Virologic and clinical characteristics for prognosis of severe COVID-19: a retrospective observational study in Wuhan, China

  1. Sha Fu
  2. Xiao-yu Fu
  3. Yang Song
  4. Min Li
  5. Pin-hua Pan
  6. Tao Tang
  7. Chun-hu Zhang
  8. Tie-jian Jiang
  9. De-ming Tan
  10. Xue-gong Fan
  11. Xin-ping Sha
  12. Jing-dong Ma
  13. Yan Huang
  14. Sha-ling Li
  15. Yi-xiang Zheng
  16. Zhao-xin Qian
  17. Zeng Xiong
  18. Li-zhi Xiao
  19. Hui-bao Long
  20. Jiang-hai Chen
  21. Yi Ouyang

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Abstract

Background

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has progressed to a pandemic associated with substantial morbidity and mortality. The WHO and the United States Center for Disease Control and Prevention (CDC) have issued interim clinical guidance for management of patients with confirmed coronavirus disease (COVID-19), but there is limited data on the virologic and clinical characteristics for prognosis of severe COVID-19.

Methods

A total of 50 patients with severe COVID-19 were divided into good and poor recovery groups. The dynamic viral shedding and serological characteristics of SARS-CoV-2 were explored. The risk factors associated with poor recovery and lung lesion resolutions were identified. In addition, the potential relationships among the viral shedding, the pro-inflammatory response, and lung lesion evolutions were characterized.

Results

A total of 58% of the patients had poor recovery and were more likely to have a prolonged interval of viral shedding. The longest viral shedding was 57 days after symptom onset. Older age, hyperlipemia, hypoproteinemia, corticosteroid therapy, consolidation on chest computed-tomography (CT), and prolonged SARS-CoV-2 IgM positive were all associated with poor recovery. Additionally, the odds of impaired lung lesion resolutions were higher in patients with hypoproteinemia, hyperlipemia, and elevated levels of IL-4 and ferritin. Finally, viral shedding and proinflammatory responses were closely correlated with lung lesion evolutions on chest CT.

Conclusions

Patients with severe COVID-19 have prolonged SARS-CoV-2 infection and delayed intermittent viral shedding. Older age, hyperlipemia, hypoproteinemia, corticosteroid usage, and prolonged SARS-CoV-2 IgM positive might be utilized as predicative factors for the patients with poor recovery.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.03.20051763: (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 Union Hospital at Tongji Medical College of HUST.
    Consent: Written informed consent was obtained directly from patient.
    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:
    This study does have some limitations. First, only 50 patients with confirmed COVID-19 were included. It would be better to include a larger number of cases to obtain a more comprehensive understanding of COVID-19. Second, the serologic tests kits for SARS-CoV-2 were available on March 8, 2020, thus the dynamic serologic pattern of SARS-CoV-2 during the early stage was not obtained. Third, the cytokine test results at the early stage of SARS-CoV-2 infection was also not obtained, thus the initial inflammation and immune response profile in severely infected patients remains unclear.

    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 10.1101/2020.04.03.20051763v1 on medRxiv