Evidence map›Paper›PMID 33797605›Full record

SynthesisArchives of gynecology and obstetrics2021

A systematic review of pregnant women with COVID-19 and their neonates.

Mona Mirbeyk, Amene Saghazadeh, Nima Rezaei

Open access · bronzeAbstract readSystematic Review
In one paragraph

Synthesis in Archives of gynecology and obstetrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 3 pooled it
20.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 3 syntheses or guidelines pooled it, 137 citations in OpenAlex.

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  18. Third dose of COVID-19 vaccine: is there any place for it for pregnant women?Journal of the Turkish German Gynecological Association · 2023
    Article
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  20. Observational

7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Mona MirbeykSystematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Amene SaghazadehSystematic Review and Meta-Analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Nima RezaeiResearch Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran. rezaei_nima@tums.ac.ir.ORCID 0000-0002-3836-1827
Universal Scientific Education and Research Network · IREducation and Research Network · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn December 2019, a novel coronavirus disease (COVID-19) emerged in Wuhan, China, with an incredible contagion rate. However, the vertical transmission of COVID-19 is uncertain.

objectivesThis is a systematic review of published studies concerning pregnant women with confirmed COVID-19 and their neonates. SEARCH STRATEGY: We carried out a systematic search in multiple databases, including PubMed, Web of Science, Google Scholar, Scopus, and WHO COVID-19 database using the following keywords: (Coronavirus) OR (novel coronavirus) OR (COVID-19) OR (COVID19) OR (COVID 19) OR (SARS-CoV2) OR (2019-nCoV)) and ((pregnancy) OR (pregnant) OR (vertical transmission) OR (neonate) OR (newborn) OR (placenta) OR (fetus) OR (Fetal)). The search took place in April 2020. SELECTION CRITERIA: Original articles published in English were eligible if they included pregnant patients infected with COVID-19 and their newborns. DATA COLLECTION AND ANALYSES: The outcomes of interest consisted of clinical manifestations of COVID-19 in pregnant patients with COVID-19 and also the effect of COVID-19 on neonatal and pregnancy outcomes. MAIN

results37 articles involving 364 pregnant women with COVID-19 and 302 neonates were included. The vast majority of pregnant patients were in their third trimester of pregnancy, and only 45 cases were in the first or second trimester (12.4%). Most mothers described mild to moderate manifestations of COVID-19. Of 364 pregnant women, 25 were asymptomatic at the time of admission. The most common symptoms were fever (62.4%) and cough (45.3%). Two maternal deaths occurred. Some pregnant patients (12.1%) had a negative SARS-CoV-2 test but displayed clinical manifestations and abnormalities in computed tomography (CT) scan related to COVID-19. Twenty-two (6.0%) pregnant patients developed severe pneumonia. Two maternal deaths occurred from severe pneumonia and multiple organ dysfunction. Studies included a total of 302 neonates from mothers with COVID-19. Of the studies that provided data on the timing of birth, there were 65 (23.6%) preterm neonates. One baby was born dead from a mother who also died from COVID-19. Of the babies born alive from mothers with COVID-19, five newborns faced critical conditions, and two later died. A total of 219 neonates underwent nasopharyngeal specimen collection for SARS-CoV-2, of which 11 tested positive (5%). Seventeen studies examined samples of the placenta, breast milk, umbilical cord, and amniotic fluid, and all tested negative except one amniotic fluid sample.

conclusionsA systematic review of published studies confirm that the course of COVID-19 in pregnant women resembles that of other populations. However, there is not sufficient evidence to establish an idea that COVID-19 would not complicate pregnancy.

Indexed as

Infectious Disease Transmission, VerticalPregnant PeopleAdultAmniotic FluidCOVID-19FemaleFeverHumansInfant, NewbornMothersPregnancyPregnancy Complications, InfectiousPregnancy OutcomePregnancy Trimester, ThirdRNA, ViralSARS-CoV-2RNA, ViralCOVID-19ImmunityNeonatesPregnancySARS-CoV2Vertical transmission

Identifiers

PMID33797605
PMCPMC8017514
OpenAlexW3149538761

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.