A Cross-sectional Study of Immune Seroconversion to SARS-CoV-2 in Frontline Maternity Health Professionals

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Abstract

( Anaesthesia . 2020;75:1614–1619)

Seroconversion rates for COVID-19 provides data on the pervasiveness and spread of the infection. One challenge is the rate of asymptomatic seroconversion. This has implications for health care providers on the frontline of obstetric care, who may be at increased risk of COVID-19 transmission to and from patients and staff. To date, there are no studies that have provided a baseline rate of seroconversion in frontline, obstetric care providers. The aim of this study was to assess the prevalence of seroconversion in obstetric providers who were not previously diagnosed with SARS-CoV-2 and examine the associations among their characteristics, symptoms, and seroconversion.

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  1. SciScore for 10.1101/2020.06.24.20139352: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Members of the research team approached potential participants and all of those enrolled into the study provided written consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    If dividing the sample RLU by the control RLU produces an index of <1.4, the sample is considered to be negative for SARS-CoV-2 IgG antibodies.
    SARS-CoV-2 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Serological testing was performed using Abbott Laboratories’ (USA) two-step, chemiluminescent micro-particle immunoassay (CMIA) technology, approved by the United States Food and Drug Administration (FDA) and Public Health England (PHE).
    Abbott Laboratories’
    suggested: None
    Statistical analysis was performed using SPSS (IBM, USA).
    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.

    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.