sphygmomanometry MAP differed significantly between normotensive
women and women who developed gestational hypertension. The ratio of day time and
night time blood pressure and the percentage of ‘dippers’ were not significantly different
between the groups.
Sphygmomanometry, mean ABPM and HBI had a comparable discriminative efficacy for
gestational hypertension (sensitivity between 54 and 77%, specificity between 41 and
78%), see figure 3B. Only MAP and DBP had a statistically significant effect. The area
under the curve for all parameters was between 0.57 and 0.66 which signifies poor test
characteristics.
The results of the different measurement techniques for the prediction of preeclampsia
did not vary largely (sensitivity between 53 and 73%, specificity between 86 and 95%),
see figure 3A. All results reached statistical significance. HBImax had the best discrimination
of preeclampsia with an area under the curve of 0.77(95% CI 0.61-0.92), which can be
classified as fair. The effect of all parameters was statistically significant and the area under
the curve was between 0.71 and 0.77. Differences between the parameters were only
small; in figure 4 and 5 ROC curves for the best parameter of each method are shown.
Preeclampsia
1 - Specificity
0,0 0,2 0,4 0,6 0,8 1,0
Sens
itivi
ty
0,0
0,2
0,4
0,6
0,8
1,0
SBPMAPHBI
MAPMAX
Gestational hypertension
1 - Specificity0,0 0,2 0,4 0,6 0,8 1,0
Sens
itivi
ty
0,0
0,2
0,4
0,6
0,8
1,0
HBIABPMMAP
MAXDBP
Figure 4. Receiver operator characteristic curve for the parameter with the highest area under the curve for predicton of preeclampsia for each method. ABPM, ambulatory blood pressure monitoring; HBI, hyperbaric index; MAP, mean arterial pressure; SBP, systolic blood pressure.
Figure 5. Receiver operator characteristic curve for the parameter with the highest area under the curve for predicton of preeclampsia for each method. ABPM, ambulatory blood pressure monitoring; HBI, hyperbaric index; MAP, mean arterial pressure; SBP, systolic blood pressure.
Chapter 3
63
The Hyperbaric Index
The optimum cut-off value for HBI was a HBImax of 17.6 mmHg x hour resulting in
a sensitivity of 73% (95% CI 48-89%) and a specificity of 86% (95% CI 77-92). The
optimum cut-off value for sphygmomanometry was a SBP of 118 mmHg corresponding
with a sensitivity of 60% (95% CI 36-81%) and a specificity of 92% (95% CI 84-96%).
Discussion
We could not reproduce the high predictive value of HBImax as observed by Hermida
and co-workers, although we used a similar method for calculation of the reference and
validation values.15-18
We calculated the time-specified tolerance intervals with 90% confidence limits in our
own population using measurements of 90 healthy nulliparous women with an uneventful
pregnancy according to the method as described by Hermida et al.17;18 Group size for
the reference population was similar to that used by Hermida et al. in their first trimester
reference graph (n=78).26 Comparison of our reference graphs with those used by
Hermida et al. demonstrates a slightly higher SBP and DBP in our reference data, while
MAP was comparable. Differences could origin from an earlier gestational age in our
study or from ethnic differences (Mediterranean vs. Northern Europe). It was therefore
more appropriate to use reference values that are specific for our population and not
those published by Hermida et al.26
The HBI cut-off used by Hermida et al.was comparable with the cut-off calculated using
ROC curve analysis (15 vs. 18 mmHg x hour) and using either value offered comparable
predictive characteristics (sensitivity 73 vs. 73 %, specificity 85 vs. 86%). The difference in
study outcome can, therefore, not be explained by differences in calculation of reference
values.
Blood pressure was measured with the same blood pressure device as used by Hermida
et al.16 The Spacelab 90207 is the only device for ABPM that was validated extensively in
pregnant women. In three studies the device passed the Association for the Advancement of
Medical Instrumentation (AAMI) criteria. However, following British Hypertension Society
(BHS) criteria, these studies graded the device as B/B, A/C and B/C respectively.27-29
We decided to use the Spacelab, notwithstanding these conflicting results, as it was used
by the group whose method we wanted to validate and as no other ABPM device was
described with better characteristics for pregnant women at the beginning of our study.
In our study, all nulliparous women and all women with high obstetric risk, who visited
our outpatient clinic for antenatal care early enough for participation, were invited for the
study. However, the method for recruitment in the study of Hermida, the percentage of
64
nulliparous or high-risk women and precise gestational age when women were measured
in the first trimester was not described.
Participants in the study by Hermida et al. were examined at 4-week intervals and part
of the participants contributed twice to the reference graph or the validation study.15;26
We only measured women once between 8 and 11 weeks of pregnancy. Because blood
pressure lowers in the first half of pregnancy a close range of time of the measurements
should only improve predictive characteristics. Although population differences or
selection bias could explain part of the differences in outcome between the study by
Hermida et al 15;26and our study, we have insufficient data to support this supposition.
One other study investigated chronobiological analysis in the first trimester of pregnancy
for prediction of gestational hypertension or preeclampsia.19 This study included 104
women with moderate to high risk for hypertensive complications of pregnancy. Most
women had a history of preeclampsia and also twin pregnancies were allowed. Participants
were examined between 8 and 16 weeks in a hospital-based research setting. The best
predictive parameter in the 8-16 week period was systolic HBI at a cut-off of 5 mmHg/
hour with a sensitivity of 80% and a specificity of 77%. The method for calculating HBI
differed from the method used by Hermida et al.17 and in our study.
Blood pressure is widely used for screening in pregnancy for hypertensive disorders but
the results, as a predictive tool early in pregnancy, are conflicting. A recent systematic
review of literature showed poor predictive accuracy for preeclampsia by measurement
of SBP, DBP, MAP, and increase of blood pressure with the best results for a MAP of at
least 90 mmHg, LR+ of 3.5 (95% CI 2.0-5.0) and LR- of 0.46 (95% CI 0.16-0.75).4
In six of the 34 included studies blood pressure measurement was performed in the first
trimester. The test characteristics of these studies were comparable to the remaining
studies. The two studies targeted at a high risk population had similar characteristics as
the remaining studies. Differences between nulliparous and multiparous women were not
assessed. These findings supported that the combination of high risk women and low risk
nulliparous women in our study is valid. The outcome of our study is comparable with
findings in this meta-analysis. Although a more sophisticated measurement technique as
proposed by Hermida et a.l15 results in slightly better characteristics than obtained in most
studies, the extremely high sensitivity and specificity as reported should be considered as
an overestimation.
A 48-h ambulatory blood pressure measurement is generally considered as a burden.
In our study, 13 % of the registrations were inadequate for analysis, sometimes because
of device failure but mostly because of missing measurements for a couple of hours.
These women discontinued wearing the device because they perceived this as too
much of a strain. Our number of dropouts is comparable to a study which investigated
Chapter 3
65
The Hyperbaric Index
patient satisfaction with the Spacelab 90207 in pregnant women.30 Sleep disturbance
was the main reason for noncompliance in this study, which was similar in our study.
Sphygmomanometry measurements are easy to perform and take only a couple of
minutes. The predictive efficacy was comparable with the hyperbaric index in our study. It
should be noted that auscultatory blood pressure measurement was performed according
to a standardized procedure, after sufficient rest in supine position and by averaging
three consecutive measurements. This differs from standard outpatient clinic procedure,
explaining better predictive characteristics than observed in most studies.4 DBP is slightly
lower in supine position than in sitting position, while SBP is similar.31 As this difference
is independent of blood pressure level or body mass index, and as we used ROC curve
analysis for determining the optimum cut-off in our population, this difference in position
could not have influenced our results
CONCLUSION
The accuracy of first trimester prediction of preeclampsia or gestational hypertension by
blood pressure measurement alone is insufficient for clinical use. Although blood pressure
is higher early in pregnancy in women who will develop preeclampsia standardized
sphygmomanometry, mean ABPM and HBI calculation from 48-h ABPM had a
comparable, restricted predictive efficacy. We could not confirm the high predictability of
the hyperbaric index using 48-h ABPM for preeclampsia or gestational hypertension as
observed by Hermida et al. 15
66
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death: a systematic review. Lancet 2006; 367(9516):1066-1074. (2) Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005; 365(9461):785-799. (3) Conde-Agudelo A, Villar J, Lindheimer M. World Health Organization systematic review of
screening tests for preeclampsia. Obstet Gynecol 2004; 104(6):1367-1391. (4) Cnossen JS, Vollebregt KC, de VN, Ter RG, Mol BW, Franx A et al. Accuracy of mean arterial
pressure and blood pressure measurements in predicting pre-eclampsia: systematic review and meta-analysis. BMJ 2008; 336(7653):1117-1120.
(5) Sibai BM, Ewell M, Levine RJ, Klebanoff MA, Esterlitz J, Catalano PM et al. Risk factors associated with preeclampsia in healthy nulliparous women. The Calcium for Preeclampsia Prevention (CPEP) Study Group. Am J Obstet Gynecol 1997; 177(5):1003-1010.
(6) Brown MA, Bowyer L, McHugh L, Davis GK, Mangos GJ, Jones M. Twenty-four-hour automated blood pressure monitoring as a predictor of preeclampsia. Am J Obstet Gynecol 2001; 185(3):618-622.
(7) Moutquin JM, Rainville C, Giroux L, Raynauld P, Amyot G, Bilodeau R et al. A prospective study of blood pressure in pregnancy: prediction of preeclampsia. Am J Obstet Gynecol 1985; 151(2):191-196.
(8) Mancia G, De BG, Dominiczak A, Cifkova R, Fagard R, Germano G et al. 2007 Guidelines for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2007; 25(6):1105-1187.
(9) Higgins JR, Walshe JJ, Halligan A, O’Brien E, Conroy R, Darling MR. Can 24-hour ambulatory blood pressure measurement predict the development of hypertension in primigravidae? Br J Obstet Gynaecol 1997; 104(3):356-362.
(10) Tranquilli AL, Giannubilo SR, Dell’Uomo B, Corradetti A. Prediction of gestational hypertension or intrauterine fetal growth restriction by mid-trimester 24-h ambulatory blood pressure monitoring. Int J Gynaecol Obstet 2004; 85(2):126-131.
(11) Perini R, Fisogni C, Bonera R, Rovetto B, Frusca T, Lojacono A et al. Role of Doppler velocimetry of uterine arteries and ambulatory blood pressure monitoring in detecting pregnancies at risk for preeclampsia. Minerva Ginecol 2004; 56(2):117-123.
(12) Benedetto C, Zonca M, Marozio L, Dolci C, Carandente F, Massobrio M. Blood pressure patterns in normal pregnancy and in pregnancy-induced hypertension, preeclampsia, and chronic hypertension. Obstet Gynecol 1996; 88(4 Pt 1):503-510.
(13) Steyn DW, Odendaal HJ, Hall DR. Diurnal blood pressure variation in the evaluation of early onset severe pre-eclampsia. Eur J Obstet Gynecol Reprod Biol 2008; 138(2):141-146.
(14) Halberg F, Ahlgren A, Haus E. Circadian systolic and diastolic hyperbaric indices of high school and college students. Chronobiologia 1984; 11(3):299-309.
(15) Hermida RC, Ayala DE, Mojon A, Fernandez JR, Silva I, Ucieda R et al. Blood pressure excess for the early identification of gestational hypertension and preeclampsia. Hypertension 1998; 31(1):83-89.
(16) Hermida RC, Ayala DE, Fernandez JR, Mojon A, Iglesias M. Prospective evaluation of the hyperbaric-tolerance test for the diagnosis of gestational hypertension and preeclampsia. Med Clin (Barc ) 2004; 123(5):161-168.
(17) Hermida RC, Fernandez JR. Computation of time-specified tolerance intervals for ambulatorily monitored blood pressure. Biomed Instrum Technol 1996; 30(3):257-266.
(18) Hermida RC, Mojon A, Fernandez JR, Ayala DE. Computer-based medical system for the computation of blood pressure excess in the diagnosis of hypertension. Biomed Instrum Technol 1996; 30(3):267-283.
Chapter 3
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(19) Benedetto C, Marozio L, Giarola M, Chiarolini L, Maula V, Massobrio M. Twenty-four hour blood pressure monitoring in early pregnancy: is it predictive of pregnancy-induced hypertension and preeclampsia? Acta Obstet Gynecol Scand 1998; 77(1):14-21.
(20) Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001; 20(1):IX-XIV.
(21) Hermida RC, Ayala DE. Sampling requirements for ambulatory blood pressure monitoring in the diagnosis of hypertension in pregnancy. Hypertension 2003; 42(4):619-624.
(22) Verdecchia P, Angeli F, Sardone M, Borgioni C, Garofoli M, Reboldi G. Is the definition of daytime and nighttime blood pressure prognostically relevant? Blood Press Monit 2008; 13(3):153-155.
(23) Staessen JA, Thijs L, Fagard R, O’Brien ET, Clement D, De Leeuw PW et al. Predicting cardiovascular risk using conventional vs ambulatory blood pressure in older patients with systolic hypertension. Systolic Hypertension in Europe Trial Investigators. JAMA 1999; 282(6):539-546.
(24) Gardosi J, Chang A, Kalyan B, Sahota D, Symonds EM. Customised antenatal growth charts. Lancet 1992; 339(8788):283-287.
(25) Youden WJ. Index for rating diagnostic tests. Cancer 1950; 3(1):32-35. (26) Hermida RC, Ayala DE, Mojon A, Fernandez JR, Silva I, Ucieda R et al. High sensitivity test
for the early diagnosis of gestational hypertension and preeclampsia. IV. Early detection of gestational hypertension and preeclampsia by the computation of a hyperbaric index. J Perinat Med 1997; 25(3):254-273.
(27) Shennan AH, Kissane J, de Swiet M. Validation of the SpaceLabs 90207 ambulatory blood pressure monitor for use in pregnancy. Br J Obstet Gynaecol 1993; 100(10):904-908.
(28) O’Brien E, Darling M, Higgins J. Ambulatory blood pressure measurement in pregnancy. Br J Obstet Gynaecol 1994; 101(5):462-463.
(29) Franx A, van der Post JAM, van Montfrans GA, Bruinse HW. Comparison of an Auscultatory Versus an Oscillometric Ambulatory Blood Pressure Monitor in Normotensive, Hypertensive, and Preeclamptic Pregnancy.
(30) Walker SP, Permezel MJ, Brennecke SP, Tuttle LK, Higgins JR. Patient satisfaction with the SpaceLabs 90207 ambulatory blood pressure monitor in pregnancy. Hypertens Pregnancy 2004; 23(3):295-301.
(31) Netea RT, Smits P, Lenders JW, Thien T. Does it matter whether blood pressure measurements are taken with subjects sitting or supine? J Hypertens 1998; 16(3):263-268.
14Karlijn C. VollebregtKees BoerJoris A.M. van der PostHans Wolf
Submitted
The association of three different techniques to measure blood pressure in the first trimester of pregnancy with later preeclampsia
70
ABSTRACT
Blood pressure (BP) in the first trimester has limited efficacy for the prediction of
preeclampsia. It is not known if automated devices perform better in this respect than
conventional sphygmomanometry. This study compares two different automated devices
(continuous finger arterial pressure waveform registration and ambulatory blood pressure
monitoring (ABPM)) with conventional sphygmomanometry for their association with later
preeclampsia and gestational hypertension. In a cohort of 289 healthy normotensive
women (235 nulliparous and 44 parous women with previous preeclampsia) at 8 0/7-11 0/7 weeks of pregnancy BP was significantly higher in women, who developed
preeclampsia with all three methods. After adjustment for previous preeclampsia the point
estimate of the Odds ratios for association with later preeclampsia of both automated
devices was better than conventional sphygmomanometry although differences were
not statistically significant. Odds ratio (95% confidence intervals) for every 1 mmHg
pressure increase of MAP was 1.08 (1.02-1.15) for sphygmomanometry, 1.17 (1.09-
1.27) for finger arterial pressure waveform registration and 1.17 (1.07-1.27) for ABPM.
Since patient compliance with ABPM was less, we concluded that finger arterial pressure
waveform registration is potentially the most useful device in first pregnancy trimester
screening and needs further evaluation.
Chapter 4
71
Blood pressure measurem
ents and later preeclampsia
INTRODUCTION
Women who develop preeclampsia have a higher blood pressure in the first trimester
of pregnancy compared to women whose pregnancy remains uncomplicated. 1;2 This
association holds when only women with a blood pressure in the normal range are
considered.3;4 Selection in early pregnancy of women at high risk for preeclampsia
could facilitate preventive interventions and could enable targeting intensive care at
those women who need this most. The predictive capacity of blood pressure has been
meta-analysed and 34 studies including 60599 women with 3341 cases of preeclampsia
showed a moderate predictive accuracy.5 Poor reporting of study populations, definitions
of preeclampsia and the use of different methods of blood pressure assessment and
devices were identified as sources of variation in this meta-analysis. No separate analysis
was performed for studies that used automated devices.
In pregnancy blood pressure is generally measured by conventional sphygmomanometry
and therapeutic interventions are based on these measurements. This technique is
questioned because blood pressure is measured only during a single heart beat cycle, is
subject to inter-observer variation and does not account for beat-to-beat variation and
diurnal rhythm in blood pressure. Automated devices with continuous or repeated diurnal
measurement might have a higher precision for the prediction of later preeclampsia.6
In the present study we compared blood pressure measurement at 8 0/7-11 0/7 weeks
of pregnancy using continuous finger arterial waveform registration and ambulatory
blood pressure monitoring with conventional sphygmomanometry. Our hypothesis
was that blood pressure measurement by automated devices in early pregnancy has
a higher association with the development of later preeclampsia than conventional
sphygmomanometry.
SUBJECTS AND METHODS
Study populationThis study is part of a prospective study which investigates cardiovascular parameters in the
beginning of pregnancy for the prediction of preeclampsia.7 Healthy nulliparous women
and healthy parous women with a previous pregnancy complicated by preeclampsia
were included between April 2004 and June 2006. Women with multiple pregnancy or a
pregnancy after hormonal fertility treatment, and women with diabetes, chronic hypertension,
antihypertensive medication or renal disease were not eligible. All women had normal blood
pressure (less than 140 / 90 mmHg, measured by conventional sphygmomanometry) at
72
their first visit. Preventive use of acetylsalicylic acid in women with a previous preeclampsia
was allowed. Women with an infant with major congenital malformations were excluded
from analysis. Women with pregnancy associated complications like gestational diabetes,
preterm birth or fetal growth restriction were not excluded.
Participants were recruited by advertisements in local newspapers, flyers at midwife
practices near our hospital and from our outpatient clinic. The Medical Ethical Committee
of the Academical Medical Center approved the study.
Outcome definitions
Pregnancy outcome was defined as preeclampsia or combined pregnancy outcome
(preeclampsia and gestational hypertension). Two obstetricians (KB and HW) being
unaware of the results of the measurements classified pregnancy outcome according to
the ISSHP guidelines.8 Gestational hypertension was defined as a systolic blood pressure
≥ 140 and / or a diastolic blood pressure ≥ 90 mmHg after 20 weeks in a previously
normotensive woman, measured twice with an interval of at least 6 hours. Preeclampsia
was defined by the combination of gestational hypertension and proteinuria ≥ 0,3 g/ 24
h or dipstick ≥ ++ after 20 weeks gestation.
Study design
After written informed consent, all participants underwent identical study protocols
at 8 0/7-11 0/7 weeks gestational age. Gestational age was defined by first trimester
ultrasonography. Women were asked about medical history, maternal age, ethnic origin
(Caucasian or other) and education (high: university or higher; median: higher or
intermediate vocational training or low: no education, primary school or lower vocational
training). The maternal weight and length were measured and the Body Mass Index (BMI)
was calculated as weight (kg)/ (length (m)) 2. Study measurements were not available for
the clinicians or midwives responsible for prenatal care. All participants received usual
obstetric care, nulliparous women by a midwife and women with previous preeclampsia
by our outpatient clinic according to our local protocol.
Measurements
Blood pressure was measured by finger arterial pressure waveform registration (Finometer,
FMS, Amsterdam, the Netherlands) in supine position after at least 15 minutes of rest
in a quiet room with an ambient temperature between 20-22° Celsius, between 7
and 12 AM. The device was validated in pregnancy and passed the Association for
the Advancement of Medical Instrumentation (AAMI) criteria. According to the British
Hypertension Society (BHS) criteria, the device was graded a B for diastolic and a C for
systolic blood pressure.9 A cuff of appropriate size was placed around the middle finger
Chapter 4
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Blood pressure measurem
ents and later preeclampsia
of the non-dominant hand with the arm along the body. Hydrostatic height correction was
used to correct for the position of the hand with respect to heart level. At a stable signal
the pressure signal was corrected by the return-to-flow method.10 Data collection was
performed over a period of 10 minutes after the signal was stable for at least 5 minutes.
The brachial arterial pressure was reconstructed from the finger pulse wave.11Offline
beat to beat systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial
pressure (MAP) and heart rate were extracted by Beatscope software (TNO Biomedical
Instrumentation, Amsterdam, the Netherlands) and averaged over 10 minutes.
Subsequently blood pressure was measured using conventional sphygmomanometry
(Maxi Stabil 3, an aneroid sphygmomanometer, Welch Allyn, Skaneateles Falls, New
York, USA), in the same position at both arms; Korotkoff V was used to determine DBP. If
there were little differences, further measurements were done at the non-dominant arm
else the woman was excluded. The average of three measurements with an interval of at
least 1 minute was used for calculations. The MAP was calculated as ((2x DBP) + SBP)/3.
Thereafter participants were instructed to measure blood pressure with an ambulatory
blood pressure monitor (ABPM; Spacelab 90207TM, Spacelabs Inc. Redmond,
Washington, USA) using oscillometry. The Spacelab 90207 is the only ABPM that was
validated extensively in pregnant women. In three studies the device passed the Association
for the Advancement of Medical Instrumentation (AAMI) criteria. Following British
Hypertension Society (BHS) criteria, these studies graded the device for systolic / diastolic
blood pressure as B/B, A/C and B/C respectively.12-14 An appropriately sized cuff was
placed on the non-dominant arm. Blood pressure was measured every 30 minutes
between 6:00 AM and 00:00 and every 60 minutes between 00:00 and 6:00 AM. All
women started the measurements between 7:00 AM and 12:00 AM and continued for
48 consecutive hours.15 The participants were instructed to maintain their daily routine.
Statistical analysis
Continuous variables were analyzed with the Kolmogorov-Smirnov test for normality.
Normally distributed data are presented as mean ± standard deviation (SD), not
normally distributed data as median (range). To investigate the differences between
the groups, one-Way ANOVA tests with post-hoc Bonferroni tests, Kruskal-Wallis test or
chi-square test were used whichever was appropriate. Next logistic regression analysis
with adjustment for previous preeclampsia was performed to determine the association
of each blood pressure variable with pregnancy outcome. Discriminative capacity was
assessed with Receiver Operating Characteristics (ROC) analysis. A p value < 0.05 was
considered significant. The statistical software package SPSS 16 (SPSS Inc, Chicago, IL)
was used for all analyses.
74
RESULTS
Study populationA total of 295 women were included, 251 nulliparous women and 44 multiparous women
with a history of preeclampsia. Five women with previous preeclampsia used prophylactic
low-dose acetylsalicylic acid. Five nulliparous women were excluded because of severe
foetal congenital malformations and one woman was lost to follow up. 289 Women were
available for analysis, 20 (6.9 %) developed preeclampsia and 16 (5.5 %) gestational
hypertension. None of them had significant differences in blood pressure by conventional
sphygmomanometry between both arms. Maternal characteristics and pregnancy
outcome are described in table 1.
Women with preeclampsia or gestational hypertension had a higher body mass index
(BMI) compared to women with uncomplicated pregnancies. Women with preeclampsia
delivered earlier and their babies had a lower birth weight compared to women with
unaffected pregnancies. Women with gestational hypertension were comparable to
those with unaffected pregnancy regarding gestational age at delivery and infant birth
weight. Women with preeclampsia had a lower education compared to those without
preeclampsia.
Table 1. Maternal characteristics and pregnancy outcomecharacteristics unaffected
n=253Preeclampsia
n=20Gestational
Hypertension n=16
P-value
Gestational age at measurement(days) 65 ± 5 64 ± 7 64 ± 3 0.78
Age (y) 30.0 ± 4.2 29.6 ± 4.5 31.6 ± 4.1 0.31
BMI (kg/m2) 23.8(17.6-41.8) 26.5(19.6-32.3)* 26.6(21.7-33.4)* <0.001
Ethnicity n (%)
Caucasian 218 (86.2) 15 (75.0) 14(87.5) 0.38
Other 35 (13.8) 5 (25.0) 2(12.5)
Smoking n (%) 27 (10.8) 3 (15.0) 1 (6.2) 0.70
Education n(%)
High 81 (32.0) 2 (10.0) 5 (31.2) 0.009
Median 94 (37.2) 4 (20.0) 7 (43.8)
low 78 (30.8) 14 (70.0) 4 (25.0)
High risk n (%) 30 (11.9) 9 (45) 5 (31.2) <0.001
Gestational age at delivery(days) 279 (207-296) 256(200-286)* # 276(245-294) <0.001
Birth weight(grams) 3338 ± 562 2106 ± 890 * # 3303 ± 639 <0.001
Small for gestational age n (%) 27 (10.7) 13 (65.0) 4 (25.0) <0.001
Data are expressed as mean ± SD, median (range) or n (%). P-value; differences between the groups. *P<0.05 compared to unaffected; #P<0.05 compared to gestational hypertension.
Chapter 4
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Blood pressure measurem
ents and later preeclampsia
Blood pressure measurements
Finger arterial pressure waveform registrations of 4 (1.4%) women were not available
for analysis because of technical difficulties. ABPM data for 48 hour were available in
220 women. Drop out was partly due to lack of a monitoring device at the scheduled
registration time (62 women). A total of 39 women (17.7%) had no or incomplete
data. Eight women refused to wear the blood pressure monitor and 31 women had
an incomplete registration. Three of these had less then 10 measurements and were
excluded. All other incomplete registrations were used.
Women who developed preeclampsia or gestational hypertension had a significantly
higher blood pressure in the first trimester than women with unaffected pregnancies.
The absolute blood pressure values were different between the devices, p<0.01 for all
measurements. The highest absolute values were measured by finger arterial pressure
waveform registration and the lowest by conventional sphygmomanometry (Table 2).
The point estimate of the Odds ratios of blood pressure in the first trimester for later
preeclampsia or combined pregnancy outcome was higher for the automated blood
pressure measurement techniques, although there was an overlap between 95% CI
intervals. For all devices MAP had the highest odds ratios. Figures 1A and 1B show the
odds ratios with 95% CI intervals for every mmHg pressure increase adjusted for previous
Table 2. First trimester blood pressure measurements in different outcome groups.Blood pressure measurements unaffected Preeclampsia Gestational
Hypertension P-value
Heart rate (beats/min) 73 ± 7 73 ± 7 72 ± 8 0.95
Sphygmomanometry
n 253 20 16
SBP (mmHg) 104 ± 9 113 ± 13** 110 ± 8 * <0.001
DBP (mmHg) 60 (46-88) 67 (50-85)** 67 (58-85)** 0.002
MAP (mmHg) 76 ± 7 82 ± 11** 81 ± 7** <0.001
Finger arterial pressure
n 250 19 16
SBP (mmHg) 121 ± 8 131 ± 13** 125 ± 9 <0.001
DBP (mmHg) 67 ± 6 74 ± 8** 71 ± 7* <0.001
MAP (mmHg) 88 ± 7 98 ± 10** 93± 7** <0.001
ABPM
n 179 19 14
SBP (mmHg) 111 ± 7 120 ± 13** 114 ± 8 <0.001
DBP (mmHg) 66 ± 4 72 ± 9** 69 ± 6* <0.001MAP (mmHg) 80 ± 5 88 ± 10** 84 ± 7* <0.001
Data are expressed as mean ± SD or median (range); P-value; differences between the groups.* P<0.05 compared to unaffected; **P<0.01 compared to unaffected
76
Sphygmo SBP
Sphygmo MAP
Sphygmo DBP
FAP SBP
FAP MAP
FAP DBP
ABPM SBP
ABPM MAP
ABPM DBP
2,01,00,0
1.08 (1.03-1.13)
1.08 (1.02-1.15)
1.06 (1.002-1.13)
1.13 (1.06-1.19)
1.17 (1.09-1.26)
1.15 (1.06-1.23)
1.12 (1.05-1.20)
1.17 (1.07-1.27)
1.17 (1.07-1.27)
Sphygmo SBP
Sphygmo MAP
Sphygmo DBP
FAP SBP
FAP MAP
FAP DBP
ABPM SBP
ABPM MAP
ABPM DBP
2,01,00,0
1.08 (1.04-1.12)
1.10 (1.04-1.15)
1.08 (1.028-1.14)
1.10 (1.05-1.15)
1.15 (1.09-1.21)
1.13 (1.07-1.20)
1.10 (1.04-1.16)
1.16 (1.08-1.25)
1.16 (1.07-1.25)
Figure 1A. Odds ratios (95% confidence intervals) for every 1 mmHg pressure increase, after adjustment for previous preeclampsia, to determine the relationship of SBP, MAP and DBP measured by the different devices and preeclampsia.
