Predictive model of risk factors of High Flow Nasal Cannula using machine learning in COVID-19

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Abstract

No abstract available

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  1. SciScore for 10.1101/2022.03.02.22271673: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethics: This study was approved by the National Center for Global Health and Medicine (NCGM) ethics review (NCGM-G-004133-00).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Research data was collected and managed using Research Electronic Data Capture (REDCap) [11], which is a safe web-based data capture application hosted by the Joint Center for Researchers, Associates and Clinicians, a data centre of the NCGM.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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:
    The present study had the following limitations. First, the effect of vaccination and variants were not taken into consideration. We plan to update the verification of accuracy, such as the positive predictive value, on the basis of new data in the future. However, it is considered that the priority of the items does not change because the change in severity does not have a great influence on the pathological condition. In this study, we gave priority to rapidity so that it can be used in the next epidemic. Second, the registry is not inclusive; it is a registry that targets inpatients. In Japan, there were changes to the hospitalisation criteria as well [4]. However, in the present study, we limited the time period and tried to organise the hospitalisation criteria as much as possible. Furthermore, in Japan, there are some hospitals with >200 beds and patients with moderate–severe illness, and because the hospitals are equipped with sufficient facilities, we believe that there is no major difference in practice. Third, there is no guideline or criteria for using nasal high flow; therefore, it partially depends on the medical resources of the institution and the practice of each physician. For this reason, accuracy was underestimated.

    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.