Impact of COVID-19 Infection on Maternal and Neonatal Outcomes: A Review of 11078 Pregnancies Reported in the Literature

  1. Fatemeh Azarkish
  2. Roksana Janghorban

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Abstract

Pregnant women are a vulnerable group in viral outbreaks, especially in the COVID-19 pandemic.

Objective:

The aim of this review was to identify maternal and neonatal outcomes in available articles on pregnancies affected by COVID-19.

Methods:

The articles that had assessed outcomes of pregnancy and perinatal of women with COVID-19 between Oct 2019 and Aug 2020 without language limitation were considered. We searched databases, selected relevant studies and extracted data regarding maternal and neonatal outcomes from each article.

Results:

Data of 11078 pregnant women with COVID-19 of 23 countries were assessed from 77 articles between December 8, 2019 and Aug 18, 2020. Most pregnant women reported in their third trimester, out of which 6229 (56.22%) cases were symptomatic at the time of admission. Common onset symptoms, abnormal laboratory findings, and chest computed tomography pattern were cough (40.88%%), lymphocytopenia (43.38%), and multiple ground-glass opacities (4.42%), respectively. 51.37% of all deliveries were done through cesarean section. 158 maternal mortality and 4.2% ICU admission were reported. Vertical transmission was not reported, but its possibility was suggested in thirty-two neonates. Ten neonatal deaths, thirteen stillbirths, and nineteen abortions were reported. 60% of newborns were not breastfed.

Conclusion:

This review showed fewer adverse maternal and neonatal outcomes in pregnant women with COVID-19 in comparison with previous coronavirus outbreak infection in pregnancy. Limited data are available regarding the possibility of virus transmission in utero, during vaginal childbirth and breastfeeding. The effect of COVID-19 on the first and second trimesters and ongoing pregnancy outcomes in infected mothers is still questionable.

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  1. Version published to 10.2174/1573404817666210908112042
  2. ScreenIT

    SciScore for 10.1101/2020.05.09.20096842: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableEligibility criteria: In this review, the articles that had assessed outcomes of pregnancy and perinatal of women with COVID-19 between Oct 2019 and Apr 30, 2020 were considered.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Literature search and data extraction: We searched PubMed, Scopus, Web of Science (WOS), and MedRxiv using MeSH-compliant keywords including: "2019-nCoV infection", "coronavirus disease 2019", "COVID-19 pandemic", "2019-nCoV disease",
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Lack of report of some variables related to maternal and neonatal outcomes in several studies is one of the limitations of this review. The other one is low methodological quality of the studies which were included in this review. Maternal and neonatal assessment of a large number of cases (287 cases), consideration of some maternal and neonatal outcomes including cause of cesarean section, early maternal chest CT findings, fetal condition, neonatal asphyxia, newborn feeding in all studies and no limitation on language of published articles are strengths of the current review in comparison with three reviews that exist to date [63-66].

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.09.20096842v1 on medRxiv