Vaccination reduces need for emergency care in breakthrough COVID-19 infections: A multicenter cohort study

  1. Amit Bahl
  2. Steven Johnson
  3. Gabriel Maine
  4. Martha Hernandez Garcia
  5. Srinivasa Nimmagadda
  6. Lihua Qu
  7. Nai-Wei Chen

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Abstract

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  1. Version published to 10.1016/j.lana.2021.100065
  2. ScreenIT

    SciScore for 10.1101/2021.06.09.21258617: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by the Institutional Review Board at Beaumont Health and registered on clinicaltrials.gov (Identifier: NCT04912700).
    Consent: Written informed consent requirement was waived due to the retrospective nature of this study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were performed using Joinpoint Regression Program v4.7.0.0, R-4.0.2 (R Foundation for Statistical Computing), and SAS v9.4 (SAS Institute, Inc.
    Joinpoint Regression Program
    suggested: None
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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 study had some limitations. The observational cohort study design was a limitation and it is possible that some patients with COVID-19 were not included despite our careful screening of all diagnostic test types. Further, patients with potential COVID-19 with negative laboratory testing were not included in this analysis. As high-risk patients often receive multiple tests to rule out infection, the miss rate was likely small. Another limitation was reliance of electronic health record data. The data is reliant on accurate documentation and it is likely that some input errors occurred. Further, some patients had incomplete data and this limited our analysis. Selection bias was another limitation as patients that were still hospitalized after the cutoff follow-up date (May 15) were excluded from the analysis. Fortunately, only 61 (0.5%) patients were still hospitalized. While some of the potentially more severe cases with longer hospital durations were excluded from the analysis, only three cases were excluded due to this reason in the fully vaccinated group, the main population of interest. As the information was time sensitive, we decided it was appropriate to move forward with analysis before waiting for all patient encounters to be complete. Additionally, we assumed vaccination rate of study patients was similar to the published data regarding vaccination status from the state population. It is possible that there were slight variations that were not captured with this ...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04912700RecruitingThe Impact of Vaccination on Severity of Illness in COVID-19

    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.

  3. Version published to 10.1101/2021.06.09.21258617v1 on medRxiv