Clinical Findings of COVID-19 Patients Admitted to Intensive Care Units in Guangdong Province, China: A Multicenter, Retrospective, Observational Study

  1. Yonghao Xu
  2. Zhiheng Xu
  3. Xuesong Liu
  4. Lihua Cai
  5. Haichong Zheng
  6. Yongbo Huang
  7. Lixin Zhou
  8. Linxi Huang
  9. Yun Ling
  10. Liehua Deng
  11. Jianwei Li
  12. Sibei Chen
  13. Dongdong Liu
  14. Zhimin Lin
  15. Liang Zhou
  16. Weiqun He
  17. Nanshan Zhong
  18. Xiaoqing Liu
  19. Yimin Li

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Abstract

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  1. Version published to 10.3389/fmed.2020.576457
  2. ScreenIT

    SciScore for 10.1101/2020.03.03.20030668: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the Ethics Commission of the First Affiliated Hospital of Guangzhou Medical University.
    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 23.0 (SPSS Inc., Chicago, IL, USA).
    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:
    Limitation: Our study has several limitations. Firstly, only 45 critically ill patients with COVID-19 were included from Guangdong Province. It might be that more clinical features related to those critically illness will be identified, if other provinces get involved. Secondly, at the time of study submission, half of the patients had not been discharged from ICU, so we are unable to estimate either ICU stay, ventilation free day, the case fatality rate or the predictors of fatality.

    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.

  3. Version published to 10.1101/2020.03.03.20030668v1 on medRxiv