key: cord-0902040-b7ogeokm
authors: Smith, E. R.; He, S.; Oakley, E. M.; Miller, L.; Tielsch, J. M.
title: Protocol for a Sequential, Prospective Meta-Analysis to Describe COVID-19 in Pregnancy and Newborn Periods
date: 2020-11-12
journal: nan
DOI: 10.1101/2020.11.08.20228056
sha: dc3b4cabbfa22245d807087b6db891df9d66af92
doc_id: 902040
cord_uid: b7ogeokm

Background. We urgently need answers to basic epidemiological questions regarding COVID-19 infection in pregnant women and newborns. While many national registries, health facilities, and research groups are collecting relevant data, we need a collaborative and methodologically appropriate approach to utilize these data to generate answers. Methods. We propose that a sequential, prospective meta-analysis (PMA) is the best approach to rapidly generate policy and practice-oriented guidelines. As the pandemic is rapidly evolving, studies identified retrospectively through a living systematic review will also be invited to participate. The primary analysis will pool data using a two-stage meta-analysis with generic inverse-variance methods. The meta-analyses will be updated as additional data accrues in each contributing study and as additional studies meet study-specific time or data accrual thresholds for sharing. Participating Studies. At the time of publication, there are 19 studies being conducted in 21 countries that prospectively agreed to pool data for this analysis. Among the 19 included studies, ten are COVID-19 registry studies, seven are cohort or surveillance studies, and two are case-control studies. More than 74,000 pregnant women are expected to contribute to the completed analysis. Dissemination: Protocols and updates will be maintained publicly. Results will be shared with key stakeholders including the World Health Organization (WHO) Maternal, Newborn, Child, and Adolescent Health (MNCAH) Research Working Group. Scientific publications will be published in open access journals on an ongoing basis.

The coronavirus disease 2019 (COVID-19) has led to over 43 million confirmed cases and claimed more than 1.1 million lives globally as of October 27, 2020 (1) . The Centers for Disease Control and Prevention (2) notes that pregnant women may be at higher risk of developing severe illness due to COVID-19. The concern was initially based on the fact that pregnant women are generally at increased risk for severe illness with many infectious diseases including influenza, hepatitis E, malaria, and herpes simplex virus (3) . The specific mechanisms as to why this might also be the case for SARS-CoV-2 infection are currently unclear, though may be related to physiologic and immunologic changes during pregnancy (4, 5) . A living systematic review suggests that pregnant women, compared with non-pregnant women, are 62% more likely to be admitted to an intensive care unit and 88% more likely to require invasive ventilation (last updated: August 2020) (5) . However, these data should be interpreted with caution, because the vast majority came from the United States surveillance program with high rates of missing data (4) . To date, evidence suggests that most reported COVID-19 cases in pregnancy occurred in the later stages of gestation, particularly in the third trimester (6) . In a US study of 64 hospitalized pregnant women, iatrogenic preterm delivery was reported in 75% of the patients with critical COVID-19 illness (7) . Another two studies (313 women) reported a two-fold higher risk of preterm birth in COVID-infected versus uninfected pregnancies (5) . There is limited evidence suggest potential risk to neonates as well. A study of 1121 neonates in the UK reported a three-fold increased odds of neonatal intensive care unit (NICU) admission among infants born to mothers with COVID-19, compared to historical controls (5) .

Despite the urgent need to accurately document the number of cases, severe illness, and deaths in pregnant people, as well as transmission rates and consequences of SARS-CoV-2 infection in newborns, relevant data are limited (4) . Further, pregnant people have been systematically excluded from clinical trials assessing the efficacy of COVID-related treatment and preventives in an effort to avoid this medically complex population (8) . There are also misplaced ethical concerns that actually creates an ethical dilemma: the exclusion of pregnant people at the stage of developing vaccines or treatments may ultimately pose harm to this very population (8) . There are also challenges in establishing mother-to-child transmission of SARS-CoV-2 because there is no consensus case definition for intrauterine versus intrapartum or early peripartum transmission, and proposed definitions require researchers to follow complex protocols; WHO is expected to share an expert consensus on the case definition before the end of 2020 (6, (9) (10) (11) (12) . Given the scarcity of COVID data in pregnancy, differences in data collection protocols globally, and potential risks for severe illnesses in this population, there is an urgent need to rapidly generate high quality information to make evidence-based decisions and create guidelines on the prevention and treatment of COVID-19 illness in pregnant women and infants.

