Hypertension and Diabetes Delay the Viral Clearance in COVID-19 Patients

  1. Xiaoping Chen
  2. Wenjia Hu
  3. Jiaxin Ling
  4. Pingzheng Mo
  5. Yongxi Zhang
  6. Qunqun Jiang
  7. Zhiyong Ma
  8. Qian Cao
  9. Liping Deng
  10. Shihui Song
  11. Ruiying Zheng
  12. Shicheng Gao
  13. Hengning Ke
  14. Xien Gui
  15. Åke Lundkvist
  16. Jinlin Li
  17. Johanna F Lindahl
  18. Yong Xiong

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Abstract

Objectives

Comorbidities have significant indications for the disease outcome of COVID-19, however which underlying diseases that contribute the most to aggravate the conditions of COVID-19 patients is still largely unknown. SARS-CoV-2 viral clearance is a golden standard for defining the recovery of COVID-19 infections. To dissect the underlying diseases that could impact on viral clearance, we enrolled 106 COVID-19 patients who were hospitalized in the Zhongnan Hospital of Wuhan University, Wuhan, China between Jan 5 and Feb 25, 2020.

Methodology

We comprehensively analyzed demographic, clinical and laboratory data, as well as patient treatment records. Survival analyses with Kaplan-Meier and Cox regression modelling were employed to identify factors influencing the viral clearance negatively.

Results

We found that increasing age, male gender, and angiotensin-converting enzyme 2 (ACE2) associated factors (including hypertension, diabetes, and cardiovascular diseases) adversely affected the viral clearance. Furthermore, analysis by a random forest survival model pointed out hypertension, cortisone treatment, gender, and age as the four most important variables.

Conclusions

We conclude that patients at old age, males, and/or having diseases associated with high expression of ACE2 will have worse prognosis during a COVID-19 infections.

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    SciScore for 10.1101/2020.03.22.20040774: (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 board in Zhongnan Hospital of Wuhan University, Wuhan, China (No.2020011).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The data were imported and analyzed using R language, implemented in RStudio [24, 25].
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    Package survival, survminer, ranger and ggplot2 were employed for survival analysis, modelling and visualization separately [26-30].
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2020.03.22.20040774v1 on medRxiv