Assessment of the Publication Trends of COVID-19 Systematic Reviews and Randomized Controlled Trials

  1. Shunsuke Taito
  2. Yuki Kataoka
  3. Takashi Ariie
  4. Shiho Oide
  5. Yasushi Tsujimoto

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Abstract

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  1. Version published to 10.37737/ace.3.2_56
  2. ScreenIT

    SciScore for 10.1101/2020.08.27.20182956: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethical approval and formal consent were not required for this study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Two of the four review authors (ST, YK, TA, and SO) independently selected abstracts from the filtered search results.
    TA
    suggested: RRID:CVCL_4315)
    Software and Algorithms
    SentencesResources
    We conducted a cross-sectional study by investigating the number of SRs and RCTs on topics related to COVID-19 practice published in PubMed and medRxiv between January 1 and June 30, 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)

    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 study was that when we counted the number of SRs, we included non-interventional SRs, as in a previous study [1]. Although the optimal SR/RCT ratio has not been determined, this mass production of SRs could be harmful [4]. In conclusion, during the study period, the trend in the COVID-19 publications comprised a more rapid increase in the number of SRs than RCTs. Researchers may benefit from using their research resources for something other than an SR.

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.08.27.20182956 on medRxiv