Reliability of serological tests for COVID-19: comparison of three immunochromatography test kits for SARS-CoV-2 antibodies

  1. Hidetsugu Fujigaki
  2. Masao Takemura
  3. Michiko Osawa
  4. Aki Sakurai
  5. Kentaro Nakamoto
  6. Koichi Seto
  7. Takashi Fujita
  8. Tadayoshi Hata
  9. Hidehiko Akiyama
  10. Yohei Doi
  11. Kuniaki Saito

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Abstract

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  1. Version published to 10.1016/j.heliyon.2020.e04929
  2. ScreenIT

    SciScore for 10.1101/2020.06.28.20140475: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Ethics Committee for Clinical Research, Center for Research Promotion and Support, Fujita Health University (authorization number HM19-493).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableStudy subjects: We utilized a series of residual serum samples left over after routine laboratory testing of 29 COVID-19 patients (mean age, 52.9 ± 21.9 years; 14 males and 15 females) who were admitted to Fujita Health University Hospital, Toyoake, Japan, from February 28 to April 15, 2020.

    Table 2: Resources

    Antibodies
    SentencesResources
    Detection of anti-SARS-CoV-2 antibodies: We evaluated three test kits for the detection of anti-SARS-CoV-2 IgM/IgG antibody in serum: 2019-nCoV IgG/IgM Rapid Test Cassette (Hangzhou AllTest Biotech Co., Ltd., China), COVID-19 IgM/IgG Duo (SD BIOSENSOR, Korea), and 2019-nCoV IgG/IgM Detection Kit (Vazyme Biotech Co., Ltd., China).
    anti-SARS-CoV-2
    suggested: None
    anti-SARS-CoV-2 IgM/IgG
    suggested: None
    2019-nCoV IgG/IgM
    suggested: None

    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.

  3. Version published to 10.1101/2020.06.28.20140475v1 on medRxiv