Gender-Based Disparities in COVID-19 Patient Outcomes: A Propensity-matched Analysis

  1. Shailendra Singh
  2. Monica Chowdhry
  3. Arka Chatterjee
  4. Ahmad Khan

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Abstract

COVID-19 epidemiological data show higher mortality among males as compared to females. However, it remains unclear if this disparity is due to gender differences in high-risk characteristics. Our study, including a large cohort of male and female patients, showed that males have a higher risk for mortality, hospitalization and mechanical ventilation even when compared to a matched cohort of females with similar age, high-risk behavior, and comorbidities. This gender-based risk of poor outcomes among COVID-19 patients is especially more pronounced in advanced age. High-risk characteristics only partially explain the gender disparity, and further research is needed to understand the causes of this disparity.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.24.20079046: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableA search query was made (April 17-18, 2020) in the EMR of patients on the COVID-19 research network to identify male and female patients (≥ 10 years age) diagnosed with COVID-19 between January 20, 2020, and April 15, 2020.

    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:
    Although our data represent one of the largest and most diverse cohorts of COVID-19 patients, our study has several limitations. The data derived from EMR based database is susceptible to errors in coding or data entry15. However, the ability of TriNetX to aggregate the data directly from the EMRs in a real-time fashion minimizes the risk of data collection errors at the investigator’s end. Patient counts were rounded up to the nearest ten, and that may influence results for infrequent outcomes; however, most of our outcomes had a relatively large number of patients. Gender differences in asymptomatic or mild cases of COVID-19 that remain undiagnosed or did not seek medical care were not accounted for16, and hence their role might be undervalued. In conclusion, males are more severely affected and have higher mortality from COVID-19. This gender-specific risk is especially more pronounced in advanced age. Gender disparity in poor outcomes can only be partially explained by differences in high-risk behavior and comorbidities. Further research is needed to understand the causes of this disparity and may be beneficial for decisions in both clinical and policy-making realms.

    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 10.1101/2020.04.24.20079046v2 on medRxiv
  3. Version published to 10.1101/2020.04.24.20079046v1 on medRxiv