We propose that a sequential, prospective meta-analysis (PMA) is the best approach to rapidly accrue harmonized global data to generate policy and practice-relevant data regarding the epidemiology of COVID-19 in the pregnancy, peripartum, and postnatal period.

A prospective meta-analysis identifies studies that will contribute data to the meta-analysis, as well as establishes the analysis plans, before the results of the individual studies are known (13) . This approach is similar to a multi-site registry or cohort in the sense that studies work to harmonize collection of key outcomes, but differs from multi-site studies in that each site will implement a study design and local protocol that is appropriate for their context (13) .

There are many benefits to our approach. One major benefit of a PMA in the context of COVID-19 is that we were able to standardize some data collection components while a number of participating studies were starting. Early efforts to plan for pooling can also reduce research waste (e.g. incompatible data, duplication of efforts) and improve the collective value of data in a collaborative way (14) . Using individual participant data also allows us to avoid duplicate case counting. This has been a major issue in COVID-related meta-analyses because much scientific literature is based on case reports or case series; the same cases sometimes appear in multiple published papers.

The protocol was registered with PROSPERO (ID: 188955) on May 28, 2020.

The study aims to answer basic epidemiological questions about COVID-19 and about maternal and newborn health in the context of COVID-19.

Specific objectives regarding COVID-19 among pregnant or recently pregnant women include:

• Describe the natural history of disease (COVID-19); • Estimate the incidence of disease severity-related healthcare utilization including hospitalization, admittance to the intensive care unit, and use of invasive ventilation (for COVID-19); • Estimate infection and case fatality rate.

Specific objectives regarding maternal health among pregnant or recently pregnant women with COVID-19 include:

• Estimate the incidence of maternal morbidities; • Estimate the maternal mortality ratio;

• Describe the incidence of adverse pregnancy outcomes.

Specific objectives regarding newborn health among newborns born to women with COVID-19 including:

• Describe the incidence of congenital anomalies; • Estimate the perinatal and (early) neonatal mortality rate;

• Estimate the incidence of transmission of SARS-CoV-2 from mother to child.

Specific objectives regarding SARS-CoV-2 in biospecimens include:

• Estimate the proportion of biospecimens with detectable SARS-COV2 virus and median viral load; • Estimate the association between virus or viral load in biospecimen and a) severity of disease, b) maternal morbidity, c) maternal mortality, d) vertical transmission.

We recruited study sites to join the proposed PMA first via professional research networks, and subsequently via key stakeholder networks. Stakeholders at the National Institute of Child Health and Human Development (NICHD) at the U.S. National Institutes of Health (NIH) supported recruitment of NIH-funded maternal and child health network groups and other US government funded projects. Stakeholders at WHO in the Maternal, Newborn, Child and Adolescent health (MNCAH) Department and Department of Sexual and Reproductive Health and Research groups supported recruitment based on the current group of researchers engaged in the COVID-19 MNCAH research network. Stakeholders from the International Federation of Gynecology and Obstetrics (FIGO) supported recruitment by issuing an invitation through their international network. Studies were invited to participate based solely on study design. Eligible study designs included a) registries enrolling all suspected or confirmed pregnant or recently postpartum women, b) cohorts enrolling all pregnant women, or c) a casecontrol studies enrolling cases of pregnant or recently postpartum women with COVID. There were no a priori sample size limitations due the dynamic epidemiology of the pandemic. Study investigators confirmed their intent to contribute to the PMA by signing a letter of intent.