Sphygmo; sphygmomanometry, FAP; finger arterial pressure waveform registration. ABPM; ambulatory blood pressure monitoring.
Figure 1B. Odds ratios (95% confidence intervals) for every 1 mmHg pressure increase after adjustment for previous preeclampsia to determine the relationship of SBP, MAP and DBP measured by the different devices and combined pregnancy outcome.
Sphygmo; sphygmomanometry, FAP; finger arterial pressure waveform registration, ABPM; ambulatory blood pressure monitoring.
Table 3. Area under the receiver operating characteristics curves with 95% CI of blood pressure measurements for the subsequent development of preeclampsia or combined pregnancy outcome.Measurement preeclampsia Combined pregnancy outcome
SphygmomanometrySBP 0.73 (95% CI 0.58-0.83) 0.73 (95% CI 0.64-0.83)
DBP 0.68 (95% CI 0.53-0.84) 0.72 (95% CI 0.61-0.82)
MAP 0.70 (95% CI 0.55-0.85) 0.73 (95% CI 0.63-0.83)
Finger arterial pressure
SBP 0.82 (95% CI 0.68-0.95) 0.77 (95% CI 0.68-0.87)
DBP 0.77 (95% CI 0.63-0.91) 0.77 (95% CI 0.68-0.86)
MAP 0.82 (95% CI 0.69-0.96) 0.80 (95% CI 0.71-0.89)
ABPM
SBP 0.78 (95% CI 0.65-0.91) 0.74 (95% CI 0.63-0.84)
DBP 0.77 (95% CI 0.63-0.90) 0.72(95% CI 0.62-0.83)MAP 0.78 (95% CI 0.65-0.91) 0.74 (95% CI 0.64-0.85)
Chapter 4
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Blood pressure measurem
ents and later preeclampsia
preeclampsia for the three measurement techniques. The largest area under the ROC
curves (AUC) was 0.82 (95% CI 0.69-0.96) for preeclampsia and 0.80 (95% CI 0.71-
0.89) for combined outcome using MAP estimated by finger arterial pressure waveform
registration (Figure 2A and 2B). Table 3 provides the values of all AUCs, with 95%
confidence intervals. Differences were small and did not reach statistical significance.
DISCUSSION
In this prospective cohort of women with normal blood pressure we confirm that blood
pressure has a significant association with hypertensive disorders later in pregnancy.
Assessment by automated devices at 8 0/7-11 0/7 weeks of pregnancy seems superior
Figure 2A. Association of mean arterial pressure measured with the different devices in the first trimester and prevois preeclampsia with subsequent development of preeclampsia, expressed by Receiver Operating Characteristics (ROC) curves.
Figure 2B. Association of mean arterial pressure measured with the different devices in the first trimester and previous preeclampsia with subsequent development of combined pregnancy outcome, expressed by Receiver Operating Characteristics (ROC) curves.
1 - Specificity1,00,80,60,40,20,0
1,0
0,8
0,6
0,4
0,2
0,0
Sens
itivi
ty
1 - Specificity1,00,80,60,40,20,0
Sens
itivi
ty1,0
0,8
0,6
0,4
0,2
0,0
MAP ABPM
MAP finger arterial waveform
MAP sphygmomanometry
MAP ABPM
MAP finger arterial waveform
MAP sphygmomanometry
78
to conventional sphygmomanometry. ABPM measurements failed more often than
finger arterial pressure waveform registration due to technical difficulties or patient
incompliance.
The accuracy of automated blood pressure devices in pregnant women is often
questioned especially in hypertensive and preeclamptic women and it is generally advised
to use conventional sphygmomanometry to establish the diagnosis of preeclampsia.8
Both Spacelab 90207™ and Finometer™ passed the less strict AAMI criteria, but none
received A/A BHS grading in validation studies in pregnant women where the devices
were compared to auscultatory conventional sphygmomanometry.9;12-14
However, it was not our intention to compare absolute blood pressure values of the
automated devices with conventional sphygmomanometry, which is the usual validation
procedure. Clinical relevance of a measurement method is far more important than
absolute values and therefore we chose a clinical endpoint (preeclampsia or combined
gestational hypertension or preeclampsia). Repeated or continuous measurements provide
a more reliable estimate of average blood pressure than a single sphygmomanometry
measurement. This could explain why finger arterial pressure waveform registration and
ABPM measurements tend to have a higher association with later preeclampsia than
sphygmomanometry in our study.
One of the limitations of our study is the relatively low number of included women. This
causes some uncertainty regarding the exact quantity of the association, as reflected by
the large confidence intervals of odds ratios and possibly causes an overestimation of the
effect.16 The point estimate of the Odds ratios for association with later preeclampsia of
both the automated devices was better for all blood pressure parameters but there was
an overlap between 95% CI intervals and significant differences could not be detected.
Women with elevated blood pressure, cardiovascular disease, renal disease or diabetes
were not included because the elevated risk of these conditions for preeclampsia or
pregnancy induced hypertension preclude the usefulness of further risk assessment.17
Recently we published a meta-analysis of the accuracy of blood pressure measurements
in predicting preeclampsia.5 Studies included in this meta-analysis used all types of blood
pressure measurement devices and it was not possible to compare devices in this meta-
analysis Areas under the ROC-curve for SBP, DBP and MAP for low risk women in the first
trimester were respectively 0.66, 0.67 and 0.79 comparable to our results.
Several studies investigated the predictive capacity of ABPM and preeclampsia and
compared this with office blood pressure measurements.18-23 With ABPM information
on diurnal blood pressure can be obtained. Some found comparable predictive capacity
while others showed better results with ABPM in second trimester pregnancy. There
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Blood pressure measurem
ents and later preeclampsia
were no differences in predictive capacity of only daytime or night time blood pressure
compared to mean values.22;24
As the origin of the disease is in early pregnancy it is likely that preventive interventions
should start early in pregnancy to be effective.25 Therefore, early prediction is of major
importance. Only one of the studies on the predictive capacity of ABPM was performed
in the first trimester. This study showed an extremely high predictive capacity with 48 hour
ABPM using the hyperbaric index.23 However, using an identical approach as Hermida
et al. we could not confirm this and observed a similar association with preeclampsia of
hyperbaric index, mean pressure of 48 hour ABPM and day/night differences in the first
trimester.7 The study population used in this analysis was included in the present study.
The three devices used in our study measure blood pressure in different ways.
Sphygmomanometry and the Spacelab 90207™ register vascular oscillations during the
gradual relaxation of vascular occlusion at the upper arm. In sphygmomanometry the
appearance and disappearance of vascular (Korotkoff) sounds determines SBP and DBP.
The Spacelab 90207™ is an oscillometric device and the MAP is estimated primarily by
the pressure where oscillations are largest and SBP and DBP are derived from this point.26
Conventional sphygmomanometry registers SBP from one and DBP from another heart
beat cycle. Both techniques are influenced by arm diameter and vascular deformability.
Finger arterial pressure waveform registration is registered by a small cuff around the
middle finger. The cuff contains a diode to measure blood flow in the finger and a server
mechanism connected to the cuff regulates pressure in such a way that flow in the finger
remains constant. Thus the cuff pressure is a copy of the arterial finger pressure wave. This
technique enables continuous non-invasive registration of cardiovascular parameters.27
The algorithm for blood pressure calculation depends on vascular compliance which is
larger in pregnant than in non-pregnant women.28 However, the return to flow method
enables calibration for blood pressure calculation and thus overcomes the disturbing
effect of pregnancy on the algorithm for blood pressure calculation.10
According to international guidelines for the classification of preeclampsia blood
pressure is preferably measured at the right arm while seated.8;29;30 In our study the cuff
for ABPM was placed around the non-dominant arm because we wanted to reduce the
inconvenience of ABPM. Therefore all other measurements were also performed at the
same arm, which usually is the left arm. We also chose supine position for measuring
blood pressure with sphygmomanometry and finger arterial waveform registration in
order to be certain that all subjects were at rest. DBP is slightly lower in supine position
than in sitting position, whereas SBP is similar.31 If blood pressure is included in a first
trimester prediction model for preeclampsia, position needs further evaluation. All
women received usual obstetric care prenatal care and blood pressure used for our
80
clinical outcome was measured by conventional sphygmomanometry according to the
international guidelines.
Both automated devices that are used in this study could help in designing prediction
models for preeclampsia. However, ambulatory blood pressure measurement in
pregnancy, as been shown earlier, is considered a burden.32;33 We could not obtain
a complete registration in 18% of the women because of patient incompliance and
technical difficulties. In contrast finger arterial pressure waveform registration only needs
20 minutes for a complete registration and thus could be used in clinical practice more
easily.
Conclusion and impact for further research
Both automated devices used in this study are considered to be of help in designing
prediction models for preeclampsia. Although our study was too small to find significant
differences between the devices and conventional sphygmomanometry, finger arterial
pressure waveform registration is potentially the most useful device in first trimester
screening in pregnancy and needs further evaluation.
Chapter 4
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ents and later preeclampsia
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preeclamptic pregnancies: a longitudinal study. Obstet Gynecol 1990; 76(6):1061-1069. (2) Rang S, Wolf H, Montfrans GA, Karemaker JM. Serial assessment of cardiovascular control
shows early signs of developing pre-eclampsia. J Hypertens 2004; 22(2):369-376. (3) Moutquin JM, Rainville C, Giroux L, Raynauld P, Amyot G, Bilodeau R et al. A prospective
study of blood pressure in pregnancy: prediction of preeclampsia. Am J Obstet Gynecol 1985; 151(2):191-196.
(4) Sibai BM, Ewell M, Levine RJ, Klebanoff MA, Esterlitz J, Catalano PM et al. Risk factors associated with preeclampsia in healthy nulliparous women. The Calcium for Preeclampsia Prevention (CPEP) Study Group. Am J Obstet Gynecol 1997; 177(5):1003-1010.
(5) Cnossen JS, Vollebregt KC, de VN, Ter RG, Mol BW, Franx A et al. Accuracy of mean arterial pressure and blood pressure measurements in predicting pre-eclampsia: systematic review and meta-analysis. BMJ 2008; 336(7653):1117-1120.
(6) Ayala DE, Hermida RC, Mojon A, Fernandez JR, Silva I, Ucieda R et al. Blood pressure variability during gestation in healthy and complicated pregnancies. Hypertension 1997; 30(3 Pt 2):611-618.
(7) Vollebregt KC, Gisolf J, Guelen I, Boer K, van MG, Wolf H. Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia. J Hypertens 2010; 28(1):127-134.
(8) Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001; 20(1):IX-XIV.
(9) Hehenkamp WJ, Rang S, van Goudoever J, Bos WJ, Wolf H, van der Post JA. Comparison of Portapres with standard sphygmomanometry in pregnancy. Hypertens Pregnancy 2002; 21(1):65-76.
(10) Bos WJ, van GJ, van Montfrans GA, van den Meiracker AH, Wesseling KH. Reconstruction of brachial artery pressure from noninvasive finger pressure measurements. Circulation 1996; 94(8):1870-1875.
(11) Guelen I, Westerhof BE, Van Der Sar GL, van Montfrans GA, Kiemeneij F, Wesseling KH et al. Finometer, finger pressure measurements with the possibility to reconstruct brachial pressure. Blood Press Monit 2003; 8(1):27-30.
(12) Shennan AH, Kissane J, de Swiet M. Validation of the SpaceLabs 90207 ambulatory blood pressure monitor for use in pregnancy. Br J Obstet Gynaecol 1993; 100(10):904-908.
(13) O’Brien E, Darling M, Higgins J. Ambulatory blood pressure measurement in pregnancy. Br J Obstet Gynaecol 1994; 101(5):462-463.
(14) Franx A, van der Post JAM, van Montfrans GA, Bruinse HW. Comparison of an Auscultatory Versus an Oscillometric Ambulatory Blood Pressure Monitor in Normotensive, Hypertensive, and Preeclamptic Pregnancy. Hypertens Pregnancy 1997; 16(2):187-202.
(15) Hermida RC, Ayala DE. Sampling requirements for ambulatory blood pressure monitoring in the diagnosis of hypertension in pregnancy. Hypertension 2003; 42(4):619-624.
(16) Leeflang MM, Bossuyt PM, Irwig L. Diagnostic test accuracy may vary with prevalence: implications for evidence-based diagnosis. J Clin Epidemiol 2009; 62(1):5-12.
(17) Caritis S, Sibai B, Hauth J, Lindheimer M, VanDorsten P, Klebanoff M et al. Predictors of pre-eclampsia in women at high risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units. Am J Obstet Gynecol 1998; 179(4):946-951.
(18) Peek M, Shennan A, Halligan A, Lambert PC, Taylor DJ, de SM. Hypertension in pregnancy: which method of blood pressure measurement is most predictive of outcome? Obstet Gynecol 1996; 88(6):1030-1033.
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(19) Halligan AW, Shennan A, Lambert PC, Bell SC, Taylor DJ, de SM. Automated blood pressure measurement as a predictor of proteinuric pre-eclampsia. Br J Obstet Gynaecol 1997; 104(5):559-562.
(20) Penny JA, Halligan AW, Shennan AH, Lambert PC, Jones DR, de SM et al. Automated, ambulatory, or conventional blood pressure measurement in pregnancy: which is the better predictor of severe hypertension? Am J Obstet Gynecol 1998; 178(3):521-526.
(21) Bellomo G, Narducci PL, Rondoni F, Pastorelli G, Stangoni G, Angeli G et al. Prognostic value of 24-hour blood pressure in pregnancy. JAMA 1999; 282(15):1447-1452.
(22) Brown MA, Bowyer L, McHugh L, Davis GK, Mangos GJ, Jones M. Twenty-four-hour automated blood pressure monitoring as a predictor of preeclampsia. Am J Obstet Gynecol 2001; 185(3):618-622.
(23) Hermida RC, Ayala DE, Fernandez JR, Mojon A, Iglesias M. Reproducibility of the tolerance-hyperbaric test for diagnosing hypertension in pregnancy. J Hypertens 2004; 22(3):565-572.
(24) Higgins JR, Walshe JJ, Halligan A, O’Brien E, Conroy R, Darling MR. Can 24-hour ambulatory blood pressure measurement predict the development of hypertension in primigravidae? Br J Obstet Gynaecol 1997; 104(3):356-362.
(25) Steegers EA, von DP, Duvekot JJ, Pijnenborg R. Pre-eclampsia. Lancet 2010; 376(9741):631-644.
(26) Ramsey M, III. Noninvasive automatic determination of mean arterial pressure. Med Biol Eng Comput 1979; 17(1):11-18.
(27) Wesseling KH, de Wit B, Settels JJ, Klawer WH. On the indirect registration of finger blood pressure after Penaz. Funkt Biol Med 1982; 1:245-250.
(28) Rang S, de Pablo LB, van Montfrans GA, Bouma BJ, Wesseling KH, Wolf H. Modelflow: a new method for noninvasive assessment of cardiac output in pregnant women. Am J Obstet Gynecol 2007; 196(3):235-238.
(29) Lowe SA, Brown MA, Dekker GA, Gatt S, McLintock CK, McMahon LP et al. Guidelines for the management of hypertensive disorders of pregnancy 2008. Aust N Z J Obstet Gynaecol 2009; 49(3):242-246.
(30) Lindheimer MD, Taler SJ, Cunningham FG. Hypertension in pregnancy. J Am Soc Hypertens 2008; 2(6):484-494.
(31) Netea RT, Smits P, Lenders JW, Thien T. Does it matter whether blood pressure measurements are taken with subjects sitting or supine? J Hypertens 1998; 16(3):263-268.
(32) Walker SP, Permezel MJ, Brennecke SP, Tuttle LK, Higgins JR. Patient satisfaction with the SpaceLabs 90207 ambulatory blood pressure monitor in pregnancy. Hypertens Pregnancy 2004; 23(3):295-301.
(33) Taylor RS, Gamble G, McCowan L, North RA. Sleep effects on ambulatory blood pressure measurements in pregnant women. Am J Hypertens 2001; 14(1):38-43.
15Karlijn C. VollebregtLarissa van leijdenKees BoerJoris A.M. van der Post Junichiro HashimotoHans WolfBerend E. Westerhof
Submitted
Arterial stiffness at 8 0/7-110/7 weeks of pregnancy and the association with later preeclampsia
86
ABSTRACT
Objective To study the association of the augmentation index (AIx), augmentation pressure (AP) at
8 0/7-11 0/7 weeks of pregnancy with the later onset of preeclampsia. And if combination
with MAP improves this association.
Study Design
235 nulliparous and 42 former preeclamptic women were included with an incidence
of preeclampsia of 4.3% and 16.6%. AIx, AP and MAP obtained from finger arterial
waveform registration were analysed using logistic regression.
Results
After adjustment for previous preeclampsia the AIx and AP were associated with later
preeclampsia (OR 1.84 (95% CI 1.10-3.0) and 1.90 (1.31-2.76) respectively). AP in
combination with MAP and previous preeclampsia had an area under the ROCcurve of
0.82 (0.66-0.97) compared to 0.74 (0.61-0.87), 0.78 (0.65-0.91) and 0.79 (0.64-
0.93) for the single parameters.
Conclusion
The combination of MAP and AP had a higher association with later preeclampsia
compared to single parameters, but the additive effect of AP was small.
Chapter 5
87
Arterial stiffness and later preeclampsia
INTRODUCTION
Preeclampsia affects 2-8% of all pregnancies and remains a leading cause of maternal
and perinatal morbidity and mortality.1;2 Women who had a pregnancy complicated
by preeclampsia are at increased risk for cardiovascular disease in later live and
preeclampsia and cardiovascular disease share similar risk factors.3;4
Increased arterial stiffness is an independent predictor of adverse outcome in
cardiovascular disease.5 Several studies showed an elevated arterial stiffness in women
with preeclampsia.6-9 One research group recently observed an increased arterial
stiffness, measured by applanation tonometry and calculation of the augmentation
index (AIx) at 11-13 weeks of pregnancy, in women who developed preeclampsia later
compared to women with normal pregnancy.10;11
It is not known if this difference in AIx only occurs in the beginning of pregnancy or if it is pre-
existing. Thus the increased risk of cardiovascular disease in former preeclamptic women
could result from persisting abnormalities in cardiovascular control after preeclampsia
or from pre-existing abnormalities which are associated with both conditions. At present,
literature is not helpful to answer this question. Studies report conflicting results about
arterial stiffness in former preeclamptic women compared to women with uncomplicated
pregnancies.7;8;12
Women predisposed to develop preeclampsia already have a higher blood pressure
early in pregnancy, long before clinical symptoms arise, compared to women with an
uncomplicated pregnancy. Although they have no hypertension yet their blood pressure
measured in the beginning of pregnancy could be used to predict preeclampsia.13;14
A systematic review concluded that mean arterial pressure was the blood pressure
parameter with the highest association with preeclampsia.15 Blood pressure and arterial
stiffness are not independent parameters and it is not well described if combined use of
these parameters improves the association with later preeclampsia.16
The primary aim of this study is to test the hypothesis that the association between early
pregnancy arterial stiffness, measured by augmentation index or augmentation pressure,
is improved if combined with mean arterial blood pressure. Our second hypothesis is that
these parameters differ between nulliparous women with an uncomplicated pregnancy
and women with a previous preeclampsia, which could indicate the presence of pre-
existing differences that might contribute to the elevated risk for cardiovascular disease in
women with previous preeclampsia.
88
METHODS
SubjectsThis study is part of a prospective study which investigated cardiovascular parameters in the
beginning of pregnancy for the prediction of preeclampsia.17 Healthy nulliparous women
and healthy parous women with a previous pregnancy complicated by preeclampsia
were included between April 2004 and June 2006. Women with multiple pregnancy,
and women with diabetes, chronic hypertension, antihypertensive medication or renal
disease were not eligible. Women with an infant with major congenital malformations
were excluded. All women had normal blood pressure (<140 / 90 mmHg, measured
by conventional sphygmomanometry) at their first visit. Preventive use of acetylsalicylic
acid in women with a previous preeclampsia was allowed. Participants were recruited
by advertisements in local newspapers, flyers at midwife practices near our hospital and
from our outpatient clinic. The Medical Ethical Committee of the Academical Medical
Center approved the study. After written informed consent, all participants underwent
identical study protocols.
Study protocol
At 8 0/7-11 0/7 weeks of pregnancy gestational age was confirmed by ultrasound.
All measurements were scheduled between 7 AM and 12 noon and took place in a
quiet room with a temperature between 20 and 22 ºC. Subjects were asked to refrain
from coffee from the night before the measurements. They were informed about the
procedures and instructed to empty their bladder before the start of the measurements.
The measurements were performed in supine position at the non-dominant arm after at
least 15 minutes of rest.
Blood pressure and hemodynamic parameters were measured continuously for 10
minutes using non-invasive finger arterial waveform recording by FinometerTM (FMS,
Amsterdam, the Netherlands).
Measurement of finger arterial pressure is based on the volume clamp method of
Peňáz and the ‘Physiocal’ criteria of Wesseling.18;19 20 The brachial arterial pressure is
reconstructed from the finger pulse wave.21 This device is validated in pregnancy and
passed the Association for the Advancement of Medical Instrumentation (AAMI) criteria.
According to the British Hypertension Society (BHS) criteria, the device was graded a B for
diastolic and a C for systolic blood pressure.22 In pregnancy stroke volume measurement
is comparable with Doppler echocardiography.23 An appropriate cuff was placed at the
middle finger of the non-dominant hand with the arm along the body. Hydrostatic height
correction was used to correct for the position of the hand with respect to heart level.
Chapter 5
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Arterial stiffness and later preeclampsia
When a stable signal was attained, the pressure signal was corrected by the return-to-
flow method.24 Data from the FinometerTM were sampled at 200 Hz and analyzed by
Beatscope software (TNO Biomedical Instrumentation, Amsterdam, the Netherlands).
The average of the systolic blood pressure (SBP), diastolic blood pressure (DBP), mean
arterial pressure (MAP) and heart rate (HR) of ten minutes were used for comparisons.
As a measure of arterial stiffness the augmentation index (AIx) was calculated. For the AIx,
a period of 60 seconds, with a stable signal, was selected from the Finometer recording.
The finger arterial waveform of this period was filtered to an aortic waveform by the
Beatscope software. In Mathematica (Wolfram Research, Inc., Mathematica, Version 4.0,
Champaign, IL) the filtered pressure was further analyzed to determine the augmentation
index. 20 Beats were selected and the averaged wave form of these 20 beats was used.
The inflection point was determined with the use of the fourth derivate of the aortic
pressure wave.25 If the inflection point was found before the first pressure peak, A-type
augmentation index was calculated. If the inflection point lay after the first pressure peak
B-type augmentation index was calculated. B-type augmentation index is expressed as
a negative index. AIx was calculated as augmenting pressure (AP, determined by the
inflection point and SBP) divided by pulse pressure (SBP-DBP).26 DAIx was calculated as
AIx postpartum-AIx first trimester.
Outcome
Gestational hypertension was defined as a systolic blood pressure ≥ 140 and/ or a
diastolic blood pressure ≥ 90 mmHg after 20 weeks in a previously normotensive
woman, measured twice with an interval of at least 6 hours. Preeclampsia was defined by
the combination of gestational hypertension and proteinuria ≥ 0,3 g/ 24 h or dipstick ≥
++ after 20 weeks gestation according to the ISSHP guidelines.27
Statistics
To assess normality of the distribution of the numerical data the Kolmogorov-Smirnov test
was used. Normally distributed data are presented as mean ± standard deviation (SD),
not normally distributed data as median (range).
(Paired) Student t-tests, Mann-Whitney U tests and chi-square tests were used when
appropriate.
Logistic regression analysis was used to determine the association of AIx, AP and MAP
in the beginning of pregnancy with later preeclampsia. The continuous variables of
AIx, AP and MAP were categorized per 10 %, 3 and 5 mmHg respectively. Because
the two inclusion groups had highly different a priori risks for preeclampsia, previous
preeclampsia (nulliparous versus parous women with previous preeclampsia) was entered
for adjustment in all models. The probability for entry was set at 0.05, for removal at
90
0.1. For comparison between the models the discriminative capacity was assessed with
Receiver Operating Characteristics (ROC) analysis. The statistical software package SPSS
18 (SPSS Inc, Chicago, IL) was used for all analyses. A p value < 0.05 was considered
statistically significant.
RESULTS
Baseline characteristics283 women participated in the study. After inclusion we excluded 3 women from analysis
because of severe lethal congenital malformations of their infants, 2 women who delivered
an infant with Down syndrome and one woman was lost to follow-up. Thus, 277 women
were available for analysis in the first trimester and 225 of them returned postpartum.
5 of the 42 parous women with previous preeclampsia used prophylactic acetylsalicylic
acid. The mean gestational age at measurement in the first trimester was 9 2/7±0.7
weeks and the mean interval post partum was 28 5/7±7 weeks. Seventeen (6.1 %)
women developed preeclampsia and 16 (5.8 %) other women gestational hypertension.
The women who developed gestational hypertension were allocated to the control group.
Maternal characteristics and pregnancy outcome are described in Table 1.
Women with preeclampsia delivered earlier and their babies had a lower birth weight
compared to women with unaffected pregnancies. Nulliparous women with preeclampsia
were younger compared to the nulliparous unaffected women. There were no differences
between parous women with or without preeclampsia in maternal characteristics.
Hemodynamics
All women who developed preeclampsia (nulliparous and parous women with previous
preeclampsia) had a higher blood pressure at 8-11 weeks and 29 weeks postpartum
Table 1. Baseline characteristics at first visit and pregnancy outcome of the study population. Nulliparous women(n=235) Parous women with previous
preeclampsia(n=42)
No preeclampsian=225
Preeclampsian=10 (4.4%)
No preeclampsian=35
Preeclampsian=7 (16.7%)
Age (y) 30.0 ± 4.2 26.0 ± 3.0‡ 30.7 ± 4.0 33.8 ± 2.2
Caucasian (%) 295 (86.7) 7 (70) 30 (85.7) 5 (71.4)
BMI (m2/kg) 23.3 (17.6-41.8) 24.3 (20.6-31.6) 23.9 (18.8-37.5) 28.5 (19.6-32.2)
Smoking (%) 25 (11.1) 1 (10.0) 3 (8.6) 1 (14.3)
Gestational age at delivery(d) 278 (207-297) 255 (209-286) ‡ 272 (243-289) 224 (200-273) ‡Birth weight (gr) 3475(1170-4585) 2031(870-3232)‡ 3165 (1620-4132) 1300(1000-3025)‡
Data are presented as mean (±standard deviation) or median (range) ‡P<0.01 vs no preeclampsia
Chapter 5
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Arterial stiffness and later preeclampsia
Alx>3525-3515-255-15<=5
100%
80%
60%
40%
20%
0%
MAP>9590-9585-9080-8575-80<=75
100%
80%
60%
40%
20%
0%
preeclampsiano preeclampsia
AP>1512-159-126-93- 6<=3
100%
80%
60%
40%
20%
0%
17 100 103 44 13
34 82 75 45 24 17
6 22 59 89 56 45
Figure 1. Percentage of preeclampsia for augmentation index (AIx) classes, augmentation pressure (AP) classes, and mean arterial pressure (MAP) classes with group size above each column.
92
compared to unaffected women, although the postpartum difference did not reach
statistical significance in parous women. Blood pressure in nulliparous and in parous
women with a previous preeclampsia, who did not develop preeclampsia, was similar at
8-11 weeks and 29 weeks postpartum (Table 2).
