Heart Rate Characteristics and Neurodevelopmental

Outcome in Very Low Birth Weight Infants

By

Kevin C. Addison

A Thesis Submitted to the Graduate Faculty of WAKE FOREST UNIVERSITY

GRADUATE SCHOOL OF ARTS AND SCIENCES

In Partial Fulfillment of the Requirements for the Degree of MASTER OF

SCIENCE

in the Clinical Epidemiology and Health Sciences Research Program

December 2009

Winston-Salem, North Carolina

Approved by:

T. Michael O’Shea, M.D.,M.P.H., Advisor ______________________________

Examining Committee:

Craig Hamilton, M.S., Ph.D., Chair ___________________________________

J. Randall Moorman, M.D. __________________________________________

Edward Ip, Ph.D. ________________________________________________

ii

ACKNOWLEDGEMENTS

I would like to thank the following people for their help and support with this

project. Mike O’Shea has been my mentor and advisor since I came to Wake

Forest University. He has helped guide me in decisions that range far beyond

the world of academics. His feedback has been invaluable in every phase of this

project.

I would also like to thank Pam Griffin, Doug Lake, and Randall Moorman

who assisted in editing the manuscript in preparation for publication. Their

research provides the foundation from which this project was created. I would

like to extend my appreciation to Drs. Randall Moorman, Craig Hamilton, and to

Eddie Ip for taking the time from their busy schedules to serve on my thesis

committee.

Finally I would like to thank Dr. Michelle Naughton for her support and

encouragement as program director.

iii

TABLE OF CONTENTS

LIST OF ILLUSTRATIONS v

LIST OF ABBREVIATIONS vi

ABSTRACT vii

CHAPTER 1: BACKGROUND

Introduction 1

Heart Rate Variability, Sepsis, and SIRS 3

1st Study Synopsis 4

2nd Study Synopsis 7

3rd Study Synopsis 10

4th Study Synopsis 12

5th Study Synopsis 14

Synthesis of Previous Studies 16

Specific Aims of the Thesis Project 21

Chapter 1 References 22

CHAPTER 2: HEART RATE CHARACTERISTICS AND

NEURODEVELOPMENTAL OUTCOME IN VERY LOW BIRTH WEIGHT

INFANTS (Published in the Journal of Perinatology, November 2009) 26

Abstract 27

Introduction 29

Methods 30

Results 36

iv

Discussion 42

Chapter 2 References 47

CHAPTER 3: DISCUSSION

Project Summary 52

Limitations 53

Research Implications 54

Future Directions 56

Chapter 3 References 58

CURRICULUM VITAE 59

v

LIST OF ILLUSTRATIONS

CHAPTER 1:

FIGURES

Figure 1: Box Plot of cHRC Scores Comparing Survivors to Non-Survivors 11

CHAPTER 2:

TABLES

Table 1: Characteristics and Outcomes of Study Infants 37

Table 2: Characteristics of VLBW Infants with and without Impairment 40

Table 3: Multivariate Analysis Results 41

FIGURES

Figure 1: The Rates of Each Outcome by cHRC Quartile 38

vi

LIST OF ABBREVIATIONS

VLBW – very low birth weight

cHRC – cumulative heart rate characteristics index

CP – cerebral palsy

HRC – heart rate characteristics

BSID-II - Bayley Scales of Infant Development-Second Edition

MDI – Mental Developmental Index

PDI – Psychomotor Developmental Index

NDI – neurodevelopmental impairment

IVH – intraventricular hemorrhage

vii

ABSTRACT

Sepsis in very low birth weight (VLBW) infants has been associated with an

increased risk of adverse developmental outcome. We have identified abnormal

heart rate characteristics (HRCs) that are predictive of impending sepsis, and we

have developed a summary measure of an infant’s HRCs during the neonatal

hospitalization that we refer to as the cumulative HRC score (cHRC). In this

study we tested the hypothesis that increasing cHRC is associated with an

increasing risk of adverse neurodevelopmental outcome in VLBW infants.

Data were collected on 65 VLBW infants whose HRCs were monitored while in

the neonatal intensive care unit and who were examined at 12-18 months

adjusted age. Using a standard neurological exam and the Bayley Scale of Infant

Development-II, we identified cerebral palsy (CP) and delays in early cognitive

function and psychomotor development.

Increasing cHRC score was associated with an increased risk of CP [odds

ratio: 2.6, (1.42, 5.1)] and delayed early cognitive development [odds ratio: 2.3

(1.3; 4.3)]. These associations remain statistically significant when adjusted for

major cranial ultrasound abnormality. In conclusion, the cHRC score is

associated with an increased risk of adverse neurodevelopmental outcome

among VLBW infants.

1

CHAPTER 1: BACKGROUND

Introduction

Sepsis is a broad term used to indicate a systemic infection; it is a frequent

complication in the Neonatal Intensive Care Unit (NICU). The risk for sepsis in

neonates is inversely related to the birth weight and gestational age. Those at

the highest risk for sepsis are very low birth weight (VLBW) infants (1). These

infants are born with birth weights equal to or less than 1500 grams. Late onset

sepsis is defined as sepsis occurring after 3 days of age. Stoll et al studied the

incidence of late onset sepsis in a cohort of VLBW infants cared for by the

NICHD Neonatal Research Network (2). There was a 2.5 fold risk in mortality

and >30% increase in hospital stay in those infants with culture proven sepsis. In

the cohort studied, 21% of all infants had a positive blood culture. Lower

gestational age was highly correlated with an increased risk for sepsis since 46%

of the infants born at less than 25 weeks gestation were diagnosed with at least

one episode of culture proven sepsis. Over 60% of the VLBW infants in the

study were suspected of sepsis, yet only one out of every three of the blood

cultures sent grew bacteria.

Frequently infants with clinical signs of sepsis have a negative blood culture;

this condition is referred to as the systemic inflammatory response syndrome

(SIRS). SIRS indicates an abnormal inflammatory response in organs remote

from the initial insult. The etiologies for SIRS can be varied and include sepsis,

necrotizing enterocolitis, and massive trauma. Since the initial insult that

2

activates the inflammatory cascade in SIRS is not always infection, a positive

culture is not necessary for the diagnosis (3).

In a study of extremely low birth weight infants (i.e., birthweight less than

1000 grams), 65% of surviving infants were diagnosed with sepsis: 40% with

culture positive sepsis and 25% with culture negative clinical sepsis. Infants who

had one or more episodes of infection during their hospitalization had a 50%

higher risk of neurodevelopmental impairment (NDI) at an 18 to 22 month follow-

up visit. This increased risk for developmental impairment was found for both the

culture positive and the culture negative sepsis groups (4).

Wheater and Rennie observed a 4 fold risk for cerebral palsy in infants

diagnosed with sepsis (5). This increased risk might be due to increased levels

of pro-inflammatory cytokines in the blood and brain. Animal studies have shown

that systemic administration of proinflammatory cytokines can produce brain

lesions similar to those seen in human infants with cerebral palsy (6). Thus,

epidemiologic evidence relating SIRS to white matter damage, cerebral palsy

and developmental delay is consistent with experiments in animal. (7)

White matter damage (WMD) is thought to be the brain structural

abnormality to which cerebral palsy can be attributed. Severe WMD seen on a

cranial ultrasound is called cystic periventricular leukomalacia (cPVL). Neonates

with cPVL are 20 times more likely to develop cerebral palsy (8). WMD has been

associated with antenatal infections such as chorioamnionitis and the fetal

inflammatory response syndrome (9,10). Cerebral palsy in preterm infants is

3

thought to result from brain ischemia, elevated cytokine levels seen with

inflammation, or a combination of both these factors (7).

Heart Rate Variability, Sepsis, and SIRS

Detecting sepsis and SIRS early in the disease process might lead to

prevention of the many adverse consequences of neonatal infection. Fetal

distress and neonatal illness are often marked by altered heart rate patterns. In

1959, Burnard noted that infants with respiratory distress would develop a fixed

heart rate at the height of the illness and that an early sign of improvement would

be an increase in heart rate lability (12). Rudolph et al confirmed these results in

premature infants with respiratory distress syndrome. The heart rate was a fixed

rate for a greater proportion of time in the infants who died compared to the

infants who survived (13). Physicians at the University of Virginia, in conjunction

with WFU, have developed a computer algorithm that identifies abnormal heart

rate patterns. These patterns have then been identified in infants with sepsis. A

synopsis of the research published to date is presented below.

4

Study 1: Griffin MP. Moorman JR. Toward the early diagnosis of neonatal

sepsis and sepsis-like illness using novel heart rate analysis. Pediatrics.

2001;107:97-104

Sepsis is a large contributor to neonatal mortality and early detection

remains difficult for the clinician. In this first study of heart rate characteristics

(HRC) it was hypothesized that early stages of sepsis could be detected by

evaluating and quantifying abnormal heart rate patterns seen prior to clinical

deterioration. As shown by both Burnard and by Rudoph, infants who are ill have

a less variable heart rate and an increased number of transient decelerations.

These abnormal HR patterns seen on the electrocardiogram can be quantified by

measuring the distances between each of the QRS complexes. This distance is

called the R-R interval. When arranged into frequency histograms these R-R

intervals will form an approximately normal distribution in healthy infants. For

infants who are ill or in distress the R-R interval frequency histogram forms a

broader and more asymmetric distribution. The abnormal patterns of reduced

variability and transient decelerations can be detected by increased asymmetry

of the frequency histogram. Therefore the HRC measures examined in this first

study were the statistical moments of these R-R interval distributions. The first

statistical moment is the mean, the second moment is the standard deviation,

and the third moment is the skewness. The frequency histogram distribution

becomes asymmetric and develops a positive skew as a greater number of R-R

intervals lengthen, such as with multiple decelerations. The median and the

5

percentiles of the RR interval distributions were also calculated for this study.

The above heart rate characteristics were calculated using 4096 beat records of

R-R intervals. Each record was normalized using the mean and standard

deviation so there could be direct comparisons between different records. Heart

rate characteristics were calculated for each 4096 beat record and were then

summarized into 6-hour epochs as median values for each patient.

