A novel cohorting and isolation strategy for suspected COVID-19 cases during a pandemic

  1. B. Patterson
  2. M. Marks
  3. G. Martinez-Garcia
  4. G. Bidwell
  5. A. Luintel
  6. D. Ludwig
  7. T. Parks
  8. P. Gothard
  9. R. Thomas
  10. S. Logan
  11. K. Shaw
  12. N. Stone
  13. M. Brown

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.05.14.20091843: (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:
    A limitation of this evaluation includes the specificity to the contemporaneous COVID-19 prevalence. From late March to early April, the UK saw a very high rate of cases admitted to hospitals in London and very likely a reduced attendance of individuals with other medical problems. Therefore the pre-test probability of COVID-19 was extremely high which may have impacted our results. Secondly the triage was conducted by an experienced infectious diseases clinician. The extent to which the accuracy of the triage can be generalised may depend on the identification of a combination of objective markers with adequate predictive value in a range of settings.

    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.

  2. Version published to 10.1016/j.jhin.2020.05.035
  3. Version published to 10.1101/2020.05.14.20091843v1 on medRxiv