All women who developed preeclampsia had a higher AIx and AP in the first trimester
compared to women who did not. This difference was not statistically significant in parous
women (Table 2). First trimester values were lower than values 29 weeks postpartum
in women with uncomplicated pregnancy. In women who developed preeclampsia first
Table 2. Hemodynamic measurements at 8-11 weeks gestational age and at 29 weeks postpartum. Nulliparous women (n=235) Multiparous women with previous preeclampsia (n=42)
Outcome No preeclampsia Preeclampsia No preeclampsia Preeclampsia8-11 w 29 w PP 8-11 w 29 w PP 8-11 w 29 w PP 8-11 w 29 w PP
n=225 N=172 n=10 N=7 n=35 n=25 N=7 N=5
Heart rate (b/m) 70±8 66±9* 69±6 69±6 70±8 69±13 71±6 70±11
SBP (mmHg) 121±8 119±11* 129±15† 132±16V 119±8 122±13 129±5† 125±10
DBP (mmHg) 67±6 69±8* 71±9† 73±9 68±7 74±9* 76±5† 75±8
MAP (mmHg) 87±6 89±9* 96±12† 97±12† 89±8 95±8* 98±5† 97±8
AIx (%) 17 (-11-47) 24 (3-45)* 26 (9-36) † 25 (20-38) 17 (-3-39) 26 (11-48)* 23 (17-33) 27 (18-29)
AP (mmHg) 6.5 (0.9-22.5) 9.4 (1.3-22.2)* 12.3(2.7-19.2) † 11.1 (9.0-25.7) 7.1 (1.1-20.1) 9.5 (3.7-31.3)* 9.8 (6.5-16.1) 10.1(7.4-14.1)DAIx - 7.5±10.9 - 2.2±12.4 - 6.7±10.5 - 0.25±10.5
Data are presented as mean (± standard deviation) or median (range) *P<0.05 vs first trimester,†P<0.05 vs. no preeclampsia, PP: postpartum, SBP: systolic blood pressure, DBP : diastolic blood pressure, MAP: mean arterial pressure, AIx : augmentation index, AP : augmentation pressure
Table 3. Results of the logistic regression analyses to assess the association between different parameters and preeclampsia later in pregnancy, with adjustment for previous preeclampsia.Entry parameters Last step parameters OR (95% CI) Area under the ROCcurve (95% CI)
AIx and parity AIx 1.84 (1.10-3.00) 0.74 (0.61-0.87)*previous preeclampsia 4.02(1.41-11.50)
AP and parity AP 1.90 (1.31-2.76) 0.78 (0.65-0.91) *
previous preeclampsia 4.29 (1.47-12.58)
MAP and parity MAP 2.26 (1.36-3.78) 0.79 (0.64-0.93) *
previous preeclampsia 3.35 (1.13-9.95)
AIx, MAP and parity AIx 1.63 (0.93-2.86) 0.80 (0.65-0.95) *
MAP 2.10 (1.25-3.51)
previous preeclampsia 3.02 (0.99-9.22)
AP, MAP and parity AP 1.72 (1.06-2.56) 0.82 (0.66-0.97)*
MAP 1.94 (1.15-3.27)previous preeclampsia 3.27(1.06-10.15)
AIx: augmentation index, AP: augmentation pressure, MAP: mean arterial pressure * Area significantly different from 0.5
Chapter 5
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Arterial stiffness and later preeclampsia
Table 2. Hemodynamic measurements at 8-11 weeks gestational age and at 29 weeks postpartum. Nulliparous women (n=235) Multiparous women with previous preeclampsia (n=42)
Outcome No preeclampsia Preeclampsia No preeclampsia Preeclampsia8-11 w 29 w PP 8-11 w 29 w PP 8-11 w 29 w PP 8-11 w 29 w PP
n=225 N=172 n=10 N=7 n=35 n=25 N=7 N=5
Heart rate (b/m) 70±8 66±9* 69±6 69±6 70±8 69±13 71±6 70±11
SBP (mmHg) 121±8 119±11* 129±15† 132±16V 119±8 122±13 129±5† 125±10
DBP (mmHg) 67±6 69±8* 71±9† 73±9 68±7 74±9* 76±5† 75±8
MAP (mmHg) 87±6 89±9* 96±12† 97±12† 89±8 95±8* 98±5† 97±8
AIx (%) 17 (-11-47) 24 (3-45)* 26 (9-36) † 25 (20-38) 17 (-3-39) 26 (11-48)* 23 (17-33) 27 (18-29)
AP (mmHg) 6.5 (0.9-22.5) 9.4 (1.3-22.2)* 12.3(2.7-19.2) † 11.1 (9.0-25.7) 7.1 (1.1-20.1) 9.5 (3.7-31.3)* 9.8 (6.5-16.1) 10.1(7.4-14.1)DAIx - 7.5±10.9 - 2.2±12.4 - 6.7±10.5 - 0.25±10.5
Data are presented as mean (± standard deviation) or median (range) *P<0.05 vs first trimester,†P<0.05 vs. no preeclampsia, PP: postpartum, SBP: systolic blood pressure, DBP : diastolic blood pressure, MAP: mean arterial pressure, AIx : augmentation index, AP : augmentation pressure
trimester and 29 weeks postpartum values were comparable. Nulliparous and parous
women with a previous preeclampsia were similar in this respect. DAIx was higher in
women with normal pregnancy compared to women who developed preeclampsia,
although this difference did not reach statistical significance.
Figure 1 shows bar plots of the incidence of preeclampsia for different classes of AIx, AP
and MAP, for the complete population of nulliparous and parous women with previous
preeclampsia. All plots had statistical significance by chi-square analysis except for AIx.
Within the time window of 8-11 weeks, gestational age was not correlated with AIx, AP
or MAP (Pearson correlation coefficient < 0.1).
Table 3 shows the results of the planned logistic regression analyses. AIx, AP and MAP at
8-11 weeks gestational age were significantly associated with later preeclampsia when
adjusted for parity. When entered in combination with MAP AIx and AP remained in the
model. The model with the highest area under the curve of the ROC curve used AP, MAP
and parity.
DISCUSSION
In this prospective cohort of women with normal blood pressure we found positive
associations between higher AIx, AP and mean arterial pressure at 8-11 weeks gestational
age and later development of preeclampsia. Within the gestational age window of
the study these parameters were not affected by gestational age. Although all indices
generally demonstrated similar associations and measures of model fit, the combination
of augmentation pressure, previous preeclampsia and mean arterial pressure showed
94
the strongest association and best model fit. The additive effect of AIx or AP to MAP and
parity was small.
Based on our data we conclude that differences in early pregnancy hemodynamic
measurements between women, who develop preeclampsia later and women who do not,
are not pre-existing and only due to early pregnancy adaptation. We found no differences
between nulliparous women and parous women with previous preeclampsia both in
the first trimester as well as 29 weeks postpartum. Both subgroups had a significantly
lower blood pressure, AIx and AP in the first trimester compared to postpartum values
when pregnancy developed normally, reflecting early pregnancy adaption. Women who
developed preeclampsia, irrespective of parity, had similar values in the first trimester
as 29 weeks postpartum. Postpartum values of AIx and AP were comparable between
women who had an uncomplicated pregnancy and women who had preeclampsia. Blood
pressure was higher 29 weeks postpartum in nulliparous women with preeclampsia;
this seems to contradict our previous statement unless a longer interval is needed for
normalization of blood pressure. A longer recovery interval for blood pressure is supported
by our observation of similar first trimester blood pressure values in nulliparous women
and in parous women with a previous preeclampsia with an uncomplicated pregnancy.
One of the limitations of our study is our limited sample size; we cannot rule out small
differences between the subgroups. Because of the limited sample size we could not
adjust for other known confounders like age and body mass index. We excluded parous
women with previous preeclampsia who had chronic hypertension because the use of
antihypertensive medication could influence arterial stiffness. In addition, these women
were not included because the elevated risk of these conditions for preeclampsia or
pregnancy induced hypertension precludes the usefulness of further risk assessment.28
Despite not selecting this high risk group, the incidence of preeclampsia was high in the
remaining women with previous preeclampsia (4.3 % vs. 16.7%)
We could not confirm the high association of the AIx and AP with later preeclampsia as
found by Khalil et al.10;11 In two studies (one cohort, one case-control) using applanation
tonometry for calculation of AIx, AIx-75 and AP at 110/7-13 6/7 weeks of pregnancy this
group observed an area under the ROC curve of approximately 0.9 for AIx, AIx-75
and AP using univariate analysis. Their first study population was specified as low-
risk, with 43% nulliparous women, but with an incidence of preeclampsia of 6.7% (of
which 50% developed preeclampsia <34 weeks). This is a high incidence of severe
preeclampsia in a low risk population and cannot be compared with our nulliparous
women. The second population was specified as high risk with 10.3 % preeclampsia. A
second difference is that in our study early pregnancy blood pressure differed between
women who developed preeclampsia and women who did not, with a comparable level
Chapter 5
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Arterial stiffness and later preeclampsia
of association as described by Cnossen et al15, while in both studies by Khalil et al no
difference in blood pressure was observed between women who developed preeclampsia
and women who did not. Thirdly, their population contained a high percentage of Afro-
Caribbean women (37%), while our population was predominantly Caucasian. These
differences in study population could explain the difference in level of association of AIx
and AP with our study.
Because a negative linear correlation exists between heart rate and AIx some advocate
to standardise AIx calculation for a heart rate of 75 beats per minute. However, studies
regarding arterial stiffness and changing heart rates report conflicting results. Studies
using pacing have different results compared to studies with other methods to adjust
for heart rate.29;30 This makes it impossible to use standard formula’s to adjust the AIx
to heart rate and these formulas are not validated in pregnancy. We therefore decided
not to use a standardised AIx. In our study population heart rate was similar between
subgroups and thus standardisation would not have changed our findings.
We used finger arterial waveform registration for calculation of AIx and AP while most
studies use Sphygmocor® or other applanation tonometry devices. One of the advantages
of finger arterial waveform registration is that it uses a cuff around the finger instead of
a transducer which has to be hold in place. This easier application allows for a sufficient
rest period and stabilization of the signal in advance of the measurement window.
All these devices have in common that the aortic pressure used for calculating AIx and
AP is not measured but reconstructed from a peripheral pulse wave registration. Invasive
methods are not widely useful in populations for screening purposes. This approach has
been validated in a wide variety of healthy and patient populations.31
CONCLUSION
Combined use of MAP and AP at 8-11 weeks in a model had the highest level of association
with later preeclampsia although the differences between the models were small. Our
results do not support the addition of AIx or AP to blood pressure measurement, which is
far easier to apply, for the assessment of risk for preeclampsia.
The differences in blood pressure, AIx or AP in the first trimester between women who will
develop preeclampsia and women whose pregnancy will develop normally seem to be
pregnancy related and not pre-existing. These differences could reflect an inadequate
hemodynamic adaption to pregnancy.
96
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death: a systematic review. Lancet 2006; 367(9516):1066-1074. (3) Sattar N, Greer IA. Pregnancy complications and maternal cardiovascular risk: opportunities for
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cardiovascular disease in women with a history of pregnancy complicated by preeclampsia or intrauterine growth restriction. Hypertens Pregnancy 2007; 26(1):39-50.
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(9) Avni B, Frenkel G, Shahar L, Golik A, Sherman D, Dishy V. Aortic stiffness in normal and hypertensive pregnancy. Blood Press 2010; 19(1):11-15.
(10) Khalil AA, Cooper DJ, Harrington KF. Pulse wave analysis: a preliminary study of a novel technique for the prediction of pre-eclampsia. BJOG 2009; 116(2):268-276.
(11) Khalil A, Cowans NJ, Spencer K, Goichman S, Meiri H, Harrington K. First-trimester markers for the prediction of pre-eclampsia in women with a-priori high risk. Ultrasound Obstet Gynecol 2010; 35(6):671-679.
(12) Paez O, Alfie J, Gorosito M, Puleio P, de MM, Prieto N et al. Parallel decrease in arterial distensibility and in endothelium-dependent dilatation in young women with a history of pre-eclampsia. Clin Exp Hypertens 2009; 31(7):544-552.
(13) Moutquin JM, Rainville C, Giroux L, Raynauld P, Amyot G, Bilodeau R et al. A prospective study of blood pressure in pregnancy: prediction of preeclampsia. Am J Obstet Gynecol 1985; 151(2):191-196.
(14) Sibai BM, Ewell M, Levine RJ, Klebanoff MA, Esterlitz J, Catalano PM et al. Risk factors associated with preeclampsia in healthy nulliparous women. The Calcium for Preeclampsia Prevention (CPEP) Study Group. Am J Obstet Gynecol 1997; 177(5):1003-1010.
(15) Cnossen JS, Vollebregt KC, de VN, Ter RG, Mol BW, Franx A et al. Accuracy of mean arterial pressure and blood pressure measurements in predicting pre-eclampsia: systematic review and meta-analysis. BMJ 2008; 336(7653):1117-1120.
(16) Benetos A, Laurent S, Asmar RG, Lacolley P. Large artery stiffness in hypertension. J Hypertens Suppl 1997; 15(2):S89-S97.
(17) Vollebregt KC, Gisolf J, Guelen I, Boer K, van MG, Wolf H. Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia. J Hypertens 2010; 28(1):127-134.
(18) Penaz J. Photoelectric measurement of blood pressure, volume and flow in the finger. Digest 10th Int Conf Med Biol Engp . 1973.
(19) Imholz BP, Wieling W, van Montfrans GA, Wesseling KH. Fifteen years experience with finger arterial pressure monitoring: assessment of the technology. Cardiovasc Res 1998; 38(3):605-616.
(20) Wesseling KH, de Wit B., van der Hoeven GM, van Goudoever J, Settels JJ. Physiocal, calibrating finger vascular physiology for finapres. Homeostasis 1995; 36:67-82.
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(21) Guelen I, Westerhof BE, Van Der Sar GL, van Montfrans GA, Kiemeneij F, Wesseling KH et al. Finometer, finger pressure measurements with the possibility to reconstruct brachial pressure. Blood Press Monit 2003; 8(1):27-30.
(22) Hehenkamp WJ, Rang S, van Goudoever J, Bos WJ, Wolf H, van der Post JA. Comparison of Portapres with standard sphygmomanometry in pregnancy. Hypertens Pregnancy 2002; 21(1):65-76.
(23) Rang S, de Pablo LB, van Montfrans GA, Bouma BJ, Wesseling KH, Wolf H. Modelflow: a new method for noninvasive assessment of cardiac output in pregnant women. Am J Obstet Gynecol 2007; 196(3):235-238.
(24) Bos WJ, van GJ, van Montfrans GA, van den Meiracker AH, Wesseling KH. Reconstruction of brachial artery pressure from noninvasive finger pressure measurements. Circulation 1996; 94(8):1870-1875.
(25) Segers P, Rietzschel E, Heireman S, De BM, Gillebert T, Verdonck P et al. Carotid tonometry versus synthesized aorta pressure waves for the estimation of central systolic blood pressure and augmentation index. Am J Hypertens 2005; 18(9 Pt 1):1168-1173.
(26) Hirata K, Kawakami M, O’Rourke MF. Pulse wave analysis and pulse wave velocity: a review of blood pressure interpretation 100 years after Korotkov. Circ J 2006; 70(10):1231-1239.
(27) Brown MA, Lindheimer MD, de Swiet M, Van Assche A, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001; 20(1):IX-XIV.
(28) Caritis S, Sibai B, Hauth J, Lindheimer M, VanDorsten P, Klebanoff M et al. Predictors of pre-eclampsia in women at high risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units. Am J Obstet Gynecol 1998; 179(4):946-951.
(29) Wilkinson IB, MacCallum H, Flint L, Cockcroft JR, Newby DE, Webb DJ. The influence of heart rate on augmentation index and central arterial pressure in humans. J Physiol 2000; 525 Pt 1:263-270.
(30) Pannier B, Slama MA, London GM, Safar ME, Cuche JL. Carotid arterial hemodynamics in response to LBNP in normal subjects: methodological aspects. J Appl Physiol 1995; 79(5):1546-1555.
(31) Gallagher D, Adji A, O’Rourke MF. Validation of the transfer function technique for generating central from peripheral upper limb pressure waveform. Am J Hypertens 2004; 17(11 Pt 1):1059-1067.
16Karlijn C. Vollebregt, Marcel F. van der Wal, Hans Wolf, Tanja G.M. Vrijkotte, Kees Boer, Gouke J. Bonsel
BJOG 2008;115:607-615
Is psychosocial stress in first ongoing pregnancies associated with preeclampsia and gestational hypertension?
100
ABSTRACT
Objective
Investigating the association of preeclampsia and gestational hypertension with
psychosocial stress in the first half of pregnancy.
Design Prospective community-based cohort study
Setting Amsterdam, The Netherlands
Population
Between January 2003 and March 2004 all pregnant Amsterdam women (n= 12 377)
were invited to fill out a questionnaire with sociodemographic and psychosocial variables
(response rate 67%). Only nulliparous women with a singleton pregnancy, who completed
the questionnaire before 24 weeks, and delivered after 24 weeks, were included.
Methods
A postpartum questionnaire was used to gather information on hypertension or proteinuria.
If this questionnaire was not available the national obstetric register was used for pregnancy
outcome. Medical files were examined for women with hypertension and/ or proteinuria
to confirm the diagnosis of pre-eclampsia and gestational hypertension according to the
International Society for the Study of Hypertension in Pregnancy guidelines. Psychosocial
stress was defined as work stress (Work Experience and Appreciation Questionnaire partly
based on the Job Content Instrument of Karasek et al.), anxiety (the State-Trait Anxiety
Inventory, STAI), depression (Center for Epidemiological Studies Depression Scale, CES-
D) and pregnancy related anxiety (PRAQ-R). The association of psychosocial stress with
the incidence of preeclampsia and gestational hypertension was explored by multivariate
analysis adjusted for sociodemographic and medical confounders.
Main outcome measures Incidence of preeclampsia and gestational hypertension.
Results
3679 women were included. The incidence of preeclampsia and gestational hypertension
was respectively 3.5% and 4.4%. Work stress, anxiety, pregnancy related anxiety or
depression had no effect on the incidence of preeclampsia or gestational hypertension.
Conclusion
Psychosocial stress in the first half of pregnancy does not influence the incidence of
preeclampsia and gestational hypertension in nulliparous women.
Chapter 6
101
Preeclampsia and psychosocial stress
INTRODUCTION
Hypertensive disorders of pregnancy are a major cause of maternal and fetal mortality
and morbidity, and affect approximately 8% of all pregnancies.1 Although risks for adverse
events are largest in case of pre-eclampsia, gestational hypertension too is associated
with maternal and fetal mortality and morbidity.
The precise pathogenesis of preeclampsia and gestational hypertension is unknown. The
origin is thought to be associated with abnormal placentation early in pregnancy, which
may be caused by immunological, genetic or environmental factors.1 Maternal factors
like increased age, obesity, chronic hypertension, diabetes mellitus, renal and connective
tissue diseases are all known to be associated with both preeclampsia and gestational
hypertension. It is still unclear whether preeclampsia, gestational hypertension and
haemolysis, elevated liver enzymes, low platelet count (HELLP) syndrome are different
stages of the same disorder or related, yet different syndromes.2;3 Here we focus on
the claimed association between psychosocial stress of the mother and hypertensive
disorders of pregnancy.4-8 Stress activates the hypothalamus- pituitary- adrenal cortex
system (HPA) which in turn increases in levels of corticosteroids and catecholamines.
Stress also activates the sympathetic nervous system and affects the immune system.9;10
Increased levels of corticotrophin releasing hormone 11 and increased sympathetic activity
have been observed in women with preeclampsia and gestational hypertension.12-14
Because psychosocial stress is, in part, an external factor, which could be mediated by
intervention, it is relevant to obtain more knowledge on the association with preeclampsia
and gestational hypertension.
This study investigates the association of psychosocial stress early in pregnancy and the
development of hypertensive disorders later in pregnancy in a prospective cohort of
nulliparous women and compares preeclampsia and gestational hypertension to assess
possible dissimilarities in origin.
METHODS
Study population
The present study is part of the Amsterdam Born Children and their Development study
(ABCD-study).15 This prospective community-based study examined the relationship
between various lifestyles during pregnancy and pregnancy outcome in a multicultural
population. Between January 2003 and March 2004, 12 381 Amsterdam women who
attended antenatal care for their first check-up were approached by their obstetric caregiver
102
to participate in the study. Within 2 weeks a questionnaire (pregnancy questionnaire) on
sociodemographic characteristics, medical history, psychosocial stress and lifestyle was
sent to the pregnant women to be filled out at home and returned by prepaid mail. All
nulliparous women with singleton pregnancy, who filled out the pregnancy questionnaire
before 24 weeks gestational age, and who delivered after 24 weeks were included.
Pregnancy outcome, infant gender, birth weight and gestational age were additionally
obtained from a second questionnaire (infant questionnaire) who completed 3-5 months
after delivery and the Youth Health Care of the Municipal Health Service registry in
Amsterdam. In case no infant questionnaire was filled out information about pregnancy
outcome was gathered from the National Obstetric Register. In the women who were
registered as having hypertension and/ or proteinuria we verified from medical records
if the diagnosis was gestational hypertension or preeclampsia according to the criteria
of the International Society for the Study of Hypertension in Pregnancy.16 Five percent of
the women in the control group were randomly selected for verification of data from their
medical records. The study protocol was approved by the medical ethical committees of
all Amsterdam hospitals and the Municipal Privacy Protection Committee of Amsterdam.
Participation and permission for data retrieval rested on written consent.
Definitions of hypertensive disorders
Gestational hypertension was defined as a diastolic pressure ≥ 90 mmHg after 20 weeks
in a previously normotensive woman. Preeclampsia was defined by the combination
of gestational hypertension and proteinuria ≥ 0.3 g/ 24 h or dipstick ≥ ++ after 20
weeks gestation, according to the International Society for the Study of Hypertension in
Pregnancy guidelines.16 Women with chronic hypertension who had a diastolic pressure
≥ 90 mmHg after 20 weeks gestation were included in the gestational hypertension
group. Superimposed preeclampsia was defined as de novo proteinuria ≥ 0.3 g/ 24
h or dipstick ≥ ++ after 20 weeks gestation together with a diastolic pressure ≥ 90
mmHg in women with chronic hypertension. Chronic hypertension was defined as a
systolic pressure ≥140 mmHg and/or diastolic pressure ≥ 90 mmHg or the necessity for
antihypertensive treatment before pregnancy or before 20 weeks gestational age.
Measurement of psychosocial stress
Psychosocial stress was decomposed into four main components; work stress, depression,
anxiety and pregnancy-related anxiety, with all concepts measured by internationally
accepted instruments. Work stress was examined using four variables: total working
hours, workload, work control and job strain. Total working hours was defined as the
weekly hours of paid work which was categorized in ‘no work’ ‘<32 h’ and ‘≥ 32 h’.
Workload was measured using three scales and workcontrol using one scale of the Work
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Preeclampsia and psychosocial stress
Experience and Appreciation Questionnaire of Van Veldhoven et al.17, partly based on
the Job Content Instrument of Karasek et al.18 The scales used were pace of work (11
items), mental work load (7 items), physical work load (7 items) and job control (11
items). Items were scored on a four-point-scale (0=never, 1=sometimes, 2=often and
3=always). The reported working hours were used as a separate variable. The scores
for workload and workcontrol were trichotomised into three categories, for workload:
low (< 50th percentile) moderate (between 50th and 90th percentile) and high (>90th
percentile), for workcontrol: high (> 50th percentile), moderate (between 10th and 50th
percentile) and low (< 10th percentile). Jobs that are high in workload (>P90) and low
in control (<P10) are presumed to give the most stress (job strain) and negative health
effects.19 Women with high workload and low or moderate workcontrol were defined as
having high job strain, women with low workload and high or moderate control as low
job strain and al remaining women as moderate job strain. The total score of the three
mood scales were all trichotomised round the 50th and 90th percentiles to create three
categories: low, moderate and high.
Depressive symptoms were measured by the Dutch version (validated by Hanewald)20 of
the Center for Epidemiological Studies Depression Scale (CES-D)21. The 20-item CES-D
scale assesses the self-reported frequency of depressive symptoms experienced over the
past week. Items were scored on a four-point scale (0= (almost) never, 1=sometimes,
2=often and 3=very often).
The Dutch version of the State-Trait Anxiety Inventory (STAI) was used to measure anxiety
symptoms22. The state anxiety scale consists of 20 items and asks subjects to indicate
how they felt in the past week. Subjects rated each item on a four-point scale (0= almost
never, 1=sometimes, 2=often and 3=very often).
Anxiety and specific fears related to pregnancy were measured by three scales developed
by Huizink et al.23 and based on the revised version of the Pregnancy Related Anxiety
Questionnaire (PRAQ-R) of Van den Bergh.24 The scales used were ‘fear of giving birth’
(three items), ‘fear of bearing a handicapped child’ (four items) and ‘concern about
one’s appearance’ (three items). Items were scored on a four-point scale (4=very true,
3=not true, 2=true, 1=certainly not true).
In this study internal consistencies (Cronbachs’alphas) were 0.90 for the depression
scale, 0.94 for the anxiety scale, 0.81 for the total pregnancy related anxiety scale, 0.85
for the total work load scale and 0.92 for the control scale.
Characteristics and Covariates
Covariates were decomposed in two categories; sociodemographic and medical
covariates. Sociodemographic covariates are maternal age, education, marital status and
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ethnicity. Medical covariates included pre-pregnancy body mass index (BMI), smoking
during pregnancy, previous miscarriage/ abortion, chronic hypertension, diabetes and
vaginal haemorrhage during pregnancy. Maternal age, gestational age (based on
routine first trimester ultrasound examination or, if unavailable, on the timing of the last
menstrual period), birth weight and infant gender, were obtained from the Youth Health
Care registration of the Municipal Health Service in Amsterdam. All other variables
were self reported and defined as follows: maternal education (years of education after
primary school; 3 categories: < 5 years; 5-10 years; > 10 years), marital status (married/
cohabiting or single) and ethnicity (Caucasian, black, Turkish/Moroccan and other
countries). Pre-pregnancy BMI was calculated using weight and height. Missing data on
pregravid maternal weight (about 5% compared to 1% general missing) were formally
imputed by models using maternal length and parity data, retaining the variability of
the data. Smoking during pregnancy (yes or no), previous miscarriage/ abortion (yes or
no), vaginal haemorrhage during pregnancy (yes or no). Women were asked if they had
hypertension, diabetes mellitus or other disease during their pregnancy and if they used
medication. This was classified according to the International Classification for Primary
Care. If women used medication for a specific disease but did not fill in this disease (e.g.
insulin) they were classified as having the associated disease (diabetes).
Statistical analysis
We estimated the effects of psychosocial stress for all seven variables of psychosocial
stress separately by predefined explorative logistic regression models, with increasing
levels of adjustment. First univariate analysis was applied for each variable to estimate the
unadjusted effects. Subsequently multivariate logistic regression was performed to adjust
for medical covariates. Those medical covariates that were statistically significant in this
analysis were combined with the sociodemographic covariates in a second multivariate
logistic analysis. The selection of covariates that influenced the model significantly was
performed by back step procedure with the p value for entry set at 0.05 and for removal
at 0.10.
For all work-related stress variables employed women with the least heavy working
condition were taken as the reference category, while unemployed women were taking
as a separate category. For anxiety, depression and pregnancy related anxiety; women
with the least anxiety/depressive feelings were taken as the reference category. The level
of significance used was p<0.05. Statistical calculations were performed with SPSS
12.0.2(SPSS Inc.Chicago, IL).
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Figure 1. Inclusion
106
RESULTS
In total, 12 373 women were invited for the ABCD-study and 8266 women returned the
questionnaire (response rate 67%). 3679 women were included in our study according
to our selection criteria (see figure 1). The median gestational age at completing
the pregnancy questionnaire was 15.6 weeks (quartiles 14.0-17.3). The diagnosis
preeclampsia or gestational hypertension could not be confirmed in the medical files in
300 of the 599 women, who were registered as hypertensive disorder in the National
Obstetrics Register, or who indicated this in the second questionnaire. These women were
allocated to the control group. The medical records of the randomly selected women in
the control group (n=190) confirmed correct allocation to the control group. Thirteen
files could not be traced and these women were allocated to the control group (Figure 1).
