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the bmj | BMJ 2020;370:m3320 | doi: 10.1136/bmj.m3320 1
RESEARCH
Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysisJohn Allotey,1,2 Elena Stallings,3,4 Mercedes Bonet,5 Magnus Yap,6 Shaunak Chatterjee,6 Tania Kew,6 Luke Debenham,6 Anna Clavé Llavall,6 Anushka Dixit,6 Dengyi Zhou,6 Rishab Balaji,6 Siang Ing Lee,1 Xiu Qiu,7,8,9 Mingyang Yuan,1,7 Dyuti Coomar,1 Madelon van Wely,10 Elizabeth van Leeuwen,11 Elena Kostova,10 Heinke Kunst,12,13 Asma Khalil,14 Simon Tiberi,12,13 Vanessa Brizuela,5 Nathalie Broutet,5 Edna Kara,3 Caron Rahn Kim,5 Anna Thorson,5 Olufemi T Oladapo,5 Lynne Mofenson,15 Javier Zamora,3,4,16 Shakila Thangaratinam,2,17 for PregCOV-19 Living Systematic Review Consortium
AbstrActObjectiveTo determine the clinical manifestations, risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed coronavirus disease 2019 (covid-19).DesignLiving systematic review and meta-analysis.Data sOurcesMedline, Embase, Cochrane database, WHO COVID-19 database, China National Knowledge Infrastructure (CNKI), and Wanfang databases from 1 December 2019 to 26 June 2020, along with preprint servers, social media, and reference lists.stuDy selectiOnCohort studies reporting the rates, clinical manifestations (symptoms, laboratory and radiological findings), risk factors, and maternal and perinatal outcomes in pregnant and recently pregnant women with suspected or confirmed covid-19.Data extractiOnAt least two researchers independently extracted the data and assessed study quality. Random effects
meta-analysis was performed, with estimates pooled as odds ratios and proportions with 95% confidence intervals. All analyses will be updated regularly.results77 studies were included. Overall, 10% (95% confidence interval 7% to14%; 28 studies, 11 432 women) of pregnant and recently pregnant women attending or admitted to hospital for any reason were diagnosed as having suspected or confirmed covid-19. The most common clinical manifestations of covid-19 in pregnancy were fever (40%) and cough (39%). Compared with non-pregnant women of reproductive age, pregnant and recently pregnant women with covid-19 were less likely to report symptoms of fever (odds ratio 0.43, 95% confidence interval 0.22 to 0.85; I2=74%; 5 studies; 80 521 women) and myalgia (0.48, 0.45 to 0.51; I2=0%; 3 studies; 80 409 women) and were more likely to need admission to an intensive care unit (1.62, 1.33 to 1.96; I2=0%) and invasive ventilation (1.88, 1.36 to 2.60; I2=0%; 4 studies, 91 606 women). 73 pregnant women (0.1%, 26 studies, 11 580 women) with confirmed covid-19 died from any cause. Increased maternal age (1.78, 1.25 to 2.55; I2=9%; 4 studies; 1058 women), high body mass index (2.38, 1.67 to 3.39; I2=0%; 3 studies; 877 women), chronic hypertension (2.0, 1.14 to 3.48; I2=0%; 2 studies; 858 women), and pre-existing diabetes (2.51, 1.31 to 4.80; I2=12%; 2 studies; 858 women) were associated with severe covid-19 in pregnancy. Pre-existing maternal comorbidity was a risk factor for admission to an intensive care unit (4.21, 1.06 to 16.72; I2=0%; 2 studies; 320 women) and invasive ventilation (4.48, 1.40 to 14.37; I2=0%; 2 studies; 313 women). Spontaneous preterm birth rate was 6% (95% confidence interval 3% to 9%; I2=55%; 10 studies; 870 women) in women with covid-19. The odds of any preterm birth (3.01, 95% confidence interval 1.16 to 7.85; I2=1%; 2 studies; 339 women) was high in pregnant women with covid-19 compared with those without the disease. A quarter of all neonates born to mothers with covid-19 were admitted to the neonatal unit (25%) and were at increased risk of admission (odds ratio 3.13, 95% confidence interval 2.05 to 4.78, I2=not estimable; 1 study, 1121 neonates) than those born to mothers without covid-19.
For numbered affiliations see end of the article.Correspondence to: S Thangaratinam [email protected] (or @thangaratinam on Twitter: ORCID 0000-0002-4254-460X)Additional material is published online only. To view please visit the journal online.cite this as: BMJ2020;370:m3320http://dx.doi.org/10.1136/bmj.m3320
Accepted: 23 August 2020
WhAt is AlreAdy knoWn on this topicPregnant women are considered to be a high risk group for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and the potential adverse effects of the virus on maternal and perinatal outcomes are of concernIn non-pregnant populations admitted to hospital with coronavirus disease 2019 (covid-19) the most common symptoms are fever, cough, and dyspnoea, reported in more than two thirds of individualsAdvancing age, high body mass index, non-white ethnicity, and pre-existing comorbidities are risk factors for severe covid-19 in the general population
WhAt this study AddsPregnant and recently pregnant women with covid-19 diagnosed in hospital are less likely to manifest symptoms of fever and myalgia than non-pregnant women of reproductive age and might be at increased risk of admission to an intensive care unitRisk factors for severe covid-19 in pregnancy include increasing maternal age, high body mass index, and pre-existing comorbiditiesPregnant women with covid-19 are more likely to experience preterm birth and their neonates are more likely to be admitted to a neonatal unit
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cOnclusiOnPregnant and recently pregnant women are less likely to manifest covid-19 related symptoms of fever and myalgia than non-pregnant women of reproductive age and are potentially more likely to need intensive care treatment for covid-19. Pre-existing comorbidities, high maternal age, and high body mass index seem to be risk factors for severe covid-19. Preterm birth rates are high in pregnant women with covid-19 than in pregnant women without the disease.systematic review registratiOnPROSPERO CRD42020178076.reaDers’ nOteThis article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication.
introductionSince the first report (December 2019) of the novel coronavirus disease 2019 (covid-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the number of confirmed cases and associated mortality and morbidity have increased rapidly.1 2 Pregnant women are considered a high risk group because of concerns about the effect of covid-19 on them during and after pregnancy, and on their neonates.3 Quantification of the rates of covid-19, its risk factors, clinical manifestations, and outcomes is key to planning clinical maternal care and management in an evolving pandemic scenario.4
Publications on covid-19 in pregnancy have risen steeply through individual case reports, case series, observational studies, and systematic reviews. As of 26 June 2020, more than 86 reviews have been published in this area,5-10 with a further 94 registered in PROSPERO.8 11 The early reviews mostly included case reports and case series that were often inappropriately meta-analysed, leading to biased estimates.12 Subsequent reviews differed little from each other, often including similar primary studies, many with duplicate data. These reviews became quickly outdated as new evidence emerged. To date, no review has comprehensively evaluated the comparative data concerning pregnant and recently pregnant women and non-pregnant women with covid-19. Moreover, the sampling frames in primary studies have varied, ranging from universal SARS-CoV-2 testing for all pregnant women admitted to hospital13 14 to symptom based testing.15 16 Testing strategies have also differed within and between countries, with diagnosis in many early studies based on epidemiological risk assessment and clinical features without confirmed infection, which need to be considered in the analysis.17 Limitations in the external and internal validity of studies make it challenging for guideline developers and policy makers to make evidence based recommendations for the management of pregnant and recently pregnant women with covid-19.
We began a living systematic review to determine the clinical manifestations of covid-19 in pregnant and recently pregnant women, identify the risk factors for complications, and quantify maternal and perinatal outcomes. This systematic review will be updated on a regular basis.
MethodsOur systematic review is based on a prospectively registered protocol (PROSPERO CRD42020178076; registered 22 April 2020)18 to evaluate a series of research questions on covid-19 during and after pregnancy. We report our findings on the rates, clinical manifestations, risk factors, and maternal and perinatal outcomes in women with covid-19 in line with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) recommendations (see appendix 1). As more relevant data become available, we shall address the research questions in our published protocol. Each cycle of our living systematic review involves weekly search updates (rounds), with analysis performed every 2-4 weeks for our monthly reporting through a dedicated website, with early analysis if new definitive evidence emerges. We plan to regularly review the planned frequency of updates.
literature searchWe performed a systematic search of major databases: Medline, Embase, Cochrane database, WHO (World Health Organization) COVID-19 database, China National Knowledge Infrastructure (CNKI), and Wanfang databases from 1 December 2019 to 26 June 2020 for relevant studies on covid-19 in pregnant and recently pregnant women. To identify potential studies, we coordinated our search efforts with the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), the WHO Library, and the Cochrane Gynaecology and Fertility group. Additional searches were conducted of preprint servers, blogs, websites that serve as repositories for covid-19 studies, social media, guidelines, and reference lists of included studies and unpublished data. We also searched the Living Overview of the Evidence (LOVE) platform from 11 to 26 June 2020.19 We contacted established groups that were coordinating or conducting surveillance and studies in pregnant women with covid-19, such as the WHO Maternal, Newborn, Child and Adolescent health (MNCAH) covid-19 research network and the International Network of Obstetric Survey Systems (INOSS) for information on published and upcoming data. No language restrictions were applied. Appendix 2 provides details of the search strategies and databases searched.
study selectionTwo reviewers independently selected studies using a two stage process: they first screened the titles and abstracts of studies and then assessed the full text of the selected studies in detail for eligibility. A total of eight reviewers contributed to study selection.
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Disagreements were resolved through discussion with a third reviewer (ST or JA). We excluded studies if the duplicate data for all outcomes of interest were published elsewhere, as reported by the study authors, or when the characteristics of the mother or neonate matched the setting, characteristics, and duration of another study. When we suspected an overlap of data between studies, the study that provided comparative data was included. When there was uncertainty about duplicate data, we contacted the authors of primary studies.
We defined women as having confirmed covid-19 if they had laboratory confirmation of covid-19 infection irrespective of clinical signs and symptoms.20 Women with a diagnosis based only on clinical or radiological findings were defined as having suspected covid-19. The recently pregnant group comprised women in the postpartum and post-abortion period. We included studies that compared covid-19 rates, clinical manifestations (symptoms, laboratory and radiological results), risk factors, and associated mortality and morbidity between pregnant and recently pregnant and non-pregnant women of reproductive age, and those that compared maternal and perinatal outcomes in pregnant women with and without covid-19. Studies on non-comparative cohorts with a minimum of 10 participants were included if they reported on the rates and clinical manifestations of covid-19 and relevant outcomes in pregnant and recently pregnant women. We defined cohort studies as those that sampled participants on the basis of exposure, followed-up participants over time, and ascertained the outcomes.21 The PROSPERO protocol provides a full list of the risk factors, clinical features, and outcomes evaluated.18
The sampling frames for detecting covid-19 included universal screening and testing, when all women were assessed for covid-19 using reverse transcriptase polymerase chain reaction (RT-PCR) for SARS-CoV-2 or chest computed tomography; risk based testing on the basis of epidemiological history and clinical manifestations by National Health Commission of China (NHCC) guidelines17; and symptom based when testing was performed on women with symptoms and those with a history of contact with affected individuals. We defined the population as being selected when only specific groups of women were included, such as those undergoing caesarean section or in the third trimester. We categorised studies as a high risk group if only women with any pre-existing medical or obstetric risk factors were included, low risk if women did not have any risk factors, and any risk if all women were included.
study quality assessment and data extractionThe quality of the comparative cohort studies was assessed for selection, comparability, and outcome ascertainment bias using the Newcastle Ottawa scale.22 Studies achieving four stars for selection, two for comparability, and three for ascertainment of the outcome were considered to have a low risk of bias.
Studies achieving two or three stars for selection, one for comparability, and two for outcome ascertainment were considered to have a medium risk of bias, and any study achieving one star for selection or outcome ascertainment, or zero for any of the three domains, was regarded as having a high risk of bias. We assessed the quality of studies reporting on the prevalence of clinical manifestations or outcomes for internal and external validity using an existing tool.23 The following were considered as low risk of bias for external validity: representative of national population for relevant variables (population), representative of target population (sampling frame), random selection (selection bias), and more than 75% response rate in individuals with and without the outcome (non-response bias).23 Two indepen-dent reviewers extracted data using a pre-piloted form.
statistical analysisWe pooled the comparative dichotomous data using random effects meta-analysis and summarised the findings as odds ratios with 95% confidence intervals. To combine comparative continuous data with dichotomous data we transformed standardised mean differences to logarithm odds ratios, assuming a normal underlying distribution.24 We pooled the dichotomous non-comparative data for rates of clinical manifestations and maternal and perinatal outcomes as proportions with 95% confidence intervals using Dersimonian and Laird random effects meta-analysis after transforming data using Freeman-Tukey double arcsin transformation. Heterogeneity was reported as I2 statistics. We undertook subgroup analysis by country status (high versus low and middle income), sampling frame (universal, risk based, and symptom based testing, including not reported), and risk status of women in the studies (high, low, any). Sensitivity analysis was performed by restricting the analysis to women with confirmed covid-19, study quality (high, low), and population (unselected, selected). All analyses were done with Stata (version 16).
Patient and public involvementThe study was supported by Katie’s Team, a dedicated patients and public involvement group in Women’s Health. The team was involved in the conduct, interpretation, and reporting of this living systematic review through participation in virtual meetings.
resultsAfter removing duplicates from 49 684 citations, 20 625 unique citations were identified and 77 cohort studies (55 comparative, 22 non-comparative) were included in the systematic review (fig 1).
characteristics of included studiesOf the 77 studies, 26 (34%) were from the United States, 24 from China (31%), seven from Italy, six from Spain, three each from the United Kingdom and France, and one each from Belgium, Brazil, Denmark, Israel, Japan,
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Mexico, the Netherlands, and Portugal. All the studies tested respiratory samples using RT-PCR to confirm the presence of SARS-CoV-2; 23 studies additionally diagnosed covid-19 based on clinical suspicion. Eight studies (95 247 women) compared pregnant populations with non-pregnant populations,25-32 and four studies (2230 women) compared pregnant women with covid-19 versus pregnant women without covid-19.33-36 Forty cohort studies reported on clinical manifestations (13 018 pregnant, 85 084 non-pregnant women),25-32 35-66 45 studies reported on covid-19 related maternal outcomes (14 094 pregnant, 85 169 non-pregnant women),25-32 35-51 53-59 61-74 and 35 studies reported on pregnancy related maternal (6279 women) and perinatal outcomes (2557 neonates)13 25 27 29 30 32-41 43-47 49-50 54 55 57 59 61 62 64-67 69 70 75 (see appendix 3). The sampling frames included universal testing (29 studies), risk based NHCC guidelines (22 studies), and symptom based (19 studies) strategies. Eleven studies did not report the sampling strategy.
Quality of included studiesOverall, 67% (37/55) of the comparative cohort studies evaluated using the Newcastle Ottawa scale had an overall low risk of bias (see appendix 4a). Forty nine (89%) had a low risk of bias for study selection and six (11%) had a medium risk. The risk of bias for comparability of cohorts was low in nine of the studies (16%), medium in 45 (82%), and high in one (2%). For outcome assessment of the cohorts, 12 (22%) studies had a low risk of bias, 42 (76%) a medium risk, and one (2%) a high risk. Quality assessment of the prevalence studies for external validity showed a low risk of bias for representativeness in 13% (10/76) of the studies, sampling in 26% (20/76), selection in 74% (56/76), and non-response in 96% (73/76). For internal validity, there was low risk of bias for data collection in 95% (72/76) of the studies, case definition in 36% (27/76), measurement in 99% (75/76), differential verification in 86% (65/76), adequate follow-up in 22% (17/76), and appropriate numerator and denominator in 83% (63/76) (see appendix 4b).
Articles excludedIrrelevant articlesDuplicates
19 46029 059
Full text articles assessed for eligibility
Citations identified
1165
49 684
48 519
Articles excludedInappropriate populationInappropriate study designDuplicate publicationInappropriate outcomeInappropriate exposureArticle not found
457452125
3518
1
Electronic databases from inception to 26 June 2020Other sources* and reference lists
49 538146
Studies included (13 118 pregnant and recently pregnant women with covid-19;83 486 non-pregnant women of reproductive age with covid-19)
Prevalence of covid-19Risk factors for covid-19 and complicationsClinical manifestations of covid-19Covid-19 related outcomesPregnancy related maternal and perinatal outcomes
2652404535
1088
77
Fig 1 | study selection process. *twitter, national reports, blog by j thornton, Obg Project, cOviD-19 and Pregnancy cases, www.obgproject.com/2020/04/07/covid-19-research-watch-with-dr-jim-thornton/ (accessed 12 may 2020); ePPi-centre, cOviD-19: a living systematic map of evidence, http://eppi.ioe.ac.uk/cms/Projects/DepartmentofHealthandsocialcare/Publishedreviews/cOviD-19livingsystematicmapoftheevidence/tabid/3765/Default.aspx (accessed 12 may 2020); norwegian institute of Public Health, niPH systematic and living map on cOviD-19 evidence, www.nornesk.no/forskningskart/niPH_mainmap.html (accessed 19 may 2020); johns Hopkins university center for Humanitarian Health; cOviD-19, maternal and child Health, nutrition, http://hopkinshumanitarianhealth.org/empower/advocacy/covid-19/covid-19-children-and-nutrition/ (accessed 2 june 2020); researchgate, cOviD-19 research community, www.researchgate.net/community/cOviD-19 (accessed 2 june 2020); and living Overview of the evidence, coronavirus disease (cOviD-19), https://app.iloveevidence.com/loves/5e6fdb9669c00e4ac072701d?population=5d062d5fc80dd41e58ba8459 (accessed 16 june 2020)
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rates of covid-19 in pregnant and recently pregnant womenThe overall rate of covid-19 diagnosis in pregnant and recently pregnant women attending or admitted to hospital for any reason was 10% (95% confidence interval 7% to 14%; 26 studies, 11 432 women; fig 2). Rates varied by sampling strategy: of the women sampled by universal screening, 7% (4% to 10%; 18 studies, 6247 women) were diagnosed as having covid-19 compared with 18% (10% to 28%; 8 studies, 4928 women) of women sampled on the basis of symptoms. All studies with a prevalence rate for covid-19 greater than 15% were from the US, except for one study, which was from France.76 One in 20 asymptomatic mothers (5%, 2% to 9%; 11 studies)
attending or admitted to hospital had a diagnosis of covid-19 (see appendix 5a). Three quarters (74%, 51% to 93%; 11 studies) of the 162 pregnant women with covid-19 in the universal screening population were asymptomatic (see appendix 5b). Based on data from a small number of studies, a diagnosis of covid-19 in pregnancy was associated with maternal obesity (odds ratio 1.75, 95% confidence interval 1.34 to 2.30; 1 study, 1080 women), pre-existing comorbidities (1.64, 1.25 to 2.13; 1 study, 1121 women), asthma (1.71, 1.03 to 2.84; 2 studies, 1250 women), history of covid-19 in the support person (44.56, 14.90 to 133.28; 1 study, 199 women), and gestational diabetes (2.42, 1.55 to 3.79; 1 study, 1121 women) (see appendix 6a).
Universal screening
Sutton 2020
Vintzileos 2020
Tassis 2020
Khalil 2020
Gagliardi 2020
Naqvi 2020
Ceulemans 2020
Miller 2020
Doria 2020
London 2020
Bianco 2020
Goldfarb 2020
LaCourse 2020
Ochiai 2020
Freiesleben 2020
Cosma 2020
Crovetto 2020
Emeruwa 2020
Subtotal: P=0.00; I2=95.1%
Symptom based screening
Blitz 2020
Campbell 2020
Fox 2020
Qadri 2020
Duffy 2020
London 2020
LaCourse 2020
Griffin 2020
Subtotal: P=0.00; I2=97.9%
Not known
Cohen
Overall: I2=96.99%, P=0.00;
estimated predictive interval
0.15 (0.11 to 0.21)
0.20 (0.14 to 0.27)
0.02 (0.01 to 0.06)
0.07 (0.04 to 0.13)
0.01 (0.00 to 0.02)
0.01 (0.00 to 0.07)
0.03 (0.02 to 0.05)
0.04 (0.02 to 0.05)
0.12 (0.07 to 0.19)
0.13 (0.07 to 0.23)
0.15 (0.10 to 0.22)
0.03 (0.02 to 0.04)
0.03 (0.01 to 0.06)
0.04 (0.01 to 0.13)
0.03 (0.02 to 0.04)
0.10 (0.07 to 0.15)
0.14 (0.12 to 0.17)
0.18 (0.14 to 0.22)
0.07 (0.04 to 0.10)
0.03 (0.02 to 0.03)
0.04 (0.03 to 0.06)
0.04 (0.03 to 0.06)
0.08 (0.05 to 0.13)
0.41 (0.26 to 0.57)
0.72 (0.61 to 0.80)
0.19 (0.10 to 0.33)
0.33 (0.24 to 0.44)
0.18 (0.10 to 0.28)
0.45 (0.39 to 0.52)
0.10 (0.07 to 0.14);
(0.00 to 0.35)0 0.803
Study Rate(95% CI)
Rate(95% CI)
1
1
2
2
3
3
3
3
3
3
3
4
4
4
5
5
5
5
2
3
3
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Round
33/215
32/161
3/139
9/129
3/533
1/82
13/470
23/635
12/103
10/75
24/158
20/757
5/188
2/52
30/1055
23/225
125/874
71/396
82/2971
30/770
33/757
16/192
15/37
58/81
8/42
26/78
88/194
Events/No in group
Fig 2 | Prevalence of severe acute respiratory syndrome coronavirus 2 in pregnant and recently pregnant women identified by various sampling strategies. meta-analysis includes one study (liao 2020) screened using national Health commission china criteria with no events. symptom based screening includes screening based on symptoms or history of contact with individuals with covid-19. round number represents search strategy updates in the living systematic review
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clinical manifestations of covid-19 during pregnancy and after deliveryThe most common symptoms reported by pregnant and recently pregnant women with suspected or confirmed covid-19 were fever (40%) and cough (39%); lymphopaenia (35%) and raised C reactive protein levels (49%) were the most common laboratory findings (fig 3). Compared with non-pregnant women of reproductive age with covid-19, pregnant and recently pregnant women with the disease were less likely to manifest symptoms of fever (0.43, 0.22 to 0.85; 5 studies, 80 521 women) and myalgia (0.48, 0.45 to 0.51; 3 studies, 80 409 women) (fig 4). A history of pre-existing diabetes was more often observed in pregnant women with covid-19 than in non-pregnant women with the disease (1.78, 1.03 to 3.05; 3 studies, 91 595 women) (see appendix 6b). Sensitivity analysis restricted to various sampling frames showed lower estimates of fever, cough, and dyspnoea in the universal screening population and higher estimates in the symptom based population (see appendix 7). The rates of clinical manifestations were similar to the overall estimates when the analysis was restricted to only women with RT-PCR confirmed covid-19, unselected populations, and women with any risk (see appendix 7).
Outcomes related to covid-19 in pregnant and recently pregnant womenOverall, 73 pregnant women (26 studies, 11 580 women) with confirmed covid-19 died from any cause (0.1%, 95% confidence interval 0.0% to 0.7%). Severe covid-19 was diagnosed in 13% (6% to 21%; 21 studies, 2271 women) of pregnant and recently pregnant women with suspected or confirmed covid-19; 4% (2% to 7%; 17 studies, 10 901 women) of the pregnant women with covid-19 were admitted to an intensive care unit, 3% (1% to 5%; 13 studies, 10 713 women) required invasive ventilation, and 0.4% (0.1% to 0.9%; 9 studies, 1935 women) required extracorporeal membrane oxygenation (fig 3). Appendix 8 provides the rates of complications by sampling strategy. Compared with non-pregnant women of reproductive age with covid-19, the odds of admission to the intensive care unit (1.62, 95% confidence interval 1.33 to 1.96) and need for invasive ventilation (1.88, 1.36 to 2.60) were higher in pregnant and recently pregnant women (four studies, 91 606 women) (table 1). Maternal risk factors associated with severe covid-19 were increasing age (1.78, 1.25 to 2.55; 4 studies, 1058 women), high body mass index (2.38, 1.67 to 3.39; 3 studies, 877 women), chronic hypertension (2.0, 1.14 to 3.48; 2 studies, 858 women), and pre-existing diabetes (2.51, 1.31 to 4.80; 2 studies, 858 women) (fig 5). Pre-existing maternal comorbidity was associated with admission to an intensive care unit (4.21, 1.06 to 16.72; 2 studies, 320 women) and the need for invasive ventilation (4.48, 1.40 to 14.37; 2 studies, 313 women) (table 2).
maternal and perinatal outcomes in pregnant and recently pregnant women with covid-19In pregnant and recently pregnant women with covid-19 the rate of overall preterm birth was 17% (95% confidence interval 13% to 21%; 30 studies, 1872 women) and of spontaneous preterm birth was 6% (3% to 9%; 10 studies, 870 women) (fig 3). In pregnant and recently pregnant women with covid-19 compared with pregnant and recently pregnant women without the disease, the odds of any preterm birth (3.0, 95% confidence interval 1.15 to 7.85; 2 studies, 339 women) were higher, but no differences were observed in other maternal outcomes (table 1). Eighteen stillbirths (27 studies; 2837 offspring) and six neonatal deaths (26 studies; 1728 neonates) occurred among pregnant and recently pregnant women with covid-19, resulting in negligible risks (fig 3). Overall, 25% (95% confidence interval 14% to 37%; 17 studies, 1348 women) of neonates born to women with covid-19 were admitted to the neonatal unit (fig 3), with a higher risk of admission (odds ratio 3.13, 95% confidence interval 2.05 to 4.78; 1 study, 1121 neonates) than those born to mothers without the disease in one study with historical controls. No differences were observed for other perinatal outcomes. Appendix 9 provides the rates of covid-19 related and pregnancy related outcomes for the individual studies.
discussionIn this living systematic review, we found that one in 10 pregnant or recently pregnant women who are attending or admitted to hospital for any reason are diagnosed as having suspected or confirmed covid-19, although the rates vary by sampling strategy. The covid-19 related symptoms of fever and myalgia manifest less often in pregnant and recently pregnant women than in non-pregnant women of reproductive age. Whereas testing for SARS-CoV-2 in non-pregnant women is based on symptoms or contact history, testing in pregnant women is usually done when they are in hospital for reasons that might not be related to covid-19. Pregnant or recently pregnant women with covid-19 seem to be at increased risk of requiring admission to an intensive care unit or invasive ventilation. Increased maternal age, high body mass index, and pre-existing comorbidities might be associated with severe disease. Pregnant women with covid-19 are at increased risk of delivering preterm and their babies being admitted to the neonatal unit. But overall rates of spontaneous preterm births are not high. Stillbirth and neonatal death rates are low in women with suspected or confirmed covid-19. All comparative findings are based on small numbers of studies, despite the large sample sizes. Substantial heterogeneity was observed in the estimates for rates of clinical manifestations and outcomes, which varied by sampling frames, participant selection, and risk status of the participants.
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strengths and limitations of this reviewIn this unprecedented pandemic situation, where evidence is rapidly produced and published in various formats, our living systematic review underpinned by robust methods and continually updated at regular intervals is relevant for several reasons. Firstly, it
addresses important research questions relevant to clinical decision making and policies. Secondly, uncertainties remain for key outcomes that require further evidence. Thirdly, the rapid turnover of evidence in various formats requires assessments of study quality and regular updating of the findings.