An abrupt clinical deterioration for which the physician obtained a blood

culture and gave antibiotics was used as the outcome measure. HRC data was

analyzed for 5 days before the event and 3 days after. Those infants requiring

these interventions were then divided into infants with positive blood cultures and

infants with negative blood cultures. A third group was also studied to use as a

control group. This group did not have a clinical deterioration and therefore did

not require any intervention during the study period. The event time was

assigned randomly for this group. There were a total of 89 patients in this initial

study. There were 46 episodes of culture positive sepsis in 40 patients and 27

episodes of culture negative sepsis like illness in 23 patients. The control group

consisted of 29 control periods analyzed in 26 patients.

The infants in the culture positive sepsis group and the infants in the culture

negative sepsis like illness group were found to have abnormal heart rate

patterns for up to 24 hours prior to an abrupt clinical deterioration when

compared to the control group. The abnormalities detected were reduced beat-

to-beat variability and transient decelerations. Comparing the means of the

frequency histograms of the R-R intervals showed no statistical differences

6

between the groups. The standard deviation was smaller in those tracings with a

reduced variability, however when transient decelerations were present, the

decelerations would raise the standard deviation back up to normal levels. The

most important statistical differences between the frequency histograms of the

groups were seen in the skewness and in the percentiles. Infants with increased

numbers of transient decelerations had a more asymmetric distribution detected

by a more positive skewness. The 50th percentile values were also significantly

different and found to be more negative in the two groups with the abrupt clinical

deterioration. Statistical differences were seen between the control group and

the groups with abrupt clinical changes but there were no statistical differences

between the group with a positive blood culture and the group with a negative

blood culture.

The level of illness for each infant was measured by the Score for Neonatal

Acute Physiology (SNAP) and the Neonatal Therapeutic Intervention Scoring

System (NTISS) for every 24 hour epoch. Like the heart rate characteristics,

both clinical scores were significantly higher prior to an abrupt clinical

deterioration in the sepsis and the sepsis like illness groups compared to the

controls. There were no significant differences in clinical scores between the

group with positive blood cultures and the group with sepsis-like illness and

negative blood cultures.

7

Study 2: Griffin MP. O’Shea TM. Bissonette EA. Harrell FE. et al. Abnormal

heart rate characteristics preceding neonatal sepsis and sepsis-like illness.

Pediatr Res. 2003;53(6):920-926

To further analyze the alterations in heart rate variability in the setting of

sepsis and sepsis-like illness the objective of this next study was to develop a

computer algorithm which used the heart rate characteristic parameters to

calculate a single score called the Heart Rate Characteristic (HRC) index. This

HRC index could then be used to help identify infants in the early stages of

sepsis. The statistical model was initially developed at the University of Virginia

(UVA) and was then validated at Wake Forest University (WFU). A total of 633

patients were evaluated, 316 infants at UVA and 317 patients at the WFU Baptist

Medical Center Neonatal Intensive Care Unit. UVA admits inborn infants as well

as outside transfers, while the WFU NICU is a referral only center. The patient

population seen at WFU therefore tends to have a higher proportion of more

critically ill infants. Both units had similar frequencies of sepsis and sepsis like

illnesses of 30%.

The study compares two statistical models. Both models used logistic

regression to calculate the odds of developing sepsis or sepsis-like illness within

the next 24 hours. The first statistical model is called the static model. This

model uses the demographics of birth weight, gestational age, and days of

postnatal age as the independent variables. The second statistical model is

called the dynamic model. In this model the independent variables are the HRC

8

parameters. As in the previous study these parameters were calculated from the

distribution of the frequency histograms of the R-R intervals. However, the

parameters calculated for this study are different. The three parameters used for

this study are the standard deviation, the sample asymmetry, and the sample

entropy.

The standard deviation was used as an HRC parameter in the previous

study but the sample asymmetry and the sample entropy are new. These two

parameters replace skewness because they are more flexible measures of

asymmetry. The sample asymmetry is calculated by splitting the R-R interval

distribution in half at the median. Thus the R-R intervals that are less than the

median represent heart rate accelerations and the R-R intervals that are greater

than the median represent heart rate decelerations. The mean squared

differences from the median for each half of the distribution are calculated and

labeled R1 for the accelerations and R2 for the decelerations. The sample

asymmetry is defined as the ratio of decelerations over accelerations: R2/R1. An

abnormal sample with many decelerations would therefore have a large sample

asymmetry (16). The third parameter is the sample entropy. For a fixed

variance, the highest entropy is found in a normal distribution. Distributions that

are asymmetric will therefore have lower sample entropy value. This measure is

based on a combination of the heart rate regularity and periodic heart rate

decelerations seen in critically ill infants. The infant in distress will have more

frequent and more severe periodic heart rate decelerations in the setting of

reduced baseline variability. The sample entropy measures both the frequency

9

of these periodic decelerations as well as the heart rate regularity seen in

between these episodes (17,18).

The HRC index is calculated by including these three HRC parameters into

a logistic regression equation as the independent variables. As in the previous

study each parameter is calculated using a 4096-beat record. The outcome

variable for both the static model and the dynamic model is the probability of

developing sepsis or SIRS within the next 24 hours. The result of the static

model is called the demographic index; the result of the dynamic model is called

the HRC index.

Several baseline differences were seen between the neonatal population

seen at WFU and the neonatal population seen at UVA. The patients at WFU

had a higher median HRC index, reduced SD and decreased sample entropy.

This implies there is a higher risk for sepsis and sepsis like illness at WFU. This

is not surprising since WFU is a referral only NICU and has a higher proportion of

critically ill infants. Despite these differences both the static and the dynamic

models were found to be significant predictors for sepsis and sepsis-like illness at

UVA and at WFU. When the two models were combined the HRC index

remained a significant predictor of sepsis or sepsis-like illness, confirming that

the statistical model developed at UVA was applicable to other centers despite

significant differences in baseline severity of illness.

10

Study 3: Griffin MP. O’Shea TM. Bissonette EA. Harrel FE. et al. Abnormal

heart rate characteristics are associated with neonatal mortality. Pediatr Res.

2004; 55(5):782-788

The objective of this study was to evaluate if there was any association

between an abnormal HRC index and an increased risk for death within the next

seven days. A cumulative HRC score (cHRC ) was devised to serve as a

measure of the total burden of illness for the entire hospital stay. This new

measure was also evaluated for any association with an increased risk for in-

hospital mortality. A total of 685 infants were enrolled in the study, 341 at UVA

and 344 at WFU.

The HRC index and the demographic index were calculated as per the

previous study. Subtracting the demographic index from the HRC index for each

6-hour epoch and then summing the results over the entire hospital stay gives

the cHRC score.

cHRC = ∑[(HRC index) – (Demographic index)]

The demographic index represents the expected clinical course based on birth

weight, gestational age, and days of postnatal age. The HRC index represents

the actual clinical course as evaluated by the HRC parameters. An infant whose

actual hospital course followed the expected hospital course would therefore

have a cHRC equal to zero. If the actual clinical course was better than the

11

expected clinical course then the cHRC would be less than zero. The cHRC

would be greater than zero if the clinical course was worse than the expected

course. Therefore those infants with the most difficult clinical courses will have

higher cHRC scores. The higher the burden of illness, the higher the cHRC is

expected to be.

Using multivariable regression analysis it was shown that both the HRC

index and the cHRC score are associated with an increased risk for death within

7 days. Multivariable analysis showed that the HRC index adds independent

information to both low birth weight and to low GA in predicting mortality. The

cHRC scores of those infants who died in-hospital were significantly higher than

the cHRC score in the surviving infants. A box plot of these results is shown in

figure 1.

Fig 1: Box plots of cHRC for survivors and non-survivors. 50% of the data points are within the

box and 80% are within the hatches. The horizontal line marks the median values; 0.05 for the

survivors and 4.68 for the non-survivors. *p < 0.001

The surviving patients enrolled at the WFU site in this study serve as the

population from which this thesis project derives its patients.

12

Study 4: Griffin MP. Lake DE. Moorman JR. Heart Rate Characterisitics and

Laboratory Tests in Neonatal Sepsis. Pediatrics. 2005;115:937-941

The previous studies have demonstrated that identification of infants at

increased risk for sepsis or sepsis like illness is possible by evaluating heart rate

characteristics. This next study compared the HRC index to more conventional

tests for sepsis and uses multivariable logistic regression to determine if the HRC

index adds information above and beyond these conventional indicators. For this

paper the definition for sepsis was the far more stringent criteria of “proven

sepsis.” Not only did the infant have to have an abrupt clinical change initiating a

blood culture and at least 5 days of antibiotics, but the blood culture must also

have been positive.

The HRC index was calculated in a similar manner as in the previous two

studies. For this paper the HRC index, which is a continuous measure, was

divided into three risk levels. The lowest 70% of the HRC measurements during

the study were less than or equal to the mean of all the HRC index values.

These were categorized as low risk. 90% of the HRC index values are less than

or equal to twice the mean of the HRC index values. Therefore the values

between the 70th and 90th percentiles were categorized as intermediate risk.

Those HRC index values above the 90th percentile were categorized as high risk.

The laboratory tests used for comparison were commonly used tests performed

on infants thought to potentially be septic. Examples include the total white blood

13

cell (WBC) count, the ratio of immature to total neutrophil count (I/T ratio), the

platelet count, and blood glucose level.

The heart rate characteristics can be monitored in a continuous fashion,

regardless of whether the infant was showing signs of sepsis or not. For this

reason a HRC index value was available 92% of the time. In comparison, the

other laboratory values were often not drawn until signs of clinical sepsis

appeared. Therefore these tests were only available for 5-10% of the time. 42%

of the HRC readings within 6 hours of a positive blood culture were in the high-

risk range and another 30% were in the intermediate-risk range. By comparison,

most I/T ratios were measured around the time of the blood culture and 44% of

these were abnormal prior to a positive blood culture. The definition of an

abnormal I/T ratio is controversial. By convention, a cutoff value of 0.2 was used

for this study. Multivariable regression analysis revealed that the tests

significantly associated with a positive blood culture were a high risk HRC index

value, an abnormal WBC count, an I/T ratio, low blood sugar and low pH. The

value considered abnormal for each of these labs can be manipulated when

performing regression analysis. It was found that even when an abnormal I/T

ratio was considered to be 0 rather than 0.2, it was still significantly associated

with a positive blood culture. Therefore it was the clinician’s decision to obtain

the I/T ratio that was significantly associated with sepsis, rather than the I/T ratio

itself. This indicates that the HRC index may add further to the diagnosis of

sepsis because it is continually being monitored regardless of the patient’s

clinical condition.