Table 1. Sociodemographic and medical characteristics of included women.Total group Controls PE GH
N (%) 3679(100) 3390 (92.1) 128 (3.5) 161 (4.4)Birth weight (g) 3381 ± 557 3397 ± 530 2875 ± 979 3380 ± 561
Gestational age (days) 278 ± 14 278 ± 14 264 ± 22 278 ± 13
Age (years) 29.9 ± 5.1 29.8 ± 5.1 31.6 ± 5.0 30.9 ± 4.7
Etnicity
-Caucasian 2461 (100) 2250 (91.4) 91 (3.7) 120 (4.9)
-Black 157 (100) 148 (94.3) 4 (2.5) 5 (3.2)
-Turkish/Moroccan 347 (100) 324 (93.4) 9 (2.6) 14 (4.0)
- Other 712 (100) 666 (93.5) 24 (3.4) 22 (3.1)
Education N (%)
-0-5 years 557 (100) 527 (94.6) 17 (3.1) 13 (2.3)
-6-10 years 1445 (100) 1324 (91.6) 48 (3.3) 73 (5.1)
->10 years 1651 (100) 1514 (91.7) 63 (3.8) 74 (4.5)
Marriage/ co-habitation N (%)
no 497 (100) 471 (94.8) 10 (2.0) 16 (3.2)
BMI (kg/m2) 22.6 ± 3.7 22.4 (3.6) 23.7 (4.4) 24.5 (4.1)
Chronic hypertension N (%)
yes 92 (100) 56 (60.9) 21 (22.8) 15 (16.3)
Diabetes N (%)
yes 19 (100) 16 (84.2) 1 (5.3) 2 (10.2)
Smoking in pregnancy N (%)
yes 343 (100) 329 (94.8) 10 (2.9) 8 (2.3)
Miscarriage/ abortion N (%)
yes 969 (100) 890 (91.8) 30 (3.1) 49 (5.1)
Hemorrhage N (%)yes 431 (100) 404 (93.7) 15 (3.5) 12 (2.8)
Data are expressed as mean ± SD or n (%)
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Preeclampsia and psychosocial stress
The incidence of preeclampsia was 3.5% and 4.4% of the women had gestational
hypertension. Women in the preeclampsia group were older than those in the control
group and both women in the preeclampsia and gestational hypertension group had a
higher pre-pregnancy BMI and had more often chronic hypertension. Fewer women in
the preeclampsia group were married or lived with a partner (Table 1).
Table 2. Odds ratio’s with 95% confidence limits for preeclampsia (PE) of psychosocial stress, calculated by univariate analysis, by multivariate analysis using Model 1 and Model 2.
Controls(%) PE(%) Univariate effects Multivariate effects model 1
Multivariate effects model 2
Working hoursNo work 24.5 14.4 0.53(0.29-0.97)* 0.49 (0.26-0.89)* 0.58 (0.30-1.11)
< 32 19.5 21.6 1 1 1
≥ 32 h 66.0 64.0 1.04 (0.67-1.63) 1.01 (0.64-1.60) 0.93 (0.59-1.49)
Workload
No work 24.5 14.3 0.61 (0.35-1.06) 0.54 (0.31-0.96)* 0.69 (0.38-1.27)
Low 35.6 34.1 1 1 1
Moderate 31.9 39.7 1.30 (0.86-1.97) 1.17 (0.76-1.80) 1.16 (0.75-1.78)
High 8.0 11.9 1.60 (0.88-2.92) 1.46 (0.78-2.72) 1.76 (0.94-3.29)
Workcontrol
No work 24.6 14.3 0.53 (0.31-0.92)* 0.49 (0.28-0.87)* 0.66 (0.36-1.21)
High 36.5 39.7 1 1 1
Moderate 30.5 32.5 0.98 (0.64-1.49) 0.99 (0.68-1.29) 1.07 (0.69-1.65)
Low 8.4 13.5 1.49 (0.85-2.62) 1.25 (0.68-2.29) 1.51 (0.81-2.82)
Jobstrain
No work 24.6 14.3 0.62 (0.35-1.09) 0.55 (0.31-0.99)* 0.71 (0.38-1.32)
Low 33.1 31.2 1 1 1
Moderate 36.7 48.0 1.39 (0.92-2.91) 1.27 (0.83-1.93) 1.27 (0.83-1.95)
high 5.6 6.5 1.36(0.65-2.85) 1.24 (0.58-2.66) 1.61 (0.75-3.49)
Anxiety
Low 45.9 50.0 1 1 1
Moderate 40.8 37.5 0.82 (0.56-1.20) 0.74 (0.49-1.10) 0.86 (0.57-1.30)
High 13.3 12.5 1.08 (0.61-1.91) 0.95 (0.52-1.75) 1.38 (0.74-2.58)
Depression
Low 46.5 50.4 1 1 1
Moderate 42.7 37.0 0.80 (0.55-1.18) 0.76 (0.51-1.13) 0.86 (0.58-1.29)
High 10.8 12.6 1.06 (0.60-1.85) 0.85 (0.46-1.56) 1.29 (0.68-2.42)
Pregnancy related anxiety
Low
Moderate 46.3 50.0 1 1 1
High 42.5 38.1 0.83 (0.57-1.22) 0.80 (0.54-1.19) 0.82 (0.55-1.22)
11.2 11.9 0.98 (0.55-1.73) 0.91 (0.50-1.65) 1.13 (0.61-2.07)Model 1:Adjusted for BMI, chronic hypertension, diabetes mellitus, smoking in pregnancy, previous miscarriage/ abortion and haemorrhage; Model 2:Model 1 + additional adjusted age, ethnicity, education and marriage/ co-habitation; *significance level <0.05
108
Working, irrespective of the duration, was associated with approximately twice the
risk for preeclampsia and gestational hypertension in comparison to not working in
univariate analysis. If high or moderate work control was present, risks were similar to not
working. Low work control increased the risks considerably (pre-eclampsia about 3 times
Table 3. Odds ratio’s with 95% confidence limits for gestational hypertension (GH) of psychosocial stress, calculated by univariate analysis, by multivariate analysis using Model 1 and Model 2.
Controls (%) GH(%) Univariate effects Multivariate effects model 1
Multivariate effects model 2
Working hoursNo work 24.5 15.0 0.63 (0.37-1.10) 0.58 (0.33-1.04) 0.72 (0.40-1.31)
< 32 h 19.5 18.8 1 1 1
≥ 32 h 66.0 66.2 1.24 (0.82-1.88) 1.30 (0.84-2.00) 1.22 (0.79-1.89)
Workload
No work 24.5 15.1 0.57 (0.35-0.92)* 0.50 (0.30-0.82)** 0.66 (0.39-1.14)
Low 35.6 38.4 1 1 1
Moderate 31.9 38.4 1.12 (0.78-1.61) 1.09 (0.75-1.59) 1.11 (0.76-1.61)
High 8.0 8.1 0.97 (0.53-1.81) 0.86 (0.44-1.65) 0.97 (0.50-1.88)
Workcontrol
No work 24.6 15.1 0.52 (0.32-0.83)* 0.45 (0.27-0.73)* 0.60 (0.35-1.03)
High 36.5 43.4 1 1 1
Moderate 30.5 33.4 0.92 (0.63-1.32) 0.89 (0.61-1.30) 0.93 (0.64-1.37)
Low 8.5 8.1 0.82 (0.45-1.51) 0.71 (0.37-1.35) 0.83 (0.43-1.59)
Jobstrain
No work 24.6 15.1 0.58 (0.35-0.94)* 0.50 (0.30-0.83)** 0.67 (0.39-1.16)
Low 33.1 35.3 1 1 1
Moderate 36.7 43.3 1.11 (0.77-1.59) 1.08 (0.77-1.57) 1.11 (0.77-1.61)
high 5.6 6.3 1.05 (0.53-2.09) 0.87 (0.41-1.84) 1.03 (0.48-2.20)
Anxiety
Low 45.9 48.5 1 1 1
Moderate 40.8 39.1 0.97 (0.69-1.36) 0.84 (0.59-1.19) 0.95 (0.66-1.36)
High 13.3 12.4 1.21 (0.73-2.01) 1.11 (0.65-1.89) 1.46 (0.84-2.54)
Depression
Low 46.5 49.1 1 1 1
Moderate 42.7 38.5 0.86 (0.61-1.20) 0.78 (0.55-1.11) 0.85 (0.60-1.22)
High 10.8 12.4 1.07 (0.65-1.78) 0.87 (0.51-1.51) 1.19 (0.67-2.11)
Pregnancy related anxiety
Low
Moderate 46.3 44.7 1 1 1
High 42.5 41.6 1.01 (0.72-1.43) 0.96 (0.67-1.36) 0.99 (0.69-1.41)11.2 13.7 1.25 (0.77-2.05) 1.18 (0.71-1.96) 1.15 (0.87-2.47)
Model 1:Adjusted for BMI, chronic hypertension, diabetes mellitus, smoking in pregnancy, previous miscarriage/ abortion and haemorrhage; Model 2:Model 1 + additional adjusted age, ethnicity, education and marriage/ co-habitation; * significance level <0.05; **significance level <0.01
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Table 4. Odds ratios of associated factors for preeclampsia and gestational hypertension compared with the controls.
Pre-eclampsia Significance Gestational Hypertension
Significance
Age (year) 1.09 (1.04-1.14) <0.001 1.04(0.99-1.08) 0.08Ethnicity
-Caucasian 1 1
-Black 0.86 (0.25-2.95) 0.81 0.67 (0.20-1.58) 0.43
-Turkish/Moroccan 1.08 (0.49-2.40) 0.85 1.04 (0.53-2.03) 0.91
- Other 0.98 (0.60-1.61) 0.95 0.66 (0.41-1.08) 0.10
Education
-0-5 years 1 1 1
-6-10 years 0.91 (0.48-1.71) 0.612 2.19 (1.12-2.27) 0.22
->10 years 1.00 (0.52-1.93) 0.847 2.01 (0.99-4.06) 0.052
Not married/ co-habitation 0.38 (0.18-0.81) 0.01 0.72 (0.41-1.29) 0.27
BMI (kg/m2) 1.07 (1.03-1.11) 0.002 1.12 (1.09-1.15) <0.001
Chronic hypertension 12.51 (6.95-22.53) <0.001 5.80 (3.00-11.22) <0.001
Diabetes 0.79 (0.91-6.86) 0.83 1.51 (0.29-7.60) 0.62
Smoking in pregnancy 1.08 (0.56-2.21) 0.76 0.60 (0.29-1.26) 0.18
miscarriage/ abortion 0.77 (0.49-1.20) 0.25 1.37 (0.95-1.97) 0.91Haemorrhage 0.94 (0.54-1.67) 0.85 0.55 (0.30-1.01) 0.053
Odds ratio’s adjusted for all the other variables in table
and gestational hypertension about 2 times). Any grade of job strain was associated
with approximately twice the risk for preeclampsia and gestational hypertension in
comparison to not working. No association between the stress components (job strain,
anxiety, depression or pregnancy-related anxiety) and preeclampsia or gestational
hypertension remained after adjustment for medical and socioeconomic covariates by
logistic regression analysis (Table 2 and 3).
In table 4 the odds ratio’s of the covariates that were used in this analysis are demonstrated.
Maternal age, high BMI and chronic hypertension contributed significantly to the model
for preeclampsia and for gestational hypertension. Being single was associated with a
significant reduction of preeclampsia, but did not contribute to the model for gestational
hypertension. None of the other confounders contributed significantly to the models,
although higher education and vaginal bleeding in the first half of pregnancy came close
to statistical significance in the models for gestational hypertension.
110
DISCUSSION
In this study we found no association of work stress, anxiety, depression or pregnancy-
related anxiety early in pregnancy and the development of gestational hypertension or
preeclampsia later in pregnancy.
Four studies observed an association of preeclampsia / gestational hypertension with job
strain in working women.4-6;25 Some of these studies used job title to calculate jobstrain
rather than individually experienced stress which is regarded as more trustworthy. 4;5
Although associations in these studies reached statistical significance, the size of their
effects was small (odds ratio’s between 1.5 and 3) and larger in case-control than in
cohort studies. Most studies adjusted for confounders, although the set of variables was
considerably smaller than used in our study. Kurki et al. found a significant association
of anxiety and depression with preeclampsia.26 They used a questionnaire with one
question for assessment of anxiety and a modified depression questionnaire which was
originally designed for psychiatric patients. They found a prevalence of depression of
30%, while other studies observed a prevalence in pregnant women of approximately 12
%, which suggest that the questionnaire Kurki et al. used was not suitable for population
studies.27 A recent study by Leeners et al. found a significant effect of emotional stress
in pregnancy on the incidence of hypertensive disorders of pregnancy (OR 1.6 CI 1.15-
2.9). In this retrospective case-control study a recall bias can not be excluded. The
emotional stress level experienced during the pregnancy by the women with hypertensive
disorders of pregnancy could be influenced by the disease and the experienced stress
from hospital admissions and treatment. Similar to our study, two other prospective
studies did not observe an association between depression or anxiety and hypertensive
complications.28;29 Sikkema et al. also used the STAI and PRAQ-R while Andersson et al.
used The Primary Care Evaluation of Mental disorders system, a questionnaire validated
for use in primary care settings.
One of the strong points of our study was that we investigated prospectively four main
components of psychosocial stress by use of well-validated questionnaires and in the
beginning of pregnancy, as it is assumed that the preclinical origin of hypertensive
disorders of pregnancy is situated early in pregnancy.1 On the contrary, we were not
informed about events later in pregnancy. However, it has been described that feelings of
anxiety and depression are stable during pregnancy.30
One of the limitations of our study was that all data about psychosocial stress were self
reported without clinical verification. This could cause a report bias underestimating or
exaggerating perceived stress. Possible cultural differences in interpreting questionnaires
and response style could also cause a cross-cultural bias in our multicultural population.
Chapter 6
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Preeclampsia and psychosocial stress
To prevent a report bias in diagnosis we retrieved all medical files of women who reported
hypertension and/ or proteinuria according to the infant questionnaire or national
obstetric register to confirm the diagnosis preeclampsia or gestational hypertension.
There was no pre-eclampsia or gestational hypertension in the randomly selected files of
the control group.
Although our study group was large, due to the low incidence of preeclampsia and
gestational hypertension and due to low numbers in the highest work and anxiety
classification groups, the confidence intervals of the risk estimates are large. Small effects
could have been overlooked therefore. However, all odds ratio’s are close to 1 and
the clinical importance appears negligible, even if in a larger study population some
effects (e.g. no work) might have reached statistically significance. Psychosocial stress
is therefore not suitable as a target for intervention for prevention of preeclampsia and
gestational hypertension.
The covariates that were used in our study to adjust the effect of psychosocial stress on
the incidence of preeclampsia and gestational hypertension have been well described
by others and the size of the effects was comparable to what has been reported in
literature (Table 4).2 In literature both young as well as older mothers are at risk.1;2 The
mean age of the women in our study was 29.9 years and only 1.8 % was ≤ 18 years.
This is comparable with the population of the Netherlands and the low incidence of
teenage pregnancy could explain why only higher maternal age was a risk indicator.
Why women who were living single had a lower incidence of preeclampsia remains
unclear. In general, risk factors were comparable between preeclampsia and gestational
hypertension suggesting a common origin of these two conditions.
The association of psychosocial stress and cardiovascular disease has been well
described and it is assumed that this effect is mediated through a mechanism involving
excessive sympathetic nervous system activation.31-33 In women with preeclampsia
higher levels of cortisol releasing hormone and signs of higher sympathetic activity in
comparison to women with normal pregnancies have been documented.12-14 However,
haemodynamic and sympathetic-nerve responses to reflex tests (e.g. paced breathing,
Valsalva manoeuvre, cold pressor test, isometric hand-grip exercise) did not differ
between women with or without preeclampsia in these studies. This could implicate that
sympathetic hyperactivity is associated with the origin of the disease but that this is not
mediated by external stress.
112
CONCLUSION
This prospective cohort study could not detect any association between work and
four major sources of stress (anxiety, depression, pregnancy-related anxiety and job
strain) in the beginning of pregnancy, and the development with pre-eclampsia or
gestational hypertension. Apparent univariate associations with a lower incidence of
preeclampsia and gestational hypertension in women with no work disappeared after
proper adjustment. The observed covariates were nearly identical for preeclampsia and
gestational hypertension suggesting a common origin.
Chapter 6
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Preeclampsia and psychosocial stress
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12. Greenwood JP, Scott EM, Walker JJ, Stoker JB, Mary DA. The magnitude of sympathetic hyperactivity in pregnancy-induced hypertension and preeclampsia. Am.J.Hypertens. 2003;16:194-99.
13. Schobel HP, Fischer T, Heuszer K, Geiger H, Schmieder RE. Preeclampsia -- a state of sympathetic overactivity. N.Engl.J.Med. 1996;335:1480-85.
14. Rang S, Wolf H, Montfrans GA, Karemaker JM. Serial assessment of cardiovascular control shows early signs of developing pre-eclampsia. J.Hypertens. 2004;22:369-76.
15. van Eijsden M, van der Wal MF, Bonsel GJ. Folic acid knowledge and use in a multi-ethnic pregnancy cohort: the role of language proficiency. BJOG. 2006;113:1446-51.
16. Brown MA, Lindheimer MD, de SM, Van AA, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens.Pregnancy. 2001;20:IX-XIV.
17. Van Velthoven M, Meijman T. het meten van psychosociale arbeidsbelasting met een vragenlijst: De Vragenlijst Beleving en Beoordeling van de Arbeid(VBBA). Amsterdam: Nederlands Instituut voor Arbeidsomstandigheden, 1994.
18. Karasek R, Theorell T. Healthy work: Stress, productivity and the reconstruction of working life. New York: Basic Books, 1990.
19. Karasek R, Brisson C, Kawakami N, Houtman I, Bongers P, Amick B. The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessments of psychosocial job characteristics. J.Occup.Health Psychol. 1998;3:322-55.
20. Hanewald G.J.F.P. CES-D: De Nederlandse versie. Een onderzoek naar de betrouwbaarheid en validiteit. 1987. Amsterdam, University of Amsterdam, department of Clinical Psychology.
21. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1977;1:385-401.
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22. Spielberger C GRLR. STAI Manual for the State-Trait Anxiety Inventory. Palo Alto CA: Consulting Psychologists Press, 1970.
23. Huizink AC, Mulder EJ, Robles de Medina PG, Visser GH, Buitelaar JK. Is pregnancy anxiety a distinctive syndrome? Early Hum.Dev. 2004;79:81-91.
24. Bergh van de B.R.H. The influence of maternal emotions during pregnancy on fetal and neonatal behavior. Pre- and perinatal psychology 1990;5:119-30.
25. Wergeland E, Strand K. Working conditions and prevalence of pre-eclampsia, Norway 1989. Int.J.Gynaecol.Obstet. 1997;58:189-96.
26. Kurki T, Hiilesmaa V, Raitasalo R, Mattila H, Ylikorkala O. Depression and anxiety in early pregnancy and risk for preeclampsia. Obstet.Gynecol. 2000;95:487-90.
27. Bennett HA, Einarson A, Taddio A, Koren G, Einarson TR. Prevalence of depression during pregnancy: systematic review. Obstet.Gynecol. 2004;103:698-709.
28. Sikkema JM, Robles de Medina PG, Schaad RR, Mulder EJ, Bruinse HW, Buitelaar JK et al. Salivary cortisol levels and anxiety are not increased in women destined to develop preeclampsia. J.Psychosom.Res. 2001;50:45-49.
29. Andersson L, Sundstrom-Poromaa I, Wulff M, Astrom M, Bixo M. Implications of antenatal depression and anxiety for obstetric outcome. Obstet.Gynecol. 2004;104:467-76.
30. Field T, Hernandez-Reif M, Diego M, Schanberg S, Kuhn C. Stability of mood states and biochemistry across pregnancy. Infant Behav.Dev. 2006;29:262-67.
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17Karlijn C. VollebregtHans WolfKees BoerMarcel F. van der WalTanja G.M. VrijkotteGouke J. Bonsel
Acta Obstetricia et Gynecologica Scandinavica 2010; 89: 261–267
Does physical activity in leisure time early in pregnancy reduce the incidence of preeclampsia or gestational hypertension?
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ABSTRACT
ObjectiveAssessment of the association of physical activity in leisure time with preeclampsia and
gestational hypertension in the first half of pregnancy in nulliparous women.
Design
Population based prospective cohort study.
Setting
Amsterdam, the Netherlands
Population
All Amsterdam pregnant women between January 2003 and March 2004 who were
nulliparous with a singleton pregnancy and delivered after 24 weeks
Design
At their first prenatal care visit women were invited to fill out a questionnaire with
sociodemographic and psychosocial variables. Physical activity in leisure time in the
past week was measured using questions about walking, cycling, doing sports and other
activities in leisure time. The amount of minutes and intensity of each activity was studied
using four categories; no, low, moderate or high activity. The 50th and 90th percentiles
of the scores of the whole group was used to create these categories. Data from the
National Obstetric Register were used for pregnancy outcome. By using multivariate
logistic regression we adjusted for sociodemographic and medical confounders.
Main outcome
Incidence of preeclampsia and gestational hypertension
Results
A total of 12.377 women were invited with a response of 67%. 3679 nulliparous women
were included. The incidence of preeclampsia and gestational hypertension was 3.5%
and 4.4% respectively. The amount of time or intensity of physical activity in leisure time
was not associated with a difference in risk of preeclampsia or gestational hypertension.
Conclusion
Physical activity in leisure time early in pregnancy does not reduce the incidence of
preeclampsia or gestational hypertension in unselected nulliparous women.
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Preeclampsia and physical exercise
INTRODUCTION
Hypertensive disorders of pregnancy are a leading cause of maternal and perinatal
morbidity and mortality worldwide.1 The origin is thought to be associated with deficient
placentation early in pregnancy, which in turn may be caused by immunological, genetic
or environmental factors.2 The expression of the disease is mediated through endothelial
dysfunction and increased systemic resistance, resulting in hypertension with a highly
variable degree of organ dysfunction of which proteinuria is the most conspicuous. So
far no effective treatment is available other than antihypertensive drugs and termination
of pregnancy.
Hypertensive disorders in pregnancy and adult cardiovascular diseases share
predisposing conditions, like elevated blood pressure and obesity. Protective or disease
modifying factors of cardiovascular disease might also be applicable for the prevention
of hypertensive disorders in pregnancy. Physical activity is one such factor, known to
prevent cardiovascular disease and to reduce its symptoms. Its precise mechanism is
unclear, but an acceptable hypothesis is that it mediates a reduction of oxidative stress,
which in turn influences the immune response and improves endothelial dysfunction.3-6
These processes are also involved in the development of preeclampsia and gestational
hypertension.2 Because physical activity is, in part, an external factor, which can be
mediated by intervention, its association with preeclampsia and gestational hypertension
is vital for the development of non-medical prevention strategies. A number of studies
explored the association, but most studies were hampered by the low incidence of
preeclampsia, and overall results appear inconsistent.7-11
This study investigates the association between physical activity in leisure time early
in pregnancy and the development of hypertensive disorders later in pregnancy in an
unselected prospective cohort of nulliparous women.
METHODS
The present study is part of the Amsterdam Born Children and their Development study
(ABCD-study).12 This prospective community-based study examined the relationship
between various lifestyles during pregnancy and pregnancy outcome in a multicultural
population. Between January 2003 and March 2004 12,381 Amsterdam women who
attended antenatal care for their first visit were approached by their obstetric caregiver
to participate in the study. Within two weeks a questionnaire (pregnancy questionnaire)
on sociodemographic characteristics and lifestyle was sent to the pregnant women to
120
be filled out at home and returned by prepaid mail. Women who gave permission to
follow-up received a second questionnaire (infant questionnaire) 3 months after birth
concerning pregnancy outcome, lifestyles, and health of the baby. Additional data like
pregnancy outcome, infant gender, birth weight and gestational age were obtained from
the national obstetric register and the Youth Health Care of the Municipal Health Service
in Amsterdam.
Study population
All nulliparous women with singleton pregnancy, who filled out the pregnancy questionnaire
before 24 weeks gestational age, who delivered after 24 weeks and gave permission
for follow-up were included. The study protocol was approved by the medical ethical
committees of all Amsterdam hospitals and the Municipal Privacy Protection Committee
of Amsterdam. Participation and permission for data retrieval rested on written consent.
Measurements
Gestational hypertension was defined as a diastolic pressure ≥ 90 mmHg after 20 weeks
in a previously normotensive woman. Preeclampsia was defined by the combination
of gestational hypertension and proteinuria ≥ 0,3 g/ 24 h or dipstick ≥ ++ after 20
weeks gestation, according to the International Society for the Study of Hypertension in
Pregnancy (ISSHP) guidelines.13 Superimposed preeclampsia was defined as de novo
proteinuria ≥ 0,3 g/ 24 h or dipstick ≥ ++ after 20 weeks gestation together with a
diastolic pressure ≥ 90 mmHg in women with chronic hypertension. Chronic hypertension
was defined as a systolic pressure ≥140 mmHg and/or diastolic pressure ≥ 90 mmHg
or the necessity for antihypertensive treatment before pregnancy or before 20 weeks
gestational age. Women with chronic hypertension who had a diastolic pressure ≥ 90
mmHg after 20 weeks gestation were included in the gestational hypertension group.
The medical files of all women who documented elevated blood pressure in the infant
questionnaire or who had a diastolic blood pressure ≥ 90 mmHg and/ or proteinuria
in The National Obstetric Register were reviewed for confirmation of the diagnosis
preeclampsia or gestational hypertension. If gestational hypertension was diagnosed first
and proteinuria occurred later in pregnancy, preeclampsia was the assigned diagnosis.
From the remaining women a random sample of 190 women was selected to validate the
absence of hypertensive disorders during pregnancy by reviewing their medical records.
Physical activity in leisure time in the past week was questioned using four questions
about walking, cycling, doing sports and other activities like ‘do it yourself’ or gardening
in leisure time. The amount of time spent in minutes and the intensity (low, moderate or
vigorous) was asked. We analyzed the amount of time spent on each activity and the total
time spent on physical activity in leisure time. The scores were trichotomized using the
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Preeclampsia and physical exercise
50th and 90th percentiles of the amount of minutes spent on activity of the total group to
create four categories. The quantity of minutes spent on each activity was multiplied with
the intensity (arbitrarily we coded low by 1, moderate by 2 and vigorous by 3), yielding
a numerical score for each activity question, which were summated into a total score.
These scores were trichotomized using the 50th and 90th percentiles of levels of intensity
of activity of the total group to create four categories;no activity, low activity, moderate
activity and high activity.
Characteristics and covariates
Maternal age, gestational age (based on routine ultrasound examination or, if
unavailable, on the date of the last menstrual period), birth weight and infant gender
were obtained from the Youth Health Care registration of the Municipal Health Service
in Amsterdam. All other variables were self reported and defined as follows: maternal
education (years of education after primary school; 3 categories: < 5 years; 5-10 years;
> 10 years), marital status (married/cohabiting or single), pre-gravid maternal weight
and height, previous miscarriage/ abortion (yes or no), smoking during pregnancy (yes
or no). Women were asked if they had hypertension, diabetes mellitus or any other
disease during their pregnancy, and if they used any medication. Drug utilization was
classified according to the International Classification for Primary Care.14 If women used
medication for a specific disease but did not report the disease (for example insulin) they
were classified as having the disease (diabetes). Pre-pregnancy body mass index (BMI)
was calculated. Missing data on pregravid maternal weight (about 5% compared to 1%
general missings) were formally imputed by models using maternal length and parity
data, retaining the variability of the data.
Statistical analyses
To compare groups one-way ANOVA with post-hoc Bonferoni analysis or Pearson’s
chi-square test was used. We estimated the effects of physical activity in the beginning
of pregnancy on the incidence of preeclampsia or gestational hypertension later in
pregnancy by predefined explorative logistic regression models, with increasing levels of
adjustment. First univariate analysis for each variable was used to calculate unadjusted
odds ratio’s. Subsequently multivariate logistic regression was performed to adjust for
medical covariates: BMI, chronic hypertension, diabetes mellitus, previous miscarriage/
abortion, smoking in pregnancy and haemorrhage in the first half of pregnancy (model
1). Those medical covariates that were statistically significant in this analysis were
combined with sociodemographic covariates in a second multivariate logistic analysis.
Sociodemographic covariates were age, ethnicity, education and marriage/ co-habitation
(model 2). The selection of covariates that influenced the model significantly was
122
performed by back step procedure with the p value for entry set at 0.05 and for removal
at 0.10. Women with no physical activity were taken as the reference category. The
Hosmer and Lemeshowtest was used to test the goodness of fit of the data. The level of
significance used was p<0.05. Statistical calculations were performed with SPSS 14.0.2(
SPSS Inc.Chicago, IL).
