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. 2020 Apr 28;16(4):e1008520.
doi: 10.1371/journal.ppat.1008520. eCollection 2020 Apr.

Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients

Affiliations

Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: A retrospective study of 168 severe patients

Yifan Meng et al. PLoS Pathog. .

Abstract

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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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. The sex-specific clinical outcomes between different age groups and with/without comorbidities.
Fig 2
Fig 2. The sex-specific dynamic changes in selected laboratory parameters during the course of COVID-19.
(A), the sex-specific dynamic change in the neutrophil-to-lymphocyte ratio in patients who died; (B), the sex-specific dynamic change in C-reactive protein in patients who died; (C), the sex-specific dynamic change in aspartate aminotransferase in patients who died; (D), the sex-specific dynamic change in lactate dehydrogenase in patients who died; (E), the sex-specific dynamic change in blood urea nitrogen in patients who died; (F), the sex-specific dynamic change in creatinine in patients who died. (G), the sex-specific dynamic change in the neutrophil-to-lymphocyte ratio in patients who were discharged; (H), the sex-specific dynamic change in C-reactive protein in patients who were discharged; (I), the sex-specific dynamic change in aspartate aminotransferase in patients who were discharged; (J), the sex-specific dynamic change in lactate dehydrogenase in patients who were discharged; (K), the sex-specific dynamic change in blood urea nitrogen in patients who were discharged; (L), the sex-specific dynamic change in creatinine in patients who were discharged. T1, the first test after hospital admission; T2, the midpoint test during the whole hospital stay; T3, the last test before discharge. The dashed lines in gray show the upper limit of normal of each parameter.
Fig 3
Fig 3. ORs (95% CI) of the rates of critically ill cases according to age and comorbidities.
Abbreviations: OR, odds ratio; 95%CI, 95% confidence interval. aCrude: unadjusted. bModel: adjusted for with/without comorbidity(for age) or age(for with/without comorbidity), with/without signs and symptoms of respiratory system, the days from onset of symptom to hospital admission, and the days from onset of symptom to pathogens identified.

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