14

Study 5: Griffin MP. Lake DE. O’Shea TM. Moorman JR. Heart rate

characteristics and clinical signs in neonatal sepsis. Pediatr Res.

2007;61(2):222-227

The previous study showed that the HRC index adds predictive information

to other laboratory tests used to identify infants with sepsis. The objective of this

paper was to determine if the HRC index also significantly adds to measures

pertaining to the patient’s clinical status. Examples of these measures would be

vital signs, general appearance, apnea, feeding intolerance, and oxygen

requirement. In the initial studies, a change in this type of information was what

was referred to as an “abrupt clinical deterioration.”

The HRC index was calculated as before. A clinical illness score was

devised which included measures for apnea, oxygen requirement, temperature

instability, lethargy, feeding intolerance, an I/T ratio greater than 0.2, a WBC

greater than 25,000 or less than 5000, and hyperglycemia greater than 180

mg/dl. Clinical points were assigned over a period of 12 hours. The outcome

measure for the statistical models included both “proven sepsis” as in the

previous study as well as “clinical sepsis,” defined as clinical signs of sepsis with

a negative blood culture requiring 5 or more days of antibiotics.

Both the HRC index and the clinical illness score were predictive of sepsis

in the next 24 hours and the HRC index and clinical score together added

significantly to the clinical score alone. As seen in previous studies the HRC

index values were significantly higher before proven or clinical sepsis compared

15

to controls but there was little difference in HRC index value between proven

sepsis and clinical sepsis.

The HRC index was once again categorized into three categories as it was

in the previous study. An HRC score within the lowest 70th percentile was

considered low risk, a score between the 70th to 90th percentiles was considered

intermediate risk, and a score greater than the 90th percentile was considered

high risk. This categorization allowed for a risk assessment tool to be developed.

An infant with a low clinical score alone would have a low risk for illness, but

when a low clinical score was combined with a high-risk HRC index value the risk

for sepsis increased 2.5 fold. For infants with high clinical scores the HRC index

has little impact on their risk for sepsis. An infant with both a high clinical score

and a high risk HRC index was at a 4 times greater risk for sepsis, but an infant

with a high clinical score and a low risk HRC index value still had a 3 times

greater risk of sepsis. The HRC index serves only as an adjunct and does not

eliminate the need for close clinical monitoring.

16

Synthesis of Previous Studies

The preliminary studies to date indicate that the heart rate characteristics

index rises with sepsis and with SIRS. The cHRC, calculated using the HRC

index, is a measure of the burden of illness throughout the entire hospital stay.

An elevated cHRC score therefore indicates significant exposure to either sepsis

or SIRS. Both these conditions cause elevated inflammatory cytokine levels in

the blood (22). A growing body of evidence suggests a link between increased

blood levels of inflammatory cytokines, fetal and neonatal inflammation, and

subsequent neurodevelopmental impairments. (7,9,10). Experiments in animal

models (9,23) and observational studies in humans (24) suggest that initiators of

fetal and neonatal inflammation are associated with neonatal white matter

damage. Studies of inflammatory cytokine levels in amniotic fluid show that

increased levels are associated with subsequent periventricular white matter

damage(11). White matter damage, indicated by persistent ventricular

enlargement or cerebral echolucency on cranial ultrasound (25), is a very strong

predictor for cerebral palsy (8,26) and neurodevelopmental delay (24,27) in

VLBW infants. The cHRC score may therefore be reporting on exposure to

inflammatory cytokines and thus a large contributor to neonatal developmental

delay.

The incidence of cerebral palsy in VLBW infants is approximately 5-6%

(28,29). The risk is much higher for those infants found to have abnormal cranial

ultrasounds. The findings which place the patient at the greatest risk are either

cystic periventricular leukomalacia (cPVL), ventricular enlargement, or a large

17

intraventricular hemorrhage (IVH) which extends into the parenchyma of the

brain itself. Yet many infants born prior to 32 weeks gestation who are

diagnosed with cerebral palsy have normal cranial ultrasounds (8, 30). Therefore

VLBW infants with normal cranial ultrasounds are still at risk for adverse

neurodevelopmental outcomes.

As both birth weight and gestational age decrease, the risk for cerebral

palsy and neurodevelopmental delay increases. Male infants are at an even

greater risk than female infants. Race is also significant. Black and Hispanic

babies have been found to have an increased risk for neurodevelopmental delay

when compared to white babies (30).

Chronic lung disease is an important risk factor for adverse

neurodevelopmental outcomes. It is defined as continued supplemental oxygen

requirement at 36 weeks gestation. It is associated with prolonged mechanical

ventilation, prematurity, and inflammation. The reason for its association with

cerebral palsy is unknown. One theory is that infants with CLD have increased

episodes of hypoxia, which increases the risk for hypoxic brain injury. Another

theory is that both cerebral palsy and CLD are associated with an elevated

inflammatory process and that both are symptoms of the same underlying

etiology. Anti-inflammatory agents, such as steroids, have been tried and were

found to decrease the incidence of CLD but the risk for cerebral palsy actually

increased in those infants treated with steroids (23).

The cHRC score measures the burden of illness for the entire hospital stay.

Other clinical measures of clinical illness have been used to predict

18

neurodevelopmental outcome. Mattia and deRegnier created a modified version

of the Score for Neonatal Acute Physiology (SNAP). The SNAP score was

initially created as a neonatal illness severity index designed to be used during

the first 24 hours of life. It consists of 26 items, including vital signs and lab

values and takes approximately 10-15 minutes to complete (36). Mattia

evaluated infants that were less than or equal to 30 weeks gestation and

retrospectively calculated a SNAP score for each hospital day. Each daily score

was plotted versus time (in days) and the area under the curve was calculated to

create the cumulative SNAP score. The infants were followed up at 1 year of

age, then again at 2 to 3 years of age. The infants with cumulative SNAP scores

greater then the 75th percentile were found to have significantly lower MDI and

PDI scores at 1 year and at 2 to 3 years. A higher incidence of CP was also

found at 2 to 3 years. Using multiple regression models, the cumulative SNAP

score greater than the 75th percentile, IVH, and gestational age were significantly

associated with lower 1 year MDI scores, but by 2 to 3 years only the cumulative

SNAP score was significant. This is suggestive that the underlying cause of the

IVH may in fact be responsible for its association with developmental delay rather

than the IVH itself (31). A large multi-center trial through the NICHD studying

over 2100 infants found that a clinical index calculated from a large number of

variables was a better predictor of developmental impairment than a cranial

ultrasound (37). In comparison to the cHRC, the cumulative SNAP score is a

labor-intensive tool. The cHRC is calculated continuously by a computer

19

algorithm, the cumulative SNAP requires 10 to 15 minutes of data input for each

day for every infant studied.

The relationship of the HRC index and the cHRC score with developmental

outcome has not previously been evaluated. However, there have been studies

evaluating the relationship between the maturation of heart rate and

developmental outcome. In 1985 Fox and Porges recorded 3 minutes of resting

heart rate by electrocardiogram in 4 groups of infants at 40 weeks conceptual

age. The 1st group was premature infants with no medical complications (15

infants), the 2nd group was premature infants with a history of respiratory distress

syndrome (RDS) (28 infants), the 3rd group was term infants with a history of birth

asphyxia (8 infants), and the 4th group was healthy term infants (29 infants).

These patients were then followed up for a neurodevelopmental exam at 8 and

12 months of age. Heart rate variability was thought to mainly be controlled by

input from the parasympathetic branch of the autonomic nervous system. The

main measure of the vagal influence used was respiratory sinus arrhythmia

(RSA). This was obtained using spectral analysis of the heart rate using filters of

various frequencies. The amplitude of RSA is primarily determined by the

parasympathetic influences on the heart. A higher RSA indicated more heart

variability and greater maturity. Therefore RSA was used as an indirect measure

of CNS integrity. The study results were that term infants at 40 weeks

postmenstrual age, both healthy and sick, had higher heart rate variability than

preterm infants at 40 weeks postmenstrual age. Higher heart rate variability was

predictive of higher Bayley MDI scores at 8 and 12 months of age. Between the

20

4 groups of infants, there were no differences in MDI scores. Yet, when

analyzed by heart rate variability, the preterm infants with a history of RDS

showed the greatest association between heart rate variability and MDI score

(32).

Heart rate variability was primarily thought to be the result of vagal tone.

Therefore Doussard-Roosevelt et al postulated that it could also serve as an

index for other regulatory abilities and perhaps serve as a measure of neural

organization. Heart rate data was recorded weekly beginning at 48 hours of life

for 10 to 15 minutes while the infants slept. Most of the infants studied were

between 33 and 35 weeks postmenstrual age. A maturational shift in heart rate

variability, measured by RSA, was correlated with better behavior regulation at 3

years (33). A follow-up study using the same cohort at 6-9 years of age showed

association of heart variability maturation with greater social competency (34).

A small study containing only 19 VLBW infants evaluated the effect of

intraventricular hemorrhage and white matter damage on heart rate variability.

There were 4 groups: 7 infants had periventricular leukomalacia (PVL), 3 infants

had IVH, 2 infants had both, and 7 infants had no evidence of brain injury. The

infants diagnosed with IVH had reduced variability while those diagnosed with

white matter damage had increased variability. The reasons for this unexpected

finding are unknown at this time (35).

21

Specific Aims of the Thesis Project

Both sepsis and SIRS are risk factors for cerebral palsy and developmental

delay. The cHRC score represents the cumulative risk for sepsis and SIRS for

the infant’s entire hospital stay. The cHRC score may therefore be predictive not

only for SIRS and sepsis but for adverse neurodevelopmental outcomes as well.

The major advantages of the cHRC score over other measures used to

determine burden of illness is that the cHRC is being measured continuously and

non-invasively. No daily data entry is necessary.

This study will build on the previous research described above. Using the

follow-up data of the VLBW infants of Study #3 we plan to retrospectively analyze

the cHRC score obtained during the neonatal hospitalization with the results of a

neurodevelpomental exam performed at 12 to 18 months corrected age. The

primary objective will be to test whether an elevated cHRC is associated with

adverse neurodevelopmental outcome. We hypothesize that an elevated cHRC

indicates a greater exposure to inflammatory mediators and therefore a greater

risk for neurodevelopmental impairment. This will be the first study to evaluate

the HRC index with long-term outcomes.

