A study protocol for a retrospective cohort study and interrupted time series analysis to assess the effect of the COVID-19 pandemic on major trauma presentations and patient outcomes in English hospitals

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

A protocol for a retrospective cohort study and interrupted time series analysis to investigate the effect of successive COVID related “lockdown” restrictions on major trauma presentations and patient outcomes in English hospitals. The study specifically aims to assess: 1) The impact of successive “lockdowns” on the volume, demographics, injury mechanism, severity, treatment and outcomes of major trauma in England. 2) If the implementation of “lockdowns” affected major trauma related mortality.

A patient cohort will be derived from the Trauma and Audit Research Network (TARN) database, for all trauma receiving hospitals in England, between 1 st of January 2017 to 1 st of September 2021. This period encompasses two national “lockdown” periods (23 rd March 2020 to 29 th June 2020 and 2 nd Nov 2020 to 16 th May 2021) in England. A time series will be used to illustrate changes in the volume and mechanism of injury associated with successive “lockdowns”. Demographic characteristics and features of the clinical care pathways will be compared during the “lockdown” and equivalent pre-COVID periods. To specifically assess if there were any changes in risk adjusted mortality associated with the “lockdowns” interrupted time series analysis will be conducted.

Article activity feed

  1. SciScore for 10.1101/2022.05.10.22274804: (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.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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: 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.