Clinical manifestations
Symptoms
Fever
Cough
Dyspnoea
Myalgia
Ageusia
Diarrhoea
Laboratory findings
Raised white cell count
Lymphopaenia
Thrombocytopaenia
Abnormal liver function test results
Raised procalcitonin level
Raised C reactive protein level
Radiological findings
Ground glass appearance
Any abnormality on computed tomography
Maternal and perinatal outcomes
Covid related outcomes
All cause mortality
Admission to intensive care unit
Severe covid-19
Invasive ventilation
ECMO
Oxygen, cannula
ARDS
Pneumonia
Cardiac, liver, renal failure
Pregnancy related outcomes
Preterm birth <37 weeks
Spontaneous preterm birth
PPROM <37 weeks
Caesarean section
Vaginal delivery
Postpartum haemorrhage
Offspring outcomes
Stillbirth
Neonatal death
Admission to neonatal unit
Neonatal sepsis
Abnormal Apgar score
Fetal distress
(0.11-0.73)
(0.03-0.81)
(0.00-0.62)
(0.00-0.25)
(0.03-0.28)
(0.00-0.18)
(0.03-0.52)
(0.09-0.90)
(0.01-0.35)
(0.00-0.29)
(0.00-0.97)
(0.23-0.71)
(0.09-1.00)
(0.02-1.00)
(0.00-0.07)
(0.00-0.13)
(0.00-1.00)
(0.00-0.09)
(0.00-0.01)
(0.02-1.00)
(0.00-0.51)
(0.00-1.00)
(0.00-0.13)
(0.00-0.59)
(0.02-0.31)
(0.03-0.17)
(0.33-1.00)
(0.00-0.67)
(0.01-0.09)
(0.00-0.02)
(0.00-0.01)
(0.00-1.00)
(0.03-0.06)
(0.00-0.06)
(0.04-0.15)
Study Proportion(95% CI)
Range
97.4 (0.00)
96.8 (0.00)
96.2 (0.00)
90.7 (0.00)
93.6 (0.00)
65.5 (0.00)
92.3 (0.00)
85.6 (0.00)
85.3 (0.00)
74.1 (0.00)
96.6 (0.00)
86.2 (0.00)
96.5 (0.00)
98.4 (0.00)
80.2 (0.00)
93.6 (0.00)
95.5 (0.00)
93.5 (0.00)
0.0 (0.93)
97.1 (0.00)
98.7 (0.00)
97.9 (0.00)
10.6 (0.35)
71.5 (0.00)
55.0 (0.02)
0.0 (0.66)
91.3 (0.00)
91.4 (0.00)
45.6 (0.14)
0.0 (1.00)
0.0 (1.00)
94.9 (0.00)
Not estimable
0.0 (0.64)
0.0 (0.74)
I2 (%)(P value)
0.40 (0.31 to 0.49)
0.39 (0.31 to 0.47)
0.19 (0.13 to 0.26)
0.10 (0.05 to 0.17)
0.15 (0.00 to 0.41)
0.07 (0.05 to 0.09)
0.27 (0.09 to 0.51)
0.35 (0.26 to 0.45)
0.08 (0.02 to 0.18)
0.11 (0.05 to 0.18)
0.21 (0.00 to 0.59)
0.49 (0.36 to 0.63)
0.69 (0.41 to 0.91)
0.65 (0.46 to 0.82)
0.00 (0.00 to 0.01)
0.04 (0.02 to 0.07)
0.13 (0.06 to 0.21)
0.03 (0.01 to 0.05)
0.00 (0.00 to 0.01)
0.30 (0.14 to 0.48)
0.09 (0.00 to 0.33)
0.49 (0.35 to 0.63)
0.00 (0.00 to 0.01)
0.17 (0.13 to 0.21)
0.06 (0.03 to 0.09)
0.05 (0.03 to 0.08)
0.65 (0.57 to 0.73)
0.35 (0.27 to 0.43)
0.03 (0.00 to 0.08)
0.00 (0.00 to 0.00)
0.00 (0.00 to 0.00)
0.25 (0.14 to 0.37)
0.04 (0.00 to 0.12)
0.01 (0.00 to 0.02)
0.08 (0.05 to 0.12)
Proportion(95% CI)
29
28
22
9
3
17
6
15
7
9
5
7
10
20
26
17
21
13
9
13
6
23
7
30
10
8
28
27
5
27
26
17
2
14
7
Studies
2733/8328
3432/8317
1928/8159
1411/6078
24/310
659/7525
50/251
262/780
36/428
51/491
60/261
174/426
246/387
599/1968
73/11 580
323/10 901
417/2271
155/10 713
16/1935
243/1281
270/1006
729/2577
7/737
386/1872
56/870
28/436
1060/1933
856/1916
13/250
18/2837
6/1728
368/1348
2/51
11/500
25/293
Events/No in group
0 0.2 0.4 0.6 0.8 1.0
Fig 3 | rates of clinical manifestations of coronavirus disease (covid-19) in pregnant women and recently pregnant women with suspected or confirmed covid-19 and associated maternal and perinatal outcomes. ecmO=extracorporeal membrane oxygenation; arDs=acute respiratory distress syndrome; PPrOm=preterm premature rupture of membranes
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Finally, our living systematic review will produce a strong evidence base for living guidelines on covid-19 and pregnancy.
We undertook a comprehensive search and coordi-nated our efforts with key organisations and research groups, such as WHO, the Cochrane Centre, and EPPI-Centre. To minimise risk of bias we restricted our meta-analysis to cohort studies, and we reported the quality of the included studies. By contacting the authors and obtaining reports not published in PubMed, we minimised the risk of missing relevant studies. Our systematic review has a large sample size and it is continuously increasing. Our living meta-analyses framework will enable us to rapidly update the findings as new data emerge. We undertook extensive work to ensure that duplicate data are not included. Our various
comparative analyses allowed us to comprehensively assess the association between pregnancy and covid-19 related outcomes, covid-19 and pregnancy outcomes, risk factors for SARS-CoV-2 infection, and complications. Our review helps to understand the variations in estimates through sensitivity analyses by sampling strategies, population characteristics, and risk factors, and it provides confidence in the rates of reported outcomes.
Our systematic review also has limitations. The primary studies used varied sampling frames to identify women with covid-19, comprised women with suspected and confirmed covid-19, and primarily reported on pregnant women who required visits to hospital, including for childbirth, thereby affecting the generalisability of the estimates. Although our
Any symptom
Cheng 2020
Wei 2020
Wang 2020
Ellington 2020
Subtotal: I2=80.3%
Fever
Liu 2020
Yin 2020
Cheng 2020
Wang 2020
Ellington 2020
Subtotal: I2=73.9%
Cough
Liu 2020
Yin 2020
Cheng 2020
Wang 2020
Ellington 2020
Subtotal: I2=67.6%
Dyspnoea
Liu 2020
Yin 2020
Cheng 2020
Wang 2020
Ellington 2020
Subtotal: I2=36.0%
Myalgia
Yin 2020
Cheng 2020
Ellington 2020
Subtotal: I2=73.9%
0.16 (0.05 to 0.54)
0.62 (0.08 to 4.92)
0.03 (0.00 to 0.56)
1.07 (0.91 to 1.26)
0.33 (0.08 to 1.41)
0.22 (0.06 to 0.85)
0.20 (0.06 to 0.66)
0.59 (0.26 to 1.37)
0.29 (0.11 to 0.77)
0.87 (0.82 to 0.93)
0.43 (0.22 to 0.85)
0.55 (0.15 to 2.05)
1.11 (0.42 to 2.93)
0.55 (0.24 to 1.27)
0.20 (0.06 to 0.62)
1.10 (1.04 to 1.17)
0.67 (0.37 to 1.23)
0.90 (0.05 to 15.47)
1.00 (0.33 to 3.03)
0.32 (0.11 to 0.92)
0.39 (0.04 to 3.72)
1.12 (1.05 to 1.20)
0.82 (0.47 to 1.43)
0.52 (0.12 to 2.27)
0.30 (0.04 to 2.50)
0.48 (0.45 to 0.51)
0.48 (0.45 to 0.51)
Symptoms Odds ratio(95% CI)
22/31
15/17
22/30
5199/5355
5258/5433
8/21
17/31
15/31
11/30
1190/5355
1241/5468
6/21
15/31
14/31
5/30
1799/5355
1839/5468
1/21
8/31
5/31
1/27
1045/5355
1060/5465
3/31
1/31
1323/8207
1327/8269
No of pregnantwomen with covid-19/
No in group
75/80
24/26
42/42
72 549/74 877
72 690/75 025
14/19
30/35
49/80
28/42
18 474/74 877
18 595/75 053
8/19
16/35
48/80
21/42
23 554/74 877
23 647/75 053
1/19
9/35
30/80
4/45
13 292/74 877
13 336/75 056
6/35
8/80
20 726/72 025
20 740/72 140
No of non-pregnantwomen with covid-19/
No in group
0.01
Note: Weights are from random effects analysis
0.25 0.5 2 101 100
Odds ratio(95% CI)
Fig 4 | clinical manifestations of coronavirus disease (covid-19) in pregnant and recently pregnant women compared with non-pregnant women of reproductive age with covid-19
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sensitivity analyses aimed to tackle some of these problems, the numbers and sample sizes of the individual studies were too small to identify differences between the subgroups. The timing of assessment of the clinical manifestations of disease was generally not available. The definitions of symptoms, tests, and outcomes were heterogeneous. Furthermore, poor reporting of the criteria for caesarean section, admissions to the neonatal unit, and the causes of preterm birth, made it difficult to disentangle iatrogenic effect from the true impact of the disease. There is a paucity of comparative data to assess the risk of severe disease in pregnant women compared with non-pregnant women in similarly aged groups, and to compare pregnancy outcomes in women with and without covid-19. Not many studies reported outcomes by trimester for symptom onset, making it difficult to assess the rates of miscarriage and postpartum complications. For some outcomes, the findings were influenced by a single large study.26 Many studies had to be excluded as we could not rule out potential overlap in the study populations.
comparison with existing evidenceAlongside the spread of the pandemic, a shift has occurred in the types of studies published, with initial studies involving pregnant women from epidemic regions in China, followed by reports of large regional and national datasets from the US, UK, Netherlands, Spain, and, more recently, Latin American countries. The study design has also changed from initial small case series and case reports to large observational data, with recent studies also providing comparative data. The prevalence of covid-19 varied widely between studies, particularly when sampling was done based on symptoms or history of contact, highlighting the variations in criteria for
testing. Moreover, the findings only relate to those women attending hospital for any reason. The true prevalence of covid-19 in pregnancy is likely to be lower when all pregnant women are included.
In the recent cohort study of all individuals admitted with covid-19 in the UK, the cluster of respiratory symptoms of cough, fever, and breathlessness were observed in more than two thirds of individuals,77 similar to reported rates in the US and China.78-80 But in our review, fewer pregnant and recently pregnant women with covid-19 manifested these symptoms than the non-pregnant population, indicating possi-ble high rates of asymptomatic presentation in this population. This is likely because of the strategy of universal screening for covid-19 in pregnancy and the low thresholds for testing than in non-pregnancy. Despite the possibility of the above strategies detecting pregnant women with mild disease, we observed an increase in admissions to the intensive care unit and need for invasive ventilation compared with non-pregnant women of reproductive age with covid-19. The findings were mainly influenced by the recent large Centers for Disease Control and Prevention report from the US.26 Pregnancy status was not ascertained in a large proportion of women of reproductive age in the CDC report that could affect the estimates. Furthermore, the outcomes for which the data were missing were considered to be absent in the report, thereby incurring bias. The pooled estimates for severe covid-19 and admission to an intensive care unit were, however, still relatively high in the non-comparative data, indicative of a potential high risk in pregnancy. This is supported by the recent analysis in a Swedish study suggesting a high risk of admission to an intensive care unit and invasive ventilation in pregnant women than non-pregnant women.81
table 1 | Outcomes in pregnant and recently pregnant women with coronavirus disease 2019 (covid-19)
Outcomes no of studieswomen (no with event/no in group (%))
Odds ratio (95% ci) i2 (%)Pregnant women with covid-19 comparison groupcomparison group: non-pregnant women of reproductive age with covid-19All cause mortality 4 16/8282 (0.2) 208/83 327 (0.2) 0.81 (0.49 to 1.33) 0ICU admission 4 121/8276 (1.5) 758/83 330 (0.9) 1.62 (1.33 to 1.96) 0Invasive ventilation 4 43/8276 (0.5) 226/83 330 (0.3) 1.88 (1.36 to 2.60) 0ECMO 1 0/31 (0) 0/80 (0) 2.56 (0.05 to 131.60) NEOxygen through nasal cannula 2 8/48 (16.7) 49/106 (46.2) 0.21 (0.04 to 1.13) 65.7ARDS 1 0/17 (0) 0/26 (0) 1.51 (0.03 to 79.93) NEMajor organ failure 1 0/17 (0) 0/26 (0) 1.51 (0.03 to 79.93) NEcomparison group: pregnant women without covid-19Maternal outcomes: All cause mortality 1* 5/427 (1.2) 0/694 (0) 18.08 (1.00 to 327.83) NE ICU admission 1* 40/427 (9.4) 1/694 (0.1) 71.63 (9.81 to 523.06) NE Preterm birth <37 weeks 2 7/44 (15.9) 18/295 (6.1) 3.01 (1.16 to 7.85) 0.9 Caesarean section 3* 184/491 (37.5) 577/1676 (34.4) 2.02 (0.67 to 6.10) 87.5Perinatal outcomes: Stillbirth 1* 3/427 (0.7) 2/694 (0.3) 2.45 (0.41 to 14.71) NE Neonatal death 1* 2/427 (0.5) 1/694 (0.1) 3.26 (0.30 to 36.07) NE Admission to neonatal unit 1* 64/427 (15.0) 37/694 (5.3) 3.13 (2.05 to 4.79) NE Abnormal Apgar score at 5 minutes 1 0/30 (0) 12/740 (1.6) 0.96 (0.06 to 16.51) NE Fetal distress 1 3/34 (8.8) 12/242 (5.0) 1.86 (0.50 to 6.94) NEICU=intensive care unit; ECMO=extracorporeal membrane oxygenation; ARDS=acute respiratory distress syndrome; NE=not estimable.The denominator is number of pregnancies for all outcomes.*Historical comparative cohort in UK Obstetric Surveillance System study.
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Age*
Kayem 2020
Martinez-Perez 2020
Khoury 2020
Chen 2020 (continuous age)
Subtotal: I2=9%
Body mass index
Kayem 2020
Martinez-Perez 2020
Khoury 2020
Wu 2020
Subtotal: I2=0%
Multiparity
Chen 2020
Savasi 2020
Martinez-Perez 2020
Subtotal: I2=0%
Third trimester
Yan 2020
Andrikopoulou 2020
Subtotal: I2=0%
Non-white
Savasi 2020
Khoury 2020
Subtotal: I2=73%
Any comorbidity
Savasi 2020
Martinez-Perez 2020
Subtotal: I2=0%
Chronic hypertension
Kayem 2020
Khoury 2020
Subtotal: I2=0%
Pre-existing diabetes
Kayem 2020
Khoury 2020
Subtotal: I2=12%
Pre-eclampsia
Yan 2020
Martinez-Perez 2020
Subtotal: I2=0%
Gestational diabetes
Andrikopoulou 2020
Kayem 2020
Martinez-Perez 2020
Yan 2020
Subtotal: I2=0%
2.24 (1.50 to 3.35)
1.00 (0.13 to 7.46)
1.19 (0.65 to 2.18)
1.87 (0.55 to 6.42)
1.78 (1.25 to 2.55)
2.39 (1.56 to 3.66)
1.11 (0.11 to 11.35)
2.51 (1.31 to 4.81)
Excluded
2.38 (1.67 to 3.39)
1.39 (0.35 to 5.47)
0.82 (0.25 to 2.66)
1.42 (0.14 to 14.29)
1.07 (0.46 to 2.46)
0.64 (0.07 to 5.76)
0.59 (0.26 to 1.32)
0.59 (0.28 to 1.27)
1.88 (0.57 to 6.17)
0.45 (0.19 to 1.06)
0.86 (0.21 to 3.50)
1.88 (0.57 to 6.17)
0.71 (0.07 to 7.14)
1.53 (0.53 to 4.41)
2.51 (0.95 to 6.62)
1.78 (0.90 to 3.51)
2.00 (1.14 to 3.48)
3.98 (1.37 to 11.57)
1.98 (0.96 to 4.08)
2.51 (1.31 to 4.80)
5.00 (0.46 to 54.51)
8.33 (0.66 to 105.71)
6.35 (1.11 to 36.22)
0.60 (0.07 to 5.13)
1.23 (0.69 to 2.21)
5.74 (0.20 to 161.79)
Excluded
1.23 (0.70 to 2.14)
Risk factors Odds ratio(95% CI)
59/128
2/4
22/75
n/9
83/216
46/128
1/4
43/62
0/0
90/194
5/9
8/14
3/4
16/27
7/8
22/34
29/42
6/14
54/65
60/79
6/14
1/4
7/18
7/128
18/75
25/203
7/128
16/75
23/203
1/8
1/4
2/12
1/34
17/128
0/4
0/0
18/166
No of pregnant womenwith risk factor and severe
covid-19/No in group
135/489
39/78
43/166
n/109
219/842
93/489
18/78
55/116
0/13
166/696
46/97
39/63
53/78
138/238
99/108
94/124
193/232
18/63
143/156
161/219
18/63
25/78
43/141
11/489
25/166
36/655
7/489
20/166
27/655
3/108
3/78
6/186
6/124
54/489
1/78
9/116
70/807
No of pregnant womenwith risk factor without
severe covid-19/No in group
Note: Weights are from random effects analysis
0.01 0.25 0.5 2 101 100
Odds ratio(95% CI)
Fig 5 | risk factors associated with severe coronavirus disease 2019 (covid-19) in pregnant and recently pregnant women. symptom based screening: savasi v, Kayem g; nHcc (national Health commission china). criteria based screening: chen, wu, yan. all other studies used universal screening. cut-off for age is 35 years or more, and for body mass index is 30 or more. *includes one study with continuous measurement of risk factor
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Similar to the general population, high body mass index and pre-existing comorbidity seemed to be risk factors for severity of covid-19 in pregnancy, including admission to an intensive care unit and invasive ventilation.77 Complications related to covid-19 did not seem to be increased in women presenting in the third trimester or in multiparous women—but existing sample sizes are not large. Both chronic hypertension and pre-existing diabetes were associated with maternal death in pregnant women with covid-19, which are known risk factors in the general population. But it is not known if covid-19 was the direct cause of death for these women, and the numbers of studies
are small. We observed an increase in rates of preterm birth in pregnant women with covid-19 compared with those without the disease. These preterm births could be medically indicated, as the overall rates of spontaneous preterm births in pregnant women with covid-19 was broadly similar to those observed in the pre-pandemic period. Although more than 60% of pregnant women underwent caesarean section in the non-comparative studies, we did not find a statistically significant difference in comparative studies of pregnant women with and without covid-19. The precision of the estimates is expected to improve with the publication of more data in the future. The overall
table 2 | maternal characteristics associated with severe coronavirus disease 2019 (covid-19) and all cause death in pregnant and recently pregnant women with a diagnosis of covid-19
maternal risk factors and outcomes
no of studies
total no of women
Pregnant women (no with risk factor/no in group (%))
Odds ratio (95% ci) i2 (%)with outcome without outcomeAge ≥35 years: Severe disease 4 1058 216* 842* 1.78 (1.25 to 2.55) 9 ICU admission 2 260 8/87 (9.2) 8/173 (4.6) 2.44 (0.43 to 14.01) 63 Invasive ventilation 1 178 3/65 (4.6) 2/113 (1.8) 2.69 (0.44 to 16.51) NE Maternal death 1 288 20/154 (13.0) 16/134 (11.9) 1.10 (0.55 to 2.22) NEMultiparity: Severe disease 3 265 16/154 (10.4) 11/111 (9.9) 1.07 (0.46 to 2.46) 0 ICU admission 1 42 4/22 (18.2) 4/20 (20.0) 0.89 (0.19 to 4.15) NEBody mass index ≥30: Severe disease 3 877 90/256 (35.2) 104/621 (16.7) 2.38 (1.67 to 3.39) 0 ICU admission 1 142 3/22 (13.6) 4/120 (3.3) 4.58 (0.95 to 22.09) NE Invasive ventilation 1 135 5/21 (23.8) 6/114 (5.3) 5.63 (1.54 to 20.59) NE Maternal death 2 596 6/62 (9.7) 37/534 (6.9) 2.57 (0.97 to 6.82) 0Non-white ethnicity: Severe disease 2 298 60/221 (27.1) 19/77 (24.7) 0.86 (0.21 to 3.50) 73 ICU admission 1 42 5/20 (25.0) 3/22 (13.6) 2.11 (0.43 to 10.28) NE Maternal death 2 596 31/220 (14.1) 12/376 (3.2) 2.40 (0.94 to 6.11) 0Any comorbidity: Severe disease 2 159 7/50 (14.0) 11/109 (10.1) 1.53 (0.53 to 4.41) 0 ICU admission 2 320 4/37 (10.8) 11/283 (3.9) 4.21 (1.06 to 16.72) 0 Invasive ventilation 2 313 6/36 (16.7) 10/277 (3.6) 4.48 (1.40 to 14.37) 0Chronic hypertension: Severe disease 2 858 25/61 (41.0) 178/797 (22.3) 2.0 (1.14 to 3.48) 0 ICU admission 1 141 2/5 (40.0) 5/136 (3.7) 17.47 (2.37 to 129.02) NE Invasive ventilation 1 134 4/5 (80.0) 7/129 (5.4) 69.71 (6.85 to 709.34) NE Maternal death 2 596 5/29 (17.2) 38/567 (6.7) 3.38 (1.17 to 9.75) 0Pre-existing diabetes: Severe disease 2 858 23/50 (46.0) 180/808 (22.3) 2.51 (1.31 to 4.80) 12 ICU admission 2 181 1/7 (14.3) 14/174 (8.0) 2.88 (0.44 to 18.96) 0 Invasive ventilation 1 132 1/6 (16.7) 9/126 (7.1) 2.60 (0.27 to 24.71) NE Maternal death 2 596 10/52 (19.2) 33/544 (6.1) 6.63 (0.27 to 161.45) 91Asthma: Severe disease 3 857 17/61 (27.9) 149/796 (18.7) 1.86 (0.88 to 3.93) 22 Maternal death 2 596 3/22 (13.6) 40/574 (7.0) 2.04 (0.61 to 6.85) 0Smoking: Severe disease 3 776 5/23 (21.7) 141/753 (18.7) 1.67 (0.64 to 4.40) 0 ICU admission 1 42 1/2 (50.0) 7/40 (17.5) 4.71 (0.26 to 84.77) NE Maternal death 1 308 0/10 (0) 7/298 (2.3) 1.85 (0.10 to 34.60) NEGestation ≥28 weeks: Severe disease 2 274 29/222 (13.1) 13/52 (25.0) 0.59 (0.28 to 1.27) 0 Maternal death 1 273 22/190 (11.6) 12/83 (14.5) 0.78 (0.36 to 1.65) NEGestational diabetes: Severe disease 4 973 18/88 (20.5) 148/885 (16.7) 1.23 (0.70 to 2.14) 0Pre-eclampsia: Severe disease 2 198 2/8 (25.0) 10/190 (5.3) 6.36 (1.12 to 36.22) 0 ICU admission 1 42 6/6 (100.0) 2/36 (5.6) 179.40 (7.69 to 4186.05) NEICU=intensive care unit; NE=not estimable.*Includes one or more studies with continuous measurement of risk factor.
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rates of stillbirths and neonatal deaths do not seem to be higher than the background rates. The indications for admissions to the neonatal unit, observed in about a quarter of neonates delivered to mothers with covid-19, have not been reported. Local policies on observation and quarantine of infants with exposure to SARS-CoV-2 might have influenced these rates.
relevance for clinical practice and researchBased on existing data, healthcare professionals should be aware that pregnant and recently pregnant women with covid-19 might manifest fewer symptoms than the general population, with the overall pattern similar to that of the general population. Emerging comparative data indicate the potential for an increase in the rates of admission to intensive care units and invasive ventilation in pregnant women compared with non-pregnant women. Mothers with pre-existing comorbidities will need to be considered as a high risk group for covid-19, along with those who are obese and of greater maternal age. Clinicians will need to balance the need for regular multidisciplinary antenatal care to manage women with pre-existing comorbidities against unnecessary exposure to the virus, through virtual clinic appointments when possible. Pregnant women with covid-19 before term gestation might need to be managed in a unit with facilities to care for preterm neonates.
Further data are needed to assess robustly if preg-nancy related maternal and neonatal complications are increased in women with covid-19 than those without the disease. Similarly, the association between other risk factors such as ethnicity and pregnancy specific risk factors such as pre-eclampsia and gestational diabetes on both covid-19 related and pregnancy related outcomes needs evaluation. Pre-eclampsia was reported to be associated with severe covid-19 in small studies, but it requires further assessment as the clinical presentation of severe pre-eclampsia could mimic worsening covid-19.82 Robust collection of maternal data by trimester of exposure, including the periconception period, is required to determine the effects of covid-19 on early pregnancy outcomes, fetal growth, and risk of stillbirth.
