Clinical academic research in the time of Corona: A simulation study in England and a call for action

  1. Amitava Banerjee
  2. Michail Katsoulis
  3. Alvina G. Lai
  4. Laura Pasea
  5. Thomas A. Treibel
  6. Charlotte Manisty
  7. Spiros Denaxas
  8. Giovanni Quarta
  9. Harry Hemingway
  10. João L. Cavalcante
  11. Mahdad Noursadeghi
  12. James C. Moon

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Abstract

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  1. Version published to 10.1371/journal.pone.0237298
  2. ScreenIT

    SciScore for 10.1101/2020.04.14.20065417: (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:
    There are limitations to our model and its assumptions. Our model was simple and was based only on observational patterns of the number of new cases and actual cases from publicly available data(17). We conducted analyses on 10 April, and on 11 April, some extra ∼3000 cases were added retrospectively and distributed over the past 10 days-we did not include these data. It did not take into account infectious disease epidemiology parameters, such as the basic reproductive number (R0), and we did not consider differing levels of risk of infection(35-37). Our model on the availability of clinical academics makes several assumptions (Web Appendix), including the total number of 100%FTE academics as ∼3200, with a uniform skillset across the workforce.

    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 10.1101/2020.04.14.20065417v1 on medRxiv