A Risk Classification Model to Predict Mortality Among Laboratory-Confirmed Avian Influenza A H7N9 Patients: A Population-Based Observational Cohort Study

Abstract

Abstract Background Avian influenza A H7N9 (A/H7N9) is characterized by rapid progressive pneumonia and respiratory failure. Mortality among laboratory-confirmed cases is above 30%; however, the clinical course of disease is variable and patients at high risk for death are not well characterized. Methods We obtained demographic, clinical, and laboratory information on all A/H7N9 patients in Zhejiang province from China Centers for Disease Control and Prevention electronic databases. Risk factors for death were identified using logistic regression and a risk score was created using regression coefficients from multivariable models. We externally validated this score in an independent cohort from Jiangsu province. Results Among 305 A/H7N9 patients, 115 (37.7%) died. Four independent predictors of death were identified: older age, diabetes, bilateral lung infection, and neutrophil percentage. We constructed a score with 0–13 points. Mortality rates in low- (0–3), medium- (4–6), and high-risk (7–13) groups were 4.6%, 32.1%, and 62.7% (Ptrend < .0001). In a validation cohort of 111 A/H7N9 patients, 61 (55%) died. Mortality rates in low-, medium-, and high-risk groups were 35.5%, 55.8, and 67.4% (Ptrend = .0063). Conclusions We developed and validated a simple-to-use, predictive risk score for clinical use, identifying patients at high mortality risk.