Systematic reviews are considered to be the highest quality evidence informing guidelines, and poor quality reviews will have a direct impact on clinical care. Despite the urgent need for evidence on the impact of covid-19 in pregnant women, systematic reviews and meta-analyses still need to adhere to the reporting guidelines on search criteria, quality assessment, and analysis. This is particularly impor-tant as large numbers of non-peer reviewed scientific papers and reports are currently available in the public domain in multiple versions. Primary studies need to explicitly state if duplicate data have been included to avoid double counting of participants in evidence synthesis. Individual participant data meta-analysis of the emerging cohorts is critical to assess both differential presentation and outcomes by underlying
risk factors, and to determine the differential effects of interventions to reduce the rates of complications. With the establishment of several national and global prospective cohorts, we expect the sample size of our meta-analysis to increase further in the coming months. Our living systematic review and meta-analysis with its regular search and analyses updates is ideally placed to assess the impact of new findings on the rapidly growing evidence base.
autHOr aFFiliatiOns1Institute of Applied Health Research, University of Birmingham, Birmingham, UK2WHO Collaborating Centre for Global Women’s Health, Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK3Clinical Biostatistics Unit, Hospital Universitario Ramón y Cajal (IRYCIS), Madrid, Spain4CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain5UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland6Birmingham Medical School, University of Birmingham, Birmingham, UK7Division of Birth Cohort Study, Guangzhou Women and Children’s Medical Centre, Guangzhou Medical University, Guangzhou, China8Department of Woman and Child Health Care, Guangzhou Women and Children’s Medical Centre, Guangzhou Medical University, Guangzhou, China9Department of Obstetrics and Gynaecology, Guangzhou Women and Children’s Medical Centre, Guangzhou Medical University, Guangzhou, China10Netherlands Satellite of the Cochrane Gynaecology and Fertility Group, Amsterdam University Medical Centre, Amsterdam, Netherlands11Department of Obstetrics and Gynaecology, Amsterdam University Medical Centre, Amsterdam, Netherlands12Blizard Institute, Queen Mary University of London, London, UK13Barts Health NHS Trust, London, UK14St George’s, University of London, London, UK15Elizabeth Glaser Paediatric AIDS Foundation, Washington DC, USA16Women’s Health Research Unit, Queen Mary University of London, London, UK17Birmingham Women’s and Children’s NHS Foundation Trust, Birmingham, UK
Other members of the PregCOV-19 Living Systematic Review Consortium are Uma Ram, Ajith S Nair, Pura Rayco-Solon, and Hector Pardo-Hernandez. The Cochrane Gynaecology and Fertility Group thank Marijke Strikwerda and Bethany Clark for help with searches and data extraction. The PregCOV-19 Living Systematic Review Group would also like to thank Katie’s Team for its contribution towards the development and reporting of this work, James Thomas from the EPPI-Centre for helping with search updates, and the PregCOV-19 Living Systematic Review steering committee members, Pisake Lumbiganon, Carolina Carvalho Ribeiro do Valle, Clare Whitehead, David Lissauer, Joao Paulo Souza, and Marian Knight, who provided guidance throughout.Contributors: JA and ES are joint first authors. ST, MB, and JA conceptualised the study. MY, SC, LD, TK, ACL, AD, DZ, RB, SL, XQ, and MYuan selected the studies. JA, ES, MY, LD, DZ, XQ, and MYuan extracted the data. JZ conducted the analyses. All coauthors contributed to the writing of the manuscript and approved the final version. ST, JA, ES, and JZ are the guarantors. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omittedFunding: The project was partially funded by the World Health Organization.Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare:
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partial funding by the World Health Organization; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.Ethical approval: Not required.Data sharing: No additional data available.The corresponding author (ST) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been disclosed.Dissemination to participants and related patient and public communities: The PregCov-19 LSR Group will disseminate the findings through a dedicated website (www.birmingham.ac.uk/research/who-collaborating-centre/pregcov/index.aspx) and social media.Provenance and peer review: Not commissioned; externally peer reviewed.This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Case Report
Efficient Maternal to Neonate Transfer of NeutralizingAntibodies after SARS-CoV-2 Vaccination with BNT162b2:A Case-Report and Discussion of the Literature
Jonathan Douxfils 1,2,* , Constant Gillot 2 , Émilie De Gottal 3, Stéphanie Vandervinne 4, Jean-Louis Bayart 5,Jean-Michel Dogné 2 and Julien Favresse 2,6
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Citation: Douxfils, J.; Gillot, C.; De
Gottal, É.; Vandervinne, S.; Bayart,
J.-L.; Dogné, J.-M.; Favresse, J.
Efficient Maternal to Neonate
Transfer of Neutralizing Antibodies
after SARS-CoV-2 Vaccination with
BNT162b2: A Case-Report and
Discussion of the Literature. Vaccines
2021, 9, 907. https://doi.org/
10.3390/vaccines9080907
Academic Editor: Laurent Dacheux
Received: 23 July 2021
Accepted: 13 August 2021
Published: 15 August 2021
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Copyright: © 2021 by the authors.
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4.0/).
1 Qualiblood s.a., 5000 Namur, Belgium2 Namur Thrombosis and Hemostasis Center, Namur Research Institute for Life Sciences,
Department of Pharmacy, Faculty of Medicine, University of Namur, 5000 Namur, Belgium;[email protected] (C.G.); [email protected] (J.-M.D.); [email protected] (J.F.)
3 Département de Gynécologie, Centre Hospitalier Régional de Huy, 4500 Liège, Belgium;[email protected]
4 Laboratoire de Biologie Clinique, Centre Hospitalier Régional Huy, 4500 Liège, Belgium; [email protected] Department of Laboratory Medicine, Clinique Saint-Pierre Ottignies, 1340 Ottignies, Belgium;
[email protected] Department of Laboratory Medicine, Clinique Saint-Luc Bouge, 5004 Namur, Belgium* Correspondence: [email protected]; Tel.: +32-81-72-42-91
Abstract: This case reports on the successful maternal to fetal transfer of neutralizing antibodies aftervaccination with BNT162b2 in a pregnant woman at 25 weeks of gestation. The levels of neutralizingantibodies were approximately 5-fold higher in the umbilical cord than in the maternal blood whilethe level of total antibodies showed only a 2-fold increase. This suggest that the antibodies thatcrossed the syncytiotrophoblast cell barrier have specific characteristics that correlate to functionalneutralizing capacity. Although pregnant and lactating women have been excluded from clinicaltrials for several reasons including ethical concerns about fetal exposure, accumulating evidence hasnow revealed that these vaccines are safe and efficient for both the fetus and the woman. Vaccinationagainst COVID-19 in pregnancy is vital to control disease burden and to decrease morbidity inthe ante-, peri- and post-natal periods. Inclusion of pregnant women in research programs for thedevelopment of SARS-CoV-2 vaccines should be mandatory to provide this population with theequitable benefits of vaccine research.
Keywords: neonates; infant; COVID-19; vaccine; antibodies; pregnancy; immunity
1. Introduction
Before the vaccine rollout, multiple cohort studies documented that pregnantwoman were more susceptible to severe COVID-19 compared to age-matched non-pregnant women [1–3]. This is in line with the initial expectations, which stated thataccording to immunologic and cardiopulmonary adaptations occurring during preg-nancy, the risk of severe illness from respiratory infections typically increases [4]. Asystematic review of 60 studies on SARS-CoV-2 in pregnancy reported that severe illnessoccurred in up to 18% of pregnant patients and critical disease complicated up to 5%of the cases, comparable to rates observed in the general population [5]. Nevertheless,despite recommendations from public health advocates for pregnant women includingthe Center for Disease Control and Prevention (CDC), the American College of Obstetri-cians and Gynecologists (ACOG), and the American Academy of Pediatrics, pregnant orbreastfeeding women have been excluded from clinical trials during the development ofexisting COVID-19 vaccines [6–12]. This causes large gaps in understanding the safetyand efficacy of these vaccines in this population, which can be definitively detrimental to
Vaccines 2021, 9, 907. https://doi.org/10.3390/vaccines9080907 https://www.mdpi.com/journal/vaccines
Vaccines 2021, 9, 907 2 of 8
vaccine acceptance. Although data are emerging documenting the efficacy and the safetyof these vaccines [13] and although guidance from these data recommend vaccination inpregnant and breastfeeding women, [14–16] getting vaccinated during pregnancy mainlyremains a personal choice. Thus, the acceptance of COVID-19 vaccination in pregnancyis an important concern. According to a survey study, the COVID-19 vaccine acceptancerate during pregnancy was 58.4%, a rate which is consistent with the acceptance rate ofother recommended vaccines in pregnancy but that is not sufficient to avoid deleteriouscases of neonate infection due to maternal to fetal transmission or infection during theearly stages of life [17,18].
Both neonates and pregnant women are particularly susceptible to respiratory in-fections, including influenza and respiratory syncytial virus (RSV) [19–21], and recentdata demonstrate that a greater proportion of neonates and infants have severe or criticalillness upon SARS-CoV-2 infection compared to older children [22–24]. Rare cases ofvertical transmission have been reported in neonates [5], but histopathological changesin the placenta have suggested that the inflammatory nature of SARS-CoV-2 infectionduring pregnancy could cause adverse obstetric and neonatal events [25,26]. The risks ofSARS-CoV-2 infection during pregnancy are preterm delivery, preeclampsia, emergencycesarian delivery, and neonatal complications including respiratory distress or pneumonia,disseminated intravascular coagulation, asphyxia, and perinatal deaths [27,28]. In addition,placental injury may increase the risk of long-term adverse neurodevelopmental, as is thecase for other conditions that affect the placenta through the release of proinflammatorycytokines such as interleukin-6, which leads to the activation of T helper cell 17 [29].
Neonates rely on the transfer of maternal immunoglobulin G (IgG) across the placentafor protection against pathogens, and vaccination aims to mimic the presence of pathogensto stimulate the maternal immune response. Data from the literature show that maternalto neonatal transfer of anti-SARS-CoV-2 antibodies is efficient although the maternal tofetal transfer ratio of IgG antibodies may differ depending on gestational age and thetype of immunization, i.e., disease- or vaccine-induced [30–33]. There is also a significantimprovement in the transfer of spike specific IgG into the umbilical cord with the time fromsecond dose, suggesting that time from vaccination may be an important determinant ofthe transfer rates of specific IgG subpopulations following immunization in pregnancy [32].Despite reassuring data, the neutralizing capacity of these transferred antibodies was notassessed [30,32,33].
This case-report assessed the neutralizing capacity of umbilical cord blood comparedto maternal blood in addition to conventional serological assay in a woman who received tatwo-dose regimen of BNT162b2 during the antenatal period. To appreciate the magnitudeof the antibody response of this dyad, a comparison with an age-matched cohort will alsobe done.
2. Case Description and Methods
A 28-year-old pregnant woman received her first dose of BNT162b2 mRNA COVID-19vaccine (Pfizer-BioNTech, Mainz, Germany) at 25 weeks of gestation. The second wasadministered at 30 weeks. No problem was reported during the antenatal period, and nosevere adverse events were reported after the vaccination. The patient only complainedheadache and tiredness the day after the second dose, which resolved with the adminis-tration of paracetamol twice a day. The delivery was planned to be on the 4th of July butoccurred 8 days earlier, on the 26th of June at the Centre Hospitalier Régional (CHR) of Huy(Liège, Belgium), 90 days after the administration of the first vaccine dose. No deliverycomplications were reported, and all of the parameters of the newborn were normal. At4 weeks, the newborn was still doing well. On the day of delivery, umbilical cord bloodwas collected as well as maternal blood to permit comparison of the level of SARS-CoV-2neutralizing antibodies.
To compare the results obtained with the umbilical cord and maternal blood samples,13 non-pregnant women of a similar age (i.e., 25 to 35 years of age) with no history of
Vaccines 2021, 9, 907 3 of 8
previous SARS-CoV-2 infection (i.e., no documented positive RT-PCR and the absence ofanti-nucleocapsid antibodies), were included. These vaccinated controls were recruitedat the Clinique Saint-Luc Bouge (Namur, Belgium) due to their participation in the CRO-VAX HCP study, a study which has already been described in detail elsewhere [34–36].All of the participants provided informed consent prior to specimen and data collection.The study was approved by a central ethical committee (EudraCT registration number:2020-006149-21).
Blood samples were collected in SST™ II advanced tubes (BD Vacutainer, Plymouth,UK) and were processed according to the manufacturer recommendations to obtain serum.Serum samples were then aliquoted and were stored at −20 ◦C until analysis. Antibodiesagainst the SARS-CoV-2 nucleocapsid (anti-NCP; Elecsys Anti-SARS-CoV-2 NCP total qual-itative ECLIA, Roche Diagnostics, Machelen, Belgium) and the receptor binding domain ofthe S1 subunit of the spike protein (anti-S; Elecsys anti-SARS-CoV-2 spike total quantitativeECLIA, Roche Diagnostics) were measured at each time point. Results above 0.8 U/mL(manufacturer’s cut-off) or 0.165 COI (cut-off index as found previously [37]) for anti-S andanti-NCP antibodies, respectively, were considered positives.
Neutralizing capacity was estimated by performing a surrogate virus neutralizationtest (sVNT) [38]. The iFlash-2019-nCoV NAbs assay (performed on an iFlash1800 analyzerfrom Shenzhen YHLO Biotech Co., Ltd. (Shenzhen, China)) is a one-step competitiveparamagnetic particle chemiluminescent immunoassay (CLIA) for the quantitative deter-mination of 2019-nCoV NAbs in human serum and plasma. The assay detects NAbs thatblock the binding of RBD and ACE2. First, NAbs (if present) react with the RBD antigencoated on paramagnetic microparticles to form a complex. Second, the acridinium-ester-labeled ACE2 conjugate is added to competitively bind to the RBD-coated particles thatwere not neutralized by the NAbs (if present) from the sample, and these form anotherreaction mixture. Under a magnetic field, magnetic particles are adsorbed to the wall of thereaction tube, and unbound materials are washed away by the wash buffer. The resultingchemiluminescent reaction is measured in relative light units (RLUs), with an inverse rela-tionship between the amount of NAbs and the RLU value being detected. A result <10.0arbitrary unit (AU)/mL is considered negative, and a result >10.0 AU/mL is consideredpositive (according to the manufacturer’s information). The neutralizing capacity was alsoconfirmed using a pseudovirus neutralization test, as previously described [38]. Samplesare considered to be neutralizing if the dilution factor provides a 50% diminution of therelative infectivity that is superior to 1:20. The agreement of the sVNT assay with the pVNTwas found to be 97.2% [38].
3. Results and Discussion
The total anti-RBD titers of the maternal and the umbilical cord blood were 1120 U/mLand 2349 U/mL compared to 1747 U/mL (geometric mean; 95%CI, 1231–2438 U/mL) in thecontrol group at the identical time point, i.e., 90 days post-vaccination. The NAbs titers were163 and 906 AU/mL for the maternal and the umbilical cord blood, respectively, comparedto 427 AU/mL (geometric mean; 95%CI, 222–820 AU/mL) for the control group at 90 dayspost-vaccination. The maternal to fetal transfer ratio was 2.10 for total anti-RBD antibodiesand 5.56 for NAbs. A summary of the results is presented in Table 1 and Figure 1. Theneutralizing capacity of the maternal and umbilical cord blood was confirmed by the pVNT,with both samples having higher dilution factors than 1:20 to half of the relative infectivity.
Vaccines 2021, 9, 907 4 of 8
Table 1. Summary of serological results obtained from the maternal and the umbilical cord blood samples. For pVNT, thehighest the dilution factor, the stronger the neutralizing capacity.
Serum Samples Anti-N Titer (U/mL) Anti-S Titer (U/mL) sVNT (AU/mL) pVNT (Dilution Factor)
Maternal <0.165 (negative) 1120 162.9 1/40 (positive)
Umbilical cord blood <0.165 (negative) 2349 906.4 1/60 (positive)
Maternal to fetal transferratio † / 2.10 5.56 1.50 ‡
† Ratio is defined as the results of umbilical cord blood divided by maternal blood. ‡ pVNT is not a calibrated quantitative method, andthus, the ratio is only given for information. Abbreviations: pVNT, pseudovirus neutralization test; N, nucleocapsid; NR, non-reactive; S,spike; sVNT, surrogate virus neutralization test.
Vaccines 2021, 9, x FOR PEER REVIEW 4 of 9
Table 1. Summary of serological results obtained from the maternal and the umbilical cord blood samples. For pVNT, the highest the dilution factor, the stronger the neutralizing capacity.
Serum Samples Anti-N Titer (U/mL) Anti-S Titer (U/mL) sVNT (AU/mL) pVNT (Dilution
Factor) Maternal <0.165 (negative) 1120 162.9 1/40 (positive)
Umbilical cord blood <0.165 (negative) 2349 906.4 1/60 (positive) Maternal to fetal transfer
ratio † / 2.10 5.56 1.50 ‡
† Ratio is defined as the results of umbilical cord blood divided by maternal blood. ‡ pVNT is not a calibrated quantitative method, and thus, the ratio is only given for information. Abbreviations: pVNT, pseudovirus neutralization test; N, nucleocapsid; NR, non-reactive; S, spike; sVNT, surrogate virus neutralization test.
Figure 1. Serological response in controls, maternal and umbilical cord sera. Control sera selected from the CRO-VAX HCP study cohort and included 13 non-pregnant women aged from 25 to 35 (median, 30 years of age; min–max range, 25–35), without history of SARS-CoV-2 infection. Blood was collected at baseline (day 0), day 14, day 28, day 42, day 56, and day 90. Maternal and umbilical cord blood were only collected on day 90 after the vaccination, at the time of delivery. Positivity thresholds for the Roche RBD total Ab and the YHLO NAbs assays were 0.8 U/mL and 10.0 AU/mL, respectively.
Recent investigations suggested that maternal SARS-CoV-2 immunization, either in-duced by the disease or by the vaccination, may provide neonatal protection through the
Figure 1. Serological response in controls, maternal and umbilical cord sera. Control sera selected from the CRO-VAX HCPstudy cohort and included 13 non-pregnant women aged from 25 to 35 (median, 30 years of age; min–max range, 25–35),without history of SARS-CoV-2 infection. Blood was collected at baseline (day 0), day 14, day 28, day 42, day 56, and day 90.Maternal and umbilical cord blood were only collected on day 90 after the vaccination, at the time of delivery. Positivitythresholds for the Roche RBD total Ab and the YHLO NAbs assays were 0.8 U/mL and 10.0 AU/mL, respectively.
Recent investigations suggested that maternal SARS-CoV-2 immunization, either in-duced by the disease or by the vaccination, may provide neonatal protection through thetransplacental transfer of antibodies [30–33]. Of particular importance was the demon-
Vaccines 2021, 9, 907 5 of 8
stration that antibody transfer is correlated with the time from vaccination to delivery,which may allow future determination of the optimal timing of COVID-19 vaccination inpregnant women [33]. Compared to the non-pregnant controls, pregnant women exhibitquite comparable vaccine-specific antibody titers, [39] although IgG titers have also beenfound to be slightly lower in pregnant women [13].
Zdanowski et al. observed a slightly lower maternal to fetal ratio, i.e., 1.28 ± 0.80 [33].Mittal et al. also report that the mean IgG titer is similar in maternal and infant sera,but the average gestational age at first vaccine dose was 33 weeks [40]. In our case, 13weeks separate the first vaccine dose to delivery, which could then explain the higher ratioobserved. This observation was also made by Beharier et al. and Mittal et al., and the samephenomenon has been also reported after SARS-CoV-2 infection [30,40]. Thus, the datain the literature are consistent and should now permit us to draw hypothesis on when tovaccine pregnant women in order to achieve the best maternal to fetal transfer ratio. A firstBNT162b2 dose administered during the second trimester could permit high umbilical cordneutralizing antibody titers that are even higher than the ones observed in the maternalblood to be obtained (Table 1).
Interestingly, our case also confirms the presence of neutralizing antibodies in theumbilical cord blood (Table 1). Another case demonstrated that the antibody subtypes,which are transferred, possess a neutralizing capacity, although a clear description of theneutralization assay that was used was not provided [41]. It is also interesting to notethat total antibodies and NAbs titers in the maternal blood were at the lower range in ourcontrol cohort (Figure 1). This may be due to individual factors or may be the consequenceof the maternal to fetal transfer of IgG antibodies, reducing the level of antibodies in thematernal blood.
The observations that we made in this case report following vaccination with BNT162b2are not so surprising. For most pathogens, umbilical cord titers of IgG are higher than inmaternal blood due to endosomal transport of IgG across the syncytiotrophoblast cell bar-rier from maternal to fetal circulation [42–44]. Among these IgG antibodies, galactosylatedIgG1 antibodies are transferred preferentially, followed by IgG3, IgG2, and IgG4 [45]. Thisis potentially the result of enhanced binding to both placental FcRN and FCGR3, enablingthe selective transfer of specific antibody subpopulations to most effectively arm neonatesin the setting of pathogen exposure [45,46]. The fact that the ratio for neutralizing anti-bodies is higher than the one of total antibodies may also be explained by this preferentialtransfer of IgG1, as most serological assays used to assess the humoral response towardsSARS-CoV-2 vaccination target either all types of antibodies or all IgG subtypes. Indeed, itis possible that specific Fc glycoforms can be linked to Fab specificity and subsequently to adifferent neutralizing capacity, as reported for influenza vaccination [47]. Thus, if a specificfraction of neutralizing galactosylated IgG subtypes is transferred from the maternal bloodto the fetus, the neutralizing capacity ratio may increase more sharply than the total levelof antibodies since other types of antibodies, which are not neutralizing and do not transfertrough the placenta, can compensate for the decrease of neutralizing antibodies in thematernal blood.
Interestingly, in line with the above explanations, immunization transfer may alsodepend on whether it is acquired after vaccination or previous infection. Indeed, somecases were reported and described inefficient maternal to fetal transfer following COVID-19disease during pregnancy [48,49]. This could have been explained by Rh isoimmunization,which can compete for IgG transfer within the neonatal Fc receptor (FcRN), but, despitehigh levels of anti-D antibodies, protective antibodies for other pathogens (i.e., rubeolaand varicella) successfully crossed the placenta [48]. This observation can be explained,however, by changes to the Fc-glycosylation profile of the SARS-CoV-2 antibodies due tothe inflammatory state generated by SARS-CoV-2 infection [31,50].
This may influence the neutralizing capacity of the antibodies and may impact thetransfer of immunity, especially during the third trimester [31,47,50]. Nonetheless, thisperturbed placental transfer is probably dependent on the trimester, as observed across two
Vaccines 2021, 9, 907 6 of 8
independent third trimester-infection cohorts where normalized following second trimesterinfection, suggesting that inflammation-induced alterations in SARS-CoV-2-specific-glycanprofiles may resolve over time from infection [31]. It remains to be known if such alterationsin Fc glycosylation are also observed after vaccination, but in any case, our results andthose from other groups [30,32,33] strongly suggest that BNT162b2 administration in thesecond trimester permit the generation of a strong immune response that can be efficientlytransferred to the fetus in order to protect neonates from SARS-CoV-2 infection.
Although these data have been obtained in a small number of subjects, these arequite reassuring, and the present case demonstrates that the antibody subtypes that aretransferred possess high neutralizing capacity.
4. Conclusions
This case reports on the successful maternal to fetal transfer of neutralizing antibodiesafter vaccination with BNT162b2 in a pregnant woman at 25 weeks of gestation. The levelsof neutralizing antibodies were approximately 5-fold higher in the umbilical cord thanin the maternal blood, while the level of total antibodies showed only a 2-fold increase.This suggests that the antibodies that crossed the syncytiotrophoblast cell barrier havespecific characteristics that correlate to functional neutralizing capacity. Although pregnantand lactating woman have been excluded from clinical trials for several reasons includingethical concerns about fetal exposure, accumulating evidence has now revealed that thesevaccines are safe and efficient for both the fetus and the woman. Vaccination againstCOVID-19 in pregnancy is vital to control disease burden and to decrease morbidity in theante-, peri- and post-natal periods. Inclusion of pregnant women in research programs forthe development of SARS-CoV-2 vaccines should be mandatory to provide this populationwith the equitable benefits of vaccine research.
Author Contributions: Conceptualization, J.D.; methodology, É.D.G., J.F., C.G., and S.V.; formalanalysis, J.D., J.F., and C.G.; investigation, J.D., J.F., and C.G.; resources, É.D.G., J.F., C.G., and S.V.;writing—original draft preparation, J.D.; writing—review and editing, J.-L.B., É.D.G., J.-M.D., J.F.,and C.G.; supervision, J.D.; project administration, J.D. All authors have read and agreed to thepublished version of the manuscript.
Funding: This research has been funded by the authors own funds.
Institutional Review Board Statement: The study was conducted according to the guidelines of theDeclaration of Helsinki and was approved by the Ethics Committee of Clinique Saint-Luc Bouge(protocol registration number: 2020-006149-21—approved on the 14th of January 2021).
Informed Consent Statement: Informed consent was obtained from all subjects involved in thestudy. In addition, written informed consent has been obtained from the patient to publish this paper.
Data Availability Statement: The data presented in this study are available upon request from thecorresponding author. The data are not publicly available due to ethical and privacy reasons.
Acknowledgments: The authors would like to acknowledge the mother and the neonate for theirparticipation in this study as well as the subjects from the CRO-Vax study who served as controls.The authors would also like to thank the midwifes at the Centre Hospitalier Régional de Huy forassisting during the delivery.
Conflicts of Interest: The authors declare no conflict of interest in relation with the present study.
