Background rates of all-cause mortality, hospitalizations, and emergency department visits among nursing home residents in Ontario, Canada to inform COVID-19 vaccine safety assessments

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Abstract

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  1. SciScore for 10.1101/2021.03.17.21253290: (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

    No key resources detected.


    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:
    This is an important limitation of this work. If feasible, we will update this report as more data become available. We intend for these findings to be used to contextualize potential increases in adverse events of special interest (AESI)11 during the COVID-19 vaccine rollout in NH residents. Whereas mortality, hospitalization, and ED visit rates were highly stable over 10 pre-pandemic years, the marked changes in rates observed during 2020 indicate that caution is needed in determining the appropriate baseline to use when interpreting rates of AESIs following the COVID-19 vaccine rollout. Existing investigations on mortality in elderly and frail individuals who received COVID-19 vaccines has identified that mortality rates were consistent with high background rates of death in this population;12 our data will help contextualize Canada- and Ontario-specific rates in a similar way.

    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.