COVID-19 Outcomes Among Persons Living With or Without Diagnosed HIV Infection in New York State

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Abstract

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  1. SciScore for 10.1101/2020.11.04.20226118: (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
    All analyses were conducted using SAS software V9.4.21 For these models, missing values were imputed for HIV transmission risk (12%), race and ethnicity (<1%), and age (<1%) using fully conditional specification, implemented using SAS PROC MI.29-30 Multiple imputation was not implemented for laboratory variables with missing data.
    SAS
    suggested: (SASqPCR, RRID:SCR_003056)

    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:
    Limitations: This earliest outcome in this study is COVID-19 laboratory confirmed diagnosis and not infection. A statewide seroprevalence study estimated that about 9% of COVID-19 cases through March 2020 had been diagnosed in NYS.46 Differences in diagnosis propensity among PLWDH or between PLWDH and the non-PLWDH population could alter the interpretation of some findings. Our analyses were limited to the demographic and laboratory data available in NYS’s HIV surveillance and COVID-19 registries, precluding more in-depth investigations into the role played by co-morbidities and underlying medical conditions, COVID-19 risk behaviors, and social determinants of health. It is important to further investigate how the observed associations may be changed by information on co-morbidities and underlying medical conditions, COVID-19 risk behaviors, and social determinants of health with more comprehensive data sources such as medical chart reviews. Our denominator of PLWDH included people who died between January 1 and June 15, 2020 and excluded persons newly diagnosed with HIV during this same timeframe. Because these numbers have historically offset each other, the impact of this limitation is likely negligible.

    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.
    • Thank you for including a protocol registration statement.

    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.