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COVID-19 mRNA Vaccination in Lactation: Assessment of adverse effects and 1
transfer of anti-SARS-CoV2 antibodies from mother to child 2
3
Yarden Golan, Ph.D.1, Mary Prahl, M.D.2,3, Arianna G. Cassidy, M.D.4, Caryl Gay Ph.D. 4
5, Alan H.B. Wu, Ph.D. 6, Unurzul Jigmeddagva, M.D. 7, Christine Y. Lin4, Veronica J. 5
Gonzalez, M.D.4, Emilia Basilio, M.D, M.P.H4, Lakshmi Warrier8, Sirirak Buarpung, 6
D.V.M., Ph.D. 4, Lin Li, M.D., Ph.D. 4, Ifeyinwa V. Asiodu, Ph.D, R.N. 5, Nadav Ahituv, 7
Ph.D.1, Valerie J. Flaherman, M.D., M.P.H.2, Stephanie L. Gaw, M.D., Ph.D. 4, 7 8
9
Author Affiliations 10
1 Department of Bioengineering and Therapeutic Sciences, University of California, San 11
Francisco, CA, 94158 and Institute for Human Genetics, University of California, San 12
Francisco, California, United States of America. 13
2 Department of Pediatrics, University of California, San Francisco, California, United 14
States of America. 15
3Division of Pediatric Infectious Diseases and Global Health, University of California, 16
San Francisco, California, United States of America. 17
4 Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and 18
Reproductive Sciences, University of California San Francisco, California, United States 19
of America. 20
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NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
5 Department of Family Health Care Nursing, University of California, San Francisco, 21
California, United States of America. 22
6 Department of Laboratory Medicine, University of California, San Francisco, California, 23
United States of America. 24
7 Center for Reproductive Sciences, Department of Obstetrics, Gynecology, and 25
Reproductive Sciences, University of California San Francisco, California, United States 26
of America. 27
8 Department of Medicine, University of California, San Francisco, California, United 28
States of America. 29
Corresponding author: Stephanie L. Gaw- Division of Maternal-Fetal Medicine, 30
Department of Obstetrics, Gynecology, and Reproductive Sciences, University of 31
California San Francisco, 513 Parnassus Ave, HSE16, Box 0556, San Francisco, CA 32
94143. Phone: 415.476.0535. Email: [email protected] 33
34
35
Conflict of interest: 36
The authors have declared that no conflict of interest exists. 37
38
39
40
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Abstract: 41
Background: Data regarding the rate of adverse effects observed in the lactating 42
mother-infant dyad and their immune response to COVID-19 mRNA vaccination during 43
lactation are needed to inform vaccination guidelines. 44
Methods: From a prospective cohort of 50 lactating individuals who received mRNA-45
based vaccines for COVID-19 (mRNA-1273 and BNT162b2), blood and milk samples 46
were collected prior to first vaccination dose, immediately prior to 2nd dose, and 4-10 47
weeks after 2nd dose. Symptoms in mother and infant were assessed by detailed 48
questionnaires. Anti-SARS-CoV-2 antibody levels in blood and milk were measured by 49
Pylon 3D automated immunoassay and ELISA, and PEGylated proteins in milk were 50
measured by ELISA. Blood samples were collected from a subset of infants whose 51
mothers received the vaccine during lactation or pregnancy (4-15 weeks after mothers’ 52
2nd dose). 53
Results: No severe maternal or infant adverse effects were reported in this cohort. Two 54
mothers and two infants were diagnosed with COVID-19 during the study period. 55
Vaccine-related products, PEGylated proteins, were not found at significant levels in 56
milk after vaccination. After vaccination, levels of anti-SARS-CoV-2 IgG and IgM 57
significantly increased in maternal plasma and there was significant transfer of anti-58
SARS-CoV-2-Receptor Binding Domain (anti-RBD) IgA and IgG antibodies to milk. Milk 59
IgA levels after 2nd dose were negatively associated with infant age. Anti-SARS-CoV-2 60
IgG antibodies were not detected in the plasma of infants whose mothers were 61
vaccinated during lactation. 62
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Conclusions: COVID-19 mRNA vaccines generate robust immune responses in 63
plasma and milk of lactating individuals without severe adverse effects reported. 64
65
66
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Introduction: 67
An important benefit of human milk is the presence of IgA and IgG antibodies that 68
provide passive immunity to the infant (1, 2). Anti-SARS-CoV-2 antibodies are present 69
in milk from lactating women who were infected with SARS-CoV-2 (3, 4) or who 70
received COVID-19 mRNA vaccines (5–8). Specifically, high titers of anti-SARS-CoV-2 71
IgG were reported after vaccination(6). The function of these antibodies in protection of 72
infants against COVID-19 is not fully understood. Recently, work has demonstrated that 73
murine pups can transfer IgG antibodies from ingested milk to their bloodstream, via 74
enteric Fc receptors (9); however, this phenomenon has not been demonstrated in 75
humans. To better understand the function and distribution if human milk antibodies and 76
infant immunization after maternal vaccination, we examine anti-SARS-CoV-2 antibody 77
levels in infant stool and blood. In addition, information is lacking on the potential 78
adverse effects of COVID-19 vaccination on lactating mothers and their infants, who 79
were excluded from initial clinical trials of mRNA vaccination (10). Many breastfeeding 80
individuals have concerns regarding the potential effects on their infant due to the lack 81
of data, leading to delayed vaccination or early cessation of breastfeeding (11). 82
In this study, we examined blood and milk samples from lactating mothers who received 83
a COVID-19 mRNA vaccine and their infants for the presence of anti- SARS-CoV2 84
antibodies, presence of PEGylated protein vaccine products, and self-reported vaccine-85
related symptoms in order to address the gap of knowledge regarding vaccination 86
efficacy and safety in this population. 87
88
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Results: 89
Participant characteristics. During the study period, 50 participants answered all 90
study questionnaires, provided blood and/or milk samples, had an infant up to 18 91
months old and were included in this analysis. Two infants were diagnosed with COVID-92
19 during this study (Table S1, infant of participants 1 and 2). One mother reported that 93
her infant had mild symptoms 1 week after the 2nd dose; this infant’s vaccinated mother 94
had a negative test at the time of the infant’s positive PCR test. A second infant had 95
positive plasma anti-SARS-CoV-2 IgG and IgA, despite the mother receiving the 96
vaccine postpartum and reported no known prior COVID-19 infection. The mother’s 97
plasma was subsequently found to be positive to antibodies against SARS-CoV-2 98
nucleocapsid protein, indicating a likely natural asymptomatic SARS-CoV-2 infection 99
(further details in Table S1). Two mothers were positive for COVID-19 and are 100
presented in Table S1 (participants 2 and 3); they were excluded from further analysis 101
of symptomatology. Cohort characteristics are presented in Table 1. Twenty-seven 102
female participants (mean age 35.7 years (± 3.9)) received the BNT162b2 vaccine 103
(Pfizer, 56%), and 21 received the mRNA-1237 (Moderna, 44%). The mean infant age 104
at mother’s 1st dose was 5 months (±3.9). All mothers continued to feed their infants 105
with milk at the time of the 2nd vaccination, and all except one continued up to the time 106
of follow up sample collection (4-10 weeks after 2nd dose). There were no significant 107
differences in maternal or infant characteristics by vaccine manufacturer. 108
109
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Post vaccination symptoms. Self-reported symptoms after each vaccine dose are 110
presented in Table 2. Fever, chills, headache, joint pain, muscle aches or body aches, 111
and fatigue or tiredness were reported by significantly more participants after the 2nd 112
dose than after the 1st dose (Table 2). All 21 participants (100%) who received the 113
mRNA-1237 vaccine reported injection site symptoms, while only 21 (78%) of 27 BNT-114
162b2 recipients reported injection site symptoms (p=0.02) (Table 2). Two mothers 115
reported slightly less milk production in the first 24-72 hours after vaccine doses (Table 116
2). With respect to infant symptoms, 12% of mothers reported at least one symptom 117
after the 1st maternal vaccine dose (primarily gastrointestinal symptoms and sleep 118
changes), and none reported an infant symptom after the 2nd dose (Table 3). In 119
summary, no severe adverse effects for mothers or nursing infants were reported in this 120
cohort after vaccination, and reported symptoms resolved up to 72 hours after 121
vaccination. 122
PEG detection in human milk. Polyethylene glycol (PEG) is present in the lipid 123
nanoparticles of the mRNA-based vaccines, and was reported to cause allergic reaction 124
after vaccination in rare cases (12, 13). To address concerns about vaccine 125
components passing to milk after vaccination, we performed ELISA assays to measure 126
PEG-ylated proteins levels in milk after vaccination from 13 participants. PEG-ylated 127
proteins were measured in milk samples collected before the vaccine, and at various 128
time points post-vaccination (from 24 hours after 1st dose to 2 weeks after 2nd dose). 129
Pre-vaccine PEG-ylated proteins levels did not significantly differ from PEG-ylated 130
proteins levels at any post-vaccine time point in either paired or unpaired comparisons 131
(Figure 1). 132
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Anti-SARS-CoV-2 antibody levels in blood and milk samples after vaccination. We 133
analyzed blood and milk samples from lactating individuals for anti-SARS-CoV-2 134
antibodies to measure immune response after vaccination. Maternal blood anti-SARS-135
CoV-2 IgM and IgG antibodies increased significantly after the 1st dose (Figure 2). Anti-136
SARS-CoV-2 IgM levels were not significantly higher 4-10 weeks after the 2nd dose 137
compared to samples collected after dose 1 (on the day of the 2nd dose) (Figure 2A). 138
In contrast, anti-SARS-CoV-2 IgG levels increased significantly after the 2nd dose (P 139
value <0.0001) when compared to samples collected immediately prior to the 2nd dose 140
(Figure 2B). There was no significant difference in blood antibody levels between 141
participants who received the mRNA-1237 compared to the BNT-162b2 vaccine after 142
dose 2. 143
We found significantly higher levels of IgA antibodies specific to SARS-CoV-2 RBD 144
protein in human milk samples collected after the 1st dose of both BNT-162b2 and 145
mRNA-1237 vaccines (Figure 3A and 3B). There was no significant increase in milk 146
anti-RBD IgA after the 2nd vaccination as compared to after dose 1 (Figure 3A and 147
3B). Twelve individuals (25%, BNT-162b2 n=7; mRNA-1237 n=5) did not have 148
detectable levels of anti-RBD IgA after either the 1st or 2nd dose (infants age at 1st 149
dose range 1-11 months). Milk anti-RBD IgG levels increased after the 1st dose of 150
vaccine and increased further after the 2nd dose (Figure 3C and 3D). There were no 151
significant differences in milk anti-RBD IgG levels between women who received BNT-152
162b2 (Figure 3C) and mRNA-1237 (Figure 3D). These findings suggest that mRNA 153
vaccine results in a robust immune response leading to increased anti SARS-CoV-2 154
antibody levels in blood, but also in milk during lactation. 155
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Correlations between antibody levels, participant characteristics, and symptoms. 156
In order to better understand the differences in antibody responses between individuals 157
in our cohort, we performed multiple correlation tests to determine whether IgG and IgA 158
antibodies levels correlated with timing of sample collection after vaccination (range 4-159
10 weeks after 2nd dose), infant age at time of vaccination, or maternal BMI (Table S2). 160
Milk IgA (but not IgG) levels declined significantly as the infant age at time of 161
vaccination increased (Figure 4A and 4B). There was no significant correlation 162
between IgG and IgA levels and either the length of time after 2nd dose or maternal BMI 163
(Table S2 and S3). The levels of IgG and IgA antibodies induced in milk were 164
significantly correlated after 1st dose (Figure 4C), but not after the 2nd dose (Figure 165
4D). There was no correlation between the anti SARS-CoV-2 IgG levels in blood and 166
milk after 1st dose (Figure 4E), but there was a positive correlation between levels at 4-167
10 weeks after 2nd dose (Figure 4F). 168
Plasma levels of anti-SARS-CoV-2 IgG are not detectable in infants after maternal 169
vaccination during lactation. Although maternal IgG antibodies have been shown in 170
multiple studies to transfer to the infant in utero, there are little data to suggest that milk-171
derived antibodies are similarly transferred to the infant blood circulation during 172
breastfeeding. To investigate whether passive immunity is conferred to the infant’s 173
blood after maternal vaccination during lactation, we analyzed infant blood samples 174
from mothers who were vaccinated after delivery (n=8) and compared to infant blood 175
samples form mothers who were vaccinated against COVID-19 during pregnancy (n=2). 176
Blood samples were collected from these 10 infants (5 male, 5 female) at 61 days to 1 177
year of age (Table S4). Plasma was tested for the presence of anti-SARS-CoV-2 IgG 178
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and IgM and anti-RBD IgA. We evaluated infant blood samples collected at time frame 179
of 4-15 weeks after 2nd dose as this time point corresponded to high anti-SARS-CoV-2 180
IgG levels in mothers’ blood and milk (Figure 2 and 3). No antibodies were detected in 181
the blood of nursing infants born to mothers who were vaccinated postpartum (Figure 182
5), despite high IgG levels in maternal blood and milk. In contrast, infants born to 183
mothers who received both doses of vaccine during pregnancy had detectable plasma 184
anti-SARS-CoV-2 IgG levels at follow-up (infant age range 61-65 days, 125-129 days 185
after maternal dose 1) (Figure 5). None of the follow-up infant blood samples (from the 186
lactation or pregnancy cohorts) had detectable levels of anti-RBD IgA antibodies. These 187
results demonstrate that vaccination during lactation induces anti-SARS-CoV-2 188
antibodies in human milk, but only vaccination during pregnancy and not lactation 189
provides additional transfer of anti-SARS-CoV-2 antibodies to the infant blood. 190
We also investigated whether ingested antibodies could survive passage through the 191
infant gastrointestinal tract by testing infant stool for anti-SARS-CoV-2 antibodies after 192
vaccination (Figure S1) in one mother-infant dyad. We found that IgG (but not IgA) was 193
detected in infant stool samples and were correlated with maternal milk anti-SARS-CoV-194
2 IgG levels. 195
196
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Conclusion: 197
Our study provides one of the first detailed reports on patient symptoms and antibody 198
responses of the COVID-19 mRNA vaccines in lactating mothers. We found that the 199
rates of reported symptoms were similar to the CDC report from the V-Safe registry(14) 200
but higher than described in the clinical trials, although we do not have a non-lactating 201
comparison group. Importantly, there were no significant side effects noted in the infants 202
of mothers vaccinated during breastfeeding. Comparing the mRNA vaccines made by 203
current manufacturers, we found that lactating individuals may experience more 204
vaccine-related side effects after mRNA-1237 compared to BNT-162b2 vaccine; 205
however, no differences in immune response were observed between those vaccines. 206
It has recently been shown in a few studies that vaccine mRNA is not present in 207
milk samples after vaccination(15, 16), or is only detected in very low levels in some 208
cases(17), providing reassurance that risks of exposure to the breastfed infant are 209
minimal. This study adds to the evidence that vaccine components are minimally 210
transferred to human milk. We found no significant increase in milk PEG-ylated protein 211
concentrations at various time points after vaccine administration in a subset of samples 212
analyzed in our cohort. We did observe one sample with higher ratio of PEG-ylated 213
proteins 24 hours post vaccination (Figure 1, patient 030). This sample had PEG-ylated 214
protein levels equivalent to 2.8µl/ml vaccine. However, we cannot confirm that the 215
increased PEG in this single sample was from the COVID-19 vaccine, as PEG exposure 216
may also be from other sources, such laxatives or ibuprofen. There was no increase in 217
protein PEG-ylation ratio after 2nd dose in the same individual, and no unusual 218
symptoms were reported in either the mother or her infant. Larger studies are needed to 219
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increase our understanding of transfer of PEG into human milk, and potential effects 220
after ingestion by the infant. Although expert consensus states there is minimal or no 221
potential risk for the infant from maternal COVID-19 vaccination(18, 19), the minor 222
symptoms that were reported (sleep changes and gastrointestinal symptoms) should be 223
further investigated in future studies to determine if they are related to vaccination. Our 224
findings also suggest that administration of maternal mRNA-based vaccine during 225
lactation did not lead to a detectable immune response in the infant blood, which further 226
suggests that the vaccine is not transferred to the infant via milk and cannot trigger 227
infant immune responses via that route. 228
We also demonstrate that COVID-19 mRNA vaccination induces significant 229
increases in anti-SARS-CoV-2 IgM and IgG levels in lactating mothers’ blood. 230
Consistent with previous studies that showed IgM levels plateaued 28 days after 231
COVID-19 infection (20), our results also demonstrated that dose 2 did not induce 232
significantly higher levels of IgM than was is observed after dose 1. In contrast, 233
maternal blood IgG levels increased by 6-fold after the 2nd dose (compare to the levels 234
after the 1st dose), highlighting the importance of the 2nd dose to boost the antibody 235
response (21). 236
Due to the lack of data about vaccination during pregnancy, many pregnant 237
individuals were initially denied access to, declined, or were recommended to delay 238
vaccination until after pregnancy. As such, many mothers have waited until after 239
delivery to receive the vaccine. Although mothers vaccinated during lactation 240
transferred antibodies to their infant through milk, which is an important component of 241
mucosal immunity for the baby, there was no passive transfer of antibodies to the infant 242
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bloodstream, as occurs if the mother is vaccinated during pregnancy. Correlates of 243
infant immune protection to COVID-19 are not yet well understood, however passive in 244
utero transfer of IgG to the infant is important in the prevention of a number of infections 245
including pertussis and influenza (22–24). Passively-transferred milk-derived IgA likely 246
provides partial mucosal immune protection in infants, as breastfeeding is associated 247
with lower risk of infections associated with mucosal defense, especially against 248
respiratory infections (25–27). 249
Two nursing infants in our cohort were infected with COVID-19 during the study 250
(one a week post maternal 2nd dose, and the second one between 1st and 2nd 251
maternal vaccine), indicating that milk antibodies cannot fully protect against SARS-252
CoV-2 infection, especially at the time before full immune response is achieved in the 253
vaccinated mother, typically 2-3 weeks after the booster dose (Figure 2D). Further 254
studies are needed to determine the degree of protection conferred by IgA and IgG anti-255
SARS-CoV-2 antibodies that are present in milk. Interestingly, we demonstrated for the 256
first time that anti-SARS-CoV-2 RBD IgG antibodies are detectable in stool samples 257
collected 4 and 8 weeks post maternal vaccine (Figure S1), which suggests that milk-258
derived antibodies can persist in the infant gastrointestinal tract and provide protection 259
against viral infection via the digestive system(28). Further studies evaluating the 260
additive benefit of both transplacentally-derived maternal IgG, as well as milk-derived 261
IgA and IgG are needed to determine protection against COVID-19 in early infancy. Our 262
findings demonstrate the importance of determining the optimal timing of vaccine 263
administration to confer maximal protection against COVID-19 in infancy. 264
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Twenty-five percent of women in our cohort had no detectable levels of anti-RBD 265
IgA in their milk after vaccination. Similar findings were reported in other studies (5, 6), 266
suggesting that production and transfer efficiency vary between individuals. Our 267
analysis showed a negative correlation between infant age and milk anti-RBD IgA 268
levels, which might explain some of the variation in milk IgA levels observed between 269
different individuals. Ten out of the 12 participants who had no detectable anti-RBD IgA, 270
had infants older than 5.5 months at the time of sample collection. Further studies are 271
needed to investigate the relationship between infant age, breastfeeding exclusivity, 272
milk IgA antibodies, and optimal timing of vaccination during lactation. 273
Strengths of our study include the prospective design and comprehensive 274
symptom reporting by the vaccinated participants. We also report on longitudinal follow-275
up of infant immune responses, which has not been previously described. Furthermore, 276
we included both BNT162b2 and mRNA-1273 vaccines and compared responses 277
between the two vaccine manufacturers. Limitations include the small sample size, and 278
that not all samples were able to be collected from all infant participants. 279
In summary, our study reports that no severe adverse effects were noted in 280
lactating individuals or their breastfeeding infants after COVID-19 mRNA vaccination. 281
We demonstrated that human milk confers passive immunity to the infants, primarily 282
through mucosal immunity in the gastrointestinal tract provided by IgA and IgG in milk. 283
These results are important evidence to aid in counseling lactating individuals on the 284
safety and efficacy of the COVID-19 mRNA vaccines, and the potential benefits to both 285
the mother and infant. 286
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Methods: 287
Study approval and study population. The institutional review board of the University of 288
California San Francisco approved the study. Written, informed consent was obtained 289
from all study volunteers in the COVID-19 Vaccine in Pregnancy and Lactation 290
(COVIPAL) cohort study from December 2020 to June 2021. Eligible participants were 291
actively pregnant or lactating, planning to receive any COVID-19 vaccine, and willing to 292
donate blood and/or milk samples. 293
Clinical data collection. Clinical data on vaccine side effects were collected through an 294
online questionnaire that was sent to participants 21 days or more after each vaccine 295
administration. Questionnaires were distributed using REDCap. 296
Sample collection. Maternal blood and milk samples were collected at three time points: 297
1) up to 1 day before the 1st dose (pre-vaccine); 2) on the day of and prior to 298
administration of the 2nd dose (after 1st dose); and between 4-10 weeks after the 2nd 299
dose (after 2nd dose). In some cases, additional milk samples were collected up to 31 300
days before the 1st dose, 24 hours after each dose, and weekly for up to 4 weeks after 301
the 2nd dose. Infant blood was collected by heel stick by trained study staff at 5-15 302
weeks after 2nd maternal vaccination. 303
Milk processing. Fresh human milk samples were self-collected by participants into 304
sterile containers at several time points before, during, and after vaccination. Milk 305
samples were either collected immediately by the study staff or frozen by mothers in 306
their home freezer as soon as possible after pumping. Samples were kept on ice during 307
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transport from home to the lab for processing. Milk was aliquoted and stored in -80°C 308
until analyzed. 309
Measurement of SARS-CoV-2 specific IgM and IgG in plasma samples. Whole blood 310
was collected into tubes containing EDTA. Plasma was isolated from whole blood by 311
centrifugation and immediately cryopreserved at -80°C until analysis. Anti-SARS-CoV-2 312
plasma IgM and IgG antibodies were measured using the Pylon 3D automated 313
immunoassay system(29) (ET Healthcare, Palo Alto, CA). In brief, quartz glass probes 314
pre-coated with either affinity-purified goat anti-human IgM (IgM capture) or Protein G 315
(IgG capture) were dipped into diluted plasma samples, washed, and then dipped into 316
the assay reagent containing both biotinylated, recombinant spike protein receptor 317
binding domain (RBD) and nucleocapsid protein (NP). After washing, the probes were 318
incubated with Cy®5-streptavidin (Cy5-SA) polysaccharide conjugate reagent, allowing 319
for cyclic amplification of the fluorescence signal. The background-corrected signal of 320
SARS-CoV-2 specific antibodies was reported as relative fluorescent units (RFU). IgM 321
and IgG measurements greater than 50 RFU were considered positive RFUs. 322
Measurement of IgA and IgG by ELISA assay in milk. After thawing, milk fat was 323
separated by cold centrifugation (10,000g for 10 min, 4°C). Milk supernatant samples 324
were diluted 1:2 in sample diluent buffer and were plated in duplicate on a 96-well plate 325
containing S1 spike protein RBD (Ray-Biotech, GA, USA, IEQ-CoVS1RBD-IgG-1 and 326
IEQ-CoVS1RBD-IgA-1). For IgA assays, samples were also plated in duplicate on a 327
second 96-well plate coated with human albumin to account for non-specific binding. 328
OD values for albumin were subtracted from the OD values for RBD. Each plate 329
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contained seven anti-RBD standards and one blank negative control. The mean 330
absorbance of each sample was captured on an ELISA plate reader at 450 nm. 331
Background values (blank negative control) were subtracted from the albumin and RBD 332
plates. Standard controls were used to create a standard curve and determine the level 333
of anti-RBD IgA and IgG in unit/ml. 334
Measurement of Polyethylene Glycol (PEG) in human milk by ELISA. Milk supernatant 335
was diluted 1:8 with the provided sample buffer and analyzed by PEGylated protein 336
ELISA kit (Enzo, Farmingdale, NY, USA). Seven wells of each plate were loaded with 337
serial dilutions (1:2) of mRNA-1273 or BNT162b2 to generate the standard curve for 338
each vaccine (Figure 1A). In addition, vaccines were inoculated into human milk 339
samples at three different concentrations (33µl/ml, 3.3µl/ml and 0.33µl/ml) and were 340
analyzed separately to ensure the ability of the kit to detect the vaccine PEGylated 341
components in milk samples (Figure 1B). Prism 9 (v 9.1.2) was used to interpolate 342
vaccine concentration in the samples based on OD values, using a sigmoidal, four 343
parameters logistic curve. A mean of pre-vaccine milk PEG concentration was 344
calculated based on 13 pre-vaccine samples analyzed. Results are presented as a ratio 345
of sample concentration divided by the mean pre-vaccine milk PEG concentration. 346
Statistics: All data analyses were conducted using Stata statistical software (v14, 347
College Station, TX). Descriptive statistics included frequencies for categorical 348
variables, and means, standard deviations, medians, and ranges for continuous 349
variables. Group differences in categorical variables were analyzed using Fisher’s exact 350
test, and group differences in continuous variables were analyzed using Mann-Whiney 351
U tests. McNemar tests were used to evaluate differences in symptom frequencies after 352
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each vaccine dose. Spearman correlations was used to assess the magnitude of 353
associations between continuous variables. Non-parametric tests were used to 354
accommodate non-normal distributions and small group sizes. 355
356
357
358
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Author contribution: 359
YG designed the study, conducted experiments, acquired data, analyzed data, and was 360
lead author of the manuscript. MP designed the study, conducted experiments, acquired 361
data, analyzed data, assisted with editing and writing the manuscript. AC recruited 362
participants, acquired data, and assisted with editing and writing the manuscript. CG 363
analyzed data, conducted statistical analysis assisted with editing the manuscript. 364
AHBW providing reagents and acquired data. UJ collected samples and conducted 365
experiments. CYL recruited participants and collected samples. VJG, LW, SB, LL 366
collected and process samples. EB collected and processed samples and assisted with 367
editing the manuscript. IVA assisted with study and questionnaires design and editing 368
and writing the manuscript. NA supervised the study and assisted in writing the 369
manuscript. SLG and VJF designed and supervised the study and assisted in writing the 370
manuscript. 371
372
373
374
375
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448
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Funding: 450
These studies were supported by the Marino Family Foundation (to M.P), the National 451
Institutes of Health (NIAID K23AI127886 to M.P. and NIAID K08AI141728 to S.L.G.), 452
the Krzyzewski Family (to S.L.G), the Weizmann Institute of Science -National 453
Postdoctoral Award Program for Advancing Women in Science (to Y.G.), the 454
International Society for Research In Human Milk and Lactation (ISRHML) Trainee 455
Bridge Fund (to Y.G.), and of the Human Frontier Science Program (to Y.G.). 456
457
458
459
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Figures: 460
461
Figure 1: Detection of vaccine PEG in human milk samples. A) different vaccine 462
concentrations were used to generate a standard curve of OD (Y axis) vs. vaccine 463 concentration (X axis). Vaccine concentrations in each sample were interpolated based 464
on Sigmoidal, four-parameter logistic (4PL) curve. B) mRNA-1273 and BNT-162b2 465 vaccines were inoculated separately from pre-vaccine milk samples and were used to 466
ensure the assay’s sensitivity to detect the vaccine PEG components in milk samples. 467 C) Values shown in heat map are the ratio of calculated PEG concentration in each 468
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sample to average PEG concentration in all pre-vaccine milk samples. No significant 469 differences were observed between samples collected at any of the post vaccine (PV) 470
time points and the pre-vaccine samples (paired and unpaired two-tailed t-tests). Y axes 471 represent time of sample collection, as hours (h) or weeks (w) Post vaccine 1 (PV 1), or 472
Post vaccine 2 (PV 2). 473
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474
Figure 2: Elevated levels of plasma anti-SARS-CoV2 antibodies in COVID-19 475
mRNA vaccinated lactating individuals. Anti-SARS-CoV2 IgM (A) and IgG (B) levels 476
in plasma of lactating individuals post COVID-19 mRNA vaccine (RFU- relative 477
fluorescent units, positive cut-off >50 RFU). After 1st dose samples were collected on 478
the day of the second vaccine, and after 2nd dose samples were collect 4-10 weeks 479
post 2nd dose. Asterisks represent p-values: *= p-value <0.05, **= p-value <0.01, ***= 480
<0.001, ****= <0.0001 as determined by unpaired Mann-Whitney test. 481
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482
Figure 3: Elevated levels of milk anti-SARS-CoV2 IgA antibodies in COVID-19 483 mRNA vaccinated lactating individuals. Milk samples from individuals receiving BNT-484
162b2 (n=27) (A) and mRNA-1273 (n=21) (B) anti- SARS-CoV2 vaccines were 485 analyzed for anti-SARS-CoV2 IgA antibodies using ELISA at various time points as 486
indicated on the X axis. After 1st dose samples were collected on the day of the second 487 vaccine, and after 2nd dose samples were collect 4-10 weeks post 2nd dose. Milk anti-488
SARS-CoV2 IgG levels were measured using ELISA in milk samples from individuals 489 receiving BNT-162b2 (n=27) (C) or mRNA-1273 (n=21) (D). Asterisks represent p-490 values: *= p-value <0.05, **= p-value <0.01, ***= <0.001 as determined by unpaired 491
Mann-Whitney test. 492
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493
Figure 4: Correlations between milk antibodies, blood antibodies and infant age. 494
Two-tailed Spearman correlation was used to correlate milk IgA (A) and IgG (B) levels 495
(Y axis) and infant age (X axis) 4-10 weeks after the 2nd dose administration (n=30). In 496
addition, two-tailed Spearman correlation was used to correlate milk IgG (Y axis) and 497
milk IgA levels (X axis) on the day of 2nd dose administration(C), 21-28 days after 1st 498
dose (n=35) and and 4-10 weeks after 2nd dose (D). We also tested correlation 499
between milk (Y axis) and maternal plasma (X axis) IgG levels at day of 2nd dose (E) 500
and 4-10 weeks after the 2nd dose administration (F) (n=30). 501
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502
Figure 5: Transfer of anti-SARS-CoV2 IgG from mother to infant. IgG levels were 503
measured in blood samples of infants and mothers 61 days to 1 year postpartum, 61-504
129 days after 1st maternal vaccine administration. Maternal and infant samples were 505
collected in the same week (except in one case in which the maternal sample was 506
collected 18 days prior to the infant sample). X axis represents the time at which the 507
mother received the 1st dose: during pregnancy (pink), or after delivery (red). (RFU- 508
relative fluorescent units, dashed line represents positive cut-off >50 RFU). Sample 509
characteristics and individual antibodies levels are present in Table S4. 510
511
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Tables: 512
Table 1. Sample characteristics overall and by vaccine manufacturer 513
Sample Characteristics Full Cohort (n=48, 100%)
BNT162b2 (n=27, 56%)
mRNA-1237 (n=21, 44%)
Maternal characteristics
Maternal age, years
Median (min, max) 35 (27, 46) 35 (30, 45) 35 (27, 46)
Race/ethnicity, % (n)
Asian 31% (15) 30% (8) 33% (7)
Black or African American 2% (1) 4% (1) 0% (0)
White/Caucasian 59% (28) 55% (15) 62% (13)
Other (Arab) 2% (1) 0% (0) 5% (1)
More than 1 race/ethnicity (White+Latina/Asian/Middle Eastern)
6% (3) 11% (3) 0% (0)
Highest level of education completed
Some college 2% (1) 0% (0) 5% (1)
College graduate 17% (8) 19% (5) 14% (3)
Advanced degree 81% (39) 81% (22) 81% (17)
Work in health care?