At the time of publication, there were 19 studies taking place in 21 countries that prospectively agreed to pool data for this analysis (Supplementary Table 1 ). Among these 19 prospectively included studies, ten are COVID-19 registry studies, seven are cohort or surveillance studies, and two are case-control studies. More than 74,000 pregnant women are expected to contribute to the completed analysis (Supplementary Table 1 Building off of the concepts laid out in the Framework for Adaptive Meta-analyses (FAME) (15), we will also collaborate with a living systematic review (LSR) project to identify studies that might be eligible for post-publication inclusion into the proposed meta-analysis. The search strategy for the LSR has been previously published (5) . LSR project team members will screen all studies for potential inclusion in the PMA using the following criteria: i) The study conforms to the study designs outlined above; ii) There is a defined catchment area (e.g. certain hospitals, states, etc.); iii) More than 25 pregnant or recently postpartum women were consecutively recruited.

Confirmed cases of COVID-19 will be defined as those with laboratory-confirmed SARS-CoV-2 via a nucleic acid amplification test, regardless of clinical signs or symptoms. The protocol may be expanded to included cases confirmed via antigen or other tests as they are validated and become widely available. Suspected cases will be defined according to the WHO August 7, 2020 case definition based on either clinical and epidemiological criteria or the severe acute respiratory illness (SARI) case definition (16) . Probable COVID-19 infections will also be defined according to the WHO August 7, 2020 case definition (16) .

Analyses will be done in three groups. First descriptive epidemiology regarding COVID-19 in pregnancy and the perinatal period will be presented without a comparison group. Second, some analyses regarding morbidity and mortality will assess outcomes comparing pregnant women with confirmed or suspected COVID-19 to other pregnant women without COVID-19. Third, we will compare women with confirmed or suspected COVID-19 to non-pregnant women with confirmed or suspected COVID-19.

• Mortality outcomes of interest for women include: all-cause mortality, COVID-19 specific mortality, and pregnancy-related mortality. • Morbidity outcomes of interest for women include COVID-19 related clinical signs and symptoms (fever, cough, shortness of breath, dizziness or fainting, body aches, runny nose, sore throat, loss of sense of smell, loss of sense of taste, sneezing, fatigue, nausea, vomiting, diarrhea, headache) and pregnancy-related clinical signs and symptoms (hypertensive disease of pregnancy (including preeclampsia/eclampsia), gestational diabetes, hyperemesis, intrauterine growth restriction, abnormal placentation (placental previa/accreta/percreta), placental abruption, bacterial infection prior to hospital visit, preterm contractions (not in labor), preterm labor, preterm rupture of membranes, hemorrhage (antepartum/intrapartum; postpartum; abortion-related), embolic disease, anesthetic complications). • Other morbidity-related healthcare outcomes include hospitalization, admittance to an intensive care unit or requiring critical care, and requiring intensive ventilation. Adverse pregnancy outcomes of interest include: stillbirth (categorized as both fetal death >28 weeks per WHO), early preterm birth (<34 weeks gestation), preterm birth (<37 weeks gestation), small-for-gestational-age birth (<10th percentile per the Intergrowth newborn reference values), and low birthweight (<2500 g). We will assess SARS-CoV-2 viral load in maternal biological specimens including: amniotic fluid, placenta (maternal or fetal side), cord blood, vaginal swab, feces or rectal swab, nasopharyngeal swab, pregnancy tissue (fetus or pregnancy sac and placenta) in the case of fetal demise or induced abortion, breastmilk, and maternal blood.