22

REFERENCES

1) Berger A. Salzer HR. Weninger M. Sageder B. Aspock C. Septicaemia inan Austrian neonatal intensive care unit: a 7-year analysis. Acta Paediatr.1998;87:1066-1069

2) Stoll BJ. Hansen N. et al. Late-onset sepsis in very low birth weightneonates: the experience of the NICHD Neonatal Research Network.Pediatrics. 2002;110(suppl):285-291

3) Bone RC. Grodzin CJ. Balk RA. Sepsis: a new hypothesis forpathogenesis of the disease process. Chest. 1997;112:235-243

4) Stoll BJ. Hansen N. et al. Neurodevelopmental and growth impairmentamong extremely low birth weight infants with neonatal infection. JAMA.2004;292:2357-2365

5) Wheater M. Rennie JM. Perinatal infection is an important risk factor forcerebral palsy in very-low-birthweight infants. Dev Med Child Neurol.2000;42:362-367

6) Dommergues M-A. Patkai J. Renauld J-C. Evrard P. Gressens P.Proinflammatory cytokines and interleukin-9 exacerbate excitotoxic lesionsof the newborn murine neopallium. Ann Neurol. 2000;47:54-63

7) O’Shea TM. Cerebral palsy in very preterm infants: new epidemiologicinsights. Met Ret Dev Dis Res Rev. 2002;8:135-145

8) Pinto-Martin JA. Riolo S. Cnaan A. et al. Cranial ultrasound prediction ofdisabling and nondisabling cerebral palsy at age two in a low birth weightpopulation. Pediatrics. 1995;95:249-254

9) Dammann O. Kuban KC. Leviton A. Perinatal infection, fetal inflammatoryresponse, white matter damage, and cognitive limitations in children bornpreterm. Ment Ret Dev Dis Res Rev. 2002;8:46-50

10) Wu YW. Colford JM. Chorioamnionitis as a risk factor for cerebral palsy.JAMA. 2000;284(11):1417-1424

11) Yoon BH. Jun JK. Romero R. et al. Amniotic fluid inflammatory cytokines(interleukin-6, interleukin-1 beta, and tumor necrosis factor-alpha), neonatalbrain white matter lesions, and cerebral palsy. Am J Obstet Gynecol.1997;177:19-26

12) Burnard ED. Changes in heart size in the dyspnoeic newborn baby. BrMed J. 1959;1:1495-1500

23

13) Rudolph AJ. Vallbona C. Desmond MM. Cardiodynamic studies in thenewborn. III. Heart rate patterns in infants with idiopathic respiratory distresssyndrome. Pediatrics. 1965;36:551-559

14) Griffin MP. Moorman JR. Toward the early diagnosis of neonatal sepsisand sepsis-like illness using novel heart rate analysis. Pediatrics.2001;107:97-104

15) Griffin MP. O’Shea TM. Bissonette EA. Harrel FE. et al. Abnormal heartrate characteristics preceding neonatal sepsis and sepsis-like illness.Pediatr Res. 2003;53(6):920-926

16) Kovatchev BP. Farhy LS. Cao H. Griffin MP. Lake DE. Moorman JR.Sample asymmetry analysis of heart rate characteristics with application toneonatal sepsis and systemic inflammatory response syndrome. PediatrRes. 2003;54:892-898

17) Lake DE. Richman JS. Griffin MP. Moorman JR. Sample entropy analysisof neonatal heart rate variability. Am J Physiol. 2002;283:R789-R797

18) Richman JS. Moorman JR. Physiological time series analysis usingapproximate entropy and sample entropy. Am J Physiol. 2000;278:H2039-H2049

19) Griffin MP. O’Shea TM. Bissonette EA. Harrel FE. et al. Abnormal heartrate characteristics are associated with neonatal mortality. Pediatr Res.2004; 55(5):782-788

20) Griffin MP. Lake DE. Moorman JR. Heart Rate Characterisitics andLaboratory Tests in Neonatal Sepsis. Pediatrics. 2005;115:937-941

21) Griffin MP. Lake DE. O’Shea TM. Moorman JR. Heart ratecharacteristics and clinical signs in neonatal sepsis. Pediatr Res.2007;61(2):222-227

24

22) Malik A, Hui CPS, Pennie RA, Kirpalani H. Beyond the complete blood cellcount and C-reactive protein - A systematic review of modern diagnostictests for neonatal sepsis. Archives of Pediatrics & Adolescent Medicine2003; 157(6):511-516.

23) O’Shea TM. Kothadia JM. Klinepeter KL. et al. Randomized placebo-controlled trial of a 42 day tapering course of dexamethasone to reduce theduration of ventilator dependency in very low birth weight infants: outcomeof study participants at 1-year adjusted age. Pediatrics. 1999;104:15-21

24) Whitaker A, Johnson J, Sebris S, Pinto J, Wasserman G, Kairam R et al.Neonatal Cranial Ultrasound Abnormalities - Association withDevelopmental Delay at Age One in Low-Birth-Weight Infants. Journal ofDevelopmental and Behavioral Pediatrics 1990; 11(5):253-260.

25) Paneth N. Classifying brain damage in preterm infants. J Pediatr 1999;134(5):527-529.

26) de Vries LS, Van Haastert ILC, Rademaker KJ, Koopman C, Groenedaal F.Ultrasound abnormalities preceding cerebral palsy in high-risk preterminfants. Journal of Pediatrics 2004; 144(6):815-820.

27) Vohr BR, Wright LL, Dusick AM, Mele L, Verter J, Steichen JJ et al.Neurodevelopmental and functional outcomes of extremely low birth weightinfants in the National Institute of Child Health and Human DevelopmentNeonatal Research Network, 1993-1994. Pediatrics 2000; 105(6):1216-1226.

28) O’Shea TM. Preisser JS. Klinepeter KL. Dillard RG. Trends in mortalityand cerebral palsy in a geographically based cohort of very low birth weightneonates born between 1982 and 1994. Pediatrics. 1998;101:642-647

29) Winter S. Autry A. Boyle C. Allsopp MY. Trends in the prevalence ofcerebral palsy in a population-based study. Pediatrics. 2002;110:1220-1225

30) Laptook AR. O’Shea TM. Shankaran S. Bhaskar B. Adverseneurodevelopmental outcomes among extremely low birth weight infantswith a normal head ultrasound: prevalence and antecedents. Pediatrics.2005;115:673-680

31) Mattia FR, deRegnier RA. Chronic physiologic instability is associated withneurodevelopmental morbidity at one and two years in extremely prematureinfants. Pediatrics 1998; 102(3):E35.

32) Fox NA, Porges SW. The Relation Between Neonatal Heart PeriodPatterns and Developmental Outcome. Child Development 1985; 56(1):28-37.

25

33) DoussardRoosevelt JA, Porges SW, Scanlon JW, Alemi B, Scanlon KB.Vagal regulation of heart rate in the prediction of developmental outcome forvery low birth weight preterm infants. Child Development 1997; 68(2):173-186.

34) Doussard-Roosevelt JA, McClenny BD, Porges SW. Neonatal cardiacvagal tone and school-age developmental outcome in very low birth weightinfants. Developmental Psychobiology 2001; 38(1):56-66.

35) Hanna BD, Nelson MN, White-Traut RC, Silvestri JM, Vasan U, Rey PM etal. Heart rate variability in preterm brain-injured and very-low-birth-weightinfants. Biology of the Neonate 2000; 77(3):147-155.

36) Richardson DK, Gray JE, McCormick MC, Workman K, Goldmann DA.Score for neonatal acute physiology: A physiologic severity index forneonatal intensive care. Pediatrics. 1993; 91:617-623

37) Broitman E, Namasivayam A, Higgins RD, Vohr BR, Das A, Bhaskar B etal. Clinical data predict neurodevelopmental outcome better than headultrasound in extremely low birth weight infants. J. Pediatr. 2007;151(5):500-505

26

Chapter 2

Heart Rate Characteristics and Neurodevelopmental Outcome

in Very Low Birth Weight Infants

Kevin Addison, MD1; M. Pamela Griffin, MD2

J. Randall Moorman, MD3; Douglas E. Lake, PhD3; T. Michael O’Shea, MD,

MPH1 ;

The following manuscript was published in the Journal of Perinatology, 2009;

volume 29, pages 750-756

27

ABSTRACT

Background: Sepsis in very low birth weight (VLBW) infants has been associated

with an increased risk of adverse developmental outcome. We have identified

abnormal heart rate characteristics (HRCs) that are predictive of impending

sepsis, and we have developed a summary measure of an infant’s HRCs during

the neonatal hospitalization that we refer to as the cumulative HRC score

(cHRC).

Objective: In this study we tested the hypothesis that increasing cHRC is

associated with an increasing risk of adverse neurodevelopmental outcome in

VLBW infants.

Methods: Data were collected on 65 VLBW infants whose HRCs were monitored

while in the neonatal intensive care unit and who were examined at 12-18

months adjusted age. Using the Bayley Scale of Infant Development-II, we

identified delays in early cognitive function (i.e., Mental Developmental Index <

70) and psychomotor development (i.e., Psychomotor Developmental Index <

70). Cerebral palsy (CP) was diagnosed using a standard neurological

examination.

Results: Increasing cHRC score was associated with an increased risk of CP

(odds ratio per 1 standard deviation increase in cHRC: 2.6, 95% confidence

limits: 1.42, 5.1) and delayed early cognitive development [odds ratio: 2.3 (1.3;

4.3)]. These associations remain statistically significant when adjusted for major

cranial ultrasound abnormality. There was an association of increasing cHRC

28

and delayed psychomotor development, which did not reach statistical

significance [odds ratio: 1.7 (1.0, 3.0)].

Conclusions: Among VLBW infants, the cumulative frequency of abnormal

HRCs, which can be assessed non-invasively in the neonatal intensive care unit,

is associated with an increased risk of adverse neurodevelopmental outcome.

29

INTRODUCTION

Very low birth weight (VLBW) infants are at a high risk for sepsis(1) and

have an increased incidence of cerebral palsy (CP) and developmental delay

compared to full term infants.(2;3) Recent studies indicate that sepsis and the

systemic inflammatory response syndrome (SIRS) are associated with an

increased risk for developmental impairments in infants born prematurely(4-6).