Yes, providing direct patient care 58% (28) 52% (14) 67% (14)
Yes, but not in direct patient care 19% (9) 15% (4) 24% (5)
No 23% (11) 33% (9) 9% (2)
Pre-Pregnancy Body Mass Index
Median (min, max) 23.4 (19.1, 37.5)
23.4 (19.1, 35.9)
22.8 (19.6, 37.5)
Number of children
1 40% (19) 41% (11) 38% (8)
2 46% (22) 41% (11) 52% (11)
3 12% (6) 15% (4) 10% (2)
4 2% (1) 3% (1) 0% (0)
Duration of most recent pregnancy, weeks
Median (min, max) 39.0 (33.9, 41.1)
39.1 (33.9, 41.0)
39.0 (37.4, 41.1)
Infant characteristics
Infant age at maternal 1st dose, months
Median (min, max) 4.7 (0.1, 17.2)
4.8 (0.2, 15.2)
4.6 (0.1, 17.2)
Sex, % (n)
Male 60% (29) 67% (18) 52% (11)
Female 40% (19) 33% (9) 48% (10)
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Exclusively breastfeeding (and no solids)
Yes 23% (11) 22% (6) 24% (5)
No 77% (37) 78% (21) 76% (16)
Days after vaccine that symptoms were assessed
Dose 1
Mean (SD) 78.7 (31.8) 78.3 (35.4) 79.2 (27.4)
Median (min, max) 81 (18, 154] 78 (18, 154) 86 (26, 117)
Dose 2
Mean (SD) 59.6 (25.1) 62.6 (28.3) 55.8 (20.2)
Median (min, max) 58.5 (28, 133)
57 (29, 133) 60 (28, 89)
Note: None of the characteristics above differed significantly by vaccine manufacturer. 514
Abbreviations: Standard deviation (SD), minimum (min), maximum (max) 515
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Table 2: Symptoms after each vaccine dose 516
Symptoms Full Cohort: After 1st dose After 2nd dose
1st dose
2nd dose
P-valuea
BNT162b2 mRNA-1237
p-valueb
BNT162b2 mRNA-1237
p-valueb
n=48 n=27 n=21 n=27 n=21
Injection site symptoms, % (n)
Any injection site symptoms
88% (42)
88% (42)
>0.99 78% (21) 100% (21)
0.02 78% (21) 100% (21)
.02
Pain 88% (42)
85% (41)
0.71 78% (21) 100% (21)
0.02 78% (21) 95% (20)
0.12
Redness 4% (2)
10% (5)
0.08 0% (0) 10% (2) 0.19 4% (1) 19% (4) 0.15
Swelling 17% (8)
17% (8)
>0.99 7% (2) 29% (6) 0.12 11% (3) 24% (5) 0.27
Itching 4% (2)
4% (2)
>0.99 4% (1) 5% (1) >.99 4% (1) 5% (1) >.99
Rash around injection site
2% (1)
4% (2)
0.32 0% (0) 5% (1) 0.44 0% (0) 10% (2) 0.19
Generalized symptoms, % (n)
Any general symptoms 48% (23)
92% (44)
<0.001 44% (12) 52% (11)
0.77 85% (23) 100% (21)
0.12
Fever 12% (6)
62% (30)
<0.001 19% (5) 5% (1) 0.21 52% (14) 76% (16) 0.13
Chills 8% (4)
48% (23)
<0.001 11% (3) 5% (1) 0.62 37% (10) 62% (13)
0.14
Headache 21% (10)
67% (32)
<0.001 11% (3) 33% (7) 0.08 56% (15) 81% (17)
0.07
Joint pain 8% (4)
31% (15)
0.002 7% (2) 10% (2) >0.99 30% (8) 33% (7) >0.99
Muscle/body aches 21% (10)
69% (33)
<0.001 30% (8) 10% (2) 0.15 59% (16) 81% (17)
0.13
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Fatigue or tiredness 44% (21)
81% (39)
<0.001 41% (11) 48% (10)
0.77 67% (18) 100% (21)
0.003
Nausea 4% (2)
12% (6)
0.10 4% (1) 5% (1) >0.99 7% (2) 19% (4) 0.38
Vomiting 0% (0)
0% (0)
--- 0% (0) 0% (0) --- 0% (0) 0% (0) ----
Diarrhea 4% (2)
4% (2)
>0.99 4% (1) 5% (1) >0.99 0% (0) 10% (2) 0.19
Abdominal pain 2% (1)
0% (0)
0.32 0% (0) 5% (1) 0.44 0% (0) 0% (0) ----
Rash not near injection site
0% (0)
0% (0)
--- 0% (0) 0% (0) --- 0% (0) 0% (0) ----
Lump/swelling in breast (same side as injection)
0% (0)
2% (1)
0.32 0% (0) 0% (0) --- 4% (1) 0% (0) >0.99
Lump/swelling in breast (opposite side as injection)
0% (0)
0% (0)
--- 0% (0) 0% (0) --- 0% (0) 0% (0) ----
Mastitis 2% (1)
0% (0)
0.32 0% (0) 5% (1) 0.44 0% (0) 0% (0) ----
Decrease in milk supply 2% (1)
2% (1)
>0.99 0% (0) 5% (1) 0.44 0% (0) 5% (1) 0.44
a McNemar’s test; b Fisher’s Exact test517
518
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35
Table 3. Infant symptoms reported after maternal vaccination (write-in only) 519
INFANT SYMPTOMS % (n) Vaccine
After 1st vaccine dose
None / no changes / blank 88% (42)
“My baby seemed a little tired.” 2% (1) BNT162b2
“He started pooping a lot! And it was more sour smelling diarrhea like poops. I don't know if there is any correlation”
2% (1) BNT162b2
“It could have been a fluke, but both my infant and I slept through the night for the first time the night after I received the 1st dose of the vaccine.”
2% (1) BNT162b2
“He had some diaper rash, but likely unrelated” 2% (1) BNT162b2
“Rash on the face / worsening of baby acne” 2% (1) mRNA-1237
“Disrupted sleep, waking at night when he usually doesn't. More fussy than normal.”
2% (1) mRNA-1237
After 2nd vaccine dose
None / no changes / blank 100% (48)
520
521
522
523
524
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Table S1. Participants testing positive for SARS-CoV-2 during the study period 525
Participants testing positive for SARS-CoV-2
Participant ID: 1 2 3
Mother positive for SARS-CoV-2 No Yes Yes
Infant positive for SARS-CoV-2 Yes Yes No
Other people in the household diagnosed Yes N/A No
Time of diagnosis 1 week after 2nd dose
N/A 10 day before 1st dose
Baby exclusively breastfed No Yes No
Maternal blood IgG (RFU)
On the day of 2nd dose 244 5503 N/A
4 weeks after 2nd dose 2558 5290 N/A
Infant blood IgG (RFU)
4 weeks after 2nd vaccine dose N/A 1928 N/A
Infant blood IgA (U/ml)
4 weeks after 2nd vaccine dose N/A 122 N/A
Milk anti-RBD IgG levels (U/ml)
Pre-vaccine N/A 55 7.3
On the day of 2nd dose 246 2653 323
4 weeks after 2nd dose 375 2834 250
Maternal blood positive for anti SARS-CoV2-N-protein antibodies
N/A Samples collected on day of 2nd dose and 5 weeks after
2nd dose were positive.
N/A
Maternal injection site symptoms
Reported after 1st vaccine dose: Pain Pain, Itching None
Reported after 2nd vaccine dose: Pain None Pain
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37
Maternal generalized symptoms
Reported after 1st vaccine dose: None None None
Reported after 2nd vaccine dose: Fever, Chills, Muscle aches or body aches,
Fatigue or tiredness
Fever, Chills, Fatigue or tiredness
Fatigue or tiredness
Baby symptoms
After 1st dose None None None
after 2nd dose: None Less active. Feverish.
None
526
527
528
529
530
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38
Table S2. Correlations between antibody levels and timing of samples in relation to childbirth and vaccine 531
Antibodies and sample types being correlated
N Spearman correlations
rho p
Samples collected after 1st dose
IgG in maternal blood and … 24
Time from childbirth to collection
0.38 0.07
Time from 2nd dose to sample -0.11 0.59
IgG in breast milk and … 35
Time from childbirth to sample -.05 0.75
Time from 2nd dose to sample -0.12 0.47
IgA in breast milk and … 38
Time from childbirth to sample -0.18 0.28
Time from 2nd dose to sample 0.12 0.45
Samples collected after dose 2
IgG in maternal blood and … 32
Time from childbirth to sample 0.01 0.92
Time from 2nd dose to sample -0.34 0.05
IgG in breast milk and … 44
Time from childbirth to sample 0.04 0.75
Time from 2nd dose to sample 0.21 0.16
IgA in breast milk and … 43
Time from childbirth to sample -0.35 0.02
Time from 2nd dose to sample -0.17 0.27
532
533
534
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39
Table S3. Antibody levels were not significantly correlated with maternal BMI 535
Correlation between maternal BMI and the following antibody levels:
n
Spearman correlations
rho p
After 1st dose
IgG in maternal blood 24 -.071 .74
IgG in milk 35 -.029 .87
IgA in milk 38 -.204 .22
4-10 weeks after 2nd dose
IgG in maternal blood 32 .113 .54
IgG in milk 44 -.101 .51
IgA in milk 43 .115 .46
536
537
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40
Table S4. Follow up maternal and infant blood samples characteristics and anti-SARS-CoV2 IgG levels 538
Participant #
Participant Cohort:
Infant sex
Infant age at
sample date
(months):
Infant age at
1st dose (months)
Time since 1st
dose until
infant sample
collection (days)
Infant anti-SARS-
CoV2 IgG antibodies
(RFU):
Maternal anti-
SARS-CoV2 IgG
antibodies
(RFU):
Vaccine type:
1 Lactating Female 0-3 0-3 84 6 2768 mRNA-1237
2 Lactating Male 0-3 0-3 58 2 1791 mRNA-1237
3 Lactating Female 0-3 0-3 64 0 1638 BNT162b2
4 Lactating Female 3-6 0-3 67 4 5028 mRNA-1237
5 Lactating Female 3-6 0-3 61 6 3449 mRNA-1237
6 Lactating Male 6-9 3-6 81 7 3292 mRNA-1237
7 Lactating Male 9-12 6-9 103 2 1574 mRNA-1237
8 Lactating Male >12 9-12 62 3 3418 BNT162b2
9 Pregnant male 0-3 -2 129 812 271 BNT162b2
10 Pregnant female 0-3 -2 125 1604 288 mRNA-1237
Note: negative values in infant age represent days before delivery. RFU>50 considered as positive value. 539
540
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541
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Menstrual changes after covid-19 vaccinationA link is plausible and should be investigated
Victoria Male lecturer in reproductive immunology
Common side effects of covid-19 vaccination listedby the UK’s Medicines and Healthcare ProductsRegulatoryAgency (MHRA) include a sore arm, fever,fatigue, and myalgia.1 Changes to periods andunexpected vaginal bleeding are not listed, butprimary care clinicians and those working inreproductive health are increasingly approached bypeople who have experienced these events shortlyafter vaccination. More than 30 000 reports of theseevents had been made to MHRA’s yellow cardsurveillance scheme for adverse drug reactions by 2September 2021, across all covid-19 vaccines currentlyoffered.1
Most peoplewho report a change to their period aftervaccination find that it returns to normal thefollowing cycle and, importantly, there is no evidencethat covid-19 vaccination adversely affects fertility.In clinical trials, unintended pregnancies occurredat similar rates in vaccinated and unvaccinatedgroups.2 In assisted reproduction clinics, fertilitymeasures and pregnancy rates are similar invaccinated and unvaccinated patients.3 -6
MHRA states that evaluation of yellow card reportsdoesnot support a linkbetweenchanges tomenstrualperiods and covid-19 vaccines since the number ofreports is low relative to both the number of peoplevaccinated and theprevalence ofmenstrual disordersgenerally.7 However, the way in which yellow carddata are collected makes firm conclusions difficult.Approaches better equipped to compare rates ofmenstrual variation in vaccinated versusunvaccinated populations are needed, and the USNational Institutes ofHealthhasmade$1.67m (£1.2m;€1.4m) available to encourage this importantresearch.8
Menstrual changes have been reported after bothmRNA and adenovirus vectored covid-19 vaccines,1suggesting that, if there is a connection, it is likelyto be a result of the immune response to vaccinationrather than a specific vaccine component.Vaccination against human papillomavirus (HPV)has also been associated with menstrual changes.9Indeed, the menstrual cycle can be affected byimmune activation in response to various stimuli,includingviral infection: inone studyofmenstruatingwomen, around a quarter of those infected withSARS-CoV-2 experienced menstrual disruption.10
Biologically plausible mechanisms linking immunestimulation with menstrual changes includeimmunological influences on the hormones drivingthe menstrual cycle11 or effects mediated by immunecells in the lining of the uterus, which are involvedin the cyclical build-up and breakdown of thistissue.12 Research exploring a possible association
between covid-19 vaccines and menstrual changesmay also help understand the mechanism.
Although reported changes to the menstrual cycleafter vaccination are short lived, robust research intothis possible adverse reaction remains critical to theoverall success of the vaccination programme.Vaccine hesitancy among young women is largelydriven by false claims that covid-19 vaccines couldharm their chances of future pregnancy.13 Failing tothoroughly investigate reports of menstrual changesafter vaccination is likely to fuel these fears. If a linkbetween vaccination and menstrual changes isconfirmed, this information will allow people to planfor potentially altered cycles. Clear and trustedinformation is particularly important for those whorely on being able to predict their menstrual cyclesto either achieve or avoid pregnancy.
We are still awaiting definitive evidence, but in theinterim how should clinicians counsel those whohave experienced these effects? Initially, they shouldbe encouraged to report any changes to periods orunexpected vaginal bleeding to the MHRA’s yellowcard scheme. This will provide more complete datato facilitate research into any link and signal topatients that their concerns about vaccine safety aretaken seriously, building trust. In terms ofmanagement, the Royal College of Obstetricians andGynaecologists and the MHRA recommend thatanyone reporting a change in periods persisting overseveral cycles, or new vaginal bleeding after themenopause, should be managed according to theusual clinical guidelines for these conditions.7 14
One important lesson is that the effects of medicalinterventions on menstruation should not be anafterthought in future research. Clinical trials providethe ideal setting in which to differentiate betweenmenstrual changes caused by interventions fromthose that occur anyway, but participants areunlikelyto report changes toperiodsunless specifically asked.Informationaboutmenstrual cycles andother vaginalbleeding should be actively solicited in future clinicaltrials, including trials of covid-19 vaccines.
Competing interests: The BMJ has judged that there are no disqualifying financialties to commercial companies. The author declares the following other interests:research funding from theWellcome Trust and research charity Borne; paymentsto act as an external examiner for the University of Cambridge and the Universityof Leeds; and royalties received for my contribution to Immunology 9th edition(Elsevier). Further details of The BMJ policy on financial interests is here:https://www.bmj.com/sites/default/files/attachments/resources/2016/03/16-current-bmj-education-coi-form.pdf.
Provenance and peer review: Commissioned; not externally peer reviewed.
1 Medicines and Healthcare Products Regulatory Agency. Coronavirusvaccine—weekly summary of yellow card reporting. 2021.https://www.gov.uk/government/publications/coronavirus-covid-19-vaccine-adverse-reactions/coronavirus-vaccine-summary-of-yellow-card-report-ing#annex-1-vaccine-analysis-print
1the bmj | BMJ ${year};374:n2211 | doi: 10.1136/bmj.n2211
EDITORIALS
Department of Metabolism, Digestionand Reproduction, Imperial CollegeLondon, Chelsea and WestminsterHospital Campus, London, UK
Cite this as: BMJ ${year};374:n2211
http://dx.doi.org/10.1136/bmj.n2211
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2 Male V. Are covid-19 vaccines safe in pregnancy?Nat Rev Immunol 2021;21:200-1.doi: 10.1038/s41577-021-00525-y pmid: 33658707
3 Morris RS. SARS-CoV-2 spike protein seropositivity from vaccination or infection does not causesterility. F S Rep 2021. doi: 10.1016/j.xfre.2021.05.010. pmid: 34095871
4 Orvieto R, Noach-Hirsh M, Segev-Zahav A, Haas J, Nahum R, Aizer A. Does mRNA SARS-CoV-2vaccine influence patients’ performance during IVF-ET cycle?Reprod Biol Endocrinol 2021;19:69.doi: 10.1186/s12958-021-00757-6 pmid: 33985514
5 Bentov Y, Beharier O, Moav-Zafrir A, et al. Ovarian follicular function is not altered by SARS-Cov-2infection or BNT162b2 mRNA Covid-19 vaccination. medRxiv 2021:2021.04.09.21255195.[Preprint.] doi: 10.1101/2021.04.09.21255195
6 Safrai M, Rottenstreich A, Herzberg S, Imbar T, Reubinoff B, Ben-Meir A. Stopping themisinformation: BNT162b2 COVID-19 vaccine has no negative effect onwomen’s fertility. medRxiv2021:2021.05.30.21258079 [Preprint.] doi: 10.1101/2021.05.30.21258079
7 Medicines and Healthcare Products Regulatory Agency. COVID-19 vaccines: updates for August2021. https://www.gov.uk/drug-safety-update/covid-19-vaccines-updates-for-august-2021
8 Eunice Kennedy Shriver National Institute of Child Health and Human Development. Item ofinterest: NIH funds studies to assess potential effects of COVID-19 vaccination on menstruation.2021.https://www.nichd.nih.gov/newsroom/news/083021-COVID-19-vaccination-menstruation
9 Suzuki S, Hosono A. No association between HPV vaccine and reported post-vaccinationsymptoms in Japanese young women: Results of the Nagoya study. Papillomavirus Res2018;5:96-103. doi: 10.1016/j.pvr.2018.02.002 pmid: 29481964
10 Li K, Chen G, Hou H, etal. Analysis of sex hormones and menstruation in COVID-19 women ofchild-bearing age. Reprod Biomed Online 2021;42:260-7.doi: 10.1016/j.rbmo.2020.09.020 pmid: 33288478
11 Karagiannis A, Harsoulis F. Gonadal dysfunction in systemic diseases. Eur J Endocrinol2005;152:501-13. doi: 10.1530/eje.1.01886 pmid: 15817904
12 Monin L, Whettlock EM, Male V. Immune responses in the human female reproductive tract.Immunology 2020;160:106-15. doi: 10.1111/imm.13136 pmid: 31630394
13 Speed B. Young women are the unlikely new face of covid-19 vaccine resistance. i News 2021Jan 6. https://inews.co.uk/news/health/coronavirus-latest-experts-debunk-vaccine-fertility-myths-women-819783
14 Royal College of Obstetricians and Gynaecologists. RCOG responds to reports that COVID-19vaccine affects periods. 2021. https://www.rcog.org.uk/en/news/rcog-responds-to-reports-that-covid-19-vaccine-affects-periods/
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the bmj | BMJ ${year};374:n2211 | doi: 10.1136/bmj.n22112
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on 28 October 2021 at U
ni of Zurich. P
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Research Letter
Severe Acute Respiratory SyndromeCoronavirus 2 (SARS-CoV-2) Vaccinationin PregnancyMeasures of Immunity and Placental Histopathology
Elisheva D. Shanes, MD, Sebastian Otero, BA, Leena B. Mithal, MD, MSCI, Chiedza A. Mupanomunda, BS,Emily S. Miller, MD, MPH, and Jeffery A. Goldstein, MD, PhD
INTRODUCTION
Vaccines against severe acute respiratory syn-drome coronavirus 2 (SARS-CoV-2) have been
approved for emergency use, but, despite elevated riskof severe disease, pregnant women were excluded fromthe clinical trials that led to their authorization.1 Placen-tal findings can indicate potential clinical risk and couldbe an early signal for rare injury seen only after wide-spread use in the pregnant population.2–6
Maternal SARS-CoV-2 infection has been associ-ated with decidual arteriopathy, fetal vascular mal-perfusion, and chronic histiocytic intervillositis.7–9
mRNA vaccines induce an immune response throughactivation of TLR3, which has been linked to decidualarteriopathy, growth restriction, preterm delivery, andfetal loss in mouse models.10–14
Our objective was to evaluate the frequency ofthese key placental lesions in patients who receivedSARS-CoV-2 vaccination in pregnancy.
METHODS
The study methods have been described previouslyand were approved by the Northwestern Univer-
sity institutional review board.7,15 We reportresults from patients who tested negative forSARS-CoV-2 infection on polymerase chain reac-tion who received vaccine (delivering between Jan-uary and April 2021) and unvaccinated women in acontrol group (negative for SARS-CoV-2 infectionon polymerase chain reaction, immunoglobulin G–
and immunoglobulin M–negative, deliveringbetween April 2020 and April 2021) from anongoing coronavirus disease 2019 (COVID-19)cohort study. Antibody testing used the ACCESSSARS-CoV-2 spike protein RBD test.
Statistical testing was performed with unpaired ttests or Fisher exact test for demographics and logisticregression with gestational age as a covariate for pla-cental lesions (Python SciPy 1.6.1). A post hoc powercalculation was performed, demonstrating at least 80%power to identify a 2.5-fold or higher increased risk ofany lesion with a baseline prevalence of 10% or greaterand a threefold or higher increased risk of any lesionwith a baseline prevalence of 7% or greater (Stata 15.0).
RESULTS
We report findings in 84 women who received aSARS-CoV-2 vaccine during pregnancy and 116women in a control group who did not receive avaccine (Table 1). Women with vaccination weremore likely to deliver vaginally. The first inocula-tion was 46624 days before delivery for the 75patients with known vaccination timing. Vaccinatedwomen showed robust antibody responses, whereaswomen in the control group were negative (Fig. 1and Table 1).
Placental examination in women with vaccinationshowed no increased incidence of decidual arterio-pathy, fetal vascular malperfusion, low-grade chronicvillitis, or chronic histiocytic intervillositis compared
From the Feinberg School of Medicine, Northwestern University, and the Annand Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois.
Supported by the Friends of Prentice (funder) and NIBIB K08EB030120 (toJAG), Stanley Manne Research Institute and K23AI139337 (to LBM).
Each author has confirmed compliance with the journal’s requirements forauthorship.
Published online ahead-of-print May 11, 2021.
Corresponding author: Jeffery A. Goldstein, MD, PhD, Olson 2-455, FeinbergSchool of Medicine, Chicago IL; email: [email protected].
Financial DisclosureThe authors did not report any potential conflicts of interest.
© 2021 by the American College of Obstetricians and Gynecologists. Publishedby Wolters Kluwer Health, Inc. All rights reserved.ISSN: 0029-7844/21
© 2021 by the American College of Obstetriciansand Gynecologists. Published by Wolters Kluwer Health, Inc.
Unauthorized reproduction of this article is prohibited.
VOL. 138, NO. 2, AUGUST 2021 OBSTETRICS & GYNECOLOGY 281
with women in the control group (Table 1). Incidenceof high-grade chronic villitis was higher in the controlgroup than in the vaccinated group.
DISCUSSION
In our cohort of vaccinated pregnant patients, therewas no observed increase in the incidence of findingscharacteristic of SARS-CoV-2 infection in pregnancyand no evidence of vaccine-triggered breakdown inmaternal immunologic tolerance of the fetus.16
Although limited by population differences betweenvaccinated and unvaccinated patients,17,18 these find-ings add to the growing literature supporting thesafety of SARS-CoV-2 vaccination in pregnancy.
REFERENCES
1. Kucirka LM, Norton A, Sheffield JS. Severity of COVID-19 inpregnancy: a review of current evidence. Am J Reprod Immu-nol 2020;84:e13332. doi: 10.1111/aji.13332.
2. Chisholm KM, Heerema-McKenney A. Fetal thrombotic vas-culopathy: significance in liveborn children using proposedsociety for pediatric pathology diagnostic criteria. Am J SurgPathol 2015;39:274–80. doi: 10.1097/PAS.0000000000000334
3. Ernst LM, Bit-Ivan EN, Miller ES, Minturn L, Bigio EH,Weese-Mayer DE. Stillbirth: correlations between brain injuryand placental pathology. Pediatr Dev Pathol 2016;19:237–43.doi: 10.2350/15-06-1658-OA.1
4. Redline RW, Pappin A. Fetal thrombotic vasculopathy: theclinical significance of extensive avascular villi. Hum Pathol1995;26:80–5. doi: 10.1016/0046-8177(95)90118-3
Table 1. Clinical, Immunologic, and Histologic Findings
VaccineGroup (n584)
ControlGroup (n5116) aOR (95% CI)* P
Clinical characteristicsMaternal age (y) 33.763.1 32.564.8 .071st vaccine-to-delivery interval (d) (n575) 45.9624.3 NAGestational age at delivery (wk) 38.562.4 38.461.9 .86Vaginal delivery 66 (79%) 75(65%) .04Anti–SARS-CoV-2 signal/cutoff ratio
(n552 vaccine group, 116 control group)IgG 22.8614.5 0.0460.05 ,.001IgM 4.1613.2 0.1960.12 .001
Placental findingsDecidual arteriopathy 8 (10) 14 (12) 0.75 (0.3–1.9) .55Fetal vascular malperfusion 5 (6) 8 (7) 0.85 (0.27–2.7) .78Low-grade chronic villitis 10 (12) 9 (8) 1.6 (0.62–4.2) .33High-grade chronic villitis 4 (5) 16 (14) 0.31 (0.1–0.97) .04Chronic histiocytic intervillositis† 0 (0) 2 (1.7) — —
aOR, adjusted odds ratio; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Ig, immunoglobulin.Data are mean6SD or n (%) unless otherwise specified.* Adjusted for gestational age at delivery.† Multivariate modeling cannot be performed for chronic histiocytic intervillositis given the low incidence.
Fig. 1. Maternal anti–severeacute respiratory syndrome co-ronavirus 2 (SARS-CoV-2) spikeprotein immunoglobulin (Ig)M(A) and IgG (B) at delivery. Vac-cinated patients showed frequent(30/52 over cutoff) IgM androbust (50/52) IgG; women in thecontrol group did not (0/116 and0/116).