• Neonatal outcomes of interest include congenital anomalies, namely neural tube defects, microcephaly, congenital malformations of ear, congenital heart defects, orofacial clefts, congenital malformations of digestive system, congenital malformations of genital organs, abdominal wall defects, chromosomal abnormalities, reduction defects of upper and lower limbs, talipes equinovarus/clubfoot. • We will measure early neonatal (7 day), neonatal (28 day), and six-week infant mortality (42 days). We will also measure perinatal death defined as a stillbirth or early neonatal death. • Mother-to-child transmission of SARS-CoV-2 will also be measured, with an effort to differentiate intrauterine versus intrapartum or early peripartum infection. These definitions will be aligned with the WHO consensus case definitions once they become available.

We developed the draft data modules and questions in April 2020 based on a proposed set of questions from the Pregnancy CoRonavIrus Outcomes RegIsTrY (PRIORITY) study. We also reviewed and included questions from the data collection forms developed by the World Health Organization (WHO) and the U.S. Center for Disease Control (CDC). We requested two rounds of feedback via a survey and by email from the >50 participants of the bi-monthly informal meeting established at the beginning of the pandemic called the "Perinatal COVID-19 Global Gathering". The current data modules reflect feedback and general consensus among survey respondents. The final draft of the data modules and core variables was finalized and shared broadly on June 2, 2020 (Supplementary File 2). We updated the data modules in September 2020 to reflect evolving understanding of SARS-CoV-2 infection in newborns and to reflect and an updated generic protocol developed by WHO for COVID-related pregnancy cohort studies (Supplementary File 3) .

We will develop a codebook and statistical codes for each study to map original study variables to the PMA core variables. The same data quality and consistency checks will be performed for each study, and any issues will be resolved with study investigators. Studies will be eligible to contribute data to the PMA when they have accrued at least 25 confirmed cases with completed follow up including obtaining maternal and neonatal outcomes.

Study-specific estimates for the two-stage meta-analysis will be produced using standardized analytical codes, and aggregated measures will be exported into a standardized database to be used for the meta-analysis.

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Ideally all individual-level data would be combined for one-stage meta-analysis. However, we anticipate that the ability to quickly share data and the degree of willingness to share individual patient data may vary by country and across collaborators. Thus, we will plan for a step-wise statistical analysis plan where the most feasible and simple analyses (that contribute directly to our research questions) are prioritized, and more advanced statistical modelling will be conducted subsequently.

For the first stage of analysis, data for each research question will be pooled using a two-stage, random-effects meta-analysis using conventional DerSimonian-Laird methods (17) . For analyses where only proportions or crude incidence rates are used, the Arcsine method may be applied to stabilize the statistics and ensure approximate asymptotic normality (18). We will assess forest plots visually for heterogeneity. When at least ten studies are being pooled, we will also quantify heterogeneity by I 2 . Further model fit analyses may also include inspection of the impact on the former two heterogeneity statistics when excluding apparent outlier studies.

Where appropriate and as sample size allows, we will consider meta-regression or subgroup analyses by the following study level characteristics: study design and sampling strategy, proportion of confirmed COVID-19 cases (out of suspected and confirmed cases), national maternal mortality ratio, national neonatal mortality rate. We will also consider subgroup analysis by the following individual patient characteristics: Confirmed versus suspected COVID case status; gestational age at COVID onset (by week, by trimester), COVID severity, prepregnancy health conditions, maternal morbidity, time since first COVID diagnosis in the study area, gravidity, parity, maternal age, race or ethnicity, and maternal education.

The steering committee will consist of at least one member from each participating site, key stakeholders (Supplementary Table 3) , and the technical coordinating team. In the case a formal vote is needed, the following can each cast one official vote: each participating study, each key stake holder organization, and the technical coordinating team. The steering committee will prioritize research questions and agree on common elements of data collection. They will disseminate results, including rapid reports to key stakeholders, webinars, and submission of manuscripts to preprint servers and scientific journals. The technical coordinating team will develop protocols for data transfer and ensuring data quality; write the statistical analysis plans; and conduct meta-analyses.