RESULTS
In all, 12,373 women were invited for the ABCD-study and 8266 women returned the
questionnaire (response rate 67%). Of these 3679 nulliparous women were included in
our study according to our selection criteria. The median gestational age at completing
the pregnancy questionnaire was 15.6 weeks (quartiles 14.0-17.3). From the 599
women, who reported elevated blood pressure in the questionnaire or who were coded
as such in the national obstetric register, the diagnosis preeclampsia was confirmed
in 128 women (3.5%) by reviewing the medical records and gestational hypertension
in 161 women(4.4%). Ten medical files could not be retrieved and 300 women had
neither preeclampsia nor gestational hypertension. These women were all allocated to
the control group. From the 190 women, who were preselected in the control group
for confirmation by reviewing medical files, 187 files could be assessed. None of these
women had preeclampsia or gestational hypertension during their pregnancy and all
were correctly allocated to the control group. All women whose medical files could not
be retrieved, were all allocated to the control group. The selection of our study group
is described elsewhere using the same cohort for studying the influence of psychosocial
stress on preeclampsia and gestational hypertension.15
From 80 women (2%), information of physical activity was missing. Demographic and
medical characteristics according to degree of physical exercise are presented in Table
1. Women with no or low leisure time physical activities were significantly younger (p <
0.001), less often Caucasian (p < 0.001), had a higher BMI (p = 0.005) and a lower
education (p < 0.001). Women with no physical activity also smoked more often (p <
0.001) and lived more often single (p < 0.001). They delivered earlier and birthweight
was lower compared tomothers who performed any exercise (p < 0.001). Low exercise
level was associated with shorter gestational length and lower birthweights compared to
moderate but not high exercise (p < 0.05). Women with moderate or high total leisure
time physical activities were similar for these parameters.
The incidence of preeclampsia and gestational hypertension did not differ between the
groups with different total physical activities in leisure time based on time and intensity. After
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Preeclampsia and physical exercise
adjustment for possible confounders, walking, bicycling, playing sports, other activities
or performing any physical activity in leisure time (minutes/week) were not associated
with a reduction of preeclampsia (Table 2) or gestational hypertension (Table 3). When
women spent more than 585 minutes on physical activities, the adjusted odds ratio
was 0.62 (95%CI (confidence interval) 0.25–1.53) for preeclampsia and 0.54 (95%CI
0.22–1.36) for gestational hypertension. Likewise, playing sports or total leisure time
physical activities at a high level lacked a significant association with preeclampsia (OR
0.43; 95%CI 0.17–1.10) and gestational hypertension (OR 0.78; 95% CI 0.36–1.69).
Table 1. Sociodemographic and medical characteristics of included women according to level and time spend on physical exercise in leisure time in early pregnancy.
Total group No exercise low moderate high
N (%) 3679 (100) 454 (12.3) 1502 (40.1) 1322 (35.9) 321 (8.7)Age (years) 29.9 ± 5.1 27.4 ± 5.4 29.4 ± 5.3 31.1 ± 4.4 31.6 ± 4.2
Etnicity N(%)
-Caucasian 2461 (66.9) 167 (36.9) 945 (63.0) 1055 (79.8) 263 (81.9)
-Black 157 (4.3) 52 (11.5) 74 (4.9) 22 (1.7) 3 (0.9)
-Turkish/Moroccan 347 (9.4) 93 (20.5) 174 (11.6) 54 (4.1) 9 (2.8)
- Other 712 (19.4) 141 (31.1) 308 (20.5) 191 (14.4) 46 (14.3)
Education N (%)
-0-5 years 557 (15.2) 123 (27.4) 261 (17.5) 120 (9.1) 21 (6.6)
-6-10 years 1445 (39.6) 239 (53.2) 638 (42.8) 442 (33.6) 99 (31.0)
->10 years 1651 (45.2) 87 (19.4) 593 (39.7) 754 (57.3) 199 (62.4)
Marriage/ co-habitation N (%)
No 497 (13.5) 99 (21.8) 197 (13.1) 145 (11.0) 50 (15.6)
BMI (kg/m2) 22.6 ± 3.7 23.3 ± 4.7 22.7 ± 3.8 22.3 ± 3.2 21.8± 2.7
Chronic hypertension N (%)
Yes 92 (2.5) 16 (3.5) 37 (2.5) 31 (2.4) 4 (1.2)
Diabetes N (%)
Yes 19 (0.5) 3 (0.7) 10 (0.7) 4 (0.3) 2 (0.6)
Smoking in pregnancy N (%)
Yes 343 (9.3) 76 (16.7) 141 (9.4) 98 (7.4) 21 (6.5)
Miscarriage/ abortion N (%)
Yes 969 (26.3) 124 (27.3) 370 (24.6) 360 (27.2) 96 (29.9)
Hemorrhage N (%)
Yes 431 (11.7) 59 (13.2) 175 (11.8) 153 (11.6) 32 (10.0)
Preeclampsia N (%) 127 (3.5) 20 (4.3) 49 (3.2) 51(3.8) 7 (2.2)
Gestational hypertension N(%) 159 (4.3) 19 (4.1) 77 (5.0) 49 (3.7) 14 (4.3)
Birth weight (g) 3381 ± 557 3229 ± 610 3370 ± 550 3432 ± 543 3346 ± 520Gestational age (days) 278 ± 14 276 ± 16 278 ± 14 280 ± 13 279 ± 14
Data are expressed as mean ± SD of N (%). BMI: body mass index
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DISCUSSION
We observed no significant association between physical activity in leisure time in
early pregnancy and the incidence of preeclampsia and gestational hypertension after
appropriate adjustment of covariates. Literature regarding this subject is conflicting. Studies
use different methods and definitions which makes it difficult to compare their results.16
Some studies investigate in particular physical activity at work with or without account for
physical activity in leisure time. Most of the studies are retrospective case-control studies.
In three retrospective case control studies with data collection by questionnaire after
delivery it was observed that leisure time physical activity in the first half of pregnancy was
more frequent in controls than in women with preeclampsia.7;8 More vigorous activity
was associated with a lower incidence of preeclampsia.17 One retrospective cohort study
of enlisted active duty military women observed less preeclampsia in nulliparous women
Table 2. The association between preeclampsia and sports and total leisure time physical activity in minutes/week or based on intensity and time, calculated by univariate analysis, by multivariate analysis using model 1 and model 2, expressed as odds ratios with 95% confidence limits.
Controls(%) PE(%) Univariate effects Multivariate effects model 1
Multivariate effects model 2
Sports (minutes/week)0 69.8 1 1 1 1
1-70 15.1 16.4 1.09 (0.67–1.77) 1.18 (0.72–1.95) 1.02 (0.61–1.71)
71-180 12.5 10.9 0.88 (0.50–1.56) 0.97 (0.54–1.75) 0.81 (0.45–1.48)
>180 2.6 3.1 1.19 (0.42–3.32) 1.32 (0.46–3.76) 1.04 (0.36–3.00)
Total LTPA ( minutes/week)
0 12.5 15.9 1 1 1
1-235 48.9 48.4 0.78(0.47-1.31) 0.92(0.53-1.60) 0.71(0.40-1.27)
236-585 31.4 29.4 0.74(0.42-1.28) 0.90(0.50-1.64) 0.63(0.33-1.18)
>585 7.2 6.3 0.70(0.30-1.61) 0.88(0.37-2.11) 0.62(0.25-1.53)
Sports
No sports 69.8 69.5 1 1 1
Low 15.2 14.9 0.98 (0.59–1.62) 1.06 (0.63–1.77) 0.91 (0.54–1.55)
Moderate 12.0 13.3 1.11 (0.66–1.89) 1.22 (0.75–2.10) 1.02 (0.58–1.78)
Vigorous 3.0 2.3 0.80 (0.25–2.56) 0.93 (0.29–3.03) 0.72 (0.22–2.37)
Total LTPA
No LTPA 12.5 15.9 1 1 1
Low 41.6 38.1 0.72 (0.42–1.23) 0.85 (0.48–1.51) 0.68 (0.38–1.32)
Moderate 36.9 40.5 0.87 (0.51–1.47) 1.04 (0.59–1.85) 0.72 (0.39–1.32)Vigorous 9.0 5.6 0.48 (0.20–1.16) 0.62 (0.25–1.53) 0.43 (0.17–1.10)
Model 1: BMI, chronic hypertension, diabetes mellitus, previous miscarriage/abortion, smoking in pregnancy and hemorrhage in the first half of pregnancy. Model 2: age, ethnicity, education and marriage/co-habitation. PE, preeclampsia; LTPA, leisure time physical activity; BMI, body mass index
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Preeclampsia and physical exercise
employed in jobs involving high levels of physical activity compared to nulliparous working
at low levels of physical activity.18 Contrary to these studies one other retrospective case-
control study of nulliparous women observed that women with clerical work experienced
less frequently preeclampsia than women with moderate to high physical activity at work,
after adjustment for age, BMI, smoking and social status.19
Three prospective cohort studies with assessment of physical activity in leisure time
early in pregnancy also showed different results.9-11 Saftlas et al. observed a non-
significant reduction of the incidence of preeclampsia. The extent of the risk reduction
was comparable to our findings. Magnus et al. found a significant reduction when there
were ≥ 25 physical activities per month. Osterdal et al. studied the largest cohort and
investigated time, intensity and metabolic equivalents. Although this study did not observe
an association between leisure time activity and the incidence of preeclampsia, those
women who spend ≥ 270 minutes on physical activity per week had an odds ratio of 1.7
Table 3. The association between gestational hypertension and sports and total leisure time physical activity in minutes/week or based on intensity and time, calculated by univariate analysis, by multivariate analysis using model 1 and model 2, expressed as odds ratios with 95% confidence limits.
Controls(%) GH(%) Univariate effects Multivariate effects model 1
Multivariate effects model 2
Sports (minutes/week)0 69.8 69.4 1 1 1
1-70 15.1 12.5 0.83(0.51-1.35) 0.91(0.55-1.49) 0.77(0.46-1.28)
71-180 12.5 15.6 1.26(0.81-1.97) 1.40(0.89-2.22) 1.18(0.74-1.88)
>180 2.6 2.5 0.96(0.35-2.65) 0.86(0.27-2.80) 0.71(0.22-2.32)
Total LTPA ( minutes/week)
0 12.5 12.0 1 1 1
1-235 48.9 55.7 1.19(0.72-1.97) 1.27(0.75-2.15) 1.01(0.58-1.75)
236-585 31.4 27.2 0.90(0.52-1.57) 1.00(0.56-1.77) 0.71(0.39-1.30)
>585 7.2 5.1 0.73(0.32-1.70) 0.73(0.30-1.79) 0.54(0.22-1.36)
Sports
No sports 69.8 69.4 1 1 1
Low 15.2 14.4 0.95 (0.60–1.50) 1.03(0.64–1.65) 0.87(0.54–1.41)
Moderate 12.0 11.3 0.94 (0.57–1.57) 1.06(0.63–1.79) 0.90(0.53–1.52)
Vigorous 3.0 5.0 1.70 (0.81–3.59) 1.75(0.79–3.90) 1.43(0.64–3.20)
Total LTPA
No LTPA 12.5 12.0 1 1 1
Low 41.6 48.1 1.21 (0.72–2.02) 1.26 (0.74–2.16) 1.02 (0.58–1.78)
Moderate 36.9 31.0 0.88 (0.51–1.51) 0.97 (0.56–1.71) 0.69 (0.38–1.26)Vigorous 9.0 8.9 1.02 (0.50–2.07) 1.12 (0.53–2.34) 0.78 (0.36–1.69)
Model 1: BMI, chronic hypertension, diabetes mellitus, previous miscarriage/abortion, smoking in pregnancy and hemorrhage in the first half of pregnancy. Model 2: age, ethnicity, education and marriage/co-habitation. GH,gestational hypertension; LTPA, leisure time physical activity; BMI, body mass index
126
for severe preeclampsia. The precise definition of severe preeclampsia was not reported.
In our study physical activity levels in women with preeclampsia < 34 weeks were not
different from women with preeclampsia ³ 34 weeks.
A recent Cochrane review could identify two trials (total n=45) randomising women
to participate in an exercise program or not.20 These studies were too small to draw
conclusions regarding the prevention of preeclampsia or gestational hypertension, as
only one case of preeclampsia was encountered. One of the two identified studies
observed that diastolic blood pressure was lower in the exercise group, which supports a
positive effect.21 A literature search using the terms used in this Cochrane review detected
one new study. This study had not enough statistical power to detect a difference in the
incidence of preeclampsia. 22
In practice the low incidence of preeclampsia precludes randomised studies using this
endpoint. Case control studies with retrospective design are prone to recall bias as the
data have to be collected after delivery. Prospective cohort studies, like the present one,
beginning in early pregnancy have the advantage that recall bias is minimised, but the
inclusion of a large number of women is needed. But lack of power, especially in groups
with high physical activity, is a serious threat even of fairly large cohort studies, due to the
low prevalence of (severe) preeclampsia and low frequency of intense physical activity.
A potential bias in case-control and cohort studies is that women who exercise probably
differ from women who do not. In our study 70 % did not practice any kind of sports while
13 % did not practice any physical activity at al. In the Danish cohort of Odenthal 63
% of the women did no sportive activity at all. We adjusted our analysis with a number
of covariates that have been well described by others to be associated with gestational
hypertension or preeclampsia.2;23 However, certainty that adjustment was adequate can
never be obtained.
Assessment of physical activity is complicated because there is no ‘gold standard’ and
unequivocal norm. Self report may suffer from recall bias. Therefore questionnaires focus
on discrete activities like sport and activity at work which are easy to recall, and less
subject to interpretation as ‘physical activity’. Activity monitors are more objective and
could reduce report errors but these are not suitable for prospective studies with a large
sample size like our study.24 Hence our approach was questionnaire-based with self-
reporting. Existing questionnaires were unacceptably long. Therefore we used our own
questionnaire. If anything, our measurement of leisure time may have been subject to
random error, although the current results most likely will not alter with more extensive
measurement.
Even if preventive physical programs are considered, practical constraints can be
expected. It is generally assumed that disturbed placental development in early pregnancy
Chapter 7
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Preeclampsia and physical exercise
is an important factor in the origin of preeclampsia and gestational hypertension.2 If the
promotion of physical activity can reduce the incidence of preeclampsia and gestational
hypertension than the first half of pregnancy is likely the most effective period. At this early
stage of pregnancy women are often easily tired and generally abstain from high activity.
CONCLUSION
Physical exercise in leisure time in early pregnancy is not associated with reduced
incidence of preeclampsia and gestational hypertension in an unselected nulliparous
population. An effect of high physical activity can not be excluded because of the low
incidence of high physical activity and the low incidence of preeclampsia.
128
Reference List (1) Khan KS, Wojdyla D, Say L, Gulmezoglu AM, Van Look PF. WHO analysis of causes of maternal
death: a systematic review. Lancet 2006; 367(9516):1066-1074. (2) Sibai B, Dekker G, Kupferminc M. Pre-eclampsia. Lancet 2005; 365(9461):785-799. (3) Mora S, Cook N, Buring JE, Ridker PM, Lee IM. Physical activity and reduced risk of cardiovascular
events: potential mediating mechanisms. Circulation 2007; 116(19):2110-2118. (4) Dickinson HO, Mason JM, Nicolson DJ, Campbell F, Beyer FR, Cook JV et al. Lifestyle
interventions to reduce raised blood pressure: a systematic review of randomized controlled trials. J Hypertens 2006; 24(2):215-233.
(5) Kojda G, Hambrecht R. Molecular mechanisms of vascular adaptations to exercise. Physical activity as an effective antioxidant therapy? Cardiovasc Res 2005; 67(2):187-197.
(6) Moyna NM, Thompson PD. The effect of physical activity on endothelial function in man. Acta Physiol Scand 2004; 180(2):113-123.
(7) Marcoux S, Brisson J, Fabia J. The effect of leisure time physical activity on the risk of pre-eclampsia and gestational hypertension. J Epidemiol Community Health 1989; 43(2):147-152.
(8) Sorensen TK, Williams MA, Lee IM, Dashow EE, Thompson ML, Luthy DA. Recreational physical activity during pregnancy and risk of preeclampsia. Hypertension 2003; 41(6):1273-1280.
(9) Saftlas AF, Logsden-Sackett N, Wang W, Woolson R, Bracken MB. Work, leisure-time physical activity, and risk of preeclampsia and gestational hypertension. Am J Epidemiol 2004; 160(8):758-765.
(10) Magnus P, Trogstad L, Owe KM, Olsen SF, Nystad W. Recreational physical activity and the risk of preeclampsia: a prospective cohort of Norwegian women. Am J Epidemiol 2008; 168(8):952-957.
(11) Osterdal ML, Strom M, Klemmensen AK, Knudsen VK, Juhl M, Halldorsson TI et al. Does leisure time physical activity in early pregnancy protect against pre-eclampsia? Prospective cohort in Danish women. BJOG 2009; 116(1):98-107.
(12) van Eijsden M, van der Wal MF, Bonsel GJ. Folic acid knowledge and use in a multi-ethnic pregnancy cohort: the role of language proficiency. BJOG 2006; 113(12):1446-1451.
(13) Brown MA, Lindheimer MD, de SM, Van AA, Moutquin JM. The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP). Hypertens Pregnancy 2001; 20(1):IX-XIV.
(14) Hofmans-Okkes IM, Lamberts H. The International Classification of Primary Care (ICPC): new applications in research and computer-based patient records in family practice. Fam Pract 1996; 13(3):294-302.
(15) Vollebregt KC, van der Wal MF, Wolf H, Vrijkotte TG, Boer K, Bonsel GJ. Is psychosocial stress in first ongoing pregnancies associated with pre-eclampsia and gestational hypertension? BJOG 2008; 115(5):607-615.
(16) Bonzini M, Coggon D, Palmer KT. Risk of prematurity, low birthweight and pre-eclampsia in relation to working hours and physical activities: a systematic review. Occup Environ Med 2007; 64(4):228-243.
(17) Rudra CB, Williams MA, Lee IM, Miller RS, Sorensen TK. Perceived exertion during prepregnancy physical activity and preeclampsia risk. Med Sci Sports Exerc 2005; 37(11):1836-1841.
(18) Irwin DE, Savitz DA, St Andre KA, Hertz-Picciotto I. Study of occupational risk factors for pregnancy-induced hypertension among active duty enlisted Navy personnel. Am J Ind Med 1994; 25(3):349-359.
(19) Spinillo A, Capuzzo E, Colonna L, Piazzi G, Nicola S, Baltaro F. The effect of work activity in pregnancy on the risk of severe preeclampsia. Aust N Z J Obstet Gynaecol 1995; 35(4):380-385.
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(20) Meher S, Duley L. Exercise or other physical activity for preventing pre-eclampsia and its complications. Cochrane Database Syst Rev 2006;(2):CD005942.
(21) Yeo S, Steele NM, Chang MC, Leclaire SM, Ronis DL, Hayashi R. Effect of exercise on blood pressure in pregnant women with a high risk of gestational hypertensive disorders. J Reprod Med 2000; 45(4):293-298.
(22) Yeo S, Davidge S, Ronis DL, Antonakos CL, Hayashi R, O’Leary S. A comparison of walking versus stretching exercises to reduce the incidence of preeclampsia: a randomized clinical trial. Hypertens Pregnancy 2008; 27(2):113-130.
(23) Villar J, Carroli G, Wojdyla D, Abalos E, Giordano D, Ba’aqeel H et al. Preeclampsia, gestational hypertension and intrauterine growth restriction, related or independent conditions? Am J Obstet Gynecol 2006; 194(4):921-931.
(24) Janz KF. Physical activity in epidemiology: moving from questionnaire to objective measurement. Br J Sports Med 2006; 40(3):191-192.
18Karlijn C. VollebregtLobke SeesingSaskia RangKees BoerHans Wolf
Hypertension in pregnancy 2006.25;3:159-167
Sensitivity of spontaneous baroreflex conrol of the heart and hemodynamic parameters are not influenced by the menstrual cycle
132
ABSTRACT
ObjectiveThe purpose of this study was to evaluate if hemodynamic parameters and sympathetic
activity vary between the follicular and luteal phase of the menstrual cycle before using
sympathetic activity in pre-pregnancy risk assessment for preeclampsia.
Methods
We studied 39 healthy women at days 5 to 10 and days 18 to 25 of the menstrual cycle.
Blood pressure, heart rate, cardiac output and total peripheral resistance were measured
continuously using noninvasive finger arterial pressure waveform registration (Portapres
Model 2, TNO-BMI, The Netherlands). Baroreflex sensitivity (BRS) and sympathetic
activity by phase angle difference were studied using spectral analysis and xBRS.
Results
There were no differences in hemodynamic parameters, BRS or phase angle difference.
Conclusion
There is no difference in blood pressure, BRS or sympathetic activity between the first and
second half of the menstrual period. We recommend using the first half of the cycle to be
certain no pregnancy exist, as the influence of very early pregnancy is unknown.
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odynamics and the m
enstrual cycle
INTRODUCTION
Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality.1 It is
a multisystem disorder with unknown etiology and is characterized by increased systemic
vascular resistance, endothelial dysfunction and increased sympathetic activity.1;2 Despite
the advances in perinatal care, there is no test for adequate prediction of the disease.3
Early selection of women at high risk could offer the opportunity to target care at those
most likely to benefit and to evaluate or design preventive strategies more effectively.
Earlier research has shown that, before pregnancy, women who will develop preeclampsia
have a slightly higher blood pressure and a larger blood pressure drop after orthostatic
stress when compared with women who have a normal blood pressure throughout
pregnancy.4 From 8 weeks gestational age onward they also had a larger negative phase
difference in the low frequency band with spectral analysis. This indicates increased
sympathetic activity early in pregnancy among women who will develop preeclampsia
later in pregnancy. Recently sympathetic hyperactivity and reduced baroreflex sensitivity
were found in formerly preeclamptic normotensive women.5 These women were formerly
preeclamptic and the sympathetic hyperactivity could be the result of the disease or it
could have been present already before pregnancy. These findings could thus be useful
for early identification for women at risk early in pregnancy and even before pregnancy.
It is well known that ovarian hormones affect the cardiovascular and renal-aldosteron
system.6-8 However, the magnitude of the effect of hormonal fluctuations during the
menstrual cycle on blood pressure regulation is not clear and literature in this respect is
not consistent.9-11 The present study was designed to ascertain if it would be necessary
to account for the menstrual cycle when measuring pre-pregnancy hemodynamic
parameters for the identification of women at risk for preeclampsia.
METHODS
Study PopulationWe recruited participants by advertisement in a local newspaper. All women were over
the age of 18 years, had a regular cycle (median 28 days; range 26 to 32 days), and
had no previous pregnancy. The participants did not use medication, oral contraceptives
or a levonorgestrel releasing intrauterine device. We excluded women with hypertension,
diabetes or cardiovascular diseases. After providing written informed consent, all
participants underwent identical study protocols. The Medical Ethical Committee of the
Academic Medical Center approved the study.
134
Study Protocol
All women were studied in the follicular phase, between the 5th and 10th day, and
in the luteal phase, between the 18th and 25th day of the menstrual cycle. Menstrual
cycle phase was determined according to the first day of the last menstruation. The first
measurement was allocated randomly to the follicular phase (FP) or the luteal phase (LP).
All measurements were doe by two researchers. The participants were advised to abstain
from drinking coffee or smoking cigarettes from the night before the measurements. After
resting in supine position for at least 10 minutes, they were informed about the study
procedure and were allowed to adapt to the measuring devices and the room before
the measurements started. The measurements were preformed with the participants
in supine position under standardized conditions and took place in a quiet room
with a temperature between 20 and 22°C. Blood pressure was measured twice with
conventional sphygmomanometry (Maxi Stabil 3, an aneroid sphygmomanometer, Welch
Allyn, Skaneateles Falls, New York, USA) before the measurement with the Portapres™
started. The mean value was used for comparisons.
Continuous recordings of hemodynamic parameters
Non-invasive finger arterial pressure waveform registration by Portapres, Model 2 (TNO-
BMI, Amsterdam, The Netherlands) was used for continuous monitoring of blood pressure,
heart rate and cardiac output. Portapres is a device for the measurement of finger arterial
pressure on a beat-to-beat basis, according to the volume clamp method of Penaz12;13.
The use of continuous recordings of finger arterial blood pressure by this method has
been validated in comparison to invasive beat-to-beat blood pressure recording in non-
pregnant subjects and in comparison to conventional sphygmomanometry in pregnant
women.14;15 Stroke volume analysis out of continuous finger arterial pressure waveform
registration by the pulse contour method of Wesseling (the Modelflow method) has been
validated extensively.16 An appropriate size finger cuff was applied at the middle finger
of the non-dominate hand. At a stable signal the pressure registration was calibrated to
upper-arm cuff pressure by the Return to Flow method.17 Data collection was started after
a stable signal had been reached for 5 minutes.
Data analysis
Data from the Portapres were sampled at 200 Hz and analyzed by the Beatfast program
(TNO-BMI, Amsterdam, The Netherlands). The average of the systolic blood pressure
(SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), heart rate (HR),
cardiac output (CO) and total peripheral resistance (TPR) of 10 minutes during supine
rest were used for analysis.
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odynamics and the m
enstrual cycle
Baroreflex sensitivity (BRS)
Beat to beat SBP and interbeat interval (IBI) time series were detrended and Hanning
windowed. Power spectral density and cross-spectra of SBP and IBI in the low-frequency
band (0.06-0.15 Hz) and the high-frequency band (0.15-0.35 Hz) were computed using
discrete Fourier transform as described elsewhere.18 The cross-correlation method xBRS
(BMEYE, Amsterdam, the Netherlands) was used for time-domain analysis of spontaneous
BRS 19 For this purpose the SDP and IBI time series were resampled at 1Hz. In a 10-s
window, the correlation and regression slope between SBP and IBI were computed. These
computations were done for 0 to 5 s delays in IBI with respect to SBP and the delay with
the highest positive coefficient of correlation was selected. The slope between SBP and IBI
was recorded as BRS estimate if the correlation was significant at p=0.01.
Statistics
Results were compared by paired t-test or Wilcoxon signed ranks test as appropriate. A
sample size of 35 participants allowed for the detection of a blood pressure difference
of 2 mmHg between the two measurement periods, assuming a mean blood pressure of
100 mmHg and a standard deviation of 10 mmHg with alpha 0.05 and beta 0.2.
RESULTS
Thirty-nine participants were recruited; all women were tested in both phases; 18 women
entered the study in the follicular phase and 21 women in the luteal phase. They had a
mean age of 29 ( ±4.7) years and a mean body mass index of 22.0 (± 2.3) kg/m2 at the
first measurement. Blood pressure measured by conventional sphygmomanometry and
Table 1. Comparison of hemodynamic parameters by phase of the menstrual cycleDay 5-10 Day18-25 P-value
Sphygmomanometry measurementsSBP (mmHg) 112 ±8 110± 9 0.21
DBP (mmHg) 73± 7 73 ±8 0.98
Portapres measurements
SBP (mmHg) 105 ± 11 105 ± 12 0.93
DBP (mmHg) 59 ± 7 60 ±8 0.56
MAP (mmHg) 78±9 79 ±10 0.74
HR (bpm) 69± 9 69 ±9 0.62
CO ( l/min) 5.9 ±1.4 6.2 ±1.9 0.38TPR (dyne.s-1.cm-5) 0.81±0.2 0.83±0.2 0.70
Data presented as mean ± standard deviation and P values calculated with paired t-test. SBP: systolic blood pressure, DBP: diastolic blood pressure, MAP: mean arterial pressure, HR: heart rate, CO: cardiac output, TPR: total peripheral resistance.
136
the parameters measured by the Portapres (SBP, DBP, HR, CO and TPR) were comparable
between the two phases of the menstrual cycle (table 1). SBP and DBP measured by
Portapres were significantly lower than SBP and DBP measured by sphygmomanometry
in both periods (p<0.01).
There was no difference of BRS and phase angle difference measured with spectral
analysis and xBRS between the two periods (figures 1). None of the measurements were
influenced by age or body mass index.
Figure 1. Baroreflex sensitivity measured with spectral analysis at low frequency (A), with xBRS (B) and phase angle difference with spectral analysis (C) at day 5-10 and day 18-25 of the menstrua; cycle. Data are displayed using box whisker plots. The box indicates the lower and upper quartiles and the central line is the median. The horizontal lines are the 2.5th and 97.5th centiles. There were no significant differences between both phases.
