High-throughput immunoassays for SARS-CoV-2 – considerable differences in performance when comparing three methods

  1. Oskar Ekelund
  2. Kim Ekblom
  3. Sofia Somajo
  4. Johanna Pattison-Granberg
  5. Karl Olsson
  6. Annika Petersson

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Abstract

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  1. Version published to 10.1080/23744235.2021.1931434
  2. ScreenIT

    SciScore for 10.1101/2020.05.22.20106294: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Sample collections: All samples in the study originated from an existing sample collection at the Microbiology department obtained after consent to deposit, store, and use for research and development.
    IRB: As a consequence, the study did not require approval from an ethics committee, according to the guidelines of the Swedish Ethical Review Agency.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    To challenge the assays, 13 additional serum samples with possible interferences (antinuclear antibodies (n=2); rheumatoid factor (n=2); anti-cytomegalovirus IgM (n=2); anti-Epstein-Barr virus IgM (n=2) and samples from pregnant donors (n=5)) were analysed.
    antinuclear
    suggested: None
    anti-cytomegalovirus IgM
    suggested: None
    anti-Epstein-Barr virus IgM
    suggested: (QED Bioscience Cat# ESR1361M, RRID:AB_1615871)
    Software and Algorithms
    SentencesResources
    Assays: Four commercially available CE marked immunoassays, and their corresponding platforms were used: 1) Abbott SARS-CoV-2 IgG on the ARCHITECT i2000 (Abbott, Illinois, USA); 2) Elecsys Anti-SARS-CoV-2 on the Cobas 8000 e801 (Roche Diagnostic Scandinavia AB, Solna, Sweden); 3) LIAISON SARS-CoV-2 S1/S2 IgG on the LIAISON XL (DiaSorin, Saluggia, Italy); and 4) the lateral flow test 2019-nCOV IgG/IgM Rapid Test
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    Calculations: Overall per cent agreement, sensitivity (per cent positive agreement), and specificity (per cent negative agreement) were calculated based on a contingency table according to EP12-A2 [6], using Microsoft Excel 2019
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    The between-test agreement was evaluated using Cohen’s kappa calculated with IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Further data analysis, including descriptive statistics, was performed using GraphPad Prism, version 7.04 for Windows (GraphPad Software, La Jolla California USA, www.graphpad.com).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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 10.1101/2020.05.22.20106294 on medRxiv