We have reported that certain heart rate characteristics (HRCs), specifically,

transient decelerations, decreased variability, and a lack of accelerations, can be

used to identify infants who are at increased risk for developing either sepsis or

systemic inflammatory response.(7-9) A summation of an infant’s abnormal HRC

during neonatal hospitalization, referred to as the cumulative HRC (cHRC) index,

is predictive of mortality.(10) In the current study we analyzed the association

between cHRC during the neonatal hospitalization and neurodevelopmental

outcome between 12 and 18 months corrected age. Our objective was to

determine if an elevated cHRC is associated with adverse neurodevelopmental

outcome at 12 to 18 months corrected age.

30

METHODS

This study was approved by the Wake Forest University Health Sciences

Institutional Review Board.

Study Participants

Inclusion criteria for this study were as follows: 1) birth weight less than

1500 grams; 2) admitted to the Wake Forest University Baptist Medical Center

Intensive Care Nursery between 1999-2001; 3) evaluated at 12 months adjusted

age at the Wake Forest University Development Evaluation Clinic; 4) at least 12,

6-hour epochs of HRC monitoring available for analysis; 5) no major congenital

anomaly. The study was approved by the Wake Forest University Baptist

Medical Center Institutional Review Board with a waiver of the requirement for

informed consent.

Measurements

Collection of HRCs data

Heart rate data were collected non-invasively from the bedside monitors

used in routine care of infants in the Wake Forest University Baptist Medical

Center Intensive Care Nursery. Data were collected continuously 24 hours a day

without selection of epochs relevant to sleep, feeding, clinical status or any other

factors. Briefly, an analog electrocardiographic signal is obtained from the defib-

sync output port of the bedside monitor. This signal is digitized at 4 kHz by a

31

microcomputer at the bedside. The data are high-pass filtered, and QRS

complexes are identified using amplitude and duration criteria to generate sets of

RR intervals. These sets of intervals are used to generate HRC parameters

including standard deviation, sample asymmetry, and sample entropy analyses.

These parameters are used as inputs to a predictive model algorithm using

multivariable logistic regression that was developed at the University of Virginia

and externally validated at Wake Forest University. The output of the model is

divided by the average risk of sepsis and presented as the fold-increase in risk of

sepsis in the next 24hours.

Calculation of HRCs

Sample Asymmetry

Quadratic ‘risk-analysis’ functions are calculated using raw data. Given a

series of 4096 RR intervals x1, x2, ... x4096 with median = m, we compute

r1(xi)=r(xi) if xi<m; 0 otherwise, and r2(xi)=r(xi) if xi>m; 0 otherwise. The Left (R1)

and Right (R2) HRC risks are:

)x(r=R 2i

1=i

1140961

4096

∑ and )x(r=R 2i

1=i

1240962

4096

∑ respectively.

The parameters of interest are R1,which relates to the number and extent of HR

accelerations, R2, which similarly reports on decelerations, and the ratio R2/R1,

which we have called the sample asymmetry.

32

Sample Entropy

Sample entropy (SampEn) is calculated with m=3, r=0.2 as described(11)

using filtered, normalized data. In this context, reduced sample entropy occurs

when both reduced variability and transient decelerations are present

Predictive multi-variable statistical models

These have the form of regression expressions of the form:

log[P(Y=1)/ (1-P(Y=1))] = β0 + β1 HRC1 + β2 HRC2 +…+ βm HRCm;

where HRCm are heart rate characteristics of interest and P(Y=1) is the

probability of sepsis or sepsis like illness within the next 24hrs

Calculation of cumulative HRC

The infant’s hospital stay was divided into 6-hour epochs. For each 6-hour

epoch, the infant was given a demographic index, calculated from a logistic

regression model containing the variables for gestational age, birth weight, and

days of age(7). The infant was also given a HRC index value for each 6-hour

epoch, calculated from a different logistic regression model using the HRCs

(standard deviation, sample asymmetry, and sample entropy) as input variables.

The probability of sepsis or SIRS over the next 24 hours of the infant’s life was

the outcome variable used in both of these logistic regression models.

33

Therefore, the demographic index is the probability that sepsis or systemic

inflammatory response will occur within the next 24 hours as predicted only by

the demographic variables and the HRC index is the probability that sepsis or

systemic inflammatory response will occur within the next 24 hours as predicted

by the HRCs. The cHRC is calculated by subtracting the demographic index

from the HRC index for each epoch, and then summing up all the epochs of the

infant’s stay(10).

cHRC = ∑[(HRC index) – (Demographic index)]

Therefore the cHRC gives an overall picture of whether the infant clinically

did better or worse than expected for the average infant based solely on knowing

the birth weight and gestational age. If the infant had a benign hospital course

and did better than expected then the majority of the HRC index values would be

low and the cHRC would be less than zero. If the infant did poorly, with multiple

episodes of sepsis or systemic inflammatory response, then the majority of the

HRC index values would be high and the cHRC would be greater than zero. If

the infant had a typical hospital course, then the cHRC would be close to zero.

Patient characteristics

Data about birth weight, gestational age, gender, race, chronic lung disease,

and cranial ultrasound abnormalities were obtained from an electronic database

maintained at our follow-up clinic. The data were abstracted from medical

records by a study coordinator who was not aware of the study hypothesis or the

34

infants' cHRC score. Sepsis was defined as a positive blood culture treated with

at least 7 days of antibiotics. Small for gestational age was defined as birth

weight less than the tenth percentile for gestational age, based on data reported

by Alexander et al(12). Chronic lung disease was defined as the need for

supplemental oxygen at 36 weeks post-menstrual age(13). Major cranial

ultrasound abnormalities were defined as any of the following: 1) periventricular

echodensity located ipsilateral to a presumed intraventricular hemorrhage (i.e.,

abnormal echodensity in the ventricle); 2) post-hemorrhagic hydrocephalus

requiring neurosurgical intervention; 3) moderate or severe ventricular

enlargement on a "late" (performed after the first month of life) ultrasound; or 4)

periventricular echolucency(14).

Developmental Outcomes

Follow-up data were obtained at 12 (n=58) or 18 (n=7) months adjusted age

at the Wake Forest University Development Evaluation Clinic. Children were

classified as having CP or not by a standardized neurological exam performed by

physicians who were aware of the patient’s medical history, but not aware of the

cHRC score. The Bayley Scales of Infant Development-Second Edition (BSID-

II)(15) was administered by child psychologists who were not aware of the child's

medical history. After testing was completed, the psychologists learned of the

child's gestational age at birth in order to derive the BSID-II scores adjusted for

gestational age.

35

CP was defined as a non-progressive central nervous system disorder

characterized by abnormal muscle tone in at least one extremity and abnormal

control of movement and posture resulting in impaired motor function(16).

Delayed early cognitive development was defined as a BSID-II Mental

Development Index (MDI) < 70; delayed psychomotor development was defined

as a Psychomotor Development Index (PDI) < 70. We used the term

neurodevelopmental impairment (NDI) to refer to a composite outcome of either

cerebral palsy or an MDI < 70.

Data Analysis

We analyzed associations between cHRC and developmental outcome in

several ways: 1) Correlations between cHRC and MDI and cHRC and PDI were

analyzed using Spearman Rank correlation coefficients. 2) Infants were

classified into cHRC quartiles for each of the dichotomous outcomes of interest

(i.e., CP, delayed early cognitive and psychomotor development, a composite

outcome of CP or delayed early cognitive development) and the resulting 2 x 4

contingency tables were analyzed using the Cochran-Armitage test for trend(17).

3) Logistic models were used to estimate the odds ratios for the association of

cHRC, entered as a continuous variable, and the dichotomous outcomes of

interest. To compare groups of infants with the outcome of interest to the groups

without the outcome of interest, we used the Wilcoxon-rank sum test for

continuous variables and the Chi-square or Fisher's exact test for categorical

variables.

36

Multivariate analysis was performed using logistic regression. Only

variables which had a p-value less than 0.1 in univariate analyses were included

in the logistic regression model. Variables with the highest p-value were

eliminated one at a time using backwards stepwise elimination until all variables

within the model had adjusted p-values less than 0.1. All statistical analyses

were performed using SAS version 9.1 (SAS Institute, Cary, NC.)

RESULTS

The attributes of these infants are summarized in Table 1. Briefly, the total

number of infants is 65, with a median gestational age of 26 weeks and a median

birthweight of 792 grams. The rates of each outcome as a function of cHRC

quartile are presented in Figure 1. The median cHRC was 4.0, and the range

was –4.9 to 43.5. cHRC was inversely correlated with both MDI (Spearman rho

= -0.29, p = 0.02) and PDI (Spearman rho = -0.39, p = 0.001). The Cochran-

Armitage test for trend showed a statistically significant linear trend between the

quartiles of cHRC and the outcomes of CP, MDI < 70, and the composite

outcome of CP or MDI < 70 (all p values < 0.05). cHRC was higher among

infants with sepsis (p=0.002), but significant associations were not found

between sepsis and any of the developmental outcomes of interest (all p values

> 0.1).

37

Table 1. Characteristics and outcomes of study infants. Data are number of infants

(percent in parenthesis) except where noted.

Characteristic / outcome VLBW Infants (n=65)

Gestational age (weeks)* 26 (22 - 33)

Birth weight (grams)* 792 (406 – 1470)

Small for gestational age 7 (11)

Race: White 37 (57)

Non-white 28 (43)

Female gender 36 (55)

Sepsis 46 (71)

Necrotizing enterocolitis 10 (15)

Chronic lung disease 34 (52)

Major Ultrasound abnormality

17 (26)

cHRC* 4.0 (-4.9 - 43.5)

Cerebral palsy 10 (16)†

MDI < 70 11 (17)

PDI < 70 27 (42)

NDI 16 (25)

* data are median (range in parenthesis)

† One infant did not undergo neurological examination at follow up

Abbreviations: cHRC – cumulative heart rate characteristics index; MDI – MentalDevelopmental Index; PDI – Psychomotor Developmental Index; NDI –neurodevelopmental impairment

38

Figure 1. The Rates of Each Outcome by cHRC Quartile

05

1015202530354045505560

CP MDI < 70 PDI < 70 NDI

1st Quartile2nd Quartile3rd Quartile4th Quartile

39

Table 2 summarizes associations between infant characteristics and the

developmental outcomes of interest. At significance level of 0.1, cHRC and

major cranial ultrasound abnormality were associated with each of the

developmental outcomes that we studied. Gestational age was associated with

an increased risk of CP, MDI < 70, and birth weight was associated with MDI <

70. Chronic lung disease was associated with MDI < 70, and necrotizing

enterocolitis was associated with PDI < 70. Non-white race was associated with

an increased risk of CP.