Shanes. Placental Pathology in SARS-CoV-2 Vaccination. Obstet Gynecol2021.
© 2021 by the American College of Obstetriciansand Gynecologists. Published by Wolters Kluwer Health, Inc.
Unauthorized reproduction of this article is prohibited.
282 Shanes et al Placental Pathology in SARS-CoV-2 Vaccination OBSTETRICS & GYNECOLOGY
5. Redline RW. Severe fetal placental vascular lesions in terminfants with neurologic impairment. Am J Obstet Gynecol2005;192:452–7. doi: 10.1016/j.ajog.2004.07.030
6. Redline RW, O’Riordan MA. Placental lesions associated withcerebral palsy and neurologic impairment following term birth.Arch Pathol Lab Med 2000;124:1785–91. doi: 10.1043/0003-9985(2000)124,1785:PLAWCP.2.0.CO;2
7. Shanes ED, Mithal LB, Otero S, Azad HA, Miller ES, GoldsteinJA. Placental pathology in COVID-19. Am J Clin Pathol 2020;154:23–32. doi: 10.1093/ajcp/aqaa089
8. Baergen RN, Heller DS. Placental pathology in covid-19 posi-tive mothers: preliminary findings. Pediatr Dev Pathol 2020;23:177–80. doi: 10.1177/1093526620925569
9. Schwartz DA, Baldewijns M, Benachi A, Bugatti M, CollinsRRJ, De Luca D, et al. Chronic histiocytic intervillositis withtrophoblast necrosis is a risk factor associated with placentalinfection from coronavirus disease 2019 (COVID-19) and intra-uterine maternal-fetal severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) transmission in live-born and stillborninfants. Arch Pathol Lab Med 2020;145:517–28. doi: 10.5858/arpa.2020-0771-SA
10. Pardi N, Hogan MJ, Porter FW, Weissman D. mRNA vaccines—a new era in vaccinology. Nat Rev Drug Discov 2018;17:261–79. doi: 10.1038/nrd.2017.243
11. Zhang J, Wei H, Wu D, Tian Z. Toll-like receptor 3 agonistinduces impairment of uterine vascular remodeling and fetallosses in CBA3DBA/2 mice. J Reprod Immunol 2007;74:61–7. doi: 10.1016/j.jri.2006.10.005
12. Baines KJ, Rampersaud AM, Hillier DM, Jeyarajah MJ,Grafham GK, Eastabrook G, et al. Antiviral inflammationduring early pregnancy reduces placental and fetal growthtrajectories. JI 2020;204:694–706. doi: 10.4049/jimmunol.1900888
13. Koga K, Cardenas I, Aldo P, Abrahams VM, Peng B, Fill S,et al. Original article: activation of TLR3 in the trophoblast isassociated with preterm delivery: activation of TLR3 in tropho-blast. Am J Reprod Immunol 2009;61:196–212. doi: 10.1111/j.1600-0897.2008.00682.x
14. Thaxton JE, Nevers T, Lippe EO, Blois SM, Saito S, Sharma S.NKG2D blockade inhibits poly(I:C)-Triggered fetal loss in wildtype but not in IL-10 2/2 mice. JI 2013;190:3639–47. doi: 10.4049/jimmunol.1203488
15. Mithal LB, Otero S, Shanes ED, Goldstein JA, Miller ES. Cordblood antibodies following maternal COVID-19 vaccinationduring pregnancy. Am J Obstet Gynecol 2021. doi: 10.1016/j.ajog.2021.03.035. [Epub ahead of print]
16. Østergaard SD, Schmidt M, Horváth-Puhó E, Thomsen RW,Sørensen HT. Thromboembolism and the Oxford-AstraZenecaCOVID-19 vaccine: side-effect or coincidence? Lancet 2021;397:1441–3. doi: 10.1016/S0140-6736(21)00762-5
17. Quansah R, Gissler M, Jaakkola JJK. Work as a nurse and amidwife and adverse pregnancy outcomes: a Finnish nation-wide population-based study. J Women’s Health 2009;18:2071–6. doi: 10.1089/jwh.2008.1062
18. Park C, Kang MY, Kim D, Park J, Eom H, Kim EA. Adversepregnancy outcomes in healthcare workers: a Korean nation-wide population-based study. Int Arch Occup Environ Health2017;90:501–6. doi: 10.1007/s00420-017-1213-3
(Obstet Gynecol 2021;138:281–283)DOI: 10.1097/AOG.0000000000004457
PEER REVIEW HISTORYReceived April 10, 2021. Received in revised form April 26, 2021.Accepted April 29, 2021. Peer reviews and author correspondenceare available at http://links.lww.com/AOG/C331.
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Unauthorized reproduction of this article is prohibited.
VOL. 138, NO. 2, AUGUST 2021 Shanes et al Placental Pathology in SARS-CoV-2 Vaccination 283
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n engl j med nejm.org 1
The authors’ affiliations are listed in the Appendix. Address reprint requests to Dr. Shimabukuro at the Immunization Safety Office, Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Dis-eases, Centers for Disease Control and Prevention, 1600 Clifton Rd., Atlanta, GA 30329, or at tshimabukuro@ cdc . gov.
*The members of the CDC v-safe COVID-19 Pregnancy Registry Team are listed in the Supplementary Appendix, available at NEJM.org.
This article was published on April 21, 2021, at NEJM.org.
DOI: 10.1056/NEJMoa2104983Copyright © 2021 Massachusetts Medical Society.
BACKGROUNDMany pregnant persons in the United States are receiving messenger RNA (mRNA) coronavirus disease 2019 (Covid-19) vaccines, but data are limited on their safety in pregnancy.
METHODSFrom December 14, 2020, to February 28, 2021, we used data from the “v-safe after vaccination health checker” surveillance system, the v-safe pregnancy registry, and the Vaccine Adverse Event Reporting System (VAERS) to characterize the initial safety of mRNA Covid-19 vaccines in pregnant persons.
RESULTSA total of 35,691 v-safe participants 16 to 54 years of age identified as pregnant. Injection-site pain was reported more frequently among pregnant persons than among nonpregnant women, whereas headache, myalgia, chills, and fever were reported less frequently. Among 3958 participants enrolled in the v-safe preg-nancy registry, 827 had a completed pregnancy, of which 115 (13.9%) resulted in a pregnancy loss and 712 (86.1%) resulted in a live birth (mostly among partici-pants with vaccination in the third trimester). Adverse neonatal outcomes included preterm birth (in 9.4%) and small size for gestational age (in 3.2%); no neonatal deaths were reported. Although not directly comparable, calculated proportions of adverse pregnancy and neonatal outcomes in persons vaccinated against Covid-19 who had a completed pregnancy were similar to incidences reported in studies involving pregnant women that were conducted before the Covid-19 pandemic. Among 221 pregnancy-related adverse events reported to the VAERS, the most frequently reported event was spontaneous abortion (46 cases).
CONCLUSIONSPreliminary findings did not show obvious safety signals among pregnant persons who received mRNA Covid-19 vaccines. However, more longitudinal follow-up, including follow-up of large numbers of women vaccinated earlier in pregnancy, is necessary to inform maternal, pregnancy, and infant outcomes.
A BS TR AC T
Preliminary Findings of mRNA Covid-19 Vaccine Safety in Pregnant Persons
Tom T. Shimabukuro, M.D., Shin Y. Kim, M.P.H., Tanya R. Myers, Ph.D., Pedro L. Moro, M.D., Titilope Oduyebo, M.D., Lakshmi Panagiotakopoulos, M.D.,
Paige L. Marquez, M.S.P.H., Christine K. Olson, M.D., Ruiling Liu, Ph.D., Karen T. Chang, Ph.D., Sascha R. Ellington, Ph.D., Veronica K. Burkel, M.P.H.,
Ashley N. Smoots, M.P.H., Caitlin J. Green, M.P.H., Charles Licata, Ph.D., Bicheng C. Zhang, M.S., Meghna Alimchandani, M.D., Adamma Mba-Jonas, M.D., Stacey W. Martin, M.S., Julianne M. Gee, M.P.H., and Dana M. Meaney-Delman, M.D.,
for the CDC v-safe COVID-19 Pregnancy Registry Team*
Original Article
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The first coronavirus disease 2019 (Covid-19) vaccines available in the United States were messenger RNA (mRNA) vac-
cines: BNT162b2 (Pfizer–BioNTech) and mRNA-1273 (Moderna). In December 2020, the vaccines were granted Emergency Use Authorization (EUA) by the Food and Drug Administration (FDA) as a two-dose series, 3 weeks apart for Pfizer–BioNTech and 1 month apart for Moderna, and were rec-ommended for use by the Advisory Committee on Immunization Practices (ACIP).1-4 Pregnant persons were excluded from preauthorization clinical trials, and only limited human data on safety during pregnancy were available at the time of authorization. However, pregnant persons with Covid-19 are at increased risk for severe ill-ness (e.g., resulting in admission to an intensive care unit, extracorporeal membrane oxygenation, or mechanical ventilation) and death, as compared with nonpregnant persons of reproductive age.5 Furthermore, pregnant persons with Covid-19 might be at increased risk for adverse pregnancy outcomes, such as preterm birth, as compared with pregnant persons without Covid-19.6 The Centers for Disease Control and Prevention (CDC) and ACIP, in collaboration with the American College of Obstetricians and Gynecologists and the American Academy of Pediatrics, have issued guidance indicating that Covid-19 vaccines should not be withheld from pregnant persons.7-9
Postauthorization monitoring in pregnant per-sons is necessary to characterize the safety of these new Covid-19 vaccines, which use mRNA, lipid nanoparticles, and state-of-the-art manu-facturing processes. Furthermore, establishing their safety profiles is critical to inform recom-mendations on maternal vaccination against Covid-19. We report preliminary findings of mRNA Covid-19 vaccine safety in pregnant per-sons from three U.S. vaccine safety monitoring systems: the “v-safe after vaccination health checker” surveillance system,10 the v-safe preg-nancy registry,11 and the Vaccine Adverse Event Reporting System (VAERS).12
Me thods
Monitoring Systems and Covered PopulationsV-safe Surveillance System and Pregnancy Registry
V-safe is a new CDC smartphone-based active-surveillance system developed for the Covid-19 vaccination program; enrollment is voluntary.
V-safe sends text messages to participants with weblinks to online surveys that assess for ad-verse reactions and health status during a post-vaccination follow-up period. Follow-up contin-ues 12 months after the final dose of a Covid-19 vaccine. During the first week after vaccination with any dose of a Covid-19 vaccine, participants are prompted to report local and systemic signs and symptoms during daily surveys and rank them as mild, moderate, or severe; surveys at all time points assess for events of adverse health effects. If participants indicate that they required medical care at any time point, they are asked to complete a report to the VAERS through active telephone outreach.
To identify persons who received one or both Covid-19 vaccine doses while pregnant or who be-came pregnant after Covid-19 vaccination, v-safe surveys include pregnancy questions for persons who do not report their sex as male. Persons who identify as pregnant are then contacted by tele-phone and, if they meet inclusion criteria, are offered enrollment in the v-safe pregnancy reg-istry. Eligible persons are those who received vaccination during pregnancy or in the pericon-ception period (30 days before the last men-strual period through 14 days after) and are 18 years of age or older. For persons who choose to enroll, the pregnancy registry telephone-based survey collects detailed information about the participant, including medical and obstetric his-tory, pregnancy complications, birth outcomes, and contact information for obstetric and pedi-atric health care providers to obtain medical records; infants are followed through the first 3 months of life. Details about v-safe and v-safe pregnancy registry methods have been published previously.10,11
VAERSThe VAERS is a national spontaneous-reporting (passive-surveillance) system established in 1990 that is administered by the CDC and the FDA.12 Anyone can submit a report to the VAERS. Health care providers are required to report cer-tain adverse events after vaccination, including pregnancy-related complications resulting in hos-pitalization and congenital anomalies, under the conditions of the EUAs for Covid-19 vaccines1,2; the CDC encourages reporting of any clinically significant maternal and infant adverse events. Signs and symptoms of adverse events are coded with the use of the Medical Dictionary for Regulatory
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Activities (MedDRA), version 23.1.13 We used a pregnancy-status question in the VAERS form and a MedDRA code and text-string search to identify reports involving vaccination in pregnant persons.14
Outcomes
V-safe outcomes included participant-reported lo-cal and systemic reactogenicity to the BNT162b2 (Pfizer–BioNTech) vaccine and the mRNA-1273 (Moderna) vaccine on the day after vaccination among all pregnant persons 16 to 54 years of age and among nonpregnant women 16 to 54 years of age as a comparator. For analysis of pregnancy outcomes in the v-safe pregnancy registry, data were restricted to completed pregnancies (i.e., live-born infant, spontaneous abortion, induced abortion, or stillbirth). Participant-reported preg-nancy outcomes included pregnancy loss (spon-taneous abortion and stillbirth) and neonatal outcomes (preterm birth, congenital anomalies, small size for gestational age, and neonatal death) (Table S1 in the Supplementary Appen-dix, available with the full text of this article at NEJM.org). In the VAERS, outcomes included non–pregnancy-specific adverse events and preg-nancy- and neonatal-specific adverse events.
Statistical Analysis
Demographic information and pregnancy charac-teristics are described for both v-safe and VAERS participants. Descriptive analyses were performed with the use of v-safe survey data for persons who identified as pregnant through February 28, 2021 (35,691 persons); persons enrolled in the v-safe pregnancy registry who were vaccinated through February 28, 2021 (3958 persons); and VAERS reports involving pregnant women re-ceived through February 28, 2021 (221 persons). Local and systemic reactogenicity was compared between persons who identified as pregnant and nonpregnant women. Descriptive analyses were conducted with the use of SAS software, version 9.4 (SAS Institute). All activities were reviewed by the CDC and were conducted in accordance with applicable federal law and CDC policy.
R esult s
V-safe Surveillance: Local and Systemic Reactogenicity in Pregnant Persons
From December 14, 2020, to February 28, 2021, a total of 35,691 v-safe participants identified as
pregnant. Age distributions were similar among the participants who received the Pfizer–BioNTech vaccine and those who received the Moderna vac-cine, with the majority of the participants being 25 to 34 years of age (61.9% and 60.6% for each vaccine, respectively) and non-Hispanic White (76.2% and 75.4%, respectively); most partici-pants (85.8% and 87.4%, respectively) reported being pregnant at the time of vaccination (Ta-ble 1). Solicited reports of injection-site pain, fatigue, headache, and myalgia were the most frequent local and systemic reactions after either dose for both vaccines (Table 2) and were re-ported more frequently after dose 2 for both vaccines. Participant-measured temperature at or above 38°C was reported by less than 1% of the participants on day 1 after dose 1 and by 8.0% after dose 2 for both vaccines.
These patterns of reporting, with respect to both most frequently reported solicited reactions and the higher reporting of reactogenicity after dose 2, were similar to patterns observed among nonpregnant women (Fig. 1). Small differences in reporting frequency between pregnant persons and nonpregnant women were observed for spe-cific reactions (injection-site pain was reported more frequently among pregnant persons, and other systemic reactions were reported more frequently among nonpregnant women), but the overall reactogenicity profile was similar. Preg-nant persons did not report having severe reac-tions more frequently than nonpregnant women, except for nausea and vomiting, which were re-ported slightly more frequently only after dose 2 (Table S3).
V-safe Pregnancy Registry: Pregnancy Outcomes and Neonatal Outcomes
As of March 30, 2021, the v-safe pregnancy reg-istry call center attempted to contact 5230 per-sons who were vaccinated through February 28, 2021, and who identified during a v-safe survey as pregnant at or shortly after Covid-19 vaccina-tion. Of these, 912 were unreachable, 86 de-clined to participate, and 274 did not meet inclu-sion criteria (e.g., were never pregnant, were pregnant but received vaccination more than 30 days before the last menstrual period, or did not provide enough information to determine eligi-bility). The registry enrolled 3958 participants with vaccination from December 14, 2020, to February 28, 2021, of whom 3719 (94.0%) identi-fied as health care personnel. Among enrolled
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participants, most were 25 to 44 years of age (98.8%), non-Hispanic White (79.0%), and, at the time of interview, did not report a Covid-19 diag-nosis during pregnancy (97.6%) (Table 3). Re-ceipt of a first dose of vaccine meeting registry-eligibility criteria was reported by 92 participants (2.3%) during the periconception period, by 1132 (28.6%) in the first trimester of pregnancy, by 1714 (43.3%) in the second trimester, and by 1019 (25.7%) in the third trimester (1 partici-pant was missing information to determine the timing of vaccination) (Table 3). Among 1040 participants (91.9%) who received a vaccine in the first trimester and 1700 (99.2%) who re-ceived a vaccine in the second trimester, initial
data had been collected and follow-up scheduled at designated time points approximately 10 to 12 weeks apart; limited follow-up calls had been made at the time of this analysis.
Among 827 participants who had a completed pregnancy, the pregnancy resulted in a live birth in 712 (86.1%), in a spontaneous abortion in 104 (12.6%), in stillbirth in 1 (0.1%), and in other outcomes (induced abortion and ectopic preg-nancy) in 10 (1.2%). A total of 96 of 104 sponta-neous abortions (92.3%) occurred before 13 weeks of gestation (Table 4), and 700 of 712 pregnan-cies that resulted in a live birth (98.3%) were among persons who received their first eligible vaccine dose in the third trimester. Adverse out-
Table 1. Characteristics of Persons Who Identified as Pregnant in the V-safe Surveillance System and Received an mRNA Covid-19 Vaccine.*
CharacteristicPfizer–BioNTech
VaccineModerna Vaccine Total
number (percent)
Total 19,252 (53.9) 16,439 (46.1) 35,691 (100)
Age at first vaccine dose
16–19 yr 23 (0.1) 36 (0.2) 59 (0.2)
20–24 yr 469 (2.4) 525 (3.2) 994 (2.8)
25–34 yr 11,913 (61.9) 9,960 (60.6) 21,873 (61.3)
35–44 yr 6,002 (31.2) 5,011 (30.5) 11,013 (30.9)
45–54 yr 845 (4.4) 907 (5.5) 1,752 (4.9)
Pregnancy status
Pregnant at time of vaccination 16,522 (85.8) 14,365 (87.4) 30,887 (86.5)
Positive pregnancy test after vaccination 2,730 (14.2) 2,074 (12.6) 4,804 (13.5)
Race and ethnic group†
Participants with available data 14,320 13,232 27,552
Non-Hispanic White 10,915 (76.2) 9,982 (75.4) 20,897 (75.8)
Hispanic 1,289 (9.0) 1,364 (10.3) 2,653 (9.6)
Non-Hispanic Asian 972 (6.8) 762 (5.8) 1,734 (6.3)
Non-Hispanic Black 371 (2.6) 338 (2.6) 709 (2.6)
Non-Hispanic multiple races 315 (2.2) 292 (2.2) 607 (2.2)
Non-Hispanic other race 76 (0.5) 56 (0.4) 132 (0.5)
Non-Hispanic American Indian or Alaska Native 40 (0.3) 54 (0.4) 94 (0.3)
Non-Hispanic Native Hawaiian or other Pacific Islander 33 (0.2) 31 (0.2) 64 (0.2)
Unknown race or unknown ethnic group 309 (2.2) 353 (2.7) 662 (2.4)
* Shown are the characteristics of v-safe participants 16 to 54 years of age who identified as pregnant and who received a messenger RNA (mRNA) coronavirus disease 2019 (Covid-19) vaccine — BNT162b2 (Pfizer–BioNTech) or mRNA-1273 (Moderna) — from December 14, 2020, to February 28, 2021. Percentages may not total 100 because of rounding.
† Race and ethnic group were reported by the participants. Questions about race and ethnic group were added to v-safe af-ter launch of the platform; not all pregnancies had recorded race and ethnic group at the time of data analysis. Therefore, data on race and ethnic group were missing for 22.8% of the total number of participants who identified as pregnant (4932 participants receiving the Pfizer–BioNTech vaccine and 3207 receiving the Moderna vaccine).
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mRNA Covid-19 Vaccine Safety in Pregnant Persons
comes among 724 live-born infants — including 12 sets of multiple gestation — were preterm birth (60 of 636 among those vaccinated before 37 weeks [9.4%]), small size for gestational age (23 of 724 [3.2%]), and major congenital anoma-lies (16 of 724 [2.2%]); no neonatal deaths were reported at the time of interview. Among the participants with completed pregnancies who reported congenital anomalies, none had re-ceived Covid-19 vaccine in the first trimester or periconception period, and no specific pattern of congenital anomalies was observed. Calculated proportions of pregnancy and neonatal outcomes appeared similar to incidences published in the peer-reviewed literature (Table 4).
Adverse-Event Findings on the VAERS
During the analysis period, the VAERS received and processed 221 reports involving Covid-19 vaccination among pregnant persons; 155 (70.1%) involved nonpregnancy-specific adverse events, and 66 (29.9%) involved pregnancy- or neonatal-specific adverse events (Table S4). The most frequently reported pregnancy-related adverse
events were spontaneous abortion (46 cases; 37 in the first trimester, 2 in the second trimester, and 7 in which the trimester was unknown or not reported), followed by stillbirth, premature rupture of membranes, and vaginal bleeding, with 3 reports for each. No congenital anoma-lies were reported to the VAERS, a requirement under the EUAs.
Discussion
This U.S. surveillance review of the safety of mRNA Covid-19 vaccines during pregnancy and the periconception period indicates that some pregnant persons in the United States are choos-ing to be vaccinated against Covid-19 in all tri-mesters of pregnancy. Solicited local and sys-temic reactions that were reported to the v-safe surveillance system were similar among persons who identified as pregnant and nonpregnant women. Although not directly comparable, the proportions of adverse pregnancy and neonatal outcomes (e.g., fetal loss, preterm birth, small size for gestational age, congenital anomalies,
Table 2. Frequency of Local and Systemic Reactions Reported on the Day after mRNA Covid-19 Vaccination in Pregnant Persons.*
Reported Reaction Pfizer–BioNTech Vaccine Moderna Vaccine Total
Dose 1 (N = 9052)
Dose 2 (N = 6638)
Dose 1 (N = 7930)
Dose 2 (N = 5635)
Dose 1 (N = 16,982)
Dose 2 (N = 12,273)
number (percent)
Injection-site pain 7602 (84.0) 5886 (88.7) 7360 (92.8) 5388 (95.6) 14,962 (88.1) 11,274 (91.9)
Fatigue 2406 (26.6) 4231 (63.7) 2616 (33.0) 4541 (80.6) 5,022 (29.6) 8,772 (71.5)
Headache 1497 (16.5) 3138 (47.3) 1581 (19.9) 3662 (65.0) 3,078 (18.1) 6,800 (55.4)
Myalgia 795 (8.8) 2916 (43.9) 1167 (14.7) 3722 (66.1) 1,962 (11.6) 6,638 (54.1)
Chills 254 (2.8) 1747 (26.3) 442 (5.6) 2755 (48.9) 696 (4.1) 4,502 (36.7)
Fever or felt feverish 256 (2.8) 1648 (24.8) 453 (5.7) 2594 (46.0) 709 (4.2) 4,242 (34.6)
Measured temperature ≥38°C 30 (0.3) 315 (4.7) 62 (0.8) 664 (11.8) 92 (0.5) 979 (8.0)
Nausea 492 (5.4) 1356 (20.4) 638 (8.0) 1909 (33.9) 1,130 (6.7) 3,265 (26.6)
Joint pain 209 (2.3) 1267 (19.1) 342 (4.3) 1871 (33.2) 551 (3.2) 3,138 (25.6)
Injection-site swelling 318 (3.5) 411 (6.2) 739 (9.3) 1051 (18.7) 1,057 (6.2) 1,462 (11.9)
Abdominal pain 117 (1.3) 316 (4.8) 160 (2.0) 401 (7.1) 277 (1.6) 717 (5.8)
Injection-site redness 160 (1.8) 169 (2.5) 348 (4.4) 491 (8.7) 508 (3.0) 660 (5.4)
Diarrhea 178 (2.0) 277 (4.2) 189 (2.4) 332 (5.9) 367 (2.2) 609 (5.0)
Vomiting 82 (0.9) 201 (3.0) 77 (1.0) 357 (6.3) 159 (0.9) 558 (4.5)
Injection-site itching 103 (1.1) 109 (1.6) 157 (2.0) 193 (3.4) 260 (1.5) 302 (2.5)
Rash 20 (0.2) 18 (0.3) 22 (0.3) 18 (0.3) 42 (0.2) 36 (0.3)
* Shown are solicited reactions in v-safe participants 16 to 54 years of age who identified as pregnant and who received an mRNA Covid-19 vaccine (BNT162b2 [Pfizer–BioNTech] or mRNA-1273 [Moderna]) from December 14, 2020, to February 28, 2021.
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and neonatal death) among participants with completed pregnancies from the v-safe preg-nancy registry appear to be similar to the pub-lished incidences in pregnant populations stud-ied before the Covid-19 pandemic.15-26 Many participants in the v-safe pregnancy registry were included in the phase 1a (highest) priority group for Covid-19 vaccination owing to their work as health care personnel.27 V-safe participation is voluntary, and registration information is not uniformly available at all vaccination locations, although information about the surveillance sys-tem is included on the EUA fact sheets for health care providers and patients. Thus, comparisons of the proportions of vaccinated women with these outcomes to previously published estimates are limited by likely differences between these populations in age, ethnic group, and other so-cial, demographic, and clinical characteristics that are known to be associated with pregnancy and neonatal outcomes. However, such compari-sons are helpful to provide a crude sense of whether there are any unexpected safety signals in these early data. At the time of this analysis, just 14.7% of persons who identified as pregnant
in the v-safe surveillance system had been con-tacted to offer enrollment in the pregnancy registry.
Other limitations should also be noted. As with all participant-reported surveillance systems, mistakes in completion of v-safe health surveys can result in misclassification of participants as pregnant; as a result, data for local and sys-temic reactions that participants reported to the v-safe platform may include some reports from nonpregnant persons. Participants are not re-quired to complete surveys at the same time every day, and our ability to assess onset or dura-tion of adverse events, such as fever, is limited. The registry data are preliminary, are from a small sample, and describe mostly neonatal out-comes from third-trimester vaccination; the find-ings may change as additional pregnancy out-comes are reported and the sample size increases, which may facilitate detection of rare outcomes. We were unable to evaluate adverse outcomes that might occur in association with exposures earlier in pregnancy, such as congenital anoma-lies, because no pregnant persons who were vac-cinated early in pregnancy have had live births
Figure 1. Most Frequent Local and Systemic Reactions Reported in the V-safe Surveillance System on the Day after mRNA Covid-19 Vaccination.
Shown are solicited reactions in pregnant persons and nonpregnant women 16 to 54 years of age who received a messenger RNA (mRNA) coronavirus disease 2019 (Covid-19) vaccine — BNT162b2 (Pfizer–BioNTech) or mRNA-1273 (Moderna) — from December 14, 2020, to February 28, 2021. The percentage of respondents was calculated among those who completed a day 1 survey, with the top events shown of injection-site pain (pain), fatigue or tiredness (fatigue), headache, muscle or body aches (myalgia), chills, and fever or felt feverish (fever).
