The Challenges of Caring for People Dying From COVID-19: A Multinational, Observational Study (CovPall)

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Abstract

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  1. SciScore for 10.1101/2020.10.30.20221465: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The survey received ethical (Institutional Review Board) approval from King’s College London Research Ethics committee (LRS-19/20-18541); study sponsor: King’s College London, co-sponsor: King’s College Hospital NHS Foundation Trust, registered ISRCTN 16561225.
    Consent: Completion indicated consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Study design and participants: CovPall is a multicentre multinational observational study of palliative care during the COVID-19 pandemic.
    CovPall
    suggested: None
    We used contingency tables, χ2 tests, correlations and multivariable logistic regression to explore relationships between variables (using SPSS v26 and STATA v16).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

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

    IdentifierStatusTitle
    ISRCTN16561225NANA


    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.