Longitudinal ventilatory ratio monitoring for COVID-19: its potential in predicting severity and assessing treatment response

  1. Natsuko Kaku
  2. Yu Nakagama
  3. Michinori Shirano
  4. Sari Shinomiya
  5. Kazuhiro Shimazu
  6. Katsuaki Yamazaki
  7. Yoshito Maehata
  8. Ryo Morita
  9. Yuko Nitahara
  10. Hiromasa Yamamoto
  11. Yasumitsu Mizobata
  12. Yasutoshi Kido

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Abstract

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  1. Version published to 10.1186/s13054-021-03768-2
  2. ScreenIT

    SciScore for 10.1101/2021.07.20.21260754: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis: All analyses were performed with GraphPad Prism 9.1.1 (GraphPad Software, Inc., San Diego, CA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    This study has some limitations. The most appropriate VR value to be used as the threshold requires further evaluation. This study only used data up to day 6 of respiratory support. Data were not available after day 7 because a large number of patients were withdrawn from respiratory support at the time. Finally, we cannot rule out the possibility of selection bias because we included only a small number of patients collected at a single institution.

    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.
    • No funding statement was detected.
    • 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.

  3. Version published to 10.1101/2021.07.20.21260754v1 on medRxiv