In multivariate analyses in which the outcomes of interest were CP, PDI <

70, and the composite outcome of CP or delayed early cognitive development,

only cHRC and major cranial ultrasound abnormalities were retained when

variables were eliminated in a stepwise fashion using α < 0.1 as the criteria for

remaining in the model. In analyses in which the outcome of interest was delayed

MDI < 70, chronic lung disease was also significant at p < 0.1. Unadjusted and

adjusted odds ratios for a one standard deviation increase in cHRC are

presented in Table 3.

40

Table 2. Characteristics of VLBW Infants with and without developmental impairments. Data are medians (range in parenthesis) ornumber of infants (percent in parenthesis).

Cerebral Palsy MDI < 70 PDI < 70

Characteristic Absent(n=54)

Present(n=10)

Absent(n=54)

Present(n=11)

Absent(n=38)

Present(n=27)

Gestational age (weeks) 27 (23 – 31) 25 (22 – 33)* 27 (22 – 33) 25 (23 – 29)* 26.5(22 – 31)

26(23 – 33)

Birth weight (grams) 798(440 – 1470)

725(406 – 1470)

814(440 – 1470)

650(406 – 1439)*

798(440 – 1470)

790(406 – 1470)

Small for gestational age 5 (9) 2 (20) 5 (9) 2 (18) 2 (5) 5 (19)

Race White 34 (63) 3 (30)* 31 (57) 6 (55) 21 (55) 16 (59)

Non-white 20 (37) 7 (70) 23 (43) 5 (45) 17 (45) 11 (41)

Female gender 31 (57) 4 (40) 29 (54) 7 (64) 21 (55) 15 (56)

Sepsis 37 (69) 8 (80) 37 (69) 9 (82) 24 (63) 22 (81)

Necrotizing enterocolitis 8 (15) 2 (20) 8 (15) 2 (18) 3 (8) 7 (26)*

Chronic lung disease 27 (50) 6 (60) 24 (44) 10 (91)* 18 (47) 16 (59)

Major Ultrasound abnormality

10 (19) 7 (70)* 11 (20) 6 (55)* 6 (16) 11 (41)*

cHRC 3.76(-4.91 - 41.08)

18.14(-1.61 - 43.48)*

-2.31(-4.91 to 33.60)

9.20(-1.61 to 43.48)*

2.05(-4.91 to 22.06)

5.53(-1.61 to 43.48)*

* p < 0.1

Abbreviations: cHRC - cumulative heart rate characteristics index

41

Table 3. Multivariate analysis. Odds ratios and 95% confidence intervals foreach 10 unit increase in cHRC.

Outcome OR (95% CI) p value Adjusted OR(95% CI)

p value

Cerebral palsy 2.6 (1.4 – 5.1) 0.004 2.3 (1.2, 4.7)1 0.02

MDI < 70 2.3 (1.3 – 4.3) 0.007 2.1 (1.0, 4.2)2 0.04

PDI < 70 1.7 (1.0 – 3.0) 0.06 1.5 (0.9, 2.7)1 0.1

NDI 3.3 (1.6 – 7.0) 0.002 3.0 (1.4, 6.6)1 0.005

1 OR adjusted for head ultrasound results

2 OR adjusted for head ultrasound results and chronic lung disease

Abbreviations: cHRC - cumulative heart rate characteristics index; OR – oddsratio; CI – confidence interval; MDI – Mental Developmental Index; PDI –Psychomotor Developmental Index; NDI – neurodevelopmental impairment

42

DISCUSSION

In a sample of VLBW infants we found that cHRC is correlated with scores

on the BSID-II and that the risk of CP increases with increasing cHRC. These

associations were attenuated only slightly when adjusted for the presence of

major abnormalities on cranial ultrasound. Thus cHRC is associated not only with

mortality, as we have previously described, but also with developmental

impairments among VLBW infants. As would be expected, we found higher

cHRC values among infants who were diagnosed with sepsis. Although we did

not collect data about the occurrence of culture-negative sepsis, our prior studies

indicate that the heart rate characteristics that influence cHRC are found in

infants with both culture-positive and culture-negative sepsis.(9)

The HRCs that determine cHRC have been associated with impending

neonatal sepsis, an event that may initiate a systemic inflammatory response

(SIRS), including increased levels of blood cytokines(18). A growing body of

evidence suggests a link between fetal and neonatal inflammation, increased

blood levels of inflammatory cytokines, and subsequent neurodevelopmental

impairments(4-6;19). Although our results demonstrate an association between

cHRC and neurodevelopmental outcome, our findings are in agreement with

Vohr et al, in that we did not find an association between culture proven sepsis

and adverse neurodevelopmental outcome.(20) Thus elevated cHRC may be

indicative of not only culture proven sepsis, but other initiators of inflammation,

such as SIRS with negative cultures and necrotizing enterocolitis.

43

White matter damage, as indicated by persistent ventricular enlargement or

cerebral echolucency on cranial ultrasound(21), is probably the strongest single

predictor of cerebral palsy(22;23) and delayed early cognitive functioning(20;24)

among VLBW infants. Experiments in animal models(4;25) and observational

studies in humans(26) suggest that initiators of fetal and neonatal inflammation

are associated with neonatal white matter damage. Increased levels of

inflammatory cytokines have been detected in the amniotic fluid of infants who

subsequently developed periventricular white matter damage(27). The HRC

index rises with sepsis(9;28;29), when blood levels of inflammatory cytokines

would be expected to increase(18). Thus an elevated cHRC score may be

reporting on exposure to one of the putative causes of brain damage in preterm

infants.

Despite its usefulness in identifying brain damage, white matter as seen on

cranial ultrasound has been referred to as the “tip of the iceberg”(30) because

ultrasound fails to detect white matter damage in a substantial proportion of

affected infants(31;32). This may explain why almost 25% of extremely low birth

weight infants with developmental impairment have normal cranial

ultrasound(33). The current study suggests that in addition to its potential as a

means of earlier identification of impending sepsis(7;9;29), HRC monitoring might

provide prognostic information that is to some degree complementary to that

provided by cranial ultrasound(34;35). Somewhat similar approaches were used

by Mattia and deRegnier, who found that the summation of the Severity of

Neonatal Acute Physiology scores was predictive of lower MDI and PDI scores at

44

2 to 3 years of age,(36) and Broitman et al,(37) who found that a multivariate

index derived from clinical data was a better predictor of developmental

impairment than cranial ultrasound(37).

The association of cHRC with delayed psychomotor development was

weaker than that between cHRC and the other neurodevelopmental outcomes

that we studied. It is possible that the reliability of our assessments of

psychomotor development at 12 to 18 months adjusted age was lower than that

of our assessments of early cognitive development (with the MDI). A second

possibility is that the risk factor profile differs for MDI < 70 and PDI < 70. For

example, major cranial ultrasound abnormalities, chronic lung disease and

necrotizing enterocolitis are associated more strongly with PDI < 70 than with

MDI < 70(20;38).

The specific HRCs that we studied here have not been previously analyzed

in relation to neurodevelopmental outcomes. However others have studied the

maturation of heart rate variability, which is one of the variables that influences

cHRC. In preterm infants, greater heart rate variability at 40 weeks

postmenstrual age was found to be predictive of higher Bayley MDI(39), and the

rate maturation of heart rate variability between 33 and 35 weeks postmenstrual

age has been correlated with better behavior regulation at 3 years(40) and

greater social competency at 6 to 9 years(41).

We should note several limitations of our study. Most important is that our

relatively small convenience sample. All of these infants were transported to a

tertiary hospital and would therefore be at high risk of developmental

45

impairments. For example, the prevalence of cerebral palsy (16%) described

here is higher than that reported from population-based studies(16;42). Second,

this is a retrospective analysis, which likely limited the validity of data about

potential confounders, such as cranial ultrasound findings, limiting our ability to

adjust for these confounders. We also had limited information about

socioeconomic status, which is associated with performance on the Bayley

Scales of Infant Development(20). Third, although the physicians who performed

the neurological assessments were not aware of infants’ cHRC, they were aware

of the infant's medical history, which could have lead to ascertainment bias if

these examiners suspected an association between events that increase cHRC

(such as neonatal sepsis) and subsequent developmental impairments. Finally,

examinations at 12 to 18 months adjusted age are somewhat limited in their

sensitivity for identification of cerebral palsy(43) and delayed early cognitive

functioning ability(44), which may have resulted in misclassification of infants with

respect to the presence of developmental impairment. Before applying our

findings to the clinical care of patients, replication is needed in a larger, and more

representative sample of high-risk infants, with data about potential confounders

prospectively collected.

Despite these limitations, the results of our study support the need for larger

analyses of the relationship of neonatal cHRC score to neurodevelopmental

outcome. If an association of cHRC and outcome is confirmed in larger studies,

more study of the antecedents of cHRC would be warranted. Study is needed

also of the relationship between HR variability and known antecedents of poor

46

long-term outcome, such as necrotizing enterocolitis(45) and chronic lung

disease(46). Research into the possible mechanisms linking heart rate

characteristics and developmental outcome should include assessment of

inflammatory cytokines and other biomarkers of inflammation.(47)

The data from which the cHRC is derived can be obtained non-invasively

with a commercially available device, but modification of the software

programming in this device would be needed to automate computation of the

cHRC. The clinical utility of continuous heart rate characteristics monitoring is

currently under study (ClinicalTrials.gov Identifier: NCT00307333). At the

present time, we can only speculate as to the clinical utility of cHRC. cHRC might

add to the predictive information conveyed by cranial ultrasound findings(22;35)

and clinical data(37). Improved prediction of neurodevelopment impairment

could allow clinicians to target infants at highest risk so that early intervention

could be initiated, and outcome improved(48).

47

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(2) Drummond PM, Colver AF. Analysis by gestational age of cerebralpalsy in singleton births in north-east England 1970-94. Paediatricand Perinatal Epidemiology 2002; 16(2):172-180.

