A composite ranking of risk factors for COVID-19 time-to-event data from a Turkish cohort

  1. Ayse Ulgen
  2. Sirin Cetin
  3. Meryem Cetin
  4. Hakan Sivgin
  5. Wentian Li

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Abstract

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  1. Version published to 10.1016/j.compbiolchem.2022.107681
  2. Version published to 10.1101/2022.01.05.22268765v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2022.01.05.22268765: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Programs used: The R statistical platform (https://www.r-project.org) is used for our analysis.
    https://www.r-project.org
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    In the main RSF program we used, the rfsrc function from randomForestSRC package, the default number of trees (ntree=1000), default number of variables for splitting a branch , default minimum (average) number of samples in the external nodes (nodesize=15), are used.
    randomForestSRC
    suggested: None

    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.

  4. Version published to 10.1101/2022.01.05.22268765v1 on medRxiv