The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients
Open accessAbstract
To confirm the relationship between sex and the progression of Coronavirus Disease-19 (COVID-19), and its potential mechanism, among severe patients. For this retrospective study, we included 168 consecutive severe patients with pathogen-confirmed COVID-19 who were hospitalized between January 16th and February 4th, 2020, at Tongji Hospital in Wuhan, China. Clinical characteristics, laboratory parameters, and outcomes were compared and analyzed between males and females. In the present study, we analyzed 168 severe patients with COVID-19, including 86 males and 82 females, and 48 patients (28.6%) were diagnosed as critically ill. Of 86 male patients, 12.8% (11/86) died and 75.6% (65/86) were discharged; of 82 female patients, 7.3% (6/82) died and 86.6% (71/82) were discharged. Eleven laboratory parameters showed significant differences between male and female patients, and six of them were higher during the whole clinical course in patients who died than in patients who were discharged. In adjusted logistic regression analysis, males with comorbidities presented a higher risk of being critically ill than males without comorbidities (OR = 3.824, 95% CI = 1.279-11.435). However, this association attenuated to null in female patients (OR = 2.992, 95% CI = 0.937-9.558). A similar sex-specific trend was observed in the relation between age and critically ill conditions. We highlighted sex-specific differences in clinical characteristics and prognosis. Male patients appeared to be more susceptible to age and comorbidities. Sex is an important biological variable that should be considered in the prevention and treatment of COVID-19.
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Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Self-citationA new coronavirus associated with human respiratory disease in China
Wu, F., Zhao, S., Yu, B., Chen, Y.-M., Wang, W., Song, Z.-G., Hu, Y., Tao, Z.-W., Tian, J.-H., Pei, Y.-Y., et al. (2020) · Nature · doi:10.1038/s41586-020-2008-3 · Cited by 11,688
Sex differences in immune responses
Klein, S. L., & Flanagan, K. L. (2016) · Nature Reviews Immunology · doi:10.1038/nri.2016.90 · Cited by 6,370
Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection
Chai, X., Hu, L., Zhang, Y., Han, W., Lu, Z., Ke, A., Zhou, J., Shi, G., Fang, N., Fan, J., et al. (2020) · doi:10.1101/2020.02.03.931766 · Cited by 952
Self-citationSingle-cell RNA expression profiling of ACE2, the receptor of SARS-CoV-2
Zhao, Y., Zhao, Z., Wang, Y., Zhou, Y., Ma, Y., & Zuo, W. (2020) · doi:10.1101/2020.01.26.919985 · Cited by 860
Yang, Y., Yang, M., Shen, C., Wang, F., Yuan, J., Li, J., Zhang, M., Wang, Z., Xing, L., Wei, J., et al. (2020) · doi:10.1101/2020.02.11.20021493 · Cited by 836
Cited by
Sex differences in immune responses that underlie COVID-19 disease outcomes
Takahashi, T., Ellingson, M. K., Wong, P., Israelow, B., Lucas, C., Klein, J., Silva, J., Mao, T., Oh, J. E., Tokuyama, M., et al. (2020) · Nature · doi:10.1038/s41586-020-2700-3 · Cited by 1,459
Tocilizumab in patients with severe COVID-19: a retrospective cohort study
Guaraldi, G., Meschiari, M., Cozzi-Lepri, A., Milic, J., Tonelli, R., Menozzi, M., Franceschini, E., Cuomo, G., Orlando, G., Borghi, V., et al. (2020) · The Lancet Rheumatology · doi:10.1016/s2665-9913(20)30173-9 · Cited by 939
Considering how biological sex impacts immune responses and COVID-19 outcomes
Scully, E. P., Haverfield, J., Ursin, R. L., Tannenbaum, C., & Klein, S. L. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0348-8 · Cited by 932
T cell responses in patients with COVID-19
Chen, Z., & John Wherry, E. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0402-6 · Cited by 797
COVID-19-neutralizing antibodies predict disease severity and survival
Garcia-Beltran, W. F., Lam, E. C., Astudillo, M. G., Yang, D., Miller, T. E., Feldman, J., Hauser, B. M., Caradonna, T. M., Clayton, K. L., Nitido, A. D., et al. (2021) · Cell · doi:10.1016/j.cell.2020.12.015 · Cited by 722
Metadata
- Authors
- Meng, Y., Wu, P., Lu, W., Liu, K., Ma, K., Huang, L., Cai, J., Zhang, H., Qin, Y., Sun, H., Ding, W., Gui, L., & Wu, P.
- Venue
- PLOS Pathogens
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-04-28
- Volume
- 16
- Issue
- 4
- Pages
- e1008520
- ISSN
- 1553-7366 (ISSN-L)
- 1553-7374
- OpenAlex
- W3019181748
- Cited by
- 343
- References
- 8
- FWCI
- 9.23
- Type
- journal article
- Language
- en
- Open access
- gold
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- Meng, Y., Wu, P., Lu, W., Liu, K., Ma, K., Huang, L., Cai, J., Zhang, H., Qin, Y., Sun, H., Ding, W., Gui, L., & Wu, P. (2020). Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients. PLOS Pathogens. https://doi.org/10.1371/journal.ppat.1008520
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