Early antibody response to SARS-CoV-2

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Abstract

Background. The role and significance of the immune response to SARS-CoV-2 infection is not yet well known. Methods. We therefore conducted a study on 46 symptomatic subjects with disease ascertained by laboratory tests to evaluate the presence of IgG and IgM antibodies in these subjects in relation to the time elapsed since the onset of symptoms. The analytical performance of the method used in the study (Maglumi 800, SNIBE, China) and the effect of two different serum and plasma matrices were also assessed. Results. IgG positivity was demonstrated in 100% of cases 15 days after the onset of the disease. IgM show lower concentrations and do not exceed 77% of cases after 15 days. The analytical performance of the method used was confirmed to be good in terms of imprecision, linearity, commutability in two blood sample matrices. Conclusion. The serological study through the search for specific IgG for SARS-CoV-2 results in our case series is sensitive and suitable for population research and can also play a role in diagnosis. The diagnostic performance of specific IgMs are lower.

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  1. SciScore for 10.1101/2020.05.19.20099317: (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 variableTherefore, 46 patients (38 males and 8 females, median age 66 years, minimum 36, maximum 89) were included, of which 30 with one blood sample, 7 with two withdrawals over the following days, 5 with 3 withdrawals, 2 with 4 withdrawals and 2 with 5 withdrawals, for a total of 77 assessed samples.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis were performed with MedCalc © Software, Version 19.2.1 (MedCalc Software, Mariakerke, Belgium)
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    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.