DISCUSSION
To our knowledge this is the first study of the baroreflex during the menstrual period
with an adequate sample size. We observed no differences in blood pressure and heart
rate between days 5 and 10 and days 18 and 25 of the menstrual cycle, which agrees
with previous studies.9;11;20-22 Our observation that hemodynamic parameters, BRS and
sympathetic activity were comparable in the first and second half of the menstrual cycle
agrees with a number of studies. 9;23;24 However, Tanaka and co-workers observed
greater baroreflex sensitivity in the early follicular phase compared to the midluteal phase
in response to a decrease in arterial blood pressure by nitroprusside, using tonometry for
blood pressure registration.10 Minson and co-workers performed a similar experiment
and did not detect such a difference, using finger pulse registration for blood pressure
calculation (Finapres), which is similar to our method.9 Additionally, this study reported
a higher sympathetic outflow of muscle sympathetic nerve activity(MSNA), determined by
microneurography and an increased sympathetic baroreflex sensitivity based on MSNA/
diastolic blood pressure slopes in the midluteal phase.9 They concluded that hormonal
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odynamics and the m
enstrual cycle
fluctuations during the normal menstrual cycle may alter sympathetic outflow but vascular
resistance is not increased. They hypothesized that the increase of sympathetic activity is
balanced by an increase of the vasodilator nitric oxide. A similar interpretation of data
was made in a longitudinal study before and during pregnancy in women who developed
preeclampsia.4
Sato and co-workers demonstrated a higher low frequency/ high frequency ratio of heart
rate variability with spectral analysis in the luteal phase.25 They suggest that sympathetic
nervous activity is predominant in the luteal phase as compared to the follicular phase.
This was not confirmed by others, using spectral analysis of heart rate variability.26;27
Blood pressure measurements with the Portapres were significantly lower than by
sphygmomanometry. The differences in DBP can be explained because measurements
with the Portapres with Return to Flow method intends to reconstruct brachial intra-arterial
pressure in a non-invasive way,17 whereas sphygmomanometry overestimate brachial
intra-arterial diastolic blood pressure.28 Sphygmomanometry always involves a certain
amount of stress due to the painfulness of cuff inflation and blood pressure rises slightly
during measurements with an upper-arm cuff.29 However, with a continuous method like
the Portapres the subject is completely at rest after a period of accustomization.
No hormone levels were measured because subjects were only selected if they had
a regular menstrual cycle between 26 and 32 days for several months. Ninety-eight
percent of women with a regular cycle have an ovulation with changes in estrogen and
progesterone plasma concentration.30 It is unlikely that our observation of similarity
between follicular and luteal phase could have been influenced by one or two subjects
without ovulation.
We chose a wide range (days 5 to10 and days 18 to 25) for the examination day. By
making this selection it might be possible that effects caused by the periovulatory estrogen
peak were not detected. However the differences in estrogen and progesterone levels
between days 5 and 10 and days 18 and 25 are of such a magnitude that significant
effects, if present, should have been detected in our study.31
Because we intend to perform a longitudinal study of the change of cardiovascular
control from the non-pregnant state to early pregnancy in future research, no controlled
stimulation of the cardiovascular system by drug injections was used as these would
not be acceptable in early pregnancy. Spontaneous BRS and drugs-induced BRS both
reflect baroreflex physiology and are generally correlated.32 In this study we measured
spontaneous BRS by averaging data over a time period of 10 minutes to get a reliable
estimation.
We only measured BRS in rest and we did not use cardiovascular reflex tests like orthostatic
stress test, isometric handgrip test, Valsalva’s manoeuvre or deep breathing test. Previous
138
work by our group did not demonstrate differences with these tests between women, who
developed preeclampsia and women who had an uneventful pregnancy. Furthermore,
it appeared difficult to perform such tests in a standardized way in pregnant women.33
CONCLUSION
No significant differences in blood pressure and baroreflex were found between days 5
and 10 and days 18 and 25. This implicates that it is not necessary to take the phase of
the menstrual cycle into account in a study of cardiovascular changes between the non-
pregnant and the pregnant state. Nevertheless it might be sensible to select the first half
of the cycle to be certain that no pregnancy exists as the influence of very early pregnancy
is unknown.
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odynamics and the m
enstrual cycle
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overactivity. N.Engl.J.Med. 1996;335:1480-85. 3. Conde-Agudelo A, Villar J, Lindheimer M. World Health Organization systematic review of
screening tests for preeclampsia. Obstet.Gynecol. 2004;104:1367-91. 4. Rang S, Wolf H, Montfrans GA, Karemaker JM. Serial assessment of cardiovascular control
shows early signs of developing pre-eclampsia. J.Hypertens. 2004;22:369-76. 5. Courtar DA, Spaanderman ME, Aardenburg R, Janssen BJ, Peeters LL. Low plasma volume
coincides with sympathetic hyperactivity and reduced baroreflex sensitivity in formerly preeclamptic patients. J.Soc.Gynecol.Investig. 2006;13:48-52.
6. Oelkers WK. Effects of estrogens and progestogens on the renin-aldosterone system and blood pressure. Steroids 1996;61:166-71.
7. Mendelsohn ME. Protective effects of estrogen on the cardiovascular system. Am.J.Cardiol. 2002;89:12E-7E.
8. Orshal JM, Khalil RA. Gender, sex hormones, and vascular tone. Am.J.Physiol Regul.Integr.Comp Physiol 2004;286:R233-R249.
9. Minson CT, Halliwill JR, Young TM, Joyner MJ. Influence of the menstrual cycle on sympathetic activity, baroreflex sensitivity, and vascular transduction in young women. Circulation 2000;101:862-68.
10. Tanaka M, Sato M, Umehara S, Nishikawa T. Influence of menstrual cycle on baroreflex control of heart rate: comparison with male volunteers. Am.J.Physiol Regul.Integr.Comp Physiol 2003;285:R1091-R1097.
11. Dubey RK, Oparil S, Imthurn B, Jackson EK. Sex hormones and hypertension. Cardiovasc.Res. 2002;53:688-708.
12. Imholz BP, Wieling W, van Montfrans GA, Wesseling KH. Fifteen years experience with finger arterial pressure monitoring: assessment of the technology. Cardiovasc.Res. 1998;38:605-16.
13. Penaz, J. Photoelectric measurement of blood pressure, volume and flow in the finger. Digest 10th Int Conf Med Biol Engp . 1973
14. Hehenkamp WJ, Rang S, van Goudoever J, Bos WJ, Wolf H, van der Post JA. Comparison of Portapres with standard sphygmomanometry in pregnancy. Hypertens.Pregnancy. 2002;21:65-76.
15. Imholz BP, Langewouters GJ, van Montfrans GA, Parati G, van GJ, Wesseling KH et al. Feasibility of ambulatory, continuous 24-hour finger arterial pressure recording. Hypertension 1993;21:65-73.
16. Jellema WT, Wesseling KH, Groeneveld AB, Stoutenbeek CP, Thijs LG, van Lieshout JJ. Continuous cardiac output in septic shock by simulating a model of the aortic input impedance: a comparison with bolus injection thermodilution. Anesthesiology 1999;90:1317-28.
17. Bos WJ, van GJ, van Montfrans GA, van den Meiracker AH, Wesseling KH. Reconstruction of brachial artery pressure from noninvasive finger pressure measurements. Circulation 1996;94:1870-75.
18. deBoer RW, Karemaker JM, Strackee J. Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. Am.J.Physiol 1987;253:H680-H689.
19. Westerhof BE, Gisolf J, Stok WJ, Wesseling KH, Karemaker JM. Time-domain cross-correlation baroreflex sensitivity: performance on the EUROBAVAR data set. J.Hypertens. 2004;22:1371-80.
20. Van Beek E., Houben AJ, van Es PN, Willekes C, Korten EC, De Leeuw PW et al. Peripheral haemodynamics and renal function in relation to the menstrual cycle. Clin.Sci.(Lond) 1996;91:163-68.
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21. Giannattasio C, Failla M, Grappiolo A, Stella ML, Del BA, Colombo M et al. Fluctuations of radial artery distensibility throughout the menstrual cycle. Arterioscler.Thromb.Vasc.Biol. 1999;19:1925-29.
22. Williamson PM, Buddle ML, Brown MA, Whitworth JA. Ambulatory blood pressure monitoring (ABPM) in the normal menstrual cycle and in women using oral contraceptives. Comparison with conventional blood pressure measurement. Am.J.Hypertens. 1996;9:953-58.
23. Cooke WH, Ludwig DA, Hogg PS, Eckberg DL, Convertino VA. Does the menstrual cycle influence the sensitivity of vagally mediated baroreflexes? Clin.Sci.(Lond) 2002;102:639-44.
24. Meendering JR, Torgrimson BN, Houghton BL, Halliwill JR, Minson CT. Menstrual cycle and sex affect the hemodynamic responses to combined orthostatic and heat stress. Am.J.Physiol Heart Circ.Physiol 2005.
25. Sato N, Miyake S, Akatsu J, Kumashiro M. Power spectral analysis of heart rate variability in healthy young women during the normal menstrual cycle. Psychosom.Med. 1995;57:331-35.
26. Leicht AS, Hirning DA, Allen GD. Heart rate variability and endogenous sex hormones during the menstrual cycle in young women. Exp.Physiol 2003;88:441-46.
27. Saeki Y, Atogami F, Takahashi K, Yoshizawa T. Reflex control of autonomic function induced by posture change during the menstrual cycle. J.Auton.Nerv.Syst. 1997;66:69-74.
28. Ochiai H, Miyazaki N, Miyata T, Mitake A, Tochikubo O, Ishii M. Assessment of the accuracy of indirect blood pressure measurements. Jpn.Heart J. 1997;38:393-407.
29. van Montfrans GA, van der Hoeven GM, Karemaker JM, Wieling W, Dunning AJ. Accuracy of auscultatory blood pressure measurement with a long cuff. Br.Med.J.(Clin.Res.Ed) 1987;295:354-55.
30. Waller K, Swan SH, Windham GC, Fenster L, Elkin EP, Lasley BL. Use of urine biomarkers to evaluate menstrual function in healthy premenopausal women. Am.J.Epidemiol. 1998;147:1071-80.
31. Speroff L, Fritz M.A. Clinical Gynecologic Endocrinology and Infertility. Philadelphia, USA: 2005:187-232.
32. Parati G, Di RM, Castiglioni P, Bouhaddi M, Cerutti C, Cividjian A et al. Assessing the sensitivity of spontaneous baroreflex control of the heart: deeper insight into complex physiology. Hypertension 2004;43:e32-e34.
33. Rang S, Wolf H, Montfrans GA, Karemaker JM. Non-invasive assessment of autonomic cardiovascular control in normal human pregnancy and pregnancy- associated hypertensive disorders: a review. J.Hypertens. 2002;20:2111-19.
19 Summary, conclusion and recommendations
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ary, conclusion and recomm
endations
SUMMARY
Preeclampsia is a major cause of maternal and neonatal morbidity and mortality. The
precise underlying mechanisms are unknown and are probably related to vascular,
immunological, genetic and environmental factors.1 Despite extensive research the onset
of preeclampsia and disease progression remains unpredictable and there is no real cure
except inducing delivery. Although the clinical symptoms appear in the second half of
pregnancy the origin of the underlying pathophysiologic mechanisms is thought to occur
much earlier in pregnancy at the time of placentation.
Prevention of preeclampsia will have a huge impact on maternal health worldwide.
Because the origin of the disease is early in pregnancy development of methods for
early detection of the preclinical stage and thus prediction of preeclampsia is of major
importance. Though some promising tests seem to arise,2;3 up to now such predictive
test is not available.4
The work presented in this thesis focuses on cardiovascular differences in the beginning
of pregnancy between women with a healthy pregnancy and women who develop
preeclampsia later in pregnancy and in the modifiable risk factors psychosocial stress
and physical activity. Effective risk assessment enables targeting intensified obstetric care
at those who need this most and selection of high risk women for the assessment of
preventive treatment strategies.
This chapter summarizes the findings from this research and evaluates the results and
future research implications. While up to now most predictive tests were designed to
be performed in the second trimester we evaluated tests for the first trimester in the
expectation that any possible preventive treatment should be applied early in pregnancy
before the development of placental vascular supply is finished.5-7 Preeclampsia and
gestational hypertension were defined according to the guidelines of the International
Society for the Study of Hypertension in Pregnancy.8
SYSTEMATIC REVIEW
In chapter 2 we present a systematic review on the use of blood pressure as a predictive
test for preeclampsia. Medline, Embase, Cochrane library, Medion and reference lists
of included articles were searched from inception to February 2007. 34 studies were
included testing 60.599 women with 3341 cases of preeclampsia. Clinical heterogeneity
between studies was found for the method or device used for measuring blood pressure,
146
the definition of preeclampsia used and the risk for preeclampsia in the patients under
study. In women at a low risk for preeclampsia the areas under the summary receiver
operating characteristics curves in the second trimester were 0.68 (95% CI 0.64-0.72),
0.66 (95% CI 0.59-0.72) and 0.76 (95% CI 0.70-0.82) for systolic blood pressure,
diastolic blood pressure and mean arterial pressure, respectively. Only six studies
reported blood pressure measurements in the first trimester. These studies showed similar
results. Second trimester mean arterial pressure of 90 mmHg or more showed a positive
likelihood ratio of 3.5 (95% CI 2.0-5.0) and a negative likelihood ratio of 0.46 (95% CI
0.16-0.75). In women at high risk a diastolic blood pressure of 75 mmHg or more at
13 to 30 weeks of gestational age predicted preeclampsia best: positive likelihood ratio
of 2.8 (95% CI 1.8-3.6) and a negative likelihood ratio of 0.39 (95% CI 0.18-0.71).
Additional subgroup analysis did not show improved predictive accuracy.
We concluded that as a single test blood pressure is insufficient for the prediction
of preeclampsia or selection of women at risk in daily clinical practice. Of all blood
pressure measurements the mean arterial pressure is the most promising parameter.
It was not possible to investigate if automated devices are superior to conventional
sphygmomanometry. This is subject to further study.
Prospective cohort study
We collected a prospective cohort of healthy nulliparous women and multiparous
women with an increased risk for developing hypertensive disorders to investigate if
cardiovascular differences can be observed early in pregnancy between women, who will
develop preeclampsia or gestational hypertension later in pregnancy and women with an
uncomplicated pregnancy. We measured blood pressure early in pregnancy between 8 0/7-11 0/7 weeks gestational age using conventional sphygmomanometry (Maxi Stabil 3,
an aneroid sphygmomanometer, Welch Allyn, Skaneateles Falls, New York, USA) (using
an aneroid sphygmomanometer), continuous finger arterial waveform registration by the
FinometerTM (Finapres Medical Systems, Amsterdam, The Netherlands) and ambulatory
blood pressure monitoring (ABPM) for 48 hours with the Spacelab 90207TM (Redmond,
WA, USA). Further data to be collected were age, ethnic origin, smoking, medical history,
and weight and length.
295 women were included, 251 nulliparous women and 44 multiparous women with a
history of preeclampsia. Five women were excluded because of serious fetal congenital
malformations and one woman was lost to follow up. 289 Women were available for
analysis, 20 (6.9 %) developed preeclampsia and 16 (5.5 %) gestational hypertension.
39 women had an incomplete ABPM registration due to signal loss and patient non-
Chapter 9
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endations
compliance. Of these women 28 had at least 10 measurements in 48 hour and were
used for analysis. Study results from this cohort are presented in chapter 3, 4 and 5.
Using 48 hour measurements of the ABPM the hyperbaric index (HBI) can be calculated
as the amount of blood pressure excess during the measurement period above a
90% tolerance limit.9 One research group evaluated the HBI for the prediction of
preeclampsia with extremely good results; they observed a sensitivity of 94% and a
specificity of 100%.10;11 Since the original report by Hermida et al. only one other
group studied HBI in pregnancy in a hospital-based research setting (sensitivity 80% and
specificity 77%).10 Therefore, we wanted to validate the HBI as a test for the prediction
of preeclampsia in our own cohort. In chapter 3 we present the results of this study.
We compared the predictive efficacy of the HBI with mean ABPM measurement for 48
hours and conventional manometry in our research cohort of nulliparous women and
parous women with a previous preeclampsia. We could include 219 of the 289 women
in our cohort in this study. For 42 women no ABPM measurement was available on
inclusion. Data of 28 women could not be analysed because of missing measurements
or failure of the device. The first 90 nulliparous women who had an uneventful pregnancy
formed thereference group for calculation of a time specified tolerance interval with 90%
confidencelimits. In the validation group, consisting of the remaining 63 nulliparous
women and 38 women with previous preeclampsia, the hyperbaric index was calculated
as the time-specified blood pressure excess over this tolerance limit for SBP, DBP and
mean arterial pressure. The maximum HBI was defined as the maximum value of either
the HBI of SBP or DBP or MAP for each individual.
For preeclampsia the maximum HBI had the best predictive capacity, however, the
difference with standard ABPM measurement or conventional manometry was small.
The HBImax had a sensitivity of 73 % and a specificity of 86 % at an optimum cut-off
of 17.6mmHg x hour. SBP with sphygmomanometry had a sensitivity of 60 % and a
specificity of 92 % at a cut-off of 118 mmHg and 24 hours ABPM using DBP had a
sensitivity of 53 % with a specificity of 95% at a cut-off of 74 mmHg. The predictive
efficacy for gestational hypertension was poor with all methods (sensitivity between 54 %
and 77 %, specificity between 41 % and 78 %).
We concluded that conventional manometry, ABPM measurement and the HBI calculated
from 48 hour ABPM had a comparable, restricted predictive efficacy in a group with low
and high risk women. The high predictive value of the HBI as observed in earlier studies
could not be reproduced and therefore this method can not be recommended for use in
daily practice.
148
We observed a significantly higher blood pressure in women who developed preeclampsia
or gestational hypertension in the first trimester compared to women with unaffected
pregnancies with all three devices (Chapter 4). The absolute blood pressure values were
different between the devices. The point estimate of the Odds ratios of blood pressure
(SBP, DBP or MAP) in the first trimester after adjustment for previous preeclampsia for later
preeclampsia or combined pregnancy outcome (preeclampsia or gestational hypertension)
was higher using the automated blood pressure measurement techniques compared to
conventional sphygmomanometry, although there was a considerable overlap of 95%
CI intervals. The area under the ROC curves for conventional sphygmomanometry with
preeclampsia as pregnancy outcome were 0.73 (95% CI 0.58-0.83), 0.68 (95% CI
0.53-0.84) and 0.70 (95% CI 0.55-0.85) for SBP, DBP and MAP respectively. For finger
arterial pressure waveform registration this was 0.82 (95% CI 0.68-0.95), 0.77 (95% CI
0.63-0.91) and 0.82 (95% CI 0.69-0.96) and for ABPM 0.78 (95% CI 0.65-0.91), 0.77
(95% CI 0.63-0.90) and 0.78 (95% CI 0.65-0.91) for SBP, DBP and MAP respectively.
For the combined pregnancy outcome results were comparable.
Since signal loss in ABPM is considerable with sub-optimal patient compliance and
conventional sphygmomanometry is subject to considerable interobserver variation in
daily practice we concluded that early pregnancy blood pressure measurement by finger
arterial pressure waveform registration is the most promising automated blood pressure
measurement technique to study in a prospective large cohort study.
In chapter 5 we use data from our research cohort to evaluate arterial stiffness early
in pregnancy and the association with later preeclampsia. We hypothesised that the
combination with blood pressure (MAP) could improve this association.
235 nulliparous women and 42 parous women were included with an incidence of
preeclampsia of 4.3% and 16.6% respectively. Data collected with finger arterial
waveform registration were used. The finger arterial waveform was filtered to an aortic
waveform and the augmentation indexes (AIx) and augmentation pressure (AP) were
determined. After adjustment for previous preeclampsia the AIx and AP were associated
with later preeclampsia, areas under the ROC-curves 0.74 (95% CI 0.61-0.87) and
0.77 (95% CI0.61-0.87). When MAP was added to the model, the combination with
AP had the highest area under the ROC-curve (0.82 (95% CI 0.66-0.97)). This is not a
considerable improvement compared to MAP and parity alone, area under the ROC-
curve 0.79 (95% CI 0.64-0.93). Our results do not support the addition of AIx or AP to
blood pressure measurement, which is far easier to apply, for the assessment of risk for
preeclampsia.
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Hypertensive disorders in pregnancy and adult cardiovascular diseases share predisposing
conditions, like elevated blood pressure, diabetes and obesity. Protective or disease
modifying factors of cardiovascular disease might also be applicable for the prevention
of hypertensive disorders in pregnancy. One of these factors is psychosocial stress.11;12
Several studies showed a relation with high psychosocial stress in pregnancy and
hypertensive disorders of pregnancy.15-18 However most of these studies are retrospective
or case-control studies.
In chapter 6 we investigated the association of preeclampsia and gestational hypertension
with psychosocial stress in the first half of pregnancy in a prospective cohort study. For
this study we used the data of the Amsterdam Born Children and their Development
study (ABCD-study). This is a prospective community-based study which examines the
relationship between various lifestyles during pregnancy and pregnancy outcome in a
multicultural population. For this assessment we included only the nulliparous women
with a singleton pregnancy in this cohort, who completed the questionnaire before 24
weeks, and delivered after 24 weeks. A postpartum questionnaire was used to gather
information on preeclampsia, hypertension or proteinuria. Data were linked with the
Dutch national obstetric register and all women who were coded as having hypertensive
complications in pregnancy were selected. Medical files were examined for all selected
women, either from the questionnaires, or from the Dutch national obstetric register
to confirm the diagnosis of preeclampsia and gestational hypertension according
to the International Society for the Study of Hypertension in Pregnancy guidelines.
From the non-selected women a random sample of 5% was drawn for confirmation
of absence of hypertensive complications by examination of medical files. The study
population consisted of 128 women with preeclampsia, 161 women with gestational
hypertension and 3390 controls. Psychosocial stress was defined as work stress (Work
Experience and Appreciation Questionnaire of van Velthoven et al,13 partly based on
the Job Content Instrument of Karasek et al.14), anxiety (the State-Trait Anxiety Inventory,
STAI15), depression (Center for Epidemiological Studies Depression Scale, CES-D16;17)
and pregnancy related anxiety (PRAQ-R18). After correction for sociodemographic and
medical confounders, we could not observe an association of psychosocial stress in the
first half of pregnancy with later preeclampsia or gestational hypertension.
Using the same cohort as described in chapter 6 we studied another disease modifying
factor for adult cardiovascular disease i.e. physical exercise. Physical exercise is known to
prevent cardiovascular disease and to reduce its symptoms. In chapter 7 we assessed if
physical activity in leisure time early in pregnancy reduces the incidence of preeclampsia
150
or gestational hypertension. In the questionnaire of the ABCD-study questions about
physical activity in leisure time in the past week were asked using questions about
walking, cycling, doing sports and other activities like “Do It Yourself” or gardening in
leisure time. As well the amount of time spent in minutes as the intensity of the physical
activity was asked.
After correction for sociodemographic and medical confounders, the amount of time or
intensity of physical activity in leisure time in the first half of pregnancy was not associated
with preeclampsia or gestational hypertension.
Many researchers focus on risk assessment for preeclampsia in (early) pregnancy
while developing prediction models which can be used before pregnancy are equally
interesting. It is well known that ovarian hormones affect the cardiovascular and renin-
aldosteron system.19-21 However, the magnitude of the effect of hormonal fluctuations
during the menstrual cycle on blood pressure regulation is not clear and literature in this
respect is not consistent.22-24 Moreover it is unclear if it is important to take into account
the menstrual cycle while performing measurements before conception. The purpose
of the study described in chapter 8 was to evaluate if hemodynamic parameters and
cardiovascular control vary between the follicular and luteal phase of the menstrual
cycle. Healthy women who were never pregnant were studied at days 5 to 10 and days
18 to 25 of the menstrual cycle. Blood pressure, heart rate, cardiac output and total
peripheral resistance were measured continuously using non-invasive finger arterial
pressure waveform registration. Baroreflex sensitivity (BRS) and sympathetic activity by
phase angle difference were studied using spectral analysis and xBRS. There were no
differences in hemodynamic parameters, BRS and sympathetic activity between the two
phases of the menstrual cycle.
We concluded that, although there is no difference in blood pressure, BRS and sympathetic
activity between the first and second half of the menstrual period, measurements are
preferably performed in the first half of the menstrual cycle as one is certain that no
pregnancy exists, since the magnitude of the influence on blood pressure of very early
pregnancy is unknown.
GENERAL DISCUSSION
This thesis reports on hemodynamic parameters early in pregnancy associated with the
development of preeclampsia or gestational hypertension later in pregnancy. These
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variables could be used for development of models for the prediction of gestational
hypertensive disease.
For a model for the prediction of preeclampsia the nature and magnitude of risk indicators
is essential. This model might in addition help to better understand the pathophysiological
mechanism of the disease and to design preventive therapies. Selection of high risk women
facilitates the establishment of effectiveness of these preventive strategies, because the
low incidence of preeclampsia in an unselected population necessitates large patient
cohorts. Strategies for prevention will have to start early in pregnancy because the origin
of the disease is thought to occur at the time of placentation.25 Consequently, a test for
the selection of women at high risk should be effective in the first trimester of pregnancy.
Furthermore, the selection of women at high risk for obstetric complications enables
targeting of intensive obstetric care at those who will benefit most. A predictive test needs
a high sensitivity to reduce the number of false-negatives since the consequences of
preeclampsia are severe for mother and child. Severe preeclampsia is a rare disease
(0,5 %) which means that test characteristics must also show high specificity. Until now
such test in the first trimester is not available for screening in the general population.26
Studies in this thesis confirmed that blood pressure is increased already in the first
trimester in women with normal blood pressure according to standard criteria, who will
develop preeclampsia or gestational hypertension. This difference of blood pressure can
potentially be used for prediction (chapter 3 and 4). This association was independent
of the device used. The mean arterial pressure (MAP) had the best predictive capacity
according to our meta-analysis of the literature.27 This we could only partially confirm in
our prospective cohort study in first trimester pregnancy. We found a higher association
with later preeclampsia (higher point estimate of Odds ratios) of ABPM and of finger
arterial waveform registration than of conventional sphygmomanometry. Unfortunately
our sample size was not large enough for detecting significant differences. Wearing an
ABPM device for 48 hours was considered as a burden and this resulted in 18% signal
loss. 28 women discontinued wearing the device because it impeded them in their daily
activities or disturbed their sleep. Especially sleep disturbance is reported as a major
cause of noncompliance.28
By using finger arterial waveform registration not only blood pressure is measured.
From the peripheral pulse wave the aortic pressure wave can be reconstructed and
parameters of arterial compliance can be calculated. This can be used to gain more
knowledge about preeclampsia and the development of the disease during pregnancy.
Increased arterial stiffness is an independent predictor of adverse outcome in adult
cardiovascular disease.29 Several studies showed an elevated arterial stiffness in women
with preeclampsia.30-33 Although in our prospective cohort study (chapter 5), women
152
who developed later preeclampsia had a higher AIx and AP compared to women with
an uncomplicated pregnancy, we found, in contrast to the results of an other research
group, comparable Odds ratios with mean arterial blood pressure.34 We concluded
that there are no advantages of adding the AIx or AP to automated blood pressure in
predicting preeclampsia.
Several other factors early in pregnancy are associated with later preeclampsia and their
predictive capacity has been studied by others. Maternal factors like age, BMI, a previous
pregnancy with preeclampsia and medical history are associated with the development
of preeclampsia.35 Even when these maternal factors are combined in a multivariate
analysis and a prediction algorithm is developed the detection rate of preeclampsia is
low. At a 5% false positive rate the detection rate of preeclampsia was approximately 30%
and 20 % for gestational hypertension.36 Other potential predictors like abnormal uterine
artery Doppler findings or biochemical markers have also been investigated. Uterine
artery Doppler assessment showed to be of limited value as a screening test. In a meta-
analysis Cnossen et al. found a sensitivity of 43% and a specificity of 93% for bilateral
notching of the uterine arteries in the second trimester in a low risk population.37 Serum
markers for Down’s syndrome are also not suitable as a single test.38 Prediction using
angiogenic factors is only reported in small studies and have insufficient discriminative
capacity.39 Combination of biochemical markers and abnormal uterine artery Doppler
findings improved the performance of early prediction of preeclampsia but in low risk
population the sensitivity was not higher than 60-80%.40 Recent developments using
metabolomics for predicting of preeclampsia need confirmation in large cohorts with
selected variables.3
A clinically useful prediction test will probably integrate a combination of multiple known
factors associated with preeclampsia. Earlier in this thesis we considered that preeclampsia
and cardiovascular disease had similar risk indicators. The most frequently used
prediction model for cardiovascular disease is the Framingham score (using sex, age, total
cholesterol, high-density-lipoprotein cholesterol, systolic blood pressure and smoking-
status) for estimating 10-year risk for adverse cardiovascular outcome. Until now this
model could not be improved by adding new biomarkers associated with cardiovascular
risk obtained by large scale genomic analysis of patients.41 These prediction models
including the Framingham score are not useful for prediction of preeclampsia so we have
to search for at more pregnancy specific markers. Using logistic regression analysis Poon
et al. developed an algorithm for the early prediction of preeclampsia combining the
logs of the uterine artery pulsatility index, mean arterial pressure, pregnancy-associated
plasma protein-A, and placental growth factor and maternal factor-derived a-priori
risk.42 Blood pressure was measured with an automated device using oscillometry. Using
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the same variables they developed three prediction models, for preeclampsia before 34
weeks of pregnancy (early preeclampsia), preeclampsia after 34 weeks of pregnancy (late
preeclampsia) and gestational hypertension. At 110/7-136/7 weeks of pregnancy 93.1%
of the women with early preeclampsia, 35.7% of the women with late preeclampsia,
and 18.3% of the women who developed gestational hypertension could be detected
with a 5% false-positive rate. This model seems promising although 476 women tested
positive for early preeclampsia, of whom 32 actually developed early disease and 444
did not. Two cases with early preeclampsia were missed. Only 35.7% of the women with
preeclampsia after 34 weeks of pregnancy were identified. Because preeclampsia at
term is associated with severe maternal morbidity and mortality this model still must be
improved before it is suitable for daily clinical practice.
