Sex differences in clinical findings among patients with coronavirus disease 2019 (COVID-19) and severe condition

  1. Jing Li
  2. Yinghua Zhang
  3. Fang Wang
  4. Bing Liu
  5. Hui Li
  6. Guodong Tang
  7. Zhigang Chang
  8. Aihua Liu
  9. Chunyi Fu
  10. Jing Gao
  11. Jing Li

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Abstract

Objective

To compare the sex differences in the clinical findings among patients with severe coronavirus disease 2019 (COVID-19).

Methods

We retrospectively collected data of 47 patients diagnosed as severe type of COVID-19 from February 8 to 22, 2020, including demographics, illness history, physical examination, laboratory test, management, and compared differences between men and women.

Results

Of the 47 patients, 28 (59.6%) were men. The median age was 62 years, and 30 (63.8%) had comorbidities. The initial symptoms were mainly fever (34 [72.3%]), cough (36 [76.6%]), myalgia (5 [10.6%]) and fatigue (7 [14.9%]). Procalcitonin level was higher in men than in women (0.08 vs. 0.04ng/ml, p=0.002). N-terminal-pro brain natriuretic peptide increased in 16 (57.1%) men and 5 (26.3%) women (p=0.037). Five men (17.9%) had detected positive influenza A antibody, but no women. During 2-week admission, 5 (17.9%) men and 1 (5.3%) woman were reclassified into the critical type due to deterioration. Mortality was 3.6% in men and 0 in women respectively. Four (21.1%) women and one man (3.6%) recovered and discharged from hospital.

Conclusion

Sex differences may exist in COVID-19 patients of severe type. Men are likely to have more complicated clinical condition and worse in-hospital outcomes as compared to women.

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    SciScore for 10.1101/2020.02.27.20027524: (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 Beijing Hospital.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableStatistical analysis: Continuous variables were expressed as median (IQR) and compared with the Mann-Whitney U test; categorical variables were expressed as number (%) and compared by χ2 test or Fisher’s exact test between the men and women groups.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were done using the SPSS software (version 23) for all analyses.
    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: 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 10.1101/2020.02.27.20027524v1 on medRxiv