Evaluation of three rapid lateral flow antigen detection tests for the diagnosis of SARS-CoV-2 infection

  1. A.E. Jääskeläinen
  2. M.J. Ahava
  3. P. Jokela
  4. L. Szirovicza
  5. S. Pohjala
  6. O. Vapalahti
  7. M. Lappalainen
  8. J. Hepojoki
  9. S. Kurkela

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Abstract

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  1. Version published to 10.1016/j.jcv.2021.104785
  2. ScreenIT

    SciScore for 10.1101/2020.12.30.20249057: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Research permit HUS/157/2020 (Helsinki University Hospital, Finland) was obtained from the local review board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Virus culture: The PCR positive subset of samples used for analytical performance evaluation was subjected to virus isolation experiments in Vero E6 TMRPSS2 cells as described in [7].
    Vero E6 TMRPSS2
    suggested: None
    Software and Algorithms
    SentencesResources
    Evaluated tests: We evaluated the performance of Quidel Sofia SARS FIA (Quidel, San Diego, CA), Standard Q COVID-19 Ag test (SD Biosensor, Republic of Korea), and Panbio™ (Abbott Diagnostic GmbH, Jena, Germany) according to each manufacturer’s guidelines for samples in virus transport medium.
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    Statistical analysis was performed using SPSS/PASW statistical program package, version 25 (IBM SPSS Inc., Chicago, IL, 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.

  3. Version published to 10.1101/2020.12.30.20249057v1 on medRxiv