The authors made different models for early and late preeclampsia with different predictive
capacity. While early preeclampsia is often complicated by fetal growth retardation
because of poor placentation, in late preeclampsia the placenta and fetus often have
an appropriate size for the gestational age. It is hypothesized that early preeclampsia is
caused by excessive or atypical maternal immune response to poor placentation while
in late preeclampsia predisposing cardiovascular and metabolic disorders are more
prominent factors that lead to a cascade of placental and systemic inflammation and
oxidative stress resulting in preeclampsia.43 This indeed can explain the necessity for
different prediction models.
Women with obesity, chronic hypertension, vascular disease, diabetes, or a previous
preeclampsia have an increased risk for developing preeclampsia. Seed et al. found an
incidence of preeclampsia 23% in nulliparous women with chronic hypertension and a
body mass index >30 m/kg2. In women with chronic hypertension and preeclampsia in a
previous preeclampsia 30% developed again preeclampsia.44 If prevention for preeclampsia
will be available it is probably more cost-effective to treat these women without testing. It
will depend on screening test efficacy and the benefit of a potential preventive treatment
to determine at which a priori risk it is cost effective to use screening for the selection of
women for preventive therapy in stead of advising preventive treatment to all.
The development of prediction models is hampered by the low incidence of preeclampsia
as a low number of events (the occurrence of preeclampsia) and many suspected
confounders cause an overestimation of regression coefficients.45 For the same reasons
we could not develop a prediction model in our cohort.
All reported models have to be validated in an external population. They must be tested
by other investigators and in populations that differ from those used to develop them, in
order to validate their use in daily clinical practice. This is underlined by the present thesis
in which we show the importance of external validation since we could not reproduce the
154
high predictive capacity of the HBI and of the AIx as found by others.34;46;47 Even if this
could be explained by small differences in population or gestational age this makes these
markers questionable for prediction of preeclampsia in the general population.
IMPLICATIONS FOR FUTURE RESEARCH
1. Development of prediction models
Prediction of preeclampsia early in pregnancy or even before pregnancy remains
important to facilitate timely preventive strategies. Prevention will have to start early
because the origin of the disease is thought to occur at the time of placentation. Large
population-based studies evaluating algorithms combining maternal characteristics
with mean arterial pressure and other parameters measured in the first trimester are
needed. As women with hypertension, renal disease, diabetes or a previous preterm
preeclampsia are at high risk for developing preeclampsia, further selection is
questionable. Because 2/3 of all cases of preeclampsia occur in nulliparous women
and in most of these cases the disease starts unexpectedly and acutely, research
should focus on this group. Possibly different prediction models are needed for early
and late preeclampsia.
2. Use of automated blood pressure devices in prediction of hypertensive disease
Conventional sphygmomanometry is sufficient to diagnose preeclampsia since
most data for intervention and anti hypertensive treatment are based on this type
of measurement. Several automated devices are validated in pregnancy and
measure blood pressure securely and in addition can measure other cardiovascular
characteristics. Data on these additional parameters to predict preeclampsia and its
complications might be worth while to obtain. Based on our findings, finger arterial
waveform registration is the preferred method for further research.
3. Prospective collection of clinical data and biomaterials of pregnant women
Prospectively collecting and storing clinical data and biomaterials of pregnant women
according to standardized and professional protocols is essential for developing
prediction models. As shown by us and by other research groups blood pressure
alone measured by conventional sphygmomanometry or other devices is not sufficient
to predict preeclampsia in daily clinical practice.27;48 A useful model will probably
contain maternal characteristics, blood pressure and biomarkers. Large cohorts are
being studied at this time and the first data are emerging. The Scope study collects such
a cohort and is an example of a high quality biobank in New Zealand, Australia, the
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UK and the USA.3;49 Since Dutch obstetricians and midwives are very well organized
in research consortia the same effort is recommended within for example the String of
Pearls Initiative (www.parelsnoer.org). By collecting data together we can enhance the
development and validation of such a prediction model.
156
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(16) Hanewald G.J.F.P. CES-D: De Nederlandse versie. Een onderzoek naar de betrouwbaarheid en validiteit. 1987. Amsterdam, University of Amsterdam, department of Clinical Psychology.
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(21) Orshal JM, Khalil RA. Gender, sex hormones, and vascular tone. Am J Physiol Regul Integr Comp Physiol 2004; 286(2):R233-R249.
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(23) Tanaka M, Sato M, Umehara S, Nishikawa T. Influence of menstrual cycle on baroreflex control of heart rate: comparison with male volunteers. Am J Physiol Regul Integr Comp Physiol 2003; 285(5):R1091-R1097.
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(25) Lykke JA, Langhoff-Roos J, Sibai BM, Funai EF, Triche EW, Paidas MJ. Hypertensive pregnancy disorders and subsequent cardiovascular morbidity and type 2 diabetes mellitus in the mother. Hypertension 2009; 53(6):944-951.
(26) Cnossen JS, Ter RG, Mol BW, van der Post JA, Leeflang MM, Meads CA et al. Are tests for predicting pre-eclampsia good enough to make screening viable? A review of reviews and critical appraisal. Acta Obstet Gynecol Scand 2009; 88(7):758-765.
(27) Cnossen JS, Vollebregt KC, de VN, Ter RG, Mol BW, Franx A et al. Accuracy of mean arterial pressure and blood pressure measurements in predicting pre-eclampsia: systematic review and meta-analysis. BMJ 2008; 336(7653):1117-1120.
(28) Walker SP, Permezel MJ, Brennecke SP, Tuttle LK, Higgins JR. Patient satisfaction with the SpaceLabs 90207 ambulatory blood pressure monitor in pregnancy. Hypertens Pregnancy 2004; 23(3):295-301.
(29) Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L et al. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension 2001; 37(5):1236-1241.
(30) Spasojevic M, Smith SA, Morris JM, Gallery ED. Peripheral arterial pulse wave analysis in women with pre-eclampsia and gestational hypertension. BJOG 2005; 112(11):1475-1478.
(31) Ronnback M, Lampinen K, Groop PH, Kaaja R. Pulse wave reflection in currently and previously preeclamptic women. Hypertens Pregnancy 2005; 24(2):171-180.
(32) Robb AO, Mills NL, Din JN, Smith IB, Paterson F, Newby DE et al. Influence of the menstrual cycle, pregnancy, and preeclampsia on arterial stiffness. Hypertension 2009; 53(6):952-958.
(33) Avni B, Frenkel G, Shahar L, Golik A, Sherman D, Dishy V. Aortic stiffness in normal and hypertensive pregnancy. Blood Press 2010; 19(1):11-15.
(34) Khalil AA, Cooper DJ, Harrington KF. Pulse wave analysis: a preliminary study of a novel technique for the prediction of pre-eclampsia. BJOG 2009; 116(2):268-276.
(35) Duckitt K, Harrington D. Risk factors for pre-eclampsia at antenatal booking: systematic review of controlled studies. BMJ 2005; 330(7491):565.
(36) Poon LC, Kametas NA, Chelemen T, Leal A, Nicolaides KH. Maternal risk factors for hypertensive disorders in pregnancy: a multivariate approach. J Hum Hypertens 2009.
(37) Cnossen JS, Morris RK, Ter RG, Mol BW, van der Post JA, Coomarasamy A et al. Use of uterine artery Doppler ultrasonography to predict pre-eclampsia and intrauterine growth restriction: a systematic review and bivariable meta-analysis. CMAJ 2008; 178(6):701-711.
(38) Morris RK, Cnossen JS, Langejans M, Robson SC, Kleijnen J, Ter RG et al. Serum screening with Down’s syndrome markers to predict pre-eclampsia and small for gestational age: systematic review and meta-analysis. BMC Pregnancy Childbirth 2008; 8:33.
(39) Lim JH, Kim SY, Park SY, Yang JH, Kim MY, Ryu HM. Effective prediction of preeclampsia by a combined ratio of angiogenesis-related factors. Obstet Gynecol 2008; 111(6):1403-1409.
(40) Giguere Y, Charland M, Bujold E, Bernard N, Grenier S, Rousseau F et al. Combining Biochemical and Ultrasonographic Markers in Predicting Preeclampsia: A Systematic Review. Clin Chem 2009.
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(41) Lloyd-Jones DM. Cardiovascular risk prediction: basic concepts, current status, and future directions. Circulation 2010; 121(15):1768-1777.
(42) Poon LC, Kametas NA, Maiz N, Akolekar R, Nicolaides KH. First-trimester prediction of hypertensive disorders in pregnancy. Hypertension 2009; 53(5):812-818.
(43) Roberts JM, Hubel CA. The two stage model of preeclampsia: variations on the theme. Placenta 2009; 30 Suppl A:S32-S37.
(44) Seed PT, Chappell LC, Black MA, Poppe KK, Hwang YC, Kasabov N et al. Prediction of Preeclampsia and Delivery of Small for Gestational Age Babies Based on a Combination of Clinical Risk Factors in High-Risk Women. Hypertens Pregnancy 2010.
(45) Steyerberg EW, Eijkemans MJ, Habbema JD. Stepwise selection in small data sets: a simulation study of bias in logistic regression analysis. J Clin Epidemiol 1999; 52(10):935-942.
(46) Hermida RC, Ayala DE, Fernandez JR, Mojon A, Iglesias M. Prospective evaluation of the hyperbaric-tolerance test for the diagnosis of gestational hypertension and preeclampsia. Med Clin (Barc ) 2004; 123(5):161-168.
(47) Vollebregt KC, Gisolf J, Guelen I, Boer K, van MG, Wolf H. Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia. J Hypertens 2010; 28(1):127-134.
(48) Poon LC, Kametas NA, Pandeva I, Valencia C, Nicolaides KH. Mean arterial pressure at 11(+0) to 13(+6) weeks in the prediction of preeclampsia. Hypertension 2008; 51(4):1027-1033.
(49) Groom KM, North RA, Stone PR, Chan EH, Taylor RS, Dekker GA et al. Patterns of change in uterine artery Doppler studies between 20 and 24 weeks of gestation and pregnancy outcomes. Obstet Gynecol 2009; 113(2 Pt 1):332-338.
19 Nederlandse samenvatting, conclusies en aanbevelingen
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SAMENVATTING
Preëclampsie is een belangrijke oorzaak van zowel moederlijke als neonatale morbiditeit
en mortaliteit.1;2 Ondanks dat er al lang onderzoek naar wordt gedaan, is het ontstaan
en het verloop van de ziekte onvoorspelbaar. Ook bestaat er geen behandeling
behalve het beëindigen van de zwangerschap. De symptomen worden pas in de
tweede helft van de zwangerschap zichtbaar, terwijl het waarschijnlijk ten tijde van de
ontwikkeling van de placenta al mis gaat. Het exacte onderliggende pathofysiologische
mechanisme is onduidelijk en waarschijnlijk spelen vasculaire, immunologische,
genetische en omgevingsgerelateerde factoren een rol.3 Preventie van preëclampsie zou
wereldwijd een belangrijke bijdrage leveren aan het verbeteren van de uitkomst van
de zwangerschap voor moeder en kind. Omdat de ziekte waarschijnlijk al in het begin
van de zwangerschap ontstaat, is het vroeg kunnen voorspellen van het ontstaan van
preëclampsie erg belangrijk.3 Hoewel er op dit moment een aantal veelbelovende testen
ontwikkeld worden is een dergelijke test niet beschikbaar in de dagelijkse praktijk.4;5
Het onderzoek, beschreven in dit proefschrift, richt zich op cardiovasculaire verschillen
in het begin van de zwangerschap tussen vrouwen met een ongecompliceerde
zwangerschap en vrouwen die later in de zwangerschap preëclampsie hebben gekregen.
En ook op mogelijke risicofactoren die beïnvloedbaar zijn zoals psychosociale stress
en lichaamsbeweging. Deze verschillen en risicofactoren zouden gebruikt kunnen
worden bij het voorspellen van de kans op preëclampsie en bij eventuele preventie
van de ziekte. Wij hebben ons onderzoek voornamelijk beperkt tot vrouwen met een
eerste doorgaande zwangerschap; zij hebben namelijk een twee keer zo hoog risico op
hypertensieve aandoeningen van de zwangerschap, vergeleken met vrouwen die al een
keer een kind hebben gekregen. Bij vrouwen, die al eerder een kind hebben gekregen,
is de obstetrische voorgeschiedenis een dusdanig belangrijke voorspeller voor het al of
niet optreden van complicaties dat aanvullende testen waarschijnlijk niet nuttig meer
zijn. In dit hoofdstuk zullen de resultaten van ons onderzoek worden samen gevat en in
de discussie zal deze kennis in perspectief worden geplaatst. Ook zullen er suggesties
gedaan worden voor toekomstig onderzoek.
SYSTEMATISCHE REVIEW
In hoofdstuk 2 worden de resultaten besproken van een meta-analyse van de literatuur
naar de accuratesse van de systolische (SBP) en diastolische bloeddruk (DBP), de
gemiddelde arteriële bloeddruk (MAP) en van een stijging in de bloeddruk als voorspeller
164
van preëclampsie. Er voldeden 34 studies aan de inclusiecriteria. In totaal zijn in die
studies 60.599 vrouwen getest, waarvan 3341 met preëclampsie. Er is geen rekening
gehouden met het gebruik van verschillende methoden en apparaten om de bloeddruk te
meten. De oppervlakten onder de samenvattende receiver operating characteristic (ROC)
curven met 95% betrouwbaarheidsinterval voor bloeddrukmeting in het tweede trimester
bij vrouwenmet een laag risico zijn: 0,68 (0,64-0,72) voor de systolische bloeddruk; 0,66
(0,59-0,72) voor de diastolische bloeddruk; en 0,76 (0,70-0,82) voor de gemiddelde
arteriële bloeddruk. Bloeddrukmeting in het eerste trimester van de zwangerschap toont
vergelijkbare voorspellende waarden voor de verschillende parameters. Een gemiddelde
arteriële bloeddruk ≥ 90 mmHg in het tweede trimester toont een likelihood ratio voor een
positief test resultaat van 4,0 (95% betrouwbaarheidsinterval 2,4-5,6) en een likelihood
ratio voor een negatief test resultaat van 0,43 (95% BI 0,10-0,78). Bij vrouwen met een
hoog risico voorspelt een diastolische bloeddruk ≥ 75 mmHg gemeten tussen de 13 en
20 weken zwangerschapsduur preëclampsie het beste met een positieve likelihood ratio
2,8 (95% BI 1,8-3,6) en een negatieve likelihood ratio van 0,39 (95% BI 0,18-0,71).
De voorspellende waarde verbetert niet in de subgroep analyses. We concluderen dat de
hoogte van de bloeddruk weliswaar geassocieerd is met het ontstaan van preëclampsie
maar dat bloeddruk als enige test onvoldoende goed voorspelt om bruikbaar te zijn in
de dagelijkse praktijk.
Prospectieve cohort studie
Om te onderzoeken of er verschillen zijn in cardiovasculaire parameters vroeg in
de zwangerschap tussen vrouwen die later een hypertensieve aandoening van de
zwangerschap zullen krijgen en vrouwen met een ongecompliceerde zwangerschap,
hebben we prospectief een cohort vrouwen verzameld bestaand uit gezonde nullipara
vrouwen en gezonde multipara vrouwen met een preëclampsie in de voorgeschiedenis.
Alle vrouwen hadden een normale bloeddruk bij inclusie. Bij deze vrouwen werd vroeg
in de zwangerschap, tussen 8 0/7-11 0/7 weken zwangerschapsduur, de bloeddruk
gemeten met behulp van conventionele sfygmomanometrie (Maxi Stabil 3, Welch Allyn,
Skaneateles Falls, New York, USA), continue registratie van de arteriële drukgolf van de
vinger met de Finometer(Finapres Medical Systems, Amsterdam, Nederland) en met een
ambulante bloeddrukmeter (ABPM) gedurende 48 uur (Spacelab 90207, Redmond, WA,
USA). Ook werd informatie verzameld over leeftijd, etnische origine, roken, medische
voorgeschiedenis, opleiding en lengte en gewicht.
295 Vrouwen konden geïncludeerd worden waarvan 251 nullipara waren en 44 multipara
met een preëclampsie in de voorgeschiedenis. Vijf vrouwen werden geëxcludeerd in
verband met ernstige congenitale afwijkingen van de foetus en van één vrouw konden de
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gegevens over de afloop van de zwangerschap niet worden achterhaald. De gegevens van
289 vrouwen waren beschikbaar voor analyse, 20 (6.9 %) kregen preëclampsie en 16 (5.5
%) zwangerschapshypertensie. 39 vrouwen hadden een incomplete ABPM registratie als
gevolg van technische problemen of omdat zij het apparaat niet konden verdragen. Van
deze vrouwen hadden 28 tenminste 10 metingen in 48 uur. Deze registraties werden wel
gebruikt bij de analyses. De resultaten van al deze metingen zijn beschreven in hoofdstuk
3, 4 en 5.
Met behulp van de 48-uurs registratie met ABPM kan de hyperbare index (HBI) berekend
worden. De HBI geeft aan hoeveel en hoe lang de bloeddruk boven de 90ste percentiel
van de normaalwaarden is geweest per tijdseenheid (mmHg x uur).6 Door één studiegroep
is de HBI gebruikt om in het eerste trimester latere preëclampsie te voorspellen met zeer
goede resultaten; zij vonden een sensitiviteit van 94% en een specificiteit van 100%.10;11
Sinds de publicatie van Hermida en collega’s is de HBI nog door één andere studiegroep
bestudeerd, waarbij de deelnemers allemaal in het ziekenhuis waren opgenomen.
(sensitiviteit 80%, specificiteit 77%).7 We wilden daarom de HBI als voorspellende test
voor preëclampsie onderzoeken in ons eigen cohort. In hoofdstuk 3 beschrijven
we de resultaten van dit onderzoek. We hebben de voorspellende waarde van de HBI
vergeleken met de voorspellende waarde van de gemiddelde bloeddruk over 48 uur
en conventionele sfygmomanometrie. 219 van de 289 vrouwen konden geïncludeerd
worden. De registraties van 28 vrouwen konden niet gebruikt worden in verband met
ontbrekende metingen of technische problemen. De eerste 90 nullipara vrouwen,
met een normale bloeddruk gedurende de hele zwangerschap, zijn gebruikt voor het
berekenen van de normaalwaarden over 24 uur. Bij de resterende 63 nullipara vrouwen
en 38 multipara vrouwen met een eerdere preëclampsie werd de HBI berekend voor de
SBP, DBP en MAP. De HBImax was gelijk aan de hoogste HBI van of SBP of DBP of MAP
voor iedere vrouw. Voor preëclampsie had de HBImax de best voorspellende waarde,
echter het verschil met de gemiddelde bloeddruk gemeten met ABPM of conventionele
sfygmomanometrie was klein. De HBImax had een sensitiviteit van 73 % en een specificiteit
van of 86 % bij een afkapwaarde van 17,6 mmHg x uur. SBP met sfygmomanometrie
had een sensitiviteit van 60 % en een specificiteit van 92 % bij een afkapwaarde van 118
mmHg. De gemiddelde DBP over 24 uur met ABPM had een sensitiviteit van 53 % met
een specificiteit van 95% bij een afkapwaarde van 74 mmHg. De voorspellende waarde
voor zwangerschapshypertensie was slecht met alle meetmethoden (sensitiviteit tussen 54
% en 77 %, specificiteit tussen 41 % and 78 %).
Onze conclusie is dan ook dat conventionele sfygmomanometry, ABPM en de HBI een
vergelijkbare maar beperkte voorspellende waarde hebben in een groep met een laag
en hoog risico. De hoge voorspellende waarde van de HBI zoals eerder beschreven
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konden wij niet reproduceren en deze test kan daarom niet aanbevolen worden als
voorspellende test in de dagelijkse praktijk.
Vrouwen die later in de zwangerschap preëclampsie of zwangerschapshypertensie
kregen, hadden in het eerste trimester een hogere bloeddruk vergeleken met
vrouwen met een onaangedane zwangerschap, gemeten met alle drie de apparaten,
conventionele sfygmomanometrie, continue registratie van de arteriële drukgolf van de
vVinger en ABPM (hoofdstuk 4). De absolute waarden waren verschillend tussen de
apparaten. De puntschatters van de Odds ratio’s voor de associatie met preëclampsie
of gecombineerde zwangerschapsuitkomst (preëclampsie of zwangerschapshypertensie)
voor de verschillende bloeddrukparameters (SBP, DBP of MAP) in het eerste trimester
waren, na correctie voor een eerdere preëclampsie, hoger bij het gebruik van de
automatische bloeddrukmeters vergeleken met conventionele sfygmomanometry. Er was
wel een aanzienlijke overlap van de 95% betrouwbaarheidsintervallen. De oppervlakte
onder de ROCcurven voor conventionele sphygmomanometry met preëclampsie als
uitkomst waren 0.73 (95% BI 0.58-0.83), 0.68 (95% BI 0.53-0.84) en 0.70 (95% BI
0.55-0.85) voor respectievelijk SBP, DBP en MAP. Voor de Finometer was dit 0.82 (95%
BI 0.68-0.95), 0.77 (95% BI 0.63-0.91) en 0.82 (95% BI 0.69-0.96) en voor ABPM
0.78 (95% BI 0.65-0.91), 0.77 (95% BI 0.63-0.90) and 0.78 (95% BI 0.65-0.91) voor
respectievelijk SBP, DBP en MAP. Voor de gecombineerde uitkomst (preëclampsie of
zwangerschapshypertensie) waren de resultaten vergelijkbaar.
Omdat het bij een aanzienlijk deel van de vrouwen niet mogelijk was een volledige
ABPM registratie te verkrijgen en er bij conventionele sfygmomanometrie in de dagelijkse
praktijk een interobserver variatie is, concluderen wij dat bloeddrukmeting met behulp van
de arteriële drukgolf van de vinger de meest belovende automatische bloeddrukmeting is
om nader te bestuderen te worden in een groter cohort.
In hoofdstuk 5 hebben we de metingen van ons cohort gebruikt om de associatie
van arteriële stijfheid vroeg in de zwangerschap en het later krijgen van preëclampsie te
bestuderen. Onze hypothese was dat in combinatie met bloeddruk (MAP) de associatie
hoger zou zijn dan van de enkele parameters.
235 nullipara vrouwen en 42 multipara vrouwen konden geïncludeerd worden met een
respectievelijke incidentie van preëclampsie van 4.3% en 16.6%. De registraties met de
Finometer zijn gebruikt voor de analyses. Van de arteriële drukgolf van de vinger werd de
aortadrukgolf gereconstrueerd en werden de augmentatieindex (AIx) en augmentatiedruk
(AP) berekend. Na correctie voor een eerdere preëclampsie waren de AIx en AP in het
eerste trimester geassocieerd met latere preëclampsie, oppervlakten onder de ROCcurven
van 0.74 (95% BI 0.61-0.87) en 0.77 (95% BI 0.61-0.87). Wanneer de MAP werd
toegevoegd aan het model gaf de combinatie met de AP de grootste oppervlakte onder
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de ROCcurve (0.82 95% BI 0.66-0.97). Vergeleken met MAP in combinatie met eerdere
preëclampsie is dit geen grote verbetering (oppervlakte onder de ROCcurve 0.79 (95%
BI 0.64-0.93)). Onze resultaten pleiten niet voor het toevoegen van de AIx of AP aan
een eventueel predictiemodel. De bloeddruk geeft vergelijkbare resultaten en is veel
makkelijker te meten.
Hypertensieve aandoeningen van de zwangerschap en hart- en vaatziekten delen een
aantal risicofactoren zoals hypertensie, diabetes en obesitas. Factoren die beïnvloedbaar
zijn en hart- en vaatziekten zouden kunnen voorkomen of een (on)gunstige invloed hebben
zouden misschien ook bruikbaar zijn bij de preventie van hypertensieve aandoeningen
van de zwangerschap. Een van deze factoren is psychosociale stress.8;9 Verscheidene
studies laten een verband zien tussen veel psychosociale stress in de zwangerschap en
het ontwikkelen van preëclampsie of zwangerschapshypertensie.15-18 Echter de meeste
van deze studies zijn retrospectief of case-control studies.
In hoofdstuk 6 hebben we de associatie van preëclampsie en zwangerschapshypertensie
met psychosociale stress in de eerste helft van de zwangerschap onderzocht in een
prospectief cohort. Voor dit onderzoek hebben we gebruik gemaakt van de data
verzameld in de ABCD-studie (Amsterdam Born Children and their Development study).
Dit is een prospectief community-based onderzoek dat de relatie tussen verschillende
levensstijlen tijdens de zwangerschap en zwangerschapuitkomsten onderzoekt in een
multiculturele populatie. In het kader van dit onderzoek werden tussen januari 2003
en maart 2004 alle zwangere vrouwen in Amsterdam bij eerste controle verzocht
een vragenlijst in te vullen. Voor dit onderzoek hebben we de gegevens gebruikt van
alle nullipara vrouwen met een eenlingzwangerschap, die de vragenlijst voor de 24e
zwangerschapsweek ingevuld hadden en na 24 weken zwangerschapsduur zijn bevallen.
De vragenlijst die postpartum was ingevuld is gebruikt om informatie te krijgen over
preëclampsie, hypertensie of eiwitverlies in de urine tijdens de zwangerschap. Ook
werden gegevens gebruikt van de Landelijke Verloskundige Registratie (LVR) om
informatie te verkrijgen over de zwangerschapsuitkomst. Van alle vrouwen die aangaven
tijdens de zwangerschap hypertensie of eiwitverlies in de urine te hebben gehad werden
de medische dossiers opgevraagd en bestudeerd. Net als van die vrouwen waarbij in de
de LVR was aangegeven dat de zwangerschap gecompliceerd was door hypertensie. De
diagnose preëclampsie of zwangerschapshypertensie werd gesteld volgens de richtlijnen
van de International Society for the Study of Hypertension in Pregnancy. Van alle vrouwen,
die niet aangegeven hadden hypertensie te hebben gehad, werd van willekeurig 5% de
medische dossiers bestudeerd om er zeker van te zijn dat er geen vrouwen met een
hypertensieve aandoening gemist werden. De studiepopulatie bestond uit 128 vrouwen
met preëclampsie, 161 vrouwen met zwangerschapshypertensie en een controlegroep
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van 3390 vrouwen. Psychosociale stress was gedefinieerd als werk stress (gemeten met
Work Experience and Appreciation Questionnaire van van Velthoven en collega’s,10
gedeeltelijk gebaseerd op the Job Content Instrument of Karasek et al.11), angst ( gemeten
met the State-Trait Anxiety Inventory, STAI12), depressie (Center for Epidemiological
Studies Depression Scale, CES-D13;14) en zwangerschapsgerelateerde angst (PRAQ-R15).
Na correctie voor sociodemografische en medische factoren vonden wij geen associatie
tussen psychosociale stress in de eerste helft van de zwangerschap en het ontwikkelen
van preëclampsie of zwangerschapshypertensie later in de zwangerschap.
