Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study

  1. Thomas D. Dobbs
  2. John A.G. Gibson
  3. Alex J. Fowler
  4. Tom E. Abbott
  5. Tasnin Shahid
  6. Fatemeh Torabi
  7. Rowena Griffiths
  8. Ronan A. Lyons
  9. Rupert M. Pearse
  10. Iain S. Whitaker

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Abstract

No abstract available

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  1. Version published to 10.1016/j.bja.2021.05.001
  2. ScreenIT

    SciScore for 10.1101/2021.02.27.21252593: (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 study also has limitations. As with any population-based study using routinely collected data there is the risk of incomplete or missing data, although from previous work this is likely to be negligible in this setting. Furthermore, the second peak of the pandemic did not occur until February 2021 in the UK, so it is likely that surgical activity continued to decline after December. We deliberately took a conservative approach in our modelling by assuming December was the nadir of surgical activity after April 2020.

    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.

  3. Version published to 10.1101/2021.02.27.21252593v1 on medRxiv