(3) Winter S, Autry A, Boyle C, Yeargin-Allsopp M. Trends in theprevalence of cerebral palsy in a population-based study. Pediatrics2002; 110(6):1220-1225.

(4) Dammann O, Leviton A. Inflammatory brain damage in pretermnewborns - dry numbers, wet lab, and causal inferences. EarlyHuman Development 2004; 79(1):1-15.

(5) Wu YW. Systematic review of chorioamnionitis and cerebral palsy.Mental Retardation and Developmental Disabilities ResearchReviews 2002; 8(1):25-29.

(6) O'Shea TM. Cerebral palsy in very preterm infants: Newepidemiological insights. Mental Retardation and DevelopmentalDisabilities Research Reviews 2002; 8(3):135-145.

(7) Griffin MP, O'Shea TM, Bissonette EA, Harrell FE, Lake DE,Moorman JR. Abnormal heart rate characteristics precedingneonatal sepsis and sepsis-like illness. Pediatric Research 2003;53(6):920-926.

(8) Griffin MP, Lake DE, Bissonette EA, Harrell FE, O'Shea TM,Moorman JR. Heart rate characteristics: Novel physiomarkers topredict neonatal infection and death. Pediatrics 2005; 116(5):1070-1074.

(9) Griffin MP, Moorman JR. Toward the early diagnosis of neonatalsepsis and sepsis-like illness using novel heart rate analysis.Pediatrics 2001; 107(1):97-104.

(10) Griffin MP, O'Shea TM, Bissonette EA, Harrell FE, Lake DE,Moorman JR. Abnormal heart rate characteristics are associatedwith neonatal mortality. Pediatric Research 2004; 55(5):782-788.

(11) Richman JS, Moorman JR. Physiological time-series analysis usingapproximate entropy and sample entropy. American Journal of

48

Physiology-Heart and Circulatory Physiology 2000; 278(6):H2039-H2049.

(12) Alexander GR, Himes JH, Kaufman RB, Mor J, Kogan M. A UnitedStates national reference for fetal growth. Obstetrics andGynecology 1996; 87(2):163-168.

(13) Shennan AT, Dunn MS, Ohlsson A, Lennox K, Hoskins EM.Abnormal pulmonary outcomes in premature infants: prediction fromoxygen requirement in the neonatal period. Pediatrics 1988;82(4):527-532.

(14) Stewart AL, Reynolds EO, Hope PL, Hamilton PA, Baudin J,Costello AM et al. Probability of neurodevelopmental disordersestimated from ultrasound appearance of brains of very preterminfants. Dev Med Child Neurol 1987; 29(1):3-11.

(15) Bayley N. Bayley Scales of Infant Development-Second Edition.Second ed. Psychological Corporation, 1993.

(16) O'Shea TM, Preisser JS, Klinepeter KL, Dillard RG. Trends inmortality and cerebral palsy in a geographically based cohort of verylow birth weight neonates born between 1982 to 1994. Pediatrics1998; 101(4 Pt 1):642-647.

(17) Armitage P. Test for linear trend in proportions and frequencies.Biometrics 1955; 11(375):386.

(18) Malik A, Hui CPS, Pennie RA, Kirpalani H. Beyond the completeblood cell count and C-reactive protein - A systematic review ofmodern diagnostic tests for neonatal sepsis. Archives of Pediatrics& Adolescent Medicine 2003; 157(6):511-516.

(19) Dammann O, Leviton A. The role of the fetus in perinatal infectionand neonatal brain injury. Curr Opin Pediatr 1999; in press.

(20) Vohr BR, Wright LL, Dusick AM, Mele L, Verter J, Steichen JJ et al.Neurodevelopmental and functional outcomes of extremely low birthweight infants in the National Institute of Child Health and HumanDevelopment Neonatal Research Network, 1993-1994. Pediatrics2000; 105(6):1216-1226.

(21) Paneth N. Classifying brain damage in preterm infants. J Pediatr1999; 134(5):527-529.

(22) de Vries LS, Van Haastert ILC, Rademaker KJ, Koopman C,Groenedaal F. Ultrasound abnormalities preceding cerebral palsy in

49

high-risk preterm infants. Journal of Pediatrics 2004; 144(6):815-820.

(23) Pinto-Martin JA, Riolo S, Cnaan A, Holzman C, Susser MW, PanethN. Cranial ultrasound prediction of disabling and nondisablingcerebral palsy at age two in a low birth weight population. Pediatrics1995; 95(2):249-254.

(24) Whitaker A, Johnson J, Sebris S, Pinto J, Wasserman G, Kairam Ret al. Neonatal Cranial Ultrasound Abnormalities - Association withDevelopmental Delay at Age One in Low-Birth-Weight Infants.Journal of Developmental and Behavioral Pediatrics 1990;11(5):253-260.

(25) Hagberg H, Peebles D, Mallard C. Models of white matter injury:Comparison of infectious, hypoxic-ischemic, and excitotoxic insults.Mental Retardation and Developmental Disabilities ResearchReviews 2002; 8(1):30-38.

(26) Wu YW, Colford JM. Chorioamnionitis as a risk factor for cerebralpalsy - A meta-analysis. Jama-Journal of the American MedicalAssociation 2000; 284(11):1417-1424.

(27) Yoon BH, Jun JK, Romero R, Park KH, Gomez R, Choi JH et al.Amniotic fluid inflammatory cytokines (interleukin-6, interleukin-1beta, and tumor necrosis factor-alpha), neonatal brain white matterlesions, and cerebral palsy. Am J Obstet Gynecol 1997; 177(1):19-26.

(28) Griffin MP, Lake DE, O'Shea TM, Moorman JR. Heart ratecharacteristics and clinical signs in neonatal sepsis. PediatricResearch 2007; 61(2):222-227.

(29) Griffin MP, Lake DE, Moorman JR. Heart rate characteristics andlaboratory tests in neonatal sepsis. Pediatrics 2005; 115(4):937-941.

(30) Leviton A, Gilles F. Ventriculomegaly, delayed myelination, whitematter hypoplasia, and "periventricular" leukomalacia: How are theyrelated? Pediatr Neurol 1996; 15:127-136.

(31) Maalouf EF, Duggan PJ, Counsell SJ, Rutherford MA, Cowan F,Azzopardi D et al. Comparison of findings on cranial ultrasound andmagnetic resonance imaging in preterm infants. Pediatrics 2001;107(4):719-727.

(32) Inder TE, Anderson NJ, Spencer C, Wells S, Volpe JJ. White matterinjury in the premature infant: A comparison between serial cranial

50

sonographic and MR findings at term. American Journal ofNeuroradiology 2003; 24(5):805-809.

(33) Laptook AR, O'Shea TM, Shankaran S, Bhaskar B, NICHDNeonatal Network. Adverse neurodevelopmental outcomes amongextremely low birth weight infants witha normal head ultrasound:Prevalence and antecedents. Pediatrics 2005; 115:673-680.

(34) Ment LR, Bada HS, Barnes P, Grant PE, Hirtz D, Papile LA et al.Practice parameter: Neuroimaging of the neonate - Report of theQuality Standards Subcommittee of the American Academy ofNeurology and the Practice Committee of the Child NeurologySociety. Neurology 2002; 58(12):1726-1738.

(35) O'Shea TM, Counsell SJ, Bartels DB, Dammann O. Magneticresonance and ultrasound brain imaging in preterm infants. EarlyHuman Development 2005; 81(3):263-271.

(36) Mattia FR, deRegnier RA. Chronic physiologic instability isassociated with neurodevelopmental morbidity at one and two yearsin extremely premature infants. Pediatrics 1998; 102(3):E35.

(37) Broitman E, Namasivayam A, Higgins RD, Vohr BR, Das A, BhaskarB et al. Clinical data predict neurodevelopmental outcome betterthan head ultrasound in extremely low birth weight infants. J Pediatr2007; 151(5):500-505.

(38) O'Shea TM, Kuban KCK, Allred EN, Paneth N, Pagano M,Dammann O et al. Neonatal cranial ultrasound lesions anddevelopmental delays at 2 years of age among extremely lowgestational age children. Pediatrics 2008; 122(3):E662-E669.

(39) Fox NA, Porges SW. The Relation Between Neonatal Heart PeriodPatterns and Developmental Outcome. Child Development 1985;56(1):28-37.

(40) DoussardRoosevelt JA, Porges SW, Scanlon JW, Alemi B, ScanlonKB. Vagal regulation of heart rate in the prediction of developmentaloutcome for very low birth weight preterm infants. ChildDevelopment 1997; 68(2):173-186.

(41) Doussard-Roosevelt JA, McClenny BD, Porges SW. Neonatalcardiac vagal tone and school-age developmental outcome in verylow birth weight infants. Developmental Psychobiology 2001;38(1):56-66.

51

(42) Cummins SK, Nelson KB, Grether JK, Velie EM. Cerebral palsy infour northern California counties, births 1983 through 1985. JPediatr 1993; 123(2):230-237.

(43) Nelson KB, Ellenberg JH. Children who "outgrew" cerebral palsy.Pediatrics 1982; 69:529-536.

(44) O'Shea TM, Goldstein DJ. Follow-up data - Their use in evidence-based decision-making. Clinics in Perinatology 2003; 30(2):217-250.

(45) Hintz SR, Kendrick DE, Stoll BJ, Vohr BR, Fanaroff AA, DonovanEF et al. Neurodevelopmental and growth outcomes of extremelylow birth weight infants after necrotizing enterocolitis. Pediatrics2005; 115(3):696-703.

(46) Ehrenkranz RA, Walsh MC, Vohr BR, Jobe AH, Wright LL, FanaroffAA et al. Validation of the National Institutes of Health consensusdefinition of bronchopulmonary dysplasia. Pediatrics 2005;116(6):1353-1360.

(47) Dammann O, O'Shea TM. Cytokines and Perinatal Brain Damage.Clinics in Perinatology 2008; 35(4):643-663.

(48) Spittle AJ, Orton J, Doyle LW, Boyd R. Early developmentalintervention programs post hospital discharge to prevent motor andcognitive impairments in preterm infants. Cochrane Database ofSystematic Reviews 2007;(2).

