Clinical and immunological features of severe and moderate coronavirus disease 2019

  1. Guang Chen
  2. Di Wu
  3. Wei Guo
  4. Yong Cao
  5. Da Huang
  6. Hongwu Wang
  7. Tao Wang
  8. Xiaoyun Zhang
  9. Huilong Chen
  10. Haijing Yu
  11. Xiaoping Zhang
  12. Minxia Zhang
  13. Shiji Wu
  14. Jianxin Song
  15. Tao Chen
  16. Meifang Han
  17. Shusheng Li
  18. Xiaoping Luo
  19. Jianping Zhao
  20. Qin Ning

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.02.16.20023903: (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 Institutional Review Board of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Our study has some limitations. First of all, we mainly evaluated the number of T cell subsets and NK cells as well as their IFN-γ production, the function of these cells, and the role of activated macrophages and lymphocytes infiltrating lung parenchyma remain unclear. Second, this study only included a small number of patients, thus the results should be interpreted with caution, and statistical non-significance may not rule out difference between severe and moderate cases. Third, since data regarding the viremia profile of SARS-CoV-2 are not available, further studies are needed to investigate the correlation between the virus load kinetics and the dynamics of cellular immune responses. Clarification of these questions will allow further dissection of the complex SARS-CoV-2 pathogenesis, with potential implications for the development of therapeutics and vaccines. In conclusion, the SARS-CoV-2 infection may affect primarily T lymphocytes, especially CD4+T cells, resulting in significant decrease in number as well as IFN-γ production, which may be associated with disease severity. Together with clinical characteristics, early immunologic indicators including diminished T lymphocytes and elevated cytokines may serve as potential markers for prognosis in COVID-19. Gaining a deeper understanding of the factors that influence lymphocytes particularly CD4+T cell counts and their decrease in patients with SARS-CoV-2 infection is of importance for clinical management of COVID-19.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 33. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1172/jci137244
  3. Version published to 10.1101/2020.02.16.20023903v1 on medRxiv