Prospective meta-analyses offer a rigorous way to generate definitive answers to emerging questions. Given the current state of limited, high-quality evidence to inform public health guidance and healthcare strategies for pregnant women and newborn, the proposed study will contribute timely and necessary evidence-based data for decision-making in the context of COVID-19 and maternal and neonatal health.

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Women will be recruited from all clinical sites across the United States where pregnant women are under investigation for COVID-19 or have received a COVID-19 diagnosis. All participants in PRIORITY will be enrolled remotely through the UCSF Coordinating Center. We will recruit women under investigation for COVID-19 or who have tested positive for COVID-19 who meet the inclusion and exclusion criteria (see study protocol). Sample Size 1,500 women, 60% of whom will be confirmed to have COVID-19 Timeline

Ongoing, opened enrollment March 2020. Following up newborns through 6 and 12 months Outcomes

Maternal outcomes: To evaluate the presentation, disease course, and clinical outcomes for pregnant women infected with COVID-19 compared with those that are COVID-19 negative. We will query participants on disease presentation, course of infection, treatments received, incidence and risk of hospitalization and/or ICU stay, and time to complete recovery.

Neonatal outcomes: To assess fetal/neonatal outcomes among infants born to women with COVID-19 compared with those that are COVID-19 negative. Notes https://priority.ucsf.edu/researchers . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

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• SARS-CoV-2 microbiologically confirmed infection in health care workers • SARS-CoV-2 seropositivity at delivery • SARS-CoV-2 seropositivity at the ANC-1 visit

The ANC-1 and DSS prospective surveillance cohorts are mutually exclusive but are designed to be analyzed together.

Supplementary Data collection complete September 2020, data sharing with PMA team by Dec 2020 or early 2021.

Pregnancy, delivery, and some neonatal outcomes. COVID-19 disease severity and hospitalization data.

If our cases are included, we recommend dropping WA state cases from the PRIORITY registry (those occurring prior to June 30, 2020) to reduce duplication. There is also a potential for a few duplicate cases with the "Inter-COVID" project; we are not sure if this group is contributing data to the PMA.

Supplementary Pregnant women confirmed to have COVID-19 in participating network sites; the cohort component of the study includes random deliveries from 2020 at selected study sites for comparison.

Approximately 2,000 COVID-19 cases; the cohort study component will include approximately 14,000 random deliveries from the same study sites as unexposed.

Actively recruiting as of June 2020; completing follow-up through February 2021 Outcomes

The primary endpoint is a maternal composite defined as at least one of the following during pregnancy and through 6 weeks postpartum: mortality, morbidity related to hypertensive disorders of pregnancy, morbidity related to postpartum hemorrhage, morbidity related to infection. 

Contribute initial data by August 2020.

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The copyright holder for this this version posted November 12, 2020. ; https://doi.org/10.1101/2020.11.08.20228056 doi: medRxiv preprint Harmonization Process: We developed the draft data modules and questions based on a proposed set of questions from the PRIORITY study. We also reviewed and included questions from the data collection forms developed by the World Health Organization (WHO) and the U.S. Center for Disease Control (CDC). We requested feedback via a survey and by email from the >50 participants of the bi-monthly "Perinatal COVID-19 Global Gathering". The current data modules reflect feedback and general consensus among survey respondents.

Which studies should harmonize data? Any registry or cohort study collecting data regarding pregnant or postpartum people suspected or confirmed to have COVID-19 (as well as their fetus / infant) should consider collecting harmonized data, whether or not they are population-based. The studies may collect data from health records, by directly questioning the participant, or both. Differences in the way participants are sampled/recruited or the way data is collected can be reconciled when specific data analyses are planned.

Participants enrolled in the study should meet the following inclusion criteria:

• Pregnant person, or person who was pregnant within the past 6 weeks (Note: 42 days/ 6weeks reflects the postpartum period / maternal mortality definition); • diagnosed with (or suspected to be infected with) COVID-19;

• provides informed consent.