Gebruik makend van hetzelfde cohort als in hoofdstuk 6 hebben we de associatie
tussen lichaamsbeweging en hypertensieve aandoeningen in de zwangerschap
onderzocht. Lichaamsbeweging voorkomt hart- en vaatziekten en kan de symptomen
verminderen.16;17 De hypothese was dat vrouwen met meer lichaamsbeweging
minder kans op een hypertensieve aandoening in de zwangerschap zouden hebben.
In hoofdstuk 7 werd deze hypothese onderzocht. In de vragenlijst gebruikt door de
ABCD-studie werden vragen gesteld over lichaamsbeweging in vrije tijd in de week
voor het invullen. Er werden vragen gesteld over wandelen, fietsen, sporten en andere
activiteiten zoals klussen en tuinieren. Ook werd er gevraagd naar het aantal minuten
en de intensiteit van de activiteit. Na correctie voor sociodemografische en medische
factoren werd er geen verband waargenomen tussen de incidentie van preëclampsie of
zwangerschapshypertensie met de duur en de mate van inspanning van lichaamsbeweging
in vrije tijd.
Veel onderzoekers richten zich op het ontwikkelen van een risicoschatting op hypertensieve
aandoeningen in de (vroege) zwangerschap. Maar ook voor de zwangerschap zou een
risicoschatting interessant zijn. Het is bekend dat de ovariële hormonen het cardiovasculaire
en renine-angiotensine-aldosteron systeem beinvloeden.18-20 Echter hoe groot het effect
van de hormonale fluctuaties tijdens de menstruatiecyclus is op de bloeddrukregulatie is
niet duidelijk en de literatuur over dit onderwerp is inconsistent.21-23 Het is dan ook niet
zeker of het noodzakelijk is rekening te houden met de menstruatiecyclus bij het doen
van metingen voor de conceptie. Het doel van de studie beschreven in hoofdstuk
8 was om te bestuderen of hemodynamische parameters en cardiovasculaire controle
anders zijn in de folliculaire fase van de menstruatiecyclus dan in de luteale fase. 39
gezonde vrouwen, die nog nooit zwanger waren geweest, werden geïncludeerd voor
deze studie. Op dag 5-10 en op dag 18-25 van de menstruatiecyclus werden bloeddruk,
hartfrequentie, cardiac output en de totale perifere weerstand gemeten met behulp van
continue registratie van de arteriële drukgolf van de vinger. De baroreflex sensitivity (BRS)
en sympatische activiteit werden bestudeerd met behulp van spectraal analyse en xBRS.
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Er waren geen verschillen in hemodynamische parameters, BRS en sympatische activiteit
tussen de twee fases van de menstruatiecyclus. Hoewel er geen verschil is tussen de eerste
en de tweede helft van de menstruatiecyclus, worden metingen bij voorkeur gedaan in de
eerste helft van de cyclus omdat het dan zeker is dat er geen zwangerschap bestaat. Dit
omdat de invloed van een zeer jonge zwangerschap op de bloeddrukregulatie onbekend
is.
DISCUSSIE
Dit proefschrift rapporteert over hemodynamische parameters vroeg in de zwangerschap
die geassocieerd zijn met het ontwikkelen van preëclampsie of zwangerschapshypertensie
later in de zwangerschap. Deze variabelen zouden gebruikt kunnen worden in een
predictiemodel voor deze aandoeningen.
Een predictiemodel zou van groot nut kunnen zijn bij het ontwikkelen van een preventieve
therapie. Omdat preëclampsie in een ongeselecteerde populatie weinig voorkomt zijn
nu grote cohorten nodig voor onderzoek. Dit onderzoek zou gemakkelijker worden
als vrouwen met een verhoogd risico geselecteerd zouden kunnen worden. Ook zal
preventie waarschijnlijk al vroeg in de zwangerschap moeten starten omdat de oorzaak
voor de ziekte vroeg in de zwangerschap ligt ten tijde van de ontwikkeling van de
placenta.24 Daarom zou een test die vrouwen met een hoog risico kan selecteren al in
het eerste trimester van de zwangerschap bruikbaar moeten zijn. Een tweede mogelijke
toepassing is om op basis van een risicoschatting op hypertensieve complicaties in de
zwangerschap de intensiteit van de prenatale zorg te bepalen. Een voorspellende test
zal een hoge sensitiviteit moeten hebben om het aantal fout negatieven te verkleinen
aangezien preëclampsie ernstige gevolgen voor moeder en kind kan hebben. Omdat
vooral ernstige preëclampsie niet veel voorkomt (0.5%) moet de voorspellende test ook
een hoge specificiteit hebben. Tot nu toe is een dergelijke test niet beschikbaar om te
gebruiken in de algemene populatie zwangere vrouwen.25
Het onderzoek beschreven in deze thesis bevestigt dat al in het eerste trimester de
bloeddruk bij vrouwen, zonder preëxistente hypertensie, die later preëclampsie
of zwangerschapshypertensie krijgen, verhoogd is. Dit verschil in bloeddruk zou
gebruikt kunnen worden bij het voorspellen van hypertensieve aandoeningen van de
zwangerschap (hoofdstuk 3 en 4). De gemiddelde arteriële bloeddruk (MAP) heeft
het meest onderscheidende vermogen volgens onze meta-analyse van de literatuur
(hoofdstuk 2).26 Dit hebben we gedeeltelijk kunnen bevestigen in onze prospectieve
cohortstudie. Ook vonden we een hogere associatie met later preëclampsie van
170
bloeddruk gemeten met een ambulante bloeddrukmeter of met de Finometer dan met
conventionele sfygmomanometrie. Helaas was het aantal vrouwen in ons cohort te
klein om significante verschillen te kunnen vinden. Het dragen van een ambulante
bloeddrukmeter is belastend, in ons onderzoek was het niet mogelijk om bij 18% van de
vrouwen een complete registratie te maken. Met de Finometer kan meer dan alleen de
bloeddruk worden gemeten. Van de arteriële drukgolf van de vinger kan de aortodrukgolf
gereconstrueerd worden en zo kan de compliantie van de vaatwand bestudeerd worden.
Dit kan worden gebruikt om meer kennis over preëclampsie te verkrijgen. Verhoogde
arteriële stijfheid is een onafhankelijke voorspeller van een slechte uitkomst bij mensen
met hart- en vaatziekten.27 Verscheidene studies hebben een verhoogde arteriële stijfheid
aangetoond bij vrouwen met preëclampsie.28-31 Ook in ons cohort hadden vrouwen
in het eerste trimester van de zwangerschap die later preëclampsie kregen een hogere
augmentatieindex en hogere augmentatiedruk (hoofdstuk 5). In tegenstelling tot anderen
vonden wij een vergelijkbare associatie van AIx, AP en MAP. Wij concluderen dan ook dat
het toevoegen van AIx of AP aan MAP in een predictiemodel geen toegevoegde waarde
heeft.32
Verscheidene andere factoren zijn al vroeg in de zwangerschap geassocieerd met
preëclampsie en hun voorspellend vermogen is bestudeerd door anderen. Maternale
factoren zoals body mass index, medische voorgeschiedenis en een eerdere zwangerschap
gecompliceerd met preëclampsie zijn geassocieerd met het krijgen van preëclampsie.33
Wanneer deze factoren gecombineerd worden in een multivariate analyse en een
predictiemodel ontwikkeld is, is het aantal vrouwen, dat preëclampsie zal krijgen, die
met dit model opgespoord worden laag. Met een fout positief percentage van 5% werd
30% van de vrouwen die een preëclampsie zou krijgen en 20% van de vrouwen die
zwangerschapshypertensie zou krijgen opgespoord.34 Andere potentiële voorspellende
factoren zoals een abnormale doorbloeding van de arteria uterina of biochemische
markers zijn ook onderzocht. In een meta-analyse vonden Cnossen en collegae een
sensitiviteit van 43% en een specificiteit van 93% bij dubbelzijdige notches in de arteria
uterina in het tweede trimester van de zwangerschap in een populatie met een laag risico
op preëclampsie.35 De eiwitten die gebruikt worden bij de screening op Down syndroom
zijn niet bruikbaar als voorspellende test.36 De voorspellende waarde van eiwitten
betrokken bij de angiogenese is alleen onderzocht in kleine studies en deze hebben
onvoldoende discriminerend vermogen.37 Het combineren van biochemische markers
met een abnormale doorbloeding van de arteria uterina verbetert het voorspellend
vermogen maar in een populatie met een laag risico op het krijgen van preëclampsie is
de sensitiviteit niet groter dan 60-80%.38
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Met behulp van logistische regressie analyse ontwikkelde Poon en collegae een
predictiemodel voor preëclampsie. Zij combineren de logs van de pulsatility index van de
arteria uterina, gemiddelde bloeddruk, 2 eiwitten gemeten in het serum van de moeder
(PAPP-A en PGF) en maternale karakteristieken.4 De bloeddruk werd gemeten met een
automatische bloeddrukmeter die gebruik maakte van oscillometrie. Met deze variabelen
ontwikkelden zij drie modellen, een voor het krijgen van preëclampsie vóór 34 weken
zwangerschap (vroege preëclampsie), een voor het krijgen van preëclampsie na 34
weken (late preëclampsie) en een voor het ontwikkelen van zwangerschapshypertensie.
Bij een zwangerschapsduur van 110/7-136/7 weken konden zij met deze modellen, bij een
percentage foutpositieven van 5%, 93.1% van de vrouwen met een vroege preëclampsie,
35.7% van de vrouwen met een late preëclampsie en 18.3% van de vrouwen met een
zwangerschapshypertensie detecteren. Dit model lijkt veel belovend. Maar van de 476
vrouwen met een positieve test kregen er 32 dadwerkelijk preëclampsie en 444 niet.
Twee vrouwen met een vroege preëclampsie werden gemist. En van de vrouwen die een
late preëclampsie kregen had maar 35.7% een positieve test.
De auteurs hebben verschillende modellen ontwikkeld voor het voorspellen van vroege
en late preëclampsie met verschillend discriminerend vermogen. Vroege preëclampsie
wordt vaak gecompliceerd door intra-uteriene groeivertraging door een inadequate
placentatie terwijl bij een late preëclampsie er vaak een normale placenta is en een
normaal gegroeid kind. Men denkt dat dit komt omdat een vroege preëclampsie
veroorzaakt wordt door een abnormale reactie van het maternale immuunsysteem op
de ontwikkeling van de placenta en dat een late preëclampsie veroorzaakt wordt door
aanleg van de moeder voor hart- en vaatziekten en metabole stoornissen. 39 Dit kan
verklaren waarom er meerdere predictiemodellen nodig zijn.
Vrouwen met obesitas, hoge bloeddruk, hart- en vaatziekten, diabetes of een eerder
doorgemaakte preëclampsie hebben een verhoogde kans om in de zwangerschap
preëclampsie te krijgen. Seed en collegae vonden een incidentie van 23 % in nullipara
vrouwen met hoge bloeddruk en obesitas. Bij vrouwen met een eerdere preëclampsie en
hoge bloeddruk was de incidentie 30 %.40 Als het voorkomen van preëclampsie in de
toekomst mogelijk is, is het waarschijnlijk goedkoper om deze vrouwen te behandelen
zonder ze eerst te testen. Het zal afhangen van de kwaliteit van het predictiemodel en
de voordelen van een preventieve behandeling of het kosteneffectief is om eerst de kans
te berekenen op het krijgen van preëclampsie of meteen alle vrouwen te behandelen.
De ontwikkeling van predictiemodellen wordt gehinderd door de lage incidentie van
preëclampsie. In een cohort zijn vaak weinig ziektegevallen en veel factoren waar voor
gecorrigeerd moet worden. Dit kan zorgen voor een overschatting van het model.41 Dit
is ook de reden dat wij geen predictiemodel konden ontwikkelen.
172
Alle gepubliceerde modellen moeten worden gevalideerd in een andere populatie dan
waarin ze ontwikkeld zijn. Dit wordt nog eens benadrukt door de resultaten van ons
onderzoek aangezien we de goede voorspellende waarde van de HBI of de AIx niet
konden reproduceren. 32;42;43 Ook al kan dit verklaard worden door kleine verschillen
tussen de populaties en zwangerschapsduur. Dit maakt deze parameters ongeschikt om
de kans op preëclampsie in de algemene populatie te voorspellen.
IMPLICATIES VOOR TOEKOMSTIG ONDERZOEK
1. Ontwikkeling van predictiemodellenHet voorspellen van de kans op preëclampsie vroeg in de zwangerschap is belangrijk
om preventie van de ziekte mogelijk te maken. Preventie zal vroeg in de zwangerschap
moeten starten omdat de oorzaak van de ziekte zeer waarschijnlijk gevonden kan
worden ten tijde van de ontwikkeling van de placenta. Het is noodzakelijk om grote
studies te doen waarin de voorspellende waarde van de combinatie van maternale
karakteristieken met de gemiddelde bloeddruk in het eerste trimester en andere
parameters geëvalueerd worden. De eerste selectie zal gemaakt moeten worden
op basis van medische en obstetrische voorgeschiedenis. Vrouwen met preëxistente
hypertensie, nierziekten, diabetes of een preëclampsie vóór 34 weken zwangerschap in
de anamnese hebben een verhoogde kans op het krijgen van preëclampsie. Het is de
vraag of er voor deze vrouwen een predictiemodel ontwikkeld moet worden. Omdat
2/3 van alle ziektegevallen optreden bij vrouwen die hun eerste kind verwachten
zal verder onderzoek zich moeten richten op deze groep. Zeer waarschijnlijk zijn er
verschillende predictiemodellen nodig voor vroege en aterme preëclampsie.
2. Het gebruik van automatische bloeddrukmeters bij het voorspellen van hypertensieve aandoeningen van de zwangerschap
Conventionele sfygmomanometrie wordt gebruikt om de diagnose preëclampsie
te stellen omdat met deze methode het meeste onderzoek is gedaan naar de
gevolgen van preëclampsie en antihypertensieve therapie. Meerdere automatische
bloeddrukmeters zijn gevalideerd voor het gebruik in de zwangerschap en meten zeer
nauwkeurig de bloeddruk. Ook kunnen er vaak andere parameters met betrekking
tot het cardiovasculaire systeem gemeten worden. Deze parameters zouden bruikbaar
kunnen zijn bij het voorspellen van het optreden van preëclampsie en eventuele
complicaties. Gebaseerd op de resultaten van ons onderzoek adviseren wij de
Chapter 9
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Nederlandse sam
envatting, conclusies en aanbevelingen
bloeddruk te meten met behulp van de arteriële drukgolf van de vinger in toekomstig
onderzoek.
3. Prospectieve verzameling van klinische gegevens en biologisch materiaal van zwangere vrouwen
Het prospectief verzamelen en opslaan van klinische gegevens en biologisch
materiaal van zwangere vrouwen is van essentieel belang voor het ontwikkelen
van predictiemodellen. Zoals blijkt uit de resultaten van ons onderzoek en dat van
anderen, is bloeddruk alleen niet voldoende om het voorkomen van preëclampsie te
voorspellen in de dagelijkse praktijk.26;44 Een bruikbaar model zal zeer waarschijnlijk
bestaan uit een combinatie van maternale karakteristieken, bloeddruk en biomarkers.
Op dit moment worden grote cohorten vrouwen bestudeerd en de eerste resultaten
gepubliceerd. De Scope studie is hier een voorbeeld van. Binnen deze studie wordt
biologisch materiaal afkomstig van vrouwen uit Nieuw Zeeland, Australië, het
Verenigd koninkrijk en de Verenigde Staten van Amerika verzameld.45;46 In Nederland
zijn gynaecologen en verloskundigen verenigd binnen onderzoeksconsortia en zijn er
dus goede mogelijkheden voor het verzamelen van een gelijksoortig cohort binnen
bijvoorbeeld het Parelsnoerinitiatief (www.parelsnoer.org). Zo kan de ontwikkeling en
validatie van een predictiemodel gestimuleerd worden.
174
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Appendices
Authors’ affiliationsBibliography
Appendices
181
Authors’ affiliations
AUTHORS’AFFILIATIONS
K. Boer Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
G.J. Bonsel Department of Social Medicine, Academic Medical Center, Amsterdam
J.S. Cnossen Department of General Practice, Academic Medical Center, Amsterdam
A.Franx Department of Obstetrics and Gynecology, St Elisabeth Hospital, Tilburg
J. Gisolf Department of Physiology, Academic Medical Center, Amsterdam
I. Guelen BMYE, Amsterdam
J. Hashimoto Department of Blood Pressure Research, Tohoku University, Japan
K.S. Khan Department of Obstetrics and Gynaecology, Birmingham Womens Hospital, Birmingham, United Kingdom
L. van Leijden Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
B.W.J. Mol Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
G.A. van Montfrans Department of Internal Medicine, Academic Medical Center, Amsterdam
J.A.M. van der Post Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
S. Rang Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
G. ter Riet Department of General Practice, Academic Medical Center, Amsterdam
L.Seesing Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
N. de Vrieze Department of General Practice, Academic Medical Center, Amsterdam
T.G.M. Vrijkotte Department of Social Medicine, Academic Medical Center, Amsterdam
M.F. van der Wal Municipal Health Services, GGD Amsterdam, Amsterdam
B.E. Westerhof BMEYE, Amsterdam and Laboratory for Clinical Cardiovascular Physiology, AMC Centre for Heart Failure Research, Amsterdam
H. Wolf Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam
Appendices
183
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ambulatory blood pressure monitoring in hypertensive disorders of pregnancy Journal of
Hypertension. 2010;28(5): 1111-3
Vollebregt KC, Gisolf J, Guelen I, Boer K, van Montfrans G, Wolf H. Limited
accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry
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Hypertension. 2010;28(1):127-34
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Vollebregt K, Ince C.The NO donor SIN-1 improves intestinal-arterial P(CO(2)) gap
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2007;51(6):693-700.
Vollebregt KC, Seesing L, Rang S, Boer K, Wolf H. Sensitivity of spontaneous baroreflex
control of the heart and hemodynamic parameters are not influenced by the menstrual
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Vollebregt KC, Boer K, Mathura KR, de Graaff JC, Ubbink DT, Ince C.Impaired
vascular function in women with pre-eclampsia observed with orthogonal polarisation
spectral imaging. BJOG. 2001;108(11):1148-53
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Dankwoord
Appendices
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Dankw
oord
DANKWOORD
Mijn proefschrift is af! Wetenschappelijk onderzoek doe je niet alleen. Dat is maar goed
ook. Als ik het even niet meer zag zitten was er altijd wel iemand die mij, door zijn of
haar enthousiasme, weer kon motiveren om door te gaan. Ik wil dan ook iedereen, met
wie ik de afgelopen jaren heb samengewerkt, heel hartelijk bedanken en een aantal in
het bijzonder.
Als eerste wil ik alle vrouwen bedanken die belangeloos hebben meegewerkt aan de
verschillende projecten. Zonder de informatie over hun zwangerschappen en bloeddruk
had dit proefschrift niet tot stand kunnen komen.
Mijn promotor Prof. Dr. J.A.M. van der Post.
Beste Joris, je hebt altijd een grote betrokkenheid getoond voor mij en mijn onderzoek.
Ook al zat je agenda helemaal vol, altijd was er nog een klein gaatje te vinden dat
vervolgens goed benut werd. Dank daarvoor. Ik ging altijd met nieuwe inspiratie naar
buiten, hopelijk is alles nu rond.
Mijn co-promotoren Dr. H. Wolf en Dr. K. Boer.
Beste Hans, altijd stond jij voor mij klaar en was er tijd voor een discussie. Het maakte
niet uit waar en wanneer; in het trappenhuis bij H3, tussen klinische bezigheden door,
zondagavond laat of per mail vanuit de Syrische woestijn. Het zou mij niets verbazen
als jij bijna net zo veel tijd als ik hebt besteed aan de manuscripten. Mede dankzij jouw
tomeloze inzet ligt dit proefschrift hier, dankjewel.
Beste Kees, eigenlijk is alles bij jou begonnen. Ik heb jou leren kennen tijdens mijn
wetenschappelijke stage onder supervisie van Prof. Dr. Çan Ince. Via dat onderzoek
ben ik in het project gerold dat is uitgemond in dit proefschrift. Al die jaren was het fijn
samenwerken. Ik vind het dan ook erg bijzonder dat je mijn voorkant gemaakt hebt,
dankjewel hiervoor. En hoe komt het toch dat ondanks de vele keren lezen van een
manuscript en de spellingcontrole jij er altijd weer een spelfout uit haalde?
De leden van de commissie: Prof. dr. E.T. van Bavel, Dr. J.M. Karemaker, Prof. dr. B.W.J.
Mol, Prof. dr. B.J.M. Mulder, Dr. M.E.A. Spaanderman en Prof. dr. E.A.P. Steegers wil ik
bedanken voor het beoordelen van mijn proefschrift.
De medeauteurs van alle manuscripten:
188
Beste Jeltsje Cnossen, Gerben ter Riet en Ben Willem Mol, het was fijn en erg leerzaam
om met jullie te werken.
Beste Gert van Montfrans, Ilja Guelen en Janneke Gisolf, jullie waren net zo enthousiast
als ik om de methode van de hyperbare index te ontcijferen en te reproduceren. Het was
eigenlijk te mooi om waar te zijn. Dat onze resultaten minder goed waren was dan ook
geen verassing. Het was erg leuk om met jullie te werken.
Beste Berend Westerhof en Junichiro Hashimoto, jullie kwamen met het idee van de
augmentatieindex en toevallig had ik de data liggen. Het is een leuk project geworden.
Beste Gouke Bonsel, Marcel van der Wal en Tanja Vrijkotte van de ABCD studiegroep,
jullie hebben een zeer waardevolle database met informatie over Amsterdamse zwangeren
en hun kinderen. Dank dat ik daar gebruik van heb kunnen maken.
Beste Saskia Rang, ik kan mij helemaal vinden in één van jouw stellingen: “Een golf is
eindeloos te analyseren”.
De studenten die bij mij hun wetenschappelijk stage hebben gedaan, Lobke, Eva, Kim,
Lize, Nicole, Maud, Eva, Larissa en Lara. In het kader van jullie wetenschappelijke stage
hebben jullie allemaal een steentje bijgedragen aan mijn onderzoek. Hopelijk hebben
jullie net zo veel geleerd van mij als ik van jullie. En bedenk met chocoladekoekjes wordt
SPSS een stuk makkelijker.
Alle medewerkers van de afdeling Verloskunde en Gynaecologie van het AMC, ik voel
mij thuis in het AMC en heb de afgelopen jaren enorm veel geleerd. Dank aan alle
stafleden en arts-assistenten voor de leuke opleidingstijd en aan alle verloskundigen,
echoscopisten, verpleegkundigen, doktersassistenten en secretaresses voor de prettige
samenwerking en niet te vergeten de gezelligheid. Ina Vink, fijn dat jij er was om, als
ik niet beschikbaar was, al die telefoontjes te beantwoorden. Peter Goossens, je hebt
meerdere malen mijn computer met kostbare data succesvol gereanimeerd en bent
daarom een van mijn helden. Debbie Bax, dank voor je hulp de laatste maanden.
Alle medewerkers van de afdeling Verloskunde en Gynaecologie van het Flevoziekenhuis.
Toen ik mijn verpleeghulpstage op jullie afdeling deed had ik nooit gedacht nog eens
terug te komen als AIOS. Ik heb dan ook veel zin in het laatste jaar van mijn opleiding.
Appendices
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Dankw
oord
Mijn paranimfen.
Lieve Mariëlle, toen ik hoorde dat jij als verpleegkundige mij kwam helpen had ik eerst zo
mijn twijfels. Je had geen ervaring met wetenschappelijk onderzoek en had niet veel met
diverse computerprogramma’s gewerkt. Maar voordat ik het wist had jij orde gebracht
in mijn chaos, kon je metingen verrichten en analyseren en had je de opleiding tot
researchnurse gedaan. Daarom vind ik dat jij bij mijn promotie moet zijn, dankjewel dat
jij mijn paranimf wil zijn.
Lieve Marjolein, samen in een hok zonder ramen dat schept een band. En die band is
er ook in de kliniek en daarbuiten. Inmiddels ben ik bezig met het laatste deel van mijn
opleiding in het Flevoziekenhuis en ben jij weer terug in het AMC voor een fellowship.
Ik ben benieuwd hoe ons verdere leven eruit gaat zien, zowel professioneel als privé.
Hopelijk zullen er nog vele etentjes met of zonder partners en kinderen volgen (Janneke
kookt wel erg lekker). Ik heb er wel langer over gedaan dan jij, maar nu ook ik het afsluit
hoor jij erbij.
Alle collega onderzoekers en dat zijn er in de loop van de jaren heel wat geworden;
Anna, Arianne, Bas, Christianne, Elisabeth, Emily, Emmy, Esther, Etelka, Evelien,
Femke,Floortje, Inge, Jan Willem, Jolande, Katrien, Laura, Liesbeth van Leeuwen,
Liesbeth Visser, Madelon, Margreet, Marscha, Menke, Moniek, Pieternel, Saskia, Stef,
Wessel, Wouter Hehenkamp en Wouter Wegdam. Als parttime onderzoeker was ik niet
overal bij maar dank voor jullie steun en gezelligheid.
In het bijzonder wil ik my roomies noemen, eerst Marjolein en daarna Jiska. En vervolgens
als oudgediende tussen de jonkies; Noortje, Lobke, Marleen en Marjet. Regelmatig
moesten wij onszelf dwingen om terug te draaien naar de beeldschermen en door te
werken in plaats van thee te leuten. Hopelijk worden jullie boekjes minstens zo mooi.
Lieve vriendinnen en dan vooral Anoek, Ilja, Ilse, Karen, Roos en Sandra. Wat is het fijn
om mensen om je heen te hebben die je al heel lang kent en waarbij weinig woorden
genoeg kunnen zijn. Of bij wie je juist heel je hart kan uitstorten. Hopelijk is er nu meer
tijd voor avondjes Eijlders of gewoon een middag op de bank.
Lieve familie de Boer-Bruch, dank voor jullie steun en interesse in mijn werk.
Lieve Ada en Jan, in bijna alles wat wij kinderen wilden hebben jullie ons gesteund en
volgens mij komt daar het doorzettingsvermogen van ons alle vier vandaan. Het is fijn
om te weten dat jullie er altijd voor ons zullen zijn.
190
Lieve Bram, Eva en Marit. Onze familie wordt steeds groter en gezelliger, eerst met jullie
partners Jennifer, Maurits en Pim en nu ook met Kyran en Jurre erbij. Fijn dat jullie altijd
naar mijn verhalen wilden luisteren.
Special thanks to Jennifer for correcting my English grammar.
Lieve D, de afgelopen jaren heb je niet alleen achter mij gestaan maar ook naast mij. Je
moest eens weten hoe belangrijk dat is geweest, ik hou van jou!
Lieve Meinske en Stella, ieder mensenkind is weer een wonder, jullie zijn mijn
wereldwonderen.
Appendices
191
Curriculum
Vitae
CURRICULUM VITAE
Karlijn Vollebregt werd op 22 april 1976 als oudste van vier kinderen geboren in Bussum
en groeide op in Weesp. Nadat zij in 1994 haar VWO diploma behaalde op het Goois
Lyceum in Bussum werd zij uitgeloot voor de studie Geneeskunde. Zij ging Geneeskunde
studeren aan de Universiteit Gent in Gent (België). Na behalen van het eerste jaar
werd zij in 1995 ingeloot en ging zij terug naar Nederland om Geneeskunde te gaan
studeren aan de Universiteit van Amsterdam. Op aanraden van haar moeder deed zij
haar verpleeghulpstage op de afdeling verloskunde van het Flevoziekenhuis te Almere en
werd zij enthousiast voor het vak. In het kader van haar wetenschappelijke stage tijdens
haar studie deed zij onderzoek onder leiding van Professor Ç. Ince bij de experimentele
anaesthesiologie. Daar ontmoette zij Kees Boer en werd de basis gelegd voor haar verder
onderzoek binnen de verloskunde. In 2002 ging zij, na haar afstuderen, werken als
ANIOS gynaecologie in het Academisch Medisch Centrum. Vanaf januari 2004 heeft zij
haar klinisch werk gecombineerd met het wetenschappelijk onderzoek wat zou uitgroeien
tot dit proefschrift. In januari 2006 startte zij met haar opleiding tot gynaecoloog in
het Flevoziekenhuis (opleider dr. G. Kleiverda) en een jaar later keerde zij terug naar
het AMC (opleider prof. dr. M.J. Heineman). Sinds juli 2010 is zij weer terug in het
Flevoziekenhuis voor het laatste deel van haar opleiding.
Karlijn woont samen met Derk Jan de Boer, zij hebben twee dochters; Meinske en Stella.