Clinical characteristics of 34 COVID-19 patients admitted to intensive care unit in Hangzhou, China

  1. Yi Zheng
  2. Li-jun Sun
  3. Mi Xu
  4. Jian Pan
  5. Yun-tao Zhang
  6. Xue-ling Fang
  7. Qiang Fang
  8. Hong-liu Cai

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.04.12.20062604: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Oral consent was obtained from the authorized person.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were performed using SPSS software, version 22.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 several limitations. Firstly, limited samples in our cohort are analyzed. A previous report enrolled 52 critically ill patients with SARS-CoV-2 infection from Wuhan Jin Yin-tan hospital. However, in places outside Hubei province, the total number of cases and the number of critical patients are relatively small. Secondly, most IMV patients had not been discharged at the time of manuscript submission, so we can’t use survival or death as a clinical end point. The case mortality rate and other outcome indicators need to be reported later.

    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.

  2. Version published to 10.1631/jzus.b2000174
  3. Version published to 10.1101/2020.04.12.20062604 on medRxiv