What is a Data Module: We define a "Data Module" as a group of questions (variables) that: 1) are thematically related; 2) are asked at the same time and with the same frequency; 3) AND refer to EITHER mother or baby (not both). These modules are organized for the purpose of prioritizing variables and themes, and do NOT reflect the order in which they should/would appear in actual data collection forms.

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What: Pregnancy registration information and non-COVID morbidity among participants When: At pregnancy registration

Medical record data extraction is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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What: Information about how the pregnancy ended; maternal mortality will be recorded in this module When: Once, after pregnancy outcome is known

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What: Information related to labor and delivery/birth and other data collected on the day of birth When: To be asked on or soon after the day of birth, at enrollment if enrollment occurs postpartum, or directly extracted from chart

Medical record data extraction Q1 is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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What: Information related to infant health, particularly related to COVID-19 When: At regular interval until up to 12 months after birth (or until chart extraction)

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What: Socio-demographic information about the study participant When: Once at the beginning of the study (maternal information); Once after birth (for infant information)

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Version Date: 08-NOV-20

What is a Data Module: We define a "Data Module" as a group of questions (variables) that: 1) are thematically related; 2) are asked at the same time and with the same frequency; 3) AND refer to EITHER mother or baby (not both). These modules are organized for the purpose of prioritizing variables and themes, and do NOT reflect the order in which they should/would appear in actual data collection forms.

Updates: Updates to the data modules in August and September 2020 reflect efforts to harmonize these modules with updated World Health Organization (WHO) case definitions and ongoing multi-site study protocols developed by WHO. Additions are highlight in yellow.

Questions that have been removed are crossed out. To identify high-risk subgroups with increased pregnancy, delivery, and infant adverse outcomes that are potentially associated with COVID-19

To clearly document all biospecimens collected related to COVID-19 in a pregnancy and delivery and diagnostic testing for COVID-19 completed for the mother and infant, with a focus on identifying any instances of vertical transmission of COVID-19.

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Version Date: 08-NOV-20 Page 3 of 14

Time intervals (e.g. gestational age, time from symptom onset to testing) should be calculated directly from dates where possible. The dates (and ages) recorded in these modules include:

• Q2a. If diagnosed as a probable COVID-19 case, by which criteria where you diagnosed?

• A patient who meets clinical criteria above AND is a contact of a probable or confirmed case, or epidemiologically linked to a cluster with at least one confirmed case.

Q2a. If diagnosed as a probable COVID-19 case, by which criteria was diagnosis made?

• A patient who meets clinical criteria above AND is a contact of a probable or confirmed case, or epidemiologically linked to a cluster with at least one confirmed case.

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The copyright holder for this this version posted November 12, 2020. A person with recent onset of anosmia (loss of smell) or ageusia (loss of taste) in the absence of any other identified cause. • Death, not otherwise explained, in an adult with respiratory distress preceding death AND was a contact of a probable or confirmed case or epidemiologically linked to a cluster with at least one confirmed case.

• A suspect case with chest imaging showing findings suggestive of COVID-19 disease • A person with recent onset of anosmia (loss of smell) or ageusia (loss of taste) in the absence of any other identified cause. Death, not otherwise explained, in an adult with respiratory distress preceding death AND was a contact of a probable or confirmed case or epidemiologically linked to a cluster with at least one confirmed case.

Q2b. If diagnosed as a probable COVID-19 case, by which criteria where you diagnosed?

• Q10. If answer "Yes" to Q8": What was the date of hospital discharge? (DD:MM:YY) (in the case of death, enter date of death).

Q10. If answer "Yes" to Q8": Extract from medical record: What was the date of hospital discharge? (DD:MM:YY) (in the case of death, enter date of death).

Q11. If answer "Yes" to Q8": what was the respiratory status of the patient while hospitalized?

• Self ventilating in room air Q12. If answer "Yes" to Q8": Was the mother admitted to an intensive care unit (ICU) or administered critical care for COVID-19?

