Sensitivity of SARS-CoV-2 antibody tests with late convalescent sera

  1. Judith Kannenberg
  2. Carolin Schnurra
  3. Nina Reiners
  4. Reinhard Henschler
  5. Raymund Buhmann
  6. Thorsten Kaiser
  7. Ronald Biemann
  8. Mario Hönemann
  9. Grit Ackermann
  10. Henning Trawinski
  11. Christian Jassoy

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Abstract

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  1. Version published to 10.1016/j.jcvp.2021.100038
  2. ScreenIT

    SciScore for 10.1101/2021.07.07.21259772: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by the Local Ethics Commission at the Medical Faculty at the University of Leipzig (ethical vote 147/20-ek).
    Consent: Sera were obtained after informed consent.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    2.2 Antibody tests: Sera were analyzed with three tests that measure antigen-specific IgG and two assays for all immunoglobulin classes.
    antigen-specific IgG
    suggested: None
    The Roche Elecsys Anti-SARS-CoV-2 is a bridging ruthenium complex ECLIA for nucleoprotein-specific antibodies of all classes (IgG, IgM, other Ig).
    Anti-SARS-CoV-2
    suggested: None
    The Abbott SARS-CoV-2 IgG and SARS-CoV-2 IgG II Quant assays are acridinium CMIA for the detection of IgG antibodies against the nucleoprotein (SARS-CoV-2 IgG) or glycoprotein receptor binding domain (SARS-CoV-2 IgG II Quant).
    the nucleoprotein (SARS-CoV-2 IgG)
    suggested: None
    glycoprotein receptor binding domain (SARS-CoV-2 IgG II Quant)
    suggested: None
    The Euroimmun Anti-SARS-CoV-2 IgG ELISA measures antibodies against the S1 domain of the spike protein and was performed with an automated ELISA processor (DSX, Dynex Technologies, U.K.).
    Anti-SARS-CoV-2 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    2.3 Data analysis: Medcalc statistical online software was used (https://www.medcalc.org/calc/) for data analysis.
    Medcalc
    suggested: (MedCalc, RRID:SCR_015044)

    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 10.1101/2021.07.07.21259772v1 on medRxiv