Mortality of Care Home Residents and Community-Dwelling Controls During the COVID-19 Pandemic in 2020: Matched Cohort Study

  1. Martin C. Gulliford
  2. A. Toby Prevost
  3. Andrew Clegg
  4. Emma Rezel-Potts

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Abstract

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  1. Version published to 10.1016/j.jamda.2022.04.003
  2. Version published to 10.1101/2021.04.24.21255968v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.04.24.21255968: (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.
    RandomizationUp to four community-dwelling control participants were randomly sampled with replacement15 for each care home resident.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were performed using the ‘statsmodels’16 package in Python 3.8.3.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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:
    Strengths and Limitations: An important strength of this study was the use of longitudinal health records to estimate predicted mortality during 2020 based on data for the preceding five years, taking into account differences in age and gender distribution, morbidities, region, calendar month and secular trends over years. This enabled us to quantify excess deaths during the pandemic months. We were also able to draw on a matched population-based comparison cohort to quantify changes in the relative risk of mortality in care homes during the pandemic after adjusting for covariates. We drew on a well-described database,13 and the quality of data offered by electronic health records has been shown to be generally high.19 However, we acknowledge that there could be misclassification of care home status and it is possible that care home residence might be under-recorded. Misclassification might generally have the effect of reducing associations. We included a count of important long-term conditions, but we did not find records of frailty index scores to be informative. In the cumulative deficit model, frailty and multiple morbidity are closely related concepts20 but more accurate phenotypic characterisation of patients frailty status over time would have added to the study.21 Deprivation is associated with reduced healthy life expectancy, which could lead to care home admission. Patients were matched for general practice, so it was not possible to adjust for deprivation at the ge...

    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.

  4. Version published to 10.1101/2021.04.24.21255968v1 on medRxiv