Q12. If answer "Yes" to Q8": Extract from medical record: Was the patient admitted to an intensive care unit (ICU) or administered critical care for COVID-19?

Q13. If answer "Yes" to Q12": What was the date of ICU admission / critical care? (DD:MM:YY)

Q13. If answer "Yes" to Q12": Extract from medical record: What was the date of ICU admission / critical care? (DD:MM:YY)

Q14. If answer "Yes" to Q8": What was the date of ICU discharge / end of critical care? (DD:MM:YY) (in the case of death, enter date of death).

Q14. If answer "Yes" to Q8": Extract from medical record: What was the date of ICU discharge / end of critical care? (DD:MM:YY) (in the case of death, enter date of death).

What: Pregnancy registration information and non-COVID morbidity among participants When: At pregnancy registration

Questionnaire-based data collection Medical record data extraction Q1. Date of study enrolment (DD:MM:YY) Q1. Extract from medical record:

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The copyright holder for this this version posted November 12, 2020. • List all pregnancy-related conditions documented in the record

What: Information about how the pregnancy ended; maternal mortality will be recorded in this module When: Once, after pregnancy outcome is known • Any congenital anomalies in the record? (Note it down exactly as in the record)

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What: Biological specimens collected from mother and infant during pregnancy, at delivery, and postpartum, with a focus on indicators of vertical transmission of COVID-19. When: Maternal biospecimens collected during the pregnancy, at the time of delivery, or after delivery, as well as biospecimens collected during delivery and from the infant at birth and during the first 6 weeks of life.

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The copyright holder for this this version posted November 12, 2020. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint

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COVID-19 map-Johns Hopkins Coronavirus Resource Center

Pregnancy and susceptibility to infectious diseases

Characteristics of Women of Reproductive Age with Laboratory-Confirmed SARS-CoV-2 Infection by Pregnancy Status -United States

Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis

Characteristics and outcomes of pregnant women admitted to hospital with confirmed SARS-CoV-2 infection in UK: national population based cohort study

Clinical course of severe and critical coronavirus disease 2019 in hospitalized pregnancies: a United States cohort study

Exclusion of Pregnant Women from Clinical Trials during the Coronavirus Disease 2019 Pandemic: A Review of International Registries

Can SARS-CoV-2 Infection Be Acquired In Utero?: More Definitive Evidence Is Needed

Mechanisms and evidence of vertical transmission of infections in pregnancy including SARS-CoV-2

Cochrane Handbook for Systematic Reviews of Interventions

A guide to prospective meta-analysis

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

World Health Organization. WHO COVID-19: Case Definitions

Meta-analysis in clinical trials

Core Variables, Prospective Meta-Analyses for Perinatal COVID-19 Version Date: 08-NOV-20 of birth? • Yes • No • Maybe / Uncertain Q12. Extract from medical record: • Breastfeeding or breast milk on the day of birth

Q13: Was the newborn isolated away from mother in another area in hospital (postnatal ward, special care nursery, NICU or special ward)? Q13: Extract from medical record: • Was the newborn isolated away from mother in another area in hospital (postnatal ward, special care nursery

Q14. Date of infant discharge from labor and delivery event (DD:MM:YY)

Q14. Extract from medical record: • Date of infant discharge (DD:MM:YY)

Newborn outcome at discharge: • Expired • Home • Transfer to another acute care facility due to clinical needs • Transfer to a chronic care facility Q15. Extract from medical record: • Newborn outcomes at discharge as documented in the record Module 5: Infant Mortality and Morbidity What: Information related to infant health

When: At regular interval until up to 12 months after birth (or until chart extraction) Questionnaire-based data collection Medical record data extraction Q1. Neonatal/infant death? • Yes • No Q1. Extract from medical record: • Neonatal/infant death

Q2. If answered "Yes" to Q1: • Date-time of neonatal/infant death? (DD:MM:YY) (HH:MM)

Extract from medical record: • If neonatal/infant death, date-time of death