Retrospective study of risk factors for mortality in human avian influenza A(H7N9) cases in Zhejiang Province, China, March 2013 to June 2014. (October 2015)

• Record Type: Journal Article
• Authors: Cheng, Qing-Lin; Ding, Hua; Sun, Zhou; Kao, Qing-Jun; Yang, Xu-Hui; Huang, Ren-Jie; Wen, Yuan-Yuan; Wang, Jing; Xie, Li
• Is Part Of: International journal of infectious diseases. Volume 39(2015:Oct.)
• Page Start: 95
• Page End: 101
• Publication Date: 2015-10
• Subjects: Influenza -- human -- Influenza A virus -- H7N9 subtype -- Outcome -- Risk factors; Communicable diseases -- Periodicals; Communicable Diseases -- Periodicals; Communicable diseases; Periodicals; Electronic journals; 616.9
• DOI: 10.1016/j.ijid.2015.09.008
• Languages: English
• ISSNs: 1201-9712

Abstract

Highlights: The demographic, epidemiological, and clinical features of fatal cases of influenza A(H7N9) virus infection are described. We identified risk factors for the case fatality with H7N9 virus infection. Based on these risk factors, effective prevention and control measures were developed. The reinforcement of self-protection measures, etc. is key to reducing the high case fatality rate. Summary: Background: The influenza A(H7N9) virus causes a serious disease that threatens human health. Fatalities associated with human infections caused by this virus are of great public health concern; however, the possible risk factors are not yet fully known. Methods: A stratified sampling method, incorporating household income levels and a random number table method, was used to select laboratory-confirmed A(H7N9) cases for this study. Eighty-five patients were selected randomly from 139 laboratory-confirmed A(H7N9) cases occurring in Zhejiang Province between March 1, 2013 and June 30, 2014. Data were collected using a standard method. To test the statistical significance among discrete variables, univariate analyses were used to compare two groups. The Kaplan–Meier product-limit method was used to analyze the patient survival fraction. The Cox proportional hazards regression model was used to analyze all variables with p ≤ 0.05 in the univariate analysis. Lastly, a stepwise procedure was used to construct a final model with a significance level of p > 0.10 for removal and p < 0.05 for re-entry. Results: A total of 85 patients with H7N9 virus infection were identified. Among these, 30 (35.29%) died. In the univariate analysis, the following factors were associated with a high risk of influenza A(H7N9) case fatality: age ≥60 years ( p = 0.008), low education level ( p = 0.030), chronic diseases ( p = 0.029), poor hand hygiene ( p = 0.010), time from illness onset to the first medical visit ( p = 0.029) and to intensive care unit admission ( p = 0.008), an incubation period of ≤5 days ( p = 0.039), a peak C-reactive protein ≥120 mg/l ( p = 0.012), increased initial neutrophil count ( p = 0.020), decreased initial lymphocyte count ( p = 0.021), and initial infection of both lungs ( p = 0.003). Multivariate analysis confirmed that the independent predictors of H7N9 virus infection mortality in Zhejiang, China were hand hygiene (hazard ratio (HR) 5.163, 95% confidence interval (CI) 1.164–22.661), age (HR 1.042, 95% CI 1.007–1.076), and peak CRP (HR 1.009, 95% CI 1.002–1.016). Conclusions: Improvements in immunity, early case identification and treatment, and personal protection measures are key to addressing the high human avian influenza A(H7N9) case fatality rate.