Pregnant Nonpregnant
A Pfizer–BioNTech Vaccine, Dose 1 B Pfizer–BioNTech Vaccine, Dose 2
C Moderna Vaccine, Dose 1 D Moderna Vaccine, Dose 2
Perc
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20
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mRNA Covid-19 Vaccine Safety in Pregnant Persons
captured in the v-safe pregnancy registry to date; follow-up is ongoing. In addition, the proportion of pregnant persons who reported spontaneous abortion may not reflect true postvaccination proportions because participants might have been vaccinated after the period of greatest risk in the first trimester, and very early pregnancy losses might not be recognized. Whereas some pregnancies with vaccination in the first and early second trimester have been completed, the majority are ongoing, and a direct comparison
of outcomes on the basis of timing of vaccina-tion is needed to define the proportion of spon-taneous abortions in this cohort. Because of sample-size constraints, both pregnancy and neo-natal outcomes were calculated as a proportion instead of a rate.
Our preliminary analysis uses participant-reported data and has limited information on other potential risk factors for adverse pregnancy and neonatal outcomes. The VAERS is subject to the limitations of passive surveillance.12 Despite
Table 3. Characteristics of V-safe Pregnancy Registry Participants.*
CharacteristicPfizer–BioNTech
VaccineModerna Vaccine Total
number (percent)
Total 2136 (54.0) 1822 (46.0) 3958 (100)
Age at first vaccine dose†
20–24 yr 17 (0.8) 19 (1.0) 36 (0.9)
25–34 yr 1335 (62.5) 1238 (67.9) 2573 (65.0)
35–44 yr 777 (36.4) 560 (30.7) 1337 (33.8)
45–54 yr 7 (0.3) 5 (0.3) 12 (0.3)
Race and ethnic group‡
Non-Hispanic White 1663 (77.9) 1463 (80.3) 3126 (79.0)
Hispanic 164 (7.7) 151 (8.3) 315 (8.0)
Non-Hispanic Asian 225 (10.5) 138 (7.6) 363 (9.2)
Non-Hispanic Black 24 (1.1) 26 (1.4) 50 (1.3)
Non-Hispanic multiple races 42 (2.0) 30 (1.6) 72 (1.8)
Non-Hispanic American Indian or Alaskan Native 5 (0.2) 1 (0.1) 6 (0.2)
Non-Hispanic Native Hawaiian or other Pacific Islander 6 (0.3) 3 (0.2) 9 (0.2)
Missing data or participant declined to answer 7 (0.3) 10 (0.5) 17 (0.4)
Timing of first eligible dose
Periconception: within 30 days before last menstrual period 55 (2.6) 37 (2.0) 92 (2.3)
First trimester: <14 wk 615 (28.8) 517 (28.4) 1132 (28.6)
Second trimester: ≥14 and <28 wk 932 (43.6) 782 (42.9) 1714 (43.3)
Third trimester: ≥28 wk 533 (25.0) 486 (26.7) 1019 (25.7)
Missing data 1 (<0.1) 0 1 (<0.1)
Covid-19 infection during pregnancy
No Covid-19 infection 2084 (97.6) 1779 (97.6) 3863 (97.6)
Before vaccination 32 (1.5) 24 (1.3) 56 (1.4)
≤14 days after first eligible dose of vaccination 3 (0.1) 7 (0.4) 10 (0.3)
>14 days after first eligible dose of vaccination 9 (0.4) 3 (0.2) 12 (0.3)
Missing data 8 (0.4) 9 (0.5) 17 (0.4)
* Shown are registry participants who received an mRNA Covid-19 vaccine (BNT162b2 [Pfizer–BioNTech] or mRNA-1273 [Moderna]) from December 14, 2020, to February 28, 2021. Percentages may not total 100 because of rounding.
† The v-safe pregnancy registry is only enrolling pregnant persons 18 years of age or older; at the time of this analysis, no participants were younger than 20 years of age.
‡ Race and ethnic group were reported by the participants.
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T h e n e w e ngl a nd j o u r na l o f m e dic i n e
EUA mandatory reporting requirements and CDC guidance on VAERS reporting, there is probably substantial underreporting of pregnancy- and neonatal-specific adverse events. We also do not know the total number of Covid-19 vaccine doses administered to pregnant persons, which further limits our ability to estimate rates of reported adverse events from VAERS data. Among pregnancy-specific conditions reported to the VAERS after Covid-19 vaccination, miscarriage was the most common. This is similar to what was observed during the influenza A (H1N1) pandemic in 2009 after the introduction of the 2009 H1N1 inactivated influenza vaccine, where miscarriage was the most common adverse event reported by pregnant persons who received that vaccine.28
In addition to vaccination protecting women against Covid-19 and its complications during pregnancy, emerging evidence has shown trans-placental transfer of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibod-ies after maternal Covid-19 vaccination during
the third trimester, which suggests that mater-nal vaccination might provide some level of pro-tection to the neonate.29-32 However, we do not have data on antibody transfer and level of pro-tection relative to the timing of vaccination. The CDC and the FDA are continuing to monitor and disseminate information about the safety of mRNA and additional types of Covid-19 vaccines in pregnant persons.
Early data from the v-safe surveillance sys-tem, the v-safe pregnancy registry, and the VAERS do not indicate any obvious safety signals with respect to pregnancy or neonatal outcomes associated with Covid-19 vaccination in the third trimester of pregnancy. Continued monitoring is needed to further assess maternal, pregnancy, neonatal, and childhood outcomes associated with maternal Covid-19 vaccination, including in earlier stages of pregnancy and during the pre-conception period. Meanwhile, the present data can help inform decision making about vaccina-tion by pregnant persons and their health care providers.
Table 4. Pregnancy Loss and Neonatal Outcomes in Published Studies and V-safe Pregnancy Registry Participants.
Participant-Reported Outcome Published Incidence* V-safe Pregnancy Registry†
% no./total no. (%)
Pregnancy loss among participants with a completed pregnancy
Spontaneous abortion: <20 wk15-17 10–26 104/827 (12.6)‡
Stillbirth: ≥ 20 wk18-20 <1 1/725 (0.1)§
Neonatal outcome among live-born infants
Preterm birth: <37 wk21,22 8–15 60/636 (9.4)¶
Small size for gestational age23,24‖ 3.5 23/724 (3.2)
Congenital anomalies25** 3 16/724 (2.2)
Neonatal death26†† <1 0/724
* The populations from which these rates are derived are not matched to the current study population for age, race and ethnic group, or other demographic and clinical factors.
† Data on pregnancy loss are based on 827 participants in the v-safe pregnancy registry who received an mRNA Covid-19 vaccine (BNT162b2 [Pfizer–BioNTech] or mRNA-1273 [Moderna]) from December 14, 2020, to February 28, 2021, and who reported a completed pregnancy. A total of 700 participants (84.6%) received their first eligible dose in the third trimester. Data on neonatal outcomes are based on 724 live-born infants, including 12 sets of multiples.
‡ A total of 96 of 104 spontaneous abortions (92.3%) occurred before 13 weeks of gestation.§ The denominator includes live-born infants and stillbirths.¶ The denominator includes only participants vaccinated before 37 weeks of gestation.‖ Small size for gestational age indicates a birthweight below the 10th percentile for gestational age and infant sex ac-
cording to INTERGROWTH-21st growth standards (http://intergrowth21 . ndog . ox . ac . uk). These standards draw from an international sample including both low-income and high-income countries but exclude children with coexisting conditions and malnutrition. They can be used as a standard for healthy children growing under optimal conditions.
** Values include only major congenital anomalies in accordance with the Metropolitan Atlanta Congenital Defects Pro-gram 6-Digit Code Defect List (www . cdc . gov/ ncbddd/ birthdefects/ macdp . html); all pregnancies with major congeni-tal anomalies were exposed to Covid-19 vaccines only in the third trimester of pregnancy (i.e., well after the period of organogenesis).
†† Neonatal death indicates death within the first 28 days after delivery.
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mRNA Covid-19 Vaccine Safety in Pregnant Persons
The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention (CDC) or the Food and Drug Administration (FDA). Mention of a product or company name is for identification purposes only and does not constitute endorsement by the CDC or the FDA. All authors are U.S. government employees or U.S. government contractors and do not have any material conflicts of interest. Oracle provided in-kind technical support to build and maintain the v-safe after
vaccination health checker infrastructure for data capture and messaging to participants.
Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.
A data sharing statement provided by the authors is available with the full text of this article at NEJM.org.
We thank the v-safe participants, the members of the Oracle v-safe development team for their contributions, and the mem-bers of the CDC COVID-19 Response Team for their support.
AppendixThe authors’ affiliations are as follows: the Immunization Safety Office, Division of Healthcare Quality Promotion (T.T.S., T.R.M., P.L. Moro, L.P., P.L. Marquez, C.K.O., C.L., B.C.Z., J.M.G.), and the Arboviral Diseases Branch, Division of Vector-Borne Diseases (S.W.M.), National Center for Emerging and Zoonotic Infectious Diseases, the Division of Birth Defects and Infant Disorders, National Center on Birth Defects and Developmental Disabilities (S.Y.K., V.K.B., C.J.G., D.M.M.-D.), the Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion (T.O., K.T.C., S.R.E., A.N.S.), the World Trade Center Health Program, Na-tional Institute for Occupational Safety and Health (R.L.), and the Epidemic Intelligence Service (K.T.C.) — all at the Centers for Disease Control and Prevention, Atlanta; and the Division of Epidemiology, Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD (M.A., A.M.-J.).
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States. 2021 (https://www . cdc . gov/ vaccines/ covid - 19/ info - by - product/ clinical - considerations . html).8. American College of Obstetricians and Gynecologists. Vaccinating pregnant and lactating patients against COVID-19: practice advisory. December 2020 (https://www . acog . org/ clinical/ clinical - guidance/ practice - advisory/ articles/ 2020/ 12/ vaccinating - pregnant - and - lactating - patients - against - covid - 19).9. American Academy of Pediatrics. In-terim guidance for COVID-19 vaccination in children and adolescents. 2021 (https://services . aap . org/ en/ pages/ 2019 - novel - coronavirus - covid - 19 - infections/ clinical - guidance/ interim - guidance - for - covid - 19 - vaccination - in - children - and - adolescents/ ).10. Centers for Disease Control and Pre-vention. V-safe active surveillance for COVID-19 vaccine safety. January 2021 (https://www . cdc . gov/ vaccinesafety/ pdf/ V - safe - Protocol - 508 . pdf).11. Centers for Disease Control and Pre-vention. V-safe pregnancy surveillance (amendment). (https://www . cdc . gov/ vaccinesafety/ pdf/ vsafe - pregnancy - surveillance - protocol - 508 . pdf).12. Shimabukuro TT, Nguyen M, Martin D, DeStefano F. Safety monitoring in the Vaccine Adverse Event Reporting System (VAERS). Vaccine 2015; 33: 4398-405.13. Medical Dictionary for Regulatory Ac-tivities (MedDRA) home page. (https://www . meddra . org/ ).14. Centers for Disease Control and Pre-vention. Vaccine Adverse Event Reporting System (VAERS): standard operating pro-cedures for COVID-19. January 2021 (https://www . cdc . gov/ vaccinesafety/ pdf/ VAERS - v2 - SOP . pdf).15. Dugas C, Slane VH. Miscarriage. In: StatPearls. Treasure Island, FL: StatPearls Publishing, 2021 (https://www . ncbi . nlm . nih . gov/ books/ NBK532992/ ).16. American College of Obstetricians and
Gynecologists’ Committee on Practice Bulletins — Gynecology. ACOG practice bulletin no. 200: early pregnancy loss. Obstet Gynecol 2018; 132(5): e197-e207.17. Practice Committee of the American Society for Reproductive Medicine. Evalu-ation and treatment of recurrent preg-nancy loss: a committee opinion. Fertil Steril 2012; 98: 1103-11.18. Hoyert DL, Gregory ECW. Cause-of-death data from the fetal death file, 2015-2017. Natl Vital Stat Rep 2020; 69(4): 1-20.19. MacDorman MF, Gregory ECW. Fetal and perinatal mortality: United States, 2013. Natl Vital Stat Rep 2015; 64(8): 1-24.20. Panagiotakopoulos L, McCarthy NL, Tepper NK, et al. Evaluating the associa-tion of stillbirths after maternal vaccina-tion in the Vaccine Safety Datalink. Ob-stet Gynecol 2020; 136: 1086-94.21. Ferré C, Callaghan W, Olson C, Shar-ma A, Barfield W. Effects of maternal age and age-specific preterm birth rates on overall preterm birth rates — United States, 2007 and 2014. MMWR Morb Mor-tal Wkly Rep 2016; 65: 1181-4.22. Centers for Disease Control and Pre-vention. Percentage of births born pre-term by state (https://www . cdc . gov/ nchs/ pressroom/ sosmap/ preterm_births/ preterm . htm).23. Boghossian NS, Geraci M, Edwards EM, Horbar JD. Morbidity and mortality in small for gestational age infants at 22 to 29 weeks’ gestation. Pediatrics 2018; 141(2): e20172533.24. Francis A, Hugh O, Gardosi J. Custom-ized vs INTERGROWTH-21st standards for the assessment of birthweight and stillbirth risk at term. Am J Obstet Gyne-col 2018; 218: Suppl: S692-S699.25. Update on overall prevalence of major birth defects — Atlanta, Georgia, 1978–2005. MMWR Morb Mortal Wkly Rep 2008; 57: 1-5.26. Centers for Disease Control and Pre-
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vention. Infant mortality rates by state (https://www . cdc . gov/ nchs/ pressroom/ sosmap/ infant_mortality_rates/ infant_mortality . htm).27. Dooling K, McClung N, Chamberland M, et al. The Advisory Committee on Im-munization Practices’ interim recommen-dation for allocating initial supplies of COVID-19 vaccine — United States, 2020. MMWR Morb Mortal Wkly Rep 2020; 69: 1857-9.28. Moro PL, Broder K, Zheteyeva Y, et al. Adverse events following administration to pregnant women of influenza A (H1N1)
2009 monovalent vaccine reported to the Vaccine Adverse Event Reporting System. Am J Obstet Gynecol 2011; 205(5): 473.e1-473.e9.29. Rottenstreich A, Zarbiv G, Oiknine-Djian E, Zigron R, Wolf DG, Porat S. Ef-ficient maternofetal transplacental trans-fer of anti-SARS-CoV-2 spike antibodies after antenatal SARS-CoV-2 BNT162b2 mRNA vaccination. March 12, 2021 (https://www . medrxiv . org/ content/ 10 . 1101/ 2021 . 03 . 11 . 21253352v1). preprint.30. Gray KJ, Bordt EA, Atyeo C, et al. COVID-19 vaccine response in pregnant
and lactating women: a cohort study. Am J Obstet Gynecol 2021 March 24 (Epub ahead of print).31. Paul G, Chad R. Newborn antibodies to SARS-CoV-2 detected in cord blood af-ter maternal vaccination — a case report. BMC Pediatr 2021; 21: 138.32. Gill L, Jones CW. Severe acute respi-ratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in neonatal cord blood after vaccination in pregnancy. Obstet Gynecol 2021 March 8 (Epub ahead of print).Copyright © 2021 Massachusetts Medical Society.
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Journal Pre-proof
Pregnancy and birth outcomes after SARS-CoV-2 vaccination inpregnancy
Regan N. Theiler , Myra Wick , Ramila Mehta , Amy L. Weaver ,Abinash Virk , Melanie Swift
PII: S2589-9333(21)00162-2DOI: https://doi.org/10.1016/j.ajogmf.2021.100467Reference: AJOGMF 100467
To appear in: American Journal of Obstetrics & Gynecology MFM
Received date: 10 June 2021Revised date: 16 August 2021Accepted date: 16 August 2021
Please cite this article as: Regan N. Theiler , Myra Wick , Ramila Mehta , Amy L. Weaver ,Abinash Virk , Melanie Swift , Pregnancy and birth outcomes after SARS-CoV-2 vacci-nation in pregnancy, American Journal of Obstetrics & Gynecology MFM (2021), doi:https://doi.org/10.1016/j.ajogmf.2021.100467
This is a PDF file of an article that has undergone enhancements after acceptance, such as the additionof a cover page and metadata, and formatting for readability, but it is not yet the definitive version ofrecord. This version will undergo additional copyediting, typesetting and review before it is publishedin its final form, but we are providing this version to give early visibility of the article. Please note that,during the production process, errors may be discovered which could affect the content, and all legaldisclaimers that apply to the journal pertain.
© 2021 Published by Elsevier Inc.
Pregnancy and birth outcomes after SARS-CoV-2 vaccination
in pregnancy
Regan N. Theiler, MD, PhD*1, Myra Wick, MD, PhD1, Ramila Mehta3, Amy L. Weaver, MS3,
Abinash Virk, MD2, Melanie Swift, MD5
1 Mayo Clinic Department of Obstetrics and Gynecology, Division of Obstetrics
2 Mayo Clinic Department of Medicine, Division of Infectious Disease
3 Mayo Clinic Department of Quantitative Health Sciences
5 Mayo Clinic Division of Preventive, Occupational, and Aerospace Medicine
*Corresponding author:
200 First St SE
Department of Obstetrics and Gynecology
Mayo Clinic
Rochester, MN 55905
Disclosures:
Dr. Theiler has a know-how license and research funding from HeraMED
Dr. Swift has funding from Pfizer via Duke University for the HERO Together vaccine safety
registry.
Dr. Virk reports being an inventor for Mayo Clinic Travel App interaction with Smart Medical Kit
and Medical Kit for Pilgrims.
The other authors have declared no conflicts of interest
Acknowledgments:
This work was funded in part by grant FP00085005-A1-03-S14 from the U.S. National Center for
Translational Sciences. The funder did not participate in the study design, data collection, data
analysis, or writing for publication.
Condensation:
COVID-19 vaccine administration during pregnancy did not result in adverse pregnancy
outcomes and was associated with a decrease in COVID-19 infections during pregnancy.
Short Title:
Clinical outcomes after COVID-19 vaccination in pregnancy
AJOG at a Glance:
Why was this study conducted?
Limited data exists supporting safety and efficacy of the COVID-19 vaccines for administration
during pregnancy.
What are the key findings?
Sociodemographic differences in COVID-19 vaccine uptake were observed among pregnant
patients. Vaccinated patients did not experience more adverse pregnancy outcomes than non-
vaccinated patients, but they were less likely to experience COVID-19 infection during
pregnancy.
What does this study add to what is already known?
The study demonstrates both safety and efficacy of the vaccines during pregnancy.
KEYWORDS:
PREGNANCY
COVID-19
SARS-C0V-2
VACCINATION
IMMUNITY
mRNA vaccine
Birth
Adverse outcomes index (AOI)
Gestation
Teratogenicity
ABSTRACT
Background: SARS-CoV-2 infection during pregnancy is associated with significant maternal
morbidity and increased rates of preterm birth. For this reason, COVID-19 vaccine
administration in pregnancy has been endorsed by multiple professional societies including
ACOG and SMFM despite exclusion of pregnant women from initial clinical trials of vaccine
safety and efficacy. However, to date little data exists regarding outcomes after COVID-19
vaccination of pregnant patients.
Study Design: A comprehensive vaccine registry was combined with a delivery database for an
integrated healthcare system to create a delivery cohort including vaccinated patients. Maternal
sociodemographic data were examined to identify factors associated with COVID-19
vaccination. Pregnancy and birth outcomes were analyzed, including a composite measure of
maternal and neonatal pregnancy complications, the Adverse Outcome Index.
Results: Of 2002 patients in the delivery cohort, 140 (7.0%) received a COVID-19 vaccination
during pregnancy and 212 (10.6%) experienced a COVID-19 infection during pregnancy. The
median gestational age at first vaccination was 32 weeks (range 13 6/7-40 4/7), and patients
vaccinated during pregnancy were less likely than unvaccinated patients to experience COVID-
19 infection prior to delivery (1.4% (2/140) vs. 11.3% (210/1862), P<0.001). No maternal
COVID-19 infections occurred after vaccination during pregnancy.
Factors significantly associated with increased likelihood of vaccination in a multivariable logistic
regression model included older age, higher level of maternal education, being a non-smoker,
use of infertility treatment for the current pregnancy, and lower gravidity. No significant
difference in the composite adverse outcome (5.0% (7/140) vs. 4.9% (91/1862), P=0.95) or
other maternal or neonatal complications, including thromboembolic events and preterm birth,
was observed in vaccinated compared to unvaccinated patients.
Conclusions: Vaccinated pregnant women in this birth cohort were less likely to experience
COVID-19 infection compared to unvaccinated pregnant patients, and COVID-19 vaccination
during pregnancy was not associated with increased pregnancy or delivery complications. The
cohort was skewed toward late pregnancy vaccination, and thus findings may not be
generalizable to vaccination during early pregnancy.
Introduction
In late 2020, the United States Food and Drug Administration (FDA) approved two mRNA
vaccines, manufactured by Pfizer-BioNTech (BNT162b2) (Pfizer, Inc; Philadelphia,
Pennsylvania) and Moderna (mRNA-1273) (ModernaTX, Inc; Cambridge, Massachusetts), for
emergency use to prevent COVID-19 illness. Both vaccines were studied in large numbers of
subjects during phase 3 randomized controlled trials, and both were shown to be highly effective
at preventing COVID-19 infection in non-pregnant participants..1, 2 Because none of the trials
undertaken to gain FDA approval included pregnant or lactating women, use of the vaccines
during pregnancy and lactation has been controversial.3 During phase 1A of the vaccine rollout
in the U.S., healthcare workers were the first population with access to vaccination, and thus
many pregnant healthcare workers received the vaccine. During phase 1B, teachers and other
essential workers were vaccinated, adding to the population of reproductive age who were
eligible for vaccination. Starting in December 2020, recommendations from the American
College of Obstetricians and Gynecologists (ACOG), the Society for Maternal-Fetal Medicine
(SMFM), and the World Health Organization (WHO) endorsed availability of COVID-19
vaccination for pregnant women using a shared decision-making model with healthcare
providers3, 4.
COVID-19 disease during pregnancy is known to have severe manifestations in pregnant
women compared to non-pregnant controls, with increased risk for maternal hospitalization, ICU
admission, invasive ventilation, and death 5-7. Other adverse outcomes observed with SARS-
CoV-2 infection during pregnancy include increased rates of preterm birth and increased pre-
eclampsia incidence, both of which have been linked to inflammatory mechanisms 8. Because
of the known increased maternal risk of adverse outcomes with COVID-19 infection and the lack
of proven harm from the available vaccines, many patients have opted for vaccination despite
limited safety and efficacy data for the vaccines in pregnant patients9. The vaccines are thought
to be effective when administered during pregnancy, as antibody production occurs rapidly after
administration. However, immune alterations that occur in pregnancy may theoretically
decrease the vigor of cell-mediated immune responses to infection. 2, 10 Neutralizing antibody
response is highly reassuring and suggests robust efficacy during pregnancy with possible
benefit to the neonate.
Recently published COVID-19 vaccine surveillance data from the Centers for Disease Control
and Prevention’s (CDC) voluntary V-SAFE registry including 3958 subjects vaccinated during
pregnancy suggests that pregnant women do not have increased rates of adverse vaccine
reactions compared to control patients, and that patients do not report increases in adverse
pregnancy outcomes compared to non-pregnant women11. The V-SAFE data, however, are
limited to patient-reported vaccine reactions and pregnancy events; conclusions are thus
subject to selection bias and lack of validated primary data supporting conclusions. For this
reason, vaccine efficacy should be demonstrated in pregnancy using infectious outcomes as
well. Adding to the available data, we present pregnancy outcomes from a Mayo Clinic Health
System delivery cohort delivering during the first four months of vaccine availability.
Methods
A comprehensive vaccine registry was created, capturing COVID-19 vaccine administrations,
manufacturer, and patient identifying information from Mayo Clinic vaccination sites as well as
other sites across the states of Minnesota and Wisconsin. The vaccination registry was then
linked to the Mayo Clinic delivery registry, which contains detailed maternal and neonatal
outcomes from all births within the Mayo Clinic Health System. The delivery registry data is
derived directly from elements in the electronic medical record and all fields have been validated
manually during development. Creation of the registries and subsequent analysis was
performed in accordance with human subjects regulations under approval by the Mayo Clinic
Institutional Review Board. These data sources were combined to form a retrospective cohort
of all births during the study timeframe.
Criteria for study inclusion included all patients age 16-55 years old with a delivery event
between December 10, 2020, and April 19, 2021 at a hospital within the Mayo Clinic Health
System. Patients who opted out of use of their medical records for research were excluded from
the study if their delivery occurred in Minnesota. COVID infection during pregnancy, regardless
of temporal relationship to vaccine, was defined as a positive SARS-CoV-2 RT-PCR test
documented in the medical record between the dates of conception and delivery, stratified by
first trimester (2-13 6/7 weeks gestation), second trimester (14 0/7- 27 6/7 weeks gestation) and
third trimester (≥28 weeks gestation) infection.
For purposes of assessing vaccine side effects and pregnancy outcomes, vaccinated
individuals are defined as those receiving any dose of vaccine during pregnancy. For purposes
of assessing vaccine effectiveness, fully vaccinated was defined as >14 days after the final
dose of vaccine.
The composite outcome, the adverse outcome index (AOI) was calculated as a composite of
any of the following events during the delivery hospitalization: a) maternal death during
hospitalization, b) intrapartum neonatal death within 7 days of birth with birthweight ≥ 2500g and
≥37 weeks gestation, c) hypoxic ischemic encephalopathy, d) uterine rupture, e) unplanned
maternal ICU admission, f) return to the operating room within 72 hours of delivery, g)
postpartum hemorrhage with blood transfusion, h) third or fourth degree laceration, i) five
minute Apgar <7 with birthweight ≥2500g and ≥37 weeks gestation, j) admission to the NICU
within 1 day of birth for >1 day with birthweight ≥2500g and ≥37 weeks gestation, or k) neonatal
birth trauma. All qualifying events were verified by chart review. The AOI for a group of patients
was calculated as the number of patients with one or more identified adverse events divided by
the total number of deliveries, multiped by 100. A woman with multiple gestations was counted
as a single delivery. A modified AOI was also calculated by not considering third- and fourth-
degree perineal laceration as an adverse event. Additional outcomes measured included
thromboembolism or stroke within 4 weeks before or after delivery, gestational hypertensive
disorders diagnosed up to 72 hours after delivery, low and very low birth weight, preterm birth (<
37 weeks gestation), length of postpartum maternal stay after delivery, and stillbirth.
The primary outcome in this study was AOI.12-14 The AOI was 4.9% within the Mayo Clinic
Health System for calendar year 2019. This study was designed with 80% power, using a two-
sided chi-square test with a type I error rate of 0.05, to detect a difference in AOI of 4.9% vs. at
least 11.5% between those without versus with a COVID-19 vaccine during pregnancy, based
on 1862 and 140 patients in the two groups.
