Protocol for a prospective, hospital-based registry of pregnant women with SARS-CoV-2 infection in India: PregCovid Registry study

  1. Rahul K Gajbhiye
  2. Niraj N Mahajan
  3. Rakesh Waghmare
  4. Suchitra V Surve
  5. Prashant Howal
  6. Aishwarya Bhurke
  7. Merlin Pious
  8. Deepak N Modi
  9. Smita D mahale

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Abstract

Pregnant women are at increased risk of contracting COVID-19 due to several factors and therefore require special attention. However, the consequences of the COVID-19 pandemic on pregnant women and their newborns remain uncharted. The PregCovid registry aims to document the impact of SARS-CoV-2 infection on pregnant, postpartum women and their newborns. The aim of the registry is also to determine mother-to-child transmission of SARS-CoV-2 infection in India.

Methods and analysis

PregCovid is a hospital-based registry for capturing information of pregnant, postpartum women with COVID-19 and their newborns in India. Medical case records of pregnant and postpartum women with a laboratory-confirmed diagnosis of COVID-19 will be captured in real-time using an online electronic patient record software. The data analysis will be carried out for symptoms, the severity of COVID-19, pregnancy complications, maternal morbidity and mortality, neonatal complications, mother-to-child transmission, etc. Data analysis will be carried out for different waves of the COVID-19 pandemic for rapid response and developing strategies well in advance to manage pregnant women infected with SARS-CoV-2. The evidence generated from the registry will be regularly shared with the appropriate authorities for policy decisions. Thus, the registry data may be useful for planning the strategies for better management of pregnant women with COVID-19.

Ethics and dissemination

The study has been approved by the Institutional Ethics Committees of all the participating study sites under the Medical Education and Drugs Department, Government of Maharashtra, Topiwala National Medical College & BYL Nair Charitable Hospital, Mumbai and ICMR-National Institute for Research in Reproductive and Child Health, Mumbai, India. The results from this study will be disseminated with local, state, and national health authorities, collaborators and the general population on the study website ( https://pregcovid.com ) as well as dissemination through scientific meetings and publications.

Trial registration number

CTRI/2020/05/025423.

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  1. Version published to 10.1136/bmjopen-2021-050039
  2. ScreenIT

    SciScore for 10.1101/2021.07.21.21260823: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Approval from Institutional Review Boards (IRB): The study is approved by the Institutional Ethics Committee of ICMR-National Institute for Research in Reproductive Health (#55/2020), BYL Nair Hospital, Mumbai, India (# 63/2020); and all the 18 participating study sites under Medical Education and Drugs Department of Government of Maharashtra.
    Consent: The Institutional Ethics Committees granted a waiver of consent as the data is collected from the medical case records.
    Field Sample Permit: Data collected from different study sites will be kept separately and only specific individuals within a research team will be able to access and edit the data.
    Sex as a biological variableThe PregCovid registry is a prospective, hospital-based study designed to capture hospital data of pregnant and post-partum women with COVID-19 and their newborns.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data pooling and statistical analysis will be carried out using MS Excel and SPSS version 26 (SPSS South Asia Pvt. Ltd., Bangalore, India).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.21.21260823v1 on medRxiv