Sustained cellular immune dysregulation in individuals recovering from SARS-CoV-2 infection

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Abstract

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  1. SciScore for 10.1101/2020.07.30.20165175: (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

    Software and Algorithms
    SentencesResources
    Events were collected using a FACS Symphony A3 (BD Biosciences) flow cytometer and analyzed using FlowJo (v10, Treestar) software.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    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: We detected the following sentences addressing limitations in the study:
    Our current study has a few limitations. For one, our immunophenotyping panel prioritizes the identification of some subsets such as lymphocytes and monocytes over others, primarily dendritic cells. Although a marker for CD11c would have increased our ability to identify this population, we believe our gating strategy (CD3-CD19-CD14-CD56-CD16-HLADRhi) still identifies a relatively pure population of dendritic cells. Additionally, we acknowledge that there are substantial differences in age, race and sex between our hospitalized, non-hospitalized and healthy groups as summarized in Table 1. These differences reflect the nature of the COVID-19 pandemic, with numerous sources reporting increased hospitalizations and more severe clinical symptoms in elderly and African-American populations. We have controlled for this by performing general linear models comparing hospitalized, non-hospitalized, and healthy groups in pairwise models that have each been adjusted for participant age, race, and sex. Results are summarized in Supplementary Tables 1-3. This analysis shows that a majority of the significant relationships as determined by Wilcoxon analysis remain significant after adjusting for age, race and sex. In the remaining relationships that were not significant by hospitalization status, there were also no significant findings to support that these relationships were driven by age, race, or sex. One exception to this was the finding that the decrease in CD16+ monocytes in our hos...

    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.