Monocyte CD169 Expression as a Biomarker in the Early Diagnosis of Coronavirus Disease 2019

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Abstract

We assessed the expression of CD169, a type I interferon-inducible receptor, on monocytes (monocyte CD169 [mCD169]) in 53 adult patients admitted to the hospital during the coronavirus disease 2019 (COVID-19) outbreak for a suspicion of severe acute respiratory syndrome coronavirus 2 infection. Monocyte CD169 was strongly overexpressed in 30 of 32 (93.7%) confirmed COVID-19 cases, compared with 3 of 21 (14.3%) patients in whom the diagnosis of COVID-19 was finally ruled out. Monocyte CD169 was associated with the plasma interferon-alpha level and thrombocytopenia. Monocyte CD169 testing may be helpful for the rapid triage of suspected COVID-19 patients during an outbreak.

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  1. SciScore for 10.1101/2020.06.28.20141556: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Serology: Plasma samples were tested for IgG antibodies directed against SARS-CoV-2 nucleocapsid using a CE-marked ELISA (ID.Vet, ID screen® SARS-CoV-2-N, Montpellier, France) as previously described11.
    IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    We acquired on a 3-laser, 10-color Navios flow cytometer and analyzed using Kaluza Software version 2.1 (both from Beckman Coulter Brea, CA Inc).
    Kaluza
    suggested: (Kaluza, RRID:SCR_016182)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04347850RecruitingA Cohort of Patients With Possible or Confirmed SARS-CoV-2 (…


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.