Association between Cardiovascular Burden and Requirement of Intensive Care among Patients with Mild COVID-19

  1. Shi Tai
  2. Jianjun Tang
  3. Bilian Yu
  4. Liang Tang
  5. Yang Wang
  6. Huilin Zhang
  7. Weihong Zhu
  8. Kui Xiao
  9. Chuan Wen
  10. Chongqin Tan
  11. Zhongbiao Jiang
  12. Chuanhao Jiang
  13. Li Zhu
  14. Li Jiang
  15. Qiming Liu
  16. Xinqun Hu
  17. Zhenfei Fang
  18. Xuping Li
  19. Jiaxing Sun
  20. Zhaowei Zhu
  21. Hui Yang
  22. Tao Tu
  23. Yichao Xiao
  24. Mingxian Chen
  25. Yuhu He
  26. Xiangping Chai
  27. Junmei Xu
  28. Shenghua Zhou

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Abstract

Background . Information regarding the impact of cardiovascular (CV) conditions on disease progression among patients with mild coronavirus disease 2019 (COVID-19) is limited. Methods . This study evaluated the association of underlying CV conditions with disease progression in patients with mild COVID-19. The primary outcome was the need to be transferred to the designated hospital for intensive care due to COVID-19 disease progression. The patients were divided into with and without CV conditions as well as stable and intensive care groups. Results . Of the 332 patients with mild COVID-19, the median age was 51 years (IQR, 40-59 years), and 200 (61.2%) were female. Of the 48 (14.5%) patients with CV conditions, 23 (47.9%) progressed to severe disease status and required intensive care. Compared with patients without CV conditions, patients with CV conditions were older and more likely to have fatigue, chest tightness, and myalgia. The rate of requiring intensive care was significantly higher among patients with CV conditions than in patients without CV conditions (47.92% vs. 12.4%; P < 0.001 ). In subgroup analysis, the rate of requiring intensive care was also higher among patients with either hypertension or coronary heart disease (CHD) than in patients without hypertension or CHD. The multivariable regression model showed that CV condition served as an independent risk factor for intensive care (odds ratio (OR), 2.652 (95% CI, 1.019-6.899)) after adjustment for various cofounders. Conclusions . Patients with mild COVID-19 complicating CV conditions are susceptible to develop severe disease status and requirement for intensive care.

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  1. Version published to 10.1155/2020/9059562
  2. ScreenIT

    SciScore for 10.1101/2020.05.25.20111757: (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 National Health Commission of China and the Institutional Review Board at Renmin Hospital of Wuhan University (Wuhan, China).
    Consent: Written informed consent was waived by the ethics commission of the designated hospital for patients with emerging infectious diseases.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical charts were generated using Excel 2016 (Microsoft) or Stata15.
    Excel
    suggested: None

    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.

  3. Version published to 10.1101/2020.05.25.20111757v1 on medRxiv