Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies

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Abstract

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  1. SciScore for 10.1101/2021.12.23.21268279: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Data collection in general practice (NWL and RSC): NWL and Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) [13, 14] primary care practices completed the RECAP-V0 electronic template in EMIS or SystmOne and captured the verbal consent of patients upon completion of the template.
    Sex as a biological variablenot detected.
    RandomizationThe extent of missing data for each variable (outcome and predictors) was assessed on degree of missingness, patterns (at random or not at random), and possible reasons.
    Blindingnot detected.
    Power AnalysisSample size calculation: We estimated a minimum sample size of 1,317 participants for model development and 1,400 for model external validation assuming 10% hospitalisation rate for COVID-19, a maximum of 24 predictor variables, a binary outcome (hospital admission), and a minimum 85% model specificity on validation.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your code.


    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: 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.