Rapid Detection of SARS-CoV-2 Antigen from Serum in a Hospitalized Population

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Abstract

SARS-CoV-2 viremia has been demonstrated in some patients using molecular assays. Here we demonstrate detection of SARS-CoV-2 antigen in a cohort of hospitalized patients using a rapid diagnostic test from Anhui Deepblue Medical Technology Co., Ltd. We detected antigen in serum from 11 of 13 patients at time points ranging from three to eighteen days from symptom onset and observed that the disappearance of an antigen signal was associated with seroconversion. These results demonstrate proof of principle use of a rapid antigen test with serum samples in a format compatible with point of care testing.

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  1. SciScore for 10.1101/2020.12.21.20248140: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Use of these specimens was reviewed and approved by the Mayo Clinic Institutional Review Board under protocol # 20-004544.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Antigen Tests: Antigen tests were performed using COVID-19 (SARS-CoV-2) Antigen Test Kit (Colloidal Gold) (Anhui Deepblue Medical Technology Co., Ltd.) using the same process described above for antibody tests. i.e. 5 μL serum was applied to the sample well, followed by 2-3 drops of buffer.
    SARS-CoV-2) Antigen Test Kit (Colloidal Gold) (Anhui Deepblue Medical Technology Co.
    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.