Clinical Characteristics and Short-Term Outcomes of Severe Patients With COVID-19 in Wuhan, China

  1. Xiaobo Feng
  2. Peiyun Li
  3. Liang Ma
  4. Hang Liang
  5. Jie Lei
  6. Wenqiang Li
  7. Kun Wang
  8. Yu Song
  9. Shuai Li
  10. Wei Yang
  11. Cao Yang

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Abstract

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  1. Version published to 10.3389/fmed.2020.00491
  2. ScreenIT

    SciScore for 10.1101/2020.04.24.20078063: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Ethics Commission of Wuhan Union Hospital of Tongji Medical College, Huazhong University of Science and Technology.
    Consent: Written informed consent was waived for the emergency of this infectious diseases.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All data were analyzed by SPSS (23.0 IBM SPSS).
    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 some limitations. First, owing to the limited number of cases, only 114 severe patients were included. Second, this study was a single-center research and a larger cohort study of severe patients with SARS-CoV-2 from other cities in China and other countries would help to further describe the clinical characteristics and predict the risk factors about this disease. In summary, we firstly reported this single-centered, prospective, observational study for short-term in severe patients with COVID-19. We found from univariate and multivariate Cox model that cytokine storm and uncontrolled inflammation responses, liver, kidney, cardiac dysfunction may play important roles in final outcome of severe ill patients with COVID-19. This will help clinicians to diagnose and treat severe patients.

    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 10.1101/2020.04.24.20078063 on medRxiv