Data management and statistical analysis was performed using SAS version 9.4 (SAS institute,
Cary, NC, USA). Comparisons between groups were evaluated using the chi-square test or
Fisher’s exact test for non-ordered categorical variables, the Wilcoxon rank sum test for ordinal
variables, and the two-sample t-test for continuous variables. A multivariable logistic regression
model was fit to identify a set of characteristics independently associated with having received a
COVID-19 vaccine during pregnancy, by including all of the factors identified with p<0.20 based
on univariate analysis. Prior to fitting the multivariable model an additional category was created
for each variable with missing data. A 95% confidence interval (CI) for the difference in the AOI
between two groups was calculated based on exact methods for a binomial parameter. All
calculated p-values were two-sided and p-values less than 0.05 were considered statistically
significant.
Results
Of 2002 total patients, 140 (7.0%) received at least one dose of a COVID-19 vaccine prior to
delivery, and 212 (10.6%) experienced a COVID-19 infection during pregnancy. Among the
vaccinated patients, one received the Janssen COVID-19 (Ad.26.COV2.S) vaccine (Janssen
Biotech, Inc, a Janssen Pharmaceutical company, Johnson & Johnson; New Brunswick, New
Jersey), 12 received the Moderna vaccine, and 127 received the Pfizer-BioNTech vaccine
(Appendix Table A1). The median estimated gestational age (EGA) at initiation of the
vaccination series was 32 (range 13 6/7-40 4/7) weeks gestation. Completed vaccination was
documented at a median EGA of 35 2/7 weeks (range 17 1/7-44 1/7), with 73.6% of the 140
patients completing vaccination prior to delivery.
Sociodemographic factors (Table 1) positively associated p<0.05) with maternal vaccination
based on univariate analysis included older maternal age at delivery, higher level of maternal
education, and use of infertility treatment for the current pregnancy. Factors negatively
associated (p<0.05) with vaccination included non-white race, Hispanic ethnicity, current
smoking, current illicit drug use, higher gravidity, and higher pre-pregnancy body mass index.
Presence of comorbid conditions including pre-gestational diabetes, chronic hypertension, and
asthma were not significantly associated with vaccination status. The following factors retained
statistical significance in the multivariable logistic regression analysis: older age, higher level of
maternal education, being a non-smoker, use of infertility treatment for the current pregnancy,
and lower gravidity.
Patients vaccinated during pregnancy were less likely than unvaccinated patients to experience
COVID-19 infection prior to delivery (1.4% (2/140) vs. 11.3% (210/1861), P <0.001), with the
two infections occurring in the vaccinated group prior to vaccine administration. In the
unvaccinated group, COVID-19 infections occurred during each trimester of pregnancy, with 26
infections in the first trimester, 84 during the second trimester, and 100 in the third trimester
(Table 2). The composite pregnancy outcome, AOI, did not differ by maternal vaccination
status, with rates of 5.0% (7/140) vs. 4.9% (91/1862) in the vaccinated and unvaccinated groups
(95% CI for difference in proportions, -3.6% to 3.6%). No maternal or early neonatal deaths
occurred in the cohort. Mode of delivery, gestational age at delivery, neonatal birth weight,
thromboembolic events, and rates of gestational hypertension and pre-eclampsia also did not
significantly differ between groups. Additional comparison between COVID-19 infected, non-
vaccinated patients (n=210) and vaccinated patients without a history of COVID-19 infection
(n=138) did not show any difference among the pregnancy outcomes examined in the cohort,
but the study was not sufficiently powered to detect a difference in these outcomes (Appendix
Table A2). Among the unvaccinated patients, pregnancy and birth outcomes did not
significantly differ between those with (n=210) versus without (n=1652) a COVID-19 infection
during pregnancy (Appendix Table A2).
Discussion
PRINCIPAL FINDINGS: COVID-19 vaccine administration to pregnant patients was associated
with fewer COVID-19 infections during pregnancy and did not result in a detectable increase in
adverse outcomes during pregnancy, delivery, or the delivery hospitalization.
RESULTS: Sociodemographic factors associated with increased vaccination rates in
pregnancy included older age, higher level of maternal education, being a non-smoker, use of
infertility treatment for the current pregnancy, and lower gravidity. No patterns of adverse
maternal or neonatal outcomes were observed in this cohort of 140 pregnant patients who were
vaccinated under the FDA emergency use authorizations for SARS-CoV-2 vaccines, and
significantly fewer vaccinated women experienced COVID-19 infection during the pregnancy
when compared to unvaccinated women.
CLINICAL IMPLICATIONS: Given the danger of COVID-19 infection during pregnancy and early
studies supporting the safety and effectiveness of vaccination in pregnant patients, specific
efforts should be targeted toward the less vaccinated populations to enhance uptake moving
forward. This study reveals sociodemographic factors associated with vaccine access and/or
uptake in the pregnant population. Vaccination eligibility during the timeframe analyzed was
limited to healthcare workers, the elderly, and teachers or other essential workers. For this
reason, we cannot discern whether sociodemographic differences in vaccination status are due
to vaccine hesitancy or differences in eligibility for vaccination, but we do observe
socioeconomic disparity between those who received vaccination during gestation and those
who did not.
RESEARCH IMPLICATIONS: The current study largely represents outcomes after third
trimester vaccination, but patients who received the vaccine during the late first through second
trimesters and delivered preterm are also represented in this data set. The absence of an
increase in preterm births in the cohort thus suggests that vaccination is unlikely to increase
preterm birth rates, but analysis of outcomes from currently ongoing pregnancies will be needed
to confirm this finding. Additional studies will be needed to examine differences in rare adverse
birth outcomes, as well as outcomes following vaccination during early pregnancy.
STRENGTHS AND LIMITATIONS: Strengths of this study include the inclusion of
comprehensive population-level vaccine registry data in combination with a validated, all-
inclusive delivery database including births at multiple community and teaching hospitals across
two states. As the data were extracted from the primary medical record it is not subject to recall
bias. Given the absence of infection in any vaccinated patients after the first dose administration
(incidence rate ratio of zero and vaccine efficacy of one) with a short observation period, our
ability to estimate vaccine efficacy is limited for this cohort. Other limitations of this analysis
include the small percentage of non-white subjects in this geographic region, the potential for
confounding due to the observational nature of the study, as well as the data currently available
being biased toward those vaccinated later in gestation and skewed toward the population in the
United States healthcare workforce. Finally, only two COVID-19 infections occurred in the
vaccinated group early in pregnancy, so they may be a group who had lower baseline exposure
compared to the unvaccinated group. Pre-pregnancy COVID-19 infection history was not
available, so previously existing antibody status was unknown and limits the efficacy
conclusions.
CONCLUSIONS: While COVID-19 infection in pregnancy has been associated with significant
adverse maternal and neonatal outcomes in multiple studies, the current findings should give
clinicians confidence that COVID-19 vaccination during pregnancy is protective against
maternal SARS-CoV-2 infection and that no pattern of adverse maternal or birth outcomes is
evident after vaccination during pregnancy. Outreach to under-represented populations of
pregnant patients should be a focus of future education and vaccination efforts.
References
1. BADEN LR, EL SAHLY HM, ESSINK B, et al. Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. New England Journal of Medicine 2021;384:403-16.
2. POLACK FP, THOMAS SJ, KITCHIN N, et al. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. New England Journal of Medicine 2020;383:2603-15.
3. ADHIKARI EH, SPONG CY. COVID-19 Vaccination in Pregnant and Lactating Women. JAMA 2021;325:1039-40.
4. Vaccinating Pregnant and Lactating Patients Against COVID-19Practice Advisory: American College of Obstetrics and Gynecology, 2021.
5. VILLAR J, ARIFF S, GUNIER RB, et al. Maternal and Neonatal Morbidity and Mortality Among Pregnant Women With and Without COVID-19 Infection: The INTERCOVID Multinational Cohort Study. JAMA pediatrics 2021.
6. ADHIKARI EH, MORENO W, ZOFKIE AC, et al. Pregnancy Outcomes Among Women With and Without Severe Acute Respiratory Syndrome Coronavirus 2 Infection. JAMA network open 2020;3:e2029256-e56.
7. LOKKEN EM, HUEBNER EM, TAYLOR GG, et al. Disease severity, pregnancy outcomes, and maternal deaths among pregnant patients with severe acute respiratory syndrome coronavirus 2 infection in Washington State. American Journal of Obstetrics and Gynecology 2021.
8. VILLAR J, ARIFF S, GUNIER RB, et al. Maternal and Neonatal Morbidity and Mortality Among Pregnant Women With and Without COVID-19 Infection: The INTERCOVID Multinational Cohort Study. JAMA Pediatr 2021.
9. RASMUSSEN SA, JAMIESON DJ. Pregnancy, Postpartum Care, and COVID-19 Vaccination in 2021. JAMA 2021;325:1099-100.
10. COLLIER A-RY, MCMAHAN K, YU J, et al. Immunogenicity of COVID-19 mRNA Vaccines in Pregnant and Lactating Women. JAMA 2021.
11. SHIMABUKURO TT, KIM SY, MYERS TR, et al. Preliminary Findings of mRNA Covid-19 Vaccine Safety in Pregnant Persons. New England Journal of Medicine 2021:NEJMoa2104983-NEJMoa83.
12. ATALLAH F, BERNSTEIN PS, DIAZ DA, MINKOFF H. The Adverse Outcome Index: Putting Quality into an Outcome Measure. Obstetrics and Gynecology 2018;132:750-53.
13. FOGLIA LM, NIELSEN PE, HEMANN EA, et al. Accuracy of the adverse outcome index: An obstetrical quality measure. Joint Commission Journal on Quality and Patient Safety 2015;41:370-77.
14. TOLCHER MC, TORBENSON VE, WEAVER AL, et al. Impact of a labor and delivery safety bundle on a modified adverse outcomes index Presented at the Central Association of Obstetricians and Gynecologists 82nd annual meeting, Oct. 21-24, 2015, Charleston, SC. American Journal of Obstetrics and Gynecology 2016;214:401.e1-01.e9.
Table 1. Socio-demographics in Unvaccinated and Vaccinated Patients
Characteristic
COVID Vaccine During Pregnancy Total
(N=2002) P-value†
No (N=1862)
Yes (N=140)
Maternal Age at Delivery (years), Mean (SD)
30.5 (5.2) 31.8 (3.7) 30.1 (5.2) <0.001
Race 0.019
Asian 89 (4.8%) 6 (4.3%) 95 (4.8%)
Black or African American 99 (5.4%) 3 (2.2%) 102 (5.1%)
Others combined 128 (6.9%) 2 (1.4%) 130 (6.6%)
White 1528 (82.9%) 128 (92.1%) 1656 (83.5%)
Unknown/Not Disclosed 18 1 19
Ethnicity 0.022
Hispanic or Latino 173 (9.5%) 5 (3.6%) 178 (9.1%)
Not Hispanic or Latino 1651 (90.5%) 132 (96.4%) 1783 (90.9%)
Unknown/Not Disclosed 38 3 41
Education (years) <0.001
<12 70 (4.7%) 0 (0.0%) 70 (4.3%)
12-16 1218 (81.9%) 70 (53.4%) 1288 (79.6%)
>16 199 (13.4%) 61 (46.6%) 260 (16.1%)
Not documented 375 9 384
Current Smoker 196 (10.5%) 0 (0.0%) 196 (9.8%) <0.001
Illicit Drug Use 56 (3.0%) 0 (0.0%) 56 (2.8%) 0.030
Gravidity 0.007
1 546 (29.3%) 56 (40.0%) 602 (30.1%)
2 519 (27.9%) 34 (24.3%) 553 (27.6%)
3 350 (18.8%) 29 (20.7%) 379 (18.9%)
4+ 447 (24.0%) 21 (15.0%) 468 (23.4%)
Pre-Pregnancy BMI 0.004
<25 573 (39.6%) 70 (56.5%) 643 (41.0%)
25-30 409 (28.3%) 21 (16.9%) 430 (27.4%)
30-35 226 (15.6%) 15 (12.1%) 241 (15.4%)
35-40 139 (9.6%) 14 (11.3%) 153 (9.7%)
40+ 99 (6.8%) 4 (3.2%) 103 (6.6%)
Not documented 416 16 432
Pre-Gestational Diabetes 11 (0.6%) 2 (1.4%) 13 (0.6%) 0.23
Pre-Gestational Hypertension
64 (3.4%) 6 (4.3%) 70 (3.5%) 0.63
Asthma 206 (11.1%) 15 (10.7%) 221 (11.0%) 0.90
Infertility Treatment 14 (0.8%) 6 (4.3%) 20 (1.0%) 0.002
Multiple Gestation 0.68
Singleton 1840 (98.8%) 138 (98.6%) 1978 (98.8%)
Twins 22 (1.2%) 2 (1.4%) 24 (1.2%)
GBS Test Result 0.51
Negative 1283 (80.8%) 94 (78.3%) 1377 (80.6%)
Positive 305 (19.2%) 26 (21.7%) 331 (19.4%)
Not Tested 274 20 294
Abbreviations: BMI, body mass index; GBS, Group B Streptococcal.
†Comparisons between groups were evaluated using the two-sample t-test for maternal
age, the Wilcoxon rank sum test for maternal education, gravida, and parity, and the
chi-square test or Fisher’s exact test for the remaining categorical
Table 2. Pregnancy and Birth Outcomes in Unvaccinated and Vaccinated Patients
Outcome
Covid-19 vaccine during pregnancy
Total (N=2002)
P-value†
No (N=1862)
Yes (N=140)
Covid-19 Infection During Pregnancy
0.003
None 1652 (88.7%)
138 (98.6%)
1790 (89.4%)
Trimester 1 26 (1.4%) 0 (0.0%) 26 (1.3%)
Trimester 2 84 (4.5%) 2 (1.4%) 86 (4.3%)
Trimester 3 100 (5.4%) 0 (0.0%) 100 (5.0%)
AOI 91 (4.9%) 7 (5.0%) 98 (4.9%) 0.95
AOI Excluding Laceration 55 (3.0%) 5 (3.6%) 60 (3.0%) 0.61
AOI components
Maternal Death During Hospitalization
0 (0.0%) 0 (0.0%) 0 (0.0%) --
Intrapartum Neonatal Death Within 7 Days of Birth, ≥ 2500 g, ≥37 Weeks Gestation
0 (0.0%) 0 (0.0%) 0 (0.0%) --
Hypoxic, Ischemic Encephalopathy
1 (0.1%) 0 (0.0%) 1 (0.0%) 1.00
Uterine Rupture 1 (0.1%) 0 (0.0%) 1 (0.0%) 1.00
Unplanned Maternal ICU Admission
2 (0.1%) 1 (0.7%) 3 (0.1%) 0.20
Birth Trauma 11 (0.6%) 0 (0.0%) 11 (0.5%) 1.00
Return to Operating Room 6 (0.3%) 1 (0.7%) 7 (0.3%) 0.40
NICU admit within 1 Day of Birth, for > 1 Day, ≥ 2500 g, ≥37 Weeks Gestation
11 (0.6%) 1 (0.7%) 12 (0.6%) 0.58
5-Minute Apgar <7, ≥ 2500 g, ≥37 Weeks Gestation
38 (2.0%) 3 (2.1%) 41 (2.0%) 0.76
Postpartum Hemorrhage With transfusion
5 (0.3%) 1 (0.7%) 6 (0.3%) 0.35
3rd or 4th Degree Laceration
37 (2.0%) 2 (1.4%) 39 (1.9%) 1.00
Mode of Delivery 0.65
Spontaneous Vaginal 1238 (66.5%)
89 (63.6%)
1327 (66.3%)
Operative Vaginal 69 (3.7%) 7 (5.0%) 76 (3.8%)
Cesarean 555 (29.8%) 44 (31.4%)
599 (29.9%)
Gestational Age at Delivery (weeks)
0.70281
37+ 1703 (91.5%)
127 (90.7%)
1830 (91.4%)
32-36 6/7 134 (7.2%) 10 (7.1%) 144 (7.2%)
24-31 6/7 21 (1.1%) 2 (1.4%) 23 (1.1%)
<24 4 (0.2%) 1 (0.7%) 5 (0.2%)
Length of Stay (days), Median (IQR)‡
2 (1, 2) 2 (1, 2) 2 (1, 2) 0.27
Quantitative Blood Loss > 1000 mL
57 (3.1%) 6 (4.3%) 63 (3.1%) 0.45
Transfusion 241 (12.9%) 25 (17.9%)
266 (13.3%) 0.12
Thromboembolism1 2/1580 (0.1%)
0/129 (0%)
2 (0.1%) 1.00
Stroke1 2/1581 (0.1%)
0/129 (0.0%)
2 (0.0%) 1.00
Eclampsia / Pre-Eclampsia Up to 72 Hours from Delivery
23 (1.2%) 1 (0.7%) 24 (1.2%) 1.00
Gestational Hypertension 225 (12.1%) 19 (13.6%)
244 (12.2%) 0.60
Low Birth Weight (<2500 g) 121 (6.5%) 11 (7.9%) 132 (6.6%) 0.53
Very Low Birth Weight (<1500 g)
21 (1.1%) 3 (2.1%) 24 (1.2%) 0.23
Stillbirth 6 (0.3%) 0 (0.0%) 6 (0.3%) 1.00
Abbreviations: AOI, Adverse Outcome Index; IQR, interquartile range (25th and 75th percentiles)
1 Thromboembolism and stroke were assessed within 4 weeks before or after delivery. Crude
percentages are reported among the subset who either had the outcome or who had sufficient follow-
up.
†Comparisons between groups were evaluated using the Wilcoxon rank sum test for gestation age and length of stay and the chi-square test or Fisher’s exact test for the categorical variables. ‡ Length of stay from time of delivery to discharge from the hospital.
COVID-19 vaccination in pregnancy
Journal Pre-proof
COVID-19 vaccination in pregnancy: early experience from a singleinstitution
Megan E. Trostle MD , Meghana A. Limaye MD ,Ms. Valeryia Avtushka , Jennifer L. Lighter MD ,Christina A. Penfield MD MPH , Ashley S. Roman MD MPH
PII: S2589-9333(21)00159-2DOI: https://doi.org/10.1016/j.ajogmf.2021.100464Reference: AJOGMF 100464
To appear in: American Journal of Obstetrics & Gynecology MFM
Received date: 7 May 2021Revised date: 2 August 2021Accepted date: 11 August 2021
Please cite this article as: Megan E. Trostle MD , Meghana A. Limaye MD , Ms. Valeryia Avtushka ,Jennifer L. Lighter MD , Christina A. Penfield MD MPH , Ashley S. Roman MD MPH , COVID-19vaccination in pregnancy: early experience from a single institution, American Journal of Obstetrics& Gynecology MFM (2021), doi: https://doi.org/10.1016/j.ajogmf.2021.100464
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© 2021 Published by Elsevier Inc.
COVID-19 vaccination in pregnancy: early experience from a single institution
Short title: COVID-19 vaccination in pregnancy
Megan E. TROSTLE MD,1 Meghana A. LIMAYE MD,
1 Ms. Valeryia AVTUSHKA,
1 Jennifer
L. LIGHTER MD,2 Christina A. PENFIELD MD MPH,
1 Ashley S. ROMAN MD MPH
1
1. Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, New
York University Langone Health, New York, NY
2. Division of Pediatric Infectious Diseases, Department of Infection Prevention and
Control and Pediatrics, New York University Langone Health, New York, NY
Disclosures: The authors report no conflict of interest.
Funding: The authors received no funding for this research.
Corresponding author:
Megan E. Trostle, MD
550 First Avenue
NBV 9N2
New York, NY 10016
Mobile: 201-873-2254
Word count: 723
Acknowledgments: none
Keywords: COVID-19, infectious disease, maternal morbidity, neonatal health, pregnancy,
public health, vaccination
Objective
Pregnant women are at increased risk for morbidity due to infection with COVID-191.
Vaccination presents an important strategy to mitigate illness in this population. However, there
is a paucity of data on vaccine safety and pregnancy outcomes as pregnant women were
excluded from initial Phase 3 clinical trials. Our objective was to describe maternal, neonatal,
and obstetrical outcomes of women who received an mRNA COVID-19 vaccine during
pregnancy during the first four months of vaccine availability.
Study Design
This was an IRB-approved descriptive study of pregnant women at NYU Langone Health
who received at least one dose of an mRNA COVID-19 vaccine approved by the Food and Drug
Administration (Pfizer/BioNTech or Moderna) from time of FDA Emergency Use Authorization
to April 22, 2021. Eligible women were identified via search of the electronic medical record
(EMR). Vaccine administration was ascertained via immunization records from the New York
State Department of Health. Women were excluded if they were vaccinated prior to conception
or during the postpartum period. Charts were reviewed for maternal demographics and
pregnancy outcomes. Descriptive analyses were performed using R Version 4.0.2 (Boston, MA).
Results
We identified 424 pregnant women who received an mRNA vaccination. 348 (82.1%)
received both doses and 76 (17.9%) received only one dose. Maternal characteristics and
vaccination information are shown in Table 1. 4.9% of women had a history of confirmed
COVID-19 infection prior to vaccination. After vaccination, no patient in our cohort was
diagnosed with COVID-19 infection. In terms of pregnancy outcomes, 9 had spontaneous
abortions, 3 terminated their pregnancies, and 327 have ongoing pregnancies. 85 delivered
liveborn infants. There were no stillbirths in our population.
Eight of the nine spontaneous abortions occurred in the first trimester at a range of 6-13
weeks gestation. There was one second trimester loss. The rate of spontaneous abortion among
women vaccinated in the first trimester was 6.5%.
The 327 women with ongoing pregnancies have been followed for a median of 4.6 weeks
(range 0-17) following their most recent dose. 113 (34.6%) initiated vaccination in the first
trimester, 178 (54.4%) in the second trimester, and 36 (11.0%) in the third trimester. Following
vaccination, two fetuses (0.6%) developed growth restriction while five (1.5%) were diagnosed
with anomalies.
Outcomes for the 85 women who delivered are shown in Table 2. 18.8% of women were
diagnosed with a hypertensive disorder of pregnancy. The rate of preterm birth was 5.9%. One
preterm delivery was medically indicated while the remaining three were spontaneous. 15.3% of
neonates required admission to the neonatal intensive care unit (NICU). 61.5% of NICU
admissions were due to hypoglycemia or evaluation for sepsis. Other reasons for admission
included prematurity, hypothermia, and transient tachypnea of the newborn. 12.2% of neonates
were small for gestational age (SGA) per World Health Organization standards.
Conclusion
This series describes our experience with women who received an mRNA COVID-19
vaccination while pregnant. In line with other published findings2, we observed no concerning
trends. There were no stillbirths. Our 6.5% rate of spontaneous abortion is within the expected
rate of 10%3 and our preterm birth rate of 5.9% is below the national average of 9.5%.
4 Our rate
of pregnancy-related hypertensive disorders is higher than our baseline institutional rate of 9.5%,
though this may be due to underlying characteristics of our study population or skewed by small
sample size. Our 12.2% rate of SGA neonates is near the expected value as well, given by
definition 10% of neonates will be SGA at birth. The NICU admission rate is on par with our
institutional rate of 12%. To date, most women in this series have had uncomplicated
pregnancies and have delivered at term.
Strengths of this study include using the EMR to identify subjects and gather data. We
did not rely on self-enrollment and self-report, reducing selection and recall bias. By performing
manual chart review, we obtained detailed and reliable information about individual patients.
One limitation of this study is lack of a matched control group consisting of unvaccinated
pregnant women, so direct conclusions are unable to be drawn about relative risk of
complications. In addition, our cohort is small and may not be generalizable. Finally, many
women included are healthcare workers who had early access to the vaccine.
As more pregnant women become eligible for the COVID-19 vaccine, there is an urgent
need to report on maternal, neonatal, and obstetrical outcomes with COVID-19 vaccine in
pregnancy. The results of this study can be used to counsel and reassure pregnant patients facing
this decision.
References
1. S Ellington S, Strid P, Tong VT, et al. Characteristics of Women of Reproductive Age with
Laboratory-Confirmed SARS-CoV-2 Infection by Pregnancy Status - United States, January
22-June 7, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(25):769-775. Published 2020 Jun
26.
2. Shimabukuro TT, Kim SY, Myers TR, et al. Preliminary Findings of mRNA Covid-19
Vaccine Safety in Pregnant Persons [published online ahead of print, 2021 Apr 21]. N Engl J
Med. 2021;10.1056/NEJMoa2104983.
3. American College of Obstetricians and Gynecologists' Committee on Practice Bulletins—
Gynecology. ACOG Practice Bulletin No. 200: Early Pregnancy Loss. Obstet Gynecol.
2018;132(5):e197-e207.
4. Ferré C, Callaghan W, Olson C, Sharma A, Barfield W. Effects of Maternal Age and Age-
Specific Preterm Birth Rates on Overall Preterm Birth Rates - United States, 2007 and
2014. MMWR Morb Mortal Wkly Rep. 2016;65(43):1181-1184. Published 2016 Nov 4.
Table 1: Study population demographics and vaccination characteristics
Study variable Total study population
N=424
Age (years) 35 (6)
Age ≥35 years 220 (51.9)
Race/ethnicity
White
Black
Asian
Hispanic/Latino
Other/not recorded
262 (61.8)
22 (5.2)
57 (13.4)
37 (8.7)
46 (10.8)
Pre-pregnancy body mass index (kg/m2) 23.2 (5.2)
a
Body mass index ≥30 kg/m2 42 (11.3)
a
Pre-pregnancy comorbidities
Chronic hypertension
Pregestational diabetes
Cardiac disease
Respiratory disease
Autoimmune disease
Malignancy (past or present)
28 (6.6)
5 (1.2)
10 (2.4)
38 (9.0)
19 (4.5)
10 (2.4)
Nulliparous 267 (63.0)
Insurance
Private
407 (96.0)
Public
Unknown/uninsured
16 (3.8)
1 (0.2)
History of COVID infection 21 (4.9)
Vaccine type
Pfizer/BioNTech
Moderna
332 (78.3)
92 (21.7)
Gestational age at first dose (weeks) 21.0 (16.4)
Gestational age at second dose (weeks) 23.9 (17.6)
Trimester at vaccine initiation
First (<14 weeks)
Second (14-27 weeks)
Third (>28 weeks)
124 (29.2)
193 (45.5)
107 (25.2)
Data reported as n (%) or median (IQR)
a. Missing values, n=371
Table 2: Characteristics and outcomes of delivered women
Study variable Total delivered population
N=85
Vaccine type
Pfizer/BioNTech
Moderna
65 (86.5)
20 (23.5)
Trimester at vaccine initiation
First (<14 weeks)
Second (14-27 weeks)
Third (>28 weeks)
0
14 (16.5)
71 (83.5)
Time from vaccination until delivery (weeks) 2.86 (0.29 - 12.7)
Both vaccine doses completed prior to delivery 68 (80)
Fetal or neonatal demise 0
Gestational age at delivery (weeks) 39.3 (33.0 - 41.7)
Preterm delivery <37 weeks 5 (5.9)
Mode of delivery
Vaginal birth
Cesarean birth
55 (64.7)
30 (35.3)
Obstetrical complications
Pregnancy-related hypertensive disorders
Preterm labor
Preterm prelabor rupture of membranes
Abruption
16 (18.8)
0
2 (2.4)
1 (1.2)
Placenta previa 1 (1.2)
Neonatal intensive care unit admission 13 (15.3)
Birthweight (grams) 3374 (1910 - 4360)
Small for gestational age 10 (12.2)
Congenital anomalies 2 (1.2)
Data reported as n (%) or median (range)