52

CHAPTER 3: DISCUSSION

Project Summary

In this study we evaluated associations between the cumulative heart rate

characteristics (cHRC) score, measured during the neonatal hospital stay, and

neurodevelopmental outcome in very low birth weight (VLBW) infants at 12 to 18

months adjusted age. The cHRC score is a measure of the burden of illness for

the entire hospital stay calculated using heart rate characteristics including heart

rate variability, decelerations, and accelerations (1). Previous studies have

shown that these characteristics are altered prior to sepsis and the systemic

inflammatory response syndrome (SIRS) and are predictive of in-hospital

mortality within 7 days (1-5).

The total number of infants studied was 65, with a mean birth weight of 792

grams and mean gestational age of 26 weeks. The follow-up data was obtained

at 12 months (58 patients) or 18 months (7 patients). 10 patients (16%) were

diagnosed with cerebral palsy (CP), 11 patients (17%) were diagnosed with

mental delay by the BSID-II Mental Development Index (MDI), 27 patients (42%)

were diagnosed with motor delay by the BSID-II Psychomotor Developmental

Index (PDI). 16 infants (25%) with either CP or MDI <70 were included in a

composite outcome called neurodevelopmental impairment (NDI).

Using multivariable logistic analysis we found statistically significant

associations between increasing cHRC scores and increasing risk for CP, MDI

53

<70, and NDI. These associations remained significant even when adjusted for

abnormal head ultrasound results and chronic lung disease. There was a trend

towards an association between cHRC and PDI < 70, but this did not reach

statistical significant using an α-value <0.05.

Limitations

There were several important limitations to this study. This is a

retrospective analysis of a small sample of high-risk patients. Our rate of cerebral

palsy was approximately three times higher than the incidence generally seen in

a cohort of VLBW infants (6,7). We attribute this relatively high incidence

primarily to the fact that the Wake Forest University NICU is a referral only center

and therefore has a high proportion of critically ill infants. Although the child

psychologists who performed the BSID-II tests were blinded to the patient’s

medical history prior to the test, the physicians performing the standardized

neurological examination were not blinded and were aware of the child’s medical

history at the time of the exam. If the examining physician suspected that a

difficult hospital course might lead to worse neurological outcomes then this

could have led to ascertainment bias.

We chose to use the 12 to 18 month neurodevelopmental exam as our

developmental measure in an attempt to minimize selection bias. During the

time of this study, all VLBW infants cared for at Wake Forest University (WFU),

regardless of hospital course or developmental status, qualified for high-risk

follow-up for up to 18 months. Beyond this period only those infants with

54

developmental delay or at especially high risk for developmental delay, such as

BW < 1000 grams, would normally be seen. Nonetheless, 12 to 18 month exams

are limited in their ability to identify CP and cognitive delay and might have

resulted in misclassification.

Research Implications

The results of this study have several important implications. If the findings

of this small study can be replicated in a larger cohort study, then the utility of the

cHRC score is potentially large. It is a measure of the burden of illness and is

continually and automatically being calculated by a computer. In conjunction with

other predictors of developmental delay, it might be able to more accurately

identify those infants most at risk for adverse outcome. These infants can then

be targeted for closer follow-up and therapy. At this time we can only speculate

on what is the actual etiology and pathogenesis of cerebral palsy. We know of

many risk factors but the true cause appears to be complex and multi-factorial,

making it difficult to develop therapies to prevent CP. Nonetheless, several

recent studies have shown promise. Schmidt et al evaluated the long-term

effects of caffeine therapy and discovered infants treated with caffeine had a

significantly lower risk for cerebral palsy at 18 to 21 months than infants treated

with placebo (8). Approximately half of this protective effect was thought to be

due to a shorter duration of positive pressure ventilation in those infants given

caffeine, but the explanation for the remainder of the protective effect is still

55

unknown. Another study has evaluated the impact on neonatal developmental

outcome of giving expectant mothers of fetuses at risk for delivery between 24

and 31 weeks gestation a dose of magnesium sulfate just prior to delivery. The

infants in the magnesium sulfate group had a significantly lower risk for moderate

to severe cerebral palsy at 2 years of age compared to the placebo group (9).

The reason for this effect is still unknown, but is thought to work through

reduction of vascular instability to prevent hypoxic damage. As our knowledge

continues to grow and more preventive therapies are discovered, the cHRC

score may be able to help identify those infants most likely to develop CP and

those that will most benefit from these new therapies.

Currently the primary utility of heart rate characteristics is their ability to

identify infants with sepsis or SIRS. The earlier an infection can be identified, the

earlier antibiotics can be started, hopefully with improved outcomes. The clinical

utility of continuous monitoring of HRCs is currently under study in a randomized

clinical control trial (ClinicalTrials.gov Identifier: NCT00307333). This study will

also be able to prospectively study the relationship between HRCs and

neurodevelopmental outcome. A prospective study will also be able to determine

if the cHRC is the best summary score to use in relation to neurodevelopmental

outcome. The cHRC is a composite index in which the demographic index is

subtracted from the HRC index. This eliminates gestational age and birthweight

from the cHRC score. Lower gestation and birthweight are both associated with

a higher risk for neurodevelopmental impairment. Other summary measures,

such as the mean or median HRC index, in addition to the cHRC, can be

56

evaluated and compared in a prospective study. New measures based on the

HRC index can also be developed, such as adding the demographic index and

the HRC index together in order to include birthweight and gestation within the

summary score. These other summary measures may more accurately predict

the infant’s risk for neurodevelopmental impairment.

The mechanism by which sepsis leads to decrease in heart rate variability

and transient decelerations is unknown. One possibility is that hypoxia, which

can result from sepsis-induced apnea, causes decelerations, as occurs with

apnea of prematurity (AOP). Although this may be the mechanism of action for

the large decreases in heart rate seen during an apneic event, the transient

decelerations seen during illness are less pronounced and do not appear to be

associated with clinical hypoxic events. Another possibility is that circulating

cytokines interfere with normal signal transduction in the pacemaker cells of the

sinus node. Future studies will need to correlate cytokine levels with changes in

heart rate variability. In addition, research is needed to investigate whether other

conditions, such as chronic lung disease (CLD) or necrotizing enterocolitis (NEC)

can be detected using HRCs. Both of these conditions are thought to be

associated with elevated inflammatory mediators.

Future Directions

Currently I am neonatologist in private practice. At this time, I am unlikely to

remain involved with further researching the utility of the HRC index score. In

today’s environment of rapidly progressing healthcare, future research for me will

57

primarily involve quality improvement studies within the hospital so I can give the

best care possible to my patients.

58

REFERENCES

1) Griffin MP. O’Shea TM. Bissonette EA. Harrel FE. et al. Abnormal heartrate characteristics are associated with neonatal mortality. Pediatr Res.2004; 55(5):782-788

2) Griffin MP. Moorman JR. Toward the early diagnosis of neonatal sepsisand sepsis-like illness using novel heart rate analysis. Pediatrics.2001;107:97-104

3) Griffin MP. O’Shea TM. Bissonette EA. Harrel FE. et al. Abnormal heartrate characteristics preceding neonatal sepsis and sepsis-like illness.Pediatr Res. 2003;53(6):920-926

4) Griffin MP. Lake DE. Moorman JR. Heart Rate Characterisitics andLaboratory Tests in Neonatal Sepsis. Pediatrics. 2005;115:937-941

5) Griffin MP. Lake DE. O’Shea TM. Moorman JR. Heart rate characteristicsand clinical signs in neonatal sepsis. Pediatr Res. 2007;61(2):222-227

6) O’Shea TM. Preisser JS. Klinepeter KL. Dillard RG. Trends in mortalityand cerebral palsy in a geographically based cohort of very low birth weightneonates born between 1982 and 1994. Pediatrics. 1998;101:642-647

7) Winter S. Autry A. Boyle C. Allsopp MY. Trends in the prevalence ofcerebral palsy in a population-based study. Pediatrics. 2002;110:1220-1225

8) Schmidt B. Roberts RS. Davis P. et al. Long-term effects of Caffeinetherapy for apnea of prematurity. N Engl J Med. 2007;357(19):1893-1902

9) Rouse DJ. Hirtz DG. Thom E. et al. A randomized, controlled trial ofmagnesium sulfate for the prevention of cerebral palsy. N Engl J Med.2008;359(9):895-905

59

CURRICULUM VITAE

NAME: Kevin C. Addison

CURRENT TITLE: Neonatologist, Full Time-Staff

ADDRESS: Residence: 21434 Country Club Dr.Cornelius, NC 28031

Residence phone number: (704) 987-5066Mobile phone number: (704) 838-6527

Office: Lake Norman Regional Medical CenterDepartment of Neonatology171 Fairview RoadMooresville, NC 28117

Office phone number: (704) 660-4396Fax: (704) 660-4399E-mail: Kevin.Addison@hma.com

PERSONAL INFORMATION: Date of Birth: 06/22/73Birthplace: Framingham, MACitizenship: U.S.A. Marital Status: Single

EDUCATION: 2004 - Present Wake Forest University School of

Public Health; M.S., ClinicalEpidemiology and Health SciencesResearch

1996 – 2000 Saint Louis University School ofMedicine; M.D.

1991 - 1995 University of California, San Diego; B.S., General Biology

PROFESSIONAL EXPERIENCE:07/01/06 – Present Full Time Staff Neonatologist @

Lake Norman Regional MedicalCenter

07/01/03 – 06/30/06 Neonatal-Perinatal Fellowship;Wake Forest University Schoolof Medicine

07/01/00 - 06/30/03 Pediatric Residency; University of Texas, Houston

60

PROFESSIONAL LICENSURE:2006 - Present North Carolina State Medical

License

SPECIALTY CERTIFICATION:October 2003 American Board of PediatricsOctober 2008 Neonatal-Perinatal Medicine

PROFESSIONAL AFFILIATIONS: American Academy of Pediatrics

HONORS AND AWARDS: Distinction in Research, Saint Louis University School of Medicine; 2000

PUBLICATIONS:Campana W.M. Masao H. Addison K.C. O’Brien J.S. Induction of MAPKphosphorylation by prosaposin and prosaptide in PC12 cells. BiochemBiophys Res Comm. 1996;229:706-712

CLINICAL INTERESTS:My current areas of interest are the effects of sepsis onneurodevelopmental outcome and the care and follow-up of late preterminfants