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Comparative Study
. 2020 Nov;92(11):2684-2692.
doi: 10.1002/jmv.26137. Epub 2020 Jun 19.

Gendered effects on inflammation reaction and outcome of COVID-19 patients in Wuhan

Affiliations
Comparative Study

Gendered effects on inflammation reaction and outcome of COVID-19 patients in Wuhan

Lu Qin et al. J Med Virol. 2020 Nov.

Abstract

Background: The rapid outbreak of coronavirus disease 2019 (COVID-19) has turned into a public health emergency of international concern. Epidemiological research has shown that sex is associated with the severity of COVID-19, but the underlying mechanism of sex predisposition remains poorly understood. We aim to study the gendered differences in inflammation reaction, and the association with severity and mortality of COVID-19.

Methods: In this retrospective study, we enrolled 548 COVID-19 inpatients from Tongji Hospital from 26 January to 5 February 2020, and followed up to 3 March 2020. Epidemiological, demographic and clinical features, and inflammatory indexes were collected and compared between males and females. The Cox proportional hazard regression model was applied to identify the gendered effect on mortality of COVID-19 after adjusting for age, comorbidity, and smoking history. The multiple linear regression method was used to explore the influence of sex on inflammation reaction.

Results: Males had higher mortality than females did (22.2% vs 10.4%), with an hazard ratio of 1.923 (95% confidence interval, 1.181-3.130); elder age and comorbidity were significantly associated with decease of COVID-19 patients. Excess inflammation reaction was related to severity of COVID-19. Male patients had greater inflammation reaction, with higher levels of interleukin 10, tumor necrosis factor-α, lactose dehydrogenase, ferritin, and hyper-sensitive C-reactive protein, but a lower lymphocyte count than females adjusted by age and comorbidity.

Conclusions: Sex, age, and comorbidity are critical risk factors for mortality of COVID-19. Excess innate immunity and proinflammation activity, and deficiency in adaptive immunity response promote males, especially elder males, to develop a cytokine storm, causing potential acute respiratory distressed syndrome, multiple organ failure and decease.

Keywords: COVID-19; age; inflammation; mortality; sex.

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Conflict of interest statement

The authors declare that there are no conflict of interests.

Figures

Figure 1
Figure 1
Kaplan‐Meier curves for COVID‐19 patients (A) grouped by sex (P = .0002) and (B) grouped by sex and age (P < .0001). (C) The effect of sex on mortality of COVID‐19 patients after adjusting for other potential risk factors
Figure 2
Figure 2
Proportions of COVID‐19 severities based on laboratory marker expressions. The cut‐off for serum cytokines were set at medians of 233 patients, that is, 5 pg/mL for IL‐1β, 737 U/mL for sIL‐2R, 16.12 pg/mL for IL‐6, 15.8 pg/mL for IL‐8, 5 pg/mL for IL‐10, and 8.5 pg/mL for TNF‐α, respectively. The cut‐off for LDH, ferritin, hsCRP, and lymphocyte count were set at 250 U/L, 400 μg/L, 100 mg/L, and 0.8 × 109/L, respectively. *P < .05; **P ≤ .001; ***P ≤ .0001. hsCRP, hyper‐sensitive C‐reactive protein; IL, interleukin; LDH, lactose dehydrogenase; Lym, lymphocyte; sIL‐2R, soluble interleukin‐2 receptor; TNF, tumor necrosis factor
Figure 3
Figure 3
Levels of laboratory markers in patients with COVID‐19 stratified by sex and age. A, Inflammatory cytokines including IL‐1β, sIL‐2R, IL‐6, IL‐8, IL‐10, and TNF‐α. B, Inflammatory proteins including LDH, ferritin and hsCRP. C, Lymphocyte count in peripheral blood. Young, 0 to 44 years; mid‐aged, 44 to 64 years; elder, greater than or equal to 65 years. hsCRP, hyper‐sensitive C‐reactive protein; IL, interleukin; LDH, lactose dehydrogenase; Lym, lymphocyte; sIL‐2R, soluble interleukin‐2 receptor; TNF, tumor necrosis factor
Figure 4
Figure 4
Effects of sex, age and comorbidities on laboratory markers in patients with COVID‐19. A, distribution of comorbidities in COVID‐19 patients grouped by sex. B, Correlation between the identified risk factors (sex, age, hypertension, and diabetes) and laboratory markers by multiple linear regression model; adjusted β, partial regression coefficient; *P < .05; **P ≤ .001; ***P ≤ .0001. CHD, coronary heart disease; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; HBV, hepatitis B virus; hsCRP, hyper‐sensitive C‐reactive protein; IL, interleukin; LDH, lactose dehydrogenase; Lym, lymphocyte; sIL‐2R, soluble interleukin‐2 receptor; TB, tuberculosis; TNF, tumor necrosis factor

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