Estimating COVID-19 Vaccination and Booster Effectiveness Using Electronic Health Records From an Academic Medical Center in Michigan

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Abstract

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  1. SciScore for 10.1101/2022.01.29.22269971: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To assess the potentially different VE across different strata of risk factors (denoted as X) associated with COVID-19 outcomes, we further conducted interaction analysis by vaccine status using the following model:All analyses were performed in R statistical software version 4.1.2 (R Project for Statistical Computing).
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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:
    As such, a limitation of results from this study design is the generalizability to individuals tested for COVID-19. Still, these studies provide insight about the long-term effectiveness and durability of vaccine protection23. A potential weakness is any missing information from the EHR, e.g., undocumented test results or vaccinations, though we believe categorizing individuals into an unknown/unvaccinated status tends to produce conservative VE estimates. Overall, these results should give confidence in the effectiveness of the vaccines and may encourage those who have not been vaccinated or not received a booster to do so.

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.