Diagnostic accuracy comparison of three fully automated chemiluminescent immunoassay platforms for the detection of SARS-CoV-2 antibodies

  1. Debaprasad Parai
  2. Girish Chandra Dash
  3. Hari Ram Choudhary
  4. Annalisha Peter
  5. Usha Kiran Rout
  6. Rashmi Ranjan Nanda
  7. Jaya Singh Kshatri
  8. Srikanta Kanungo
  9. Sanghamitra Pati
  10. Debdutta Bhattacharya

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Abstract

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  1. Version published to 10.1016/j.jviromet.2021.114121
  2. ScreenIT

    SciScore for 10.1101/2020.10.07.20207696: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: COVID-19 patients were informed about the serological test with proper written consent.
    IRB: The study was approved by Institutional Ethics Committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Test method: All three different automated machines can qualitatively detect anti-SARS-CoV-2 antibodies based on the two-step immunoassay principle.
    anti-SARS-CoV-2
    suggested: None
    Abbott made ARCHITECT i2000SR platform uses chemiluminescent microparticle immunoassay (CMIA) technology for the detection of immunoglobulin class G (IgG) antibodies against the nucleocapsid protein of SARS-CoV-2 from human serum.
    immunoglobulin class G (IgG
    suggested: None
    The third one, Yhlo Biotech manufactured iFlash-SARS-CoV-2 IgG was a paramagnetic particle based chemiluminescent immunoassay (CLIA) to determine the IgG antibodies against SARS-CoV-2 nucleocapsid and spike protein.
    SARS-CoV-2 nucleocapsid and spike protein.
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analysis: Descriptive statistical analyses were performed by SPSS software (IBM SPSS statistics for Windows, version 24.0, Armonk, NY).
    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.

  3. Version published to 10.1101/2020.10.07.20207696v1 on medRxiv