Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,325

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Gender Differences in Patients With COVID-19: Focus on Severity and Mortality

Open access
Jin, Jian-Min, Bai, Peng, He, Wei, Wu, Fei, Liu, Xiao-Fang, Han, De-Min, Liu, Shi, Yang, Jin-Kui·2020·Frontiers in Public Health

Published version of a preprint

Abstract

Abstract Importance The recent outbreak of Novel Coronavirus (SARS-CoV-2) Disease (COVID-19) has put the world on alert, that is reminiscent of the SARS outbreak seventeen years ago. Objective We aim to compare the severity and mortality between male and female patients with both COVID-19 and SARS, to explore the most useful prognostic factors for individualized assessment. Design, Setting, and Participants We extracted the data from a case series of 43 hospitalized patients we treated, a public data set of the first 37 cases died of COVID-19 in Wuhan city and 1019 survived patients from six cities in China. We also analyzed the data of 524 patients with SARS, including 139 deaths, from Beijing city in early 2003. Main Outcomes and Measures Severity and mortality. Results Older age and high number of comorbidities were associated with higher severity and mortality in patients with both COVID-19 and SARS. The percentages of older age (≥65 years) were much higher in the deceased group than in the survived group in patients with both COVID-19 (83.8 vs. 13.2, P<0.001) and SARS (37.4 vs. 4.9, P<0.001). In the case series, men tend to be more serious than women (P=0.035), although age was comparable between men and women. In the public data set, age was also comparable between men and women in the deceased group or the survived group in patients with COVID-19. Meanwhile, gender distribution was exactly symmetrical in the 1019 survivors of COVID-19. However, the percentage of male were higher in the deceased group than in the survived group (70.3 vs. 50.0, P=0.015). The gender role in mortality was also observed in SARS patients. Survival analysis showed that men (hazard ratio [95% CI] 1.47 [1.05-2.06, P= 0.025) had a significantly higher mortality rate than women in patients with SARS. Conclusions and Relevance Older age and male gender are risk factors for worse outcome in patients with COVID. While men and women have the same susceptibility to both SARS-CoV-2 and SARS-CoV, men may be more prone to have higher severity and mortality independent of age and susceptibility. Key Points Question Are men more susceptible to getting and dying from COVID-19? Findings In the case series, men tend to be more serious than women. In the public data set, the percentage of men were higher in the deceased group than in the survived group, although age was comparable between men and women. Meaning Male gender is a risk factor for worse outcome in patients with COVID independent of age and susceptibility.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fpubh.2020.00152

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Research works printed but not linked: 8

  1. Zaki, 2012, Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia, N Engl J Med., 367, 1814, 10.1056/NEJMoa1211721 · DOI · Paper page
  2. Chan, 2020, A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster, Lancet., 395, 514, 10.1016/S0140-6736(20)30154-9 · DOI · Paper page
  3. Zhang, 2020, Clinical characteristics of 140 patients infected by SARS-CoV-2 in Wuhan, China, Allergy., 10.1111/all.14238 · DOI · Paper page
  4. Wang, 2020, Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China, JAMA., 10.1001/jama.2020.1585 · DOI · Paper page
  5. Yang, 2006, Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS, Diabet Med., 23, 623, 10.1111/j.1464-5491.2006.01861.x · DOI · Paper page
  6. Yang, 2010, Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes, Acta Diabetol., 47, 193, 10.1007/s00592-009-0109-4 · DOI · Paper page
  7. Patel, 2013, Emerging markers in cardiovascular disease: where does angiotensin-converting enzyme 2 fit in?, Clin Exp Pharmacol Physiol., 40, 551, 10.1111/1440-1681.12069 · DOI
  8. Jin, 2020, Gender differences in patients with COVID-19: focus on severity and mortality, medRxiv [Preprint], 10.1101/2020.02.23.20026864 · DOI

Cited by

See all 2,325

Metadata

Authors
Jin, J.-M., Bai, P., He, W., Wu, F., Liu, X.-F., Han, D.-M., Liu, S., & Yang, J.-K.
Venue
Frontiers in Public Health
Published
2020-04-29
Volume
8
Pages
152-152
ISSN
2296-2565 (ISSN-L)
OpenAlex
W3020512604
Cited by
2,325
References
5
FWCI
60.66
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Gender Differences in Patients With COVID-19: Focus on Severity and Mortality. https://app.cochat.ai/papers/10.3389/fpubh.2020.00152
The paper
Jin, J.-M., Bai, P., He, W., Wu, F., Liu, X.-F., Han, D.-M., Liu, S., & Yang, J.-K. (2020). Gender Differences in Patients With COVID-19: Focus on Severity and Mortality. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2020.00152

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.