OBJECTIVES: To explore the relation between inflammation-associated factors and in-hospital mortality and investigate which factor is an independent predictor of in-hospital death in patients with coronavirus disease-2019 .

METHODS: This study included patients with coronavirus disease-2019 who were hospitalized between February 9 , 2020, and March 30 , 2020 . Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) were used to select variables . Multivariate Cox regression analysis was applied to identify independent risk factors in coronavirus disease-2019 .

RESULTS: 1135 patients were analysed during the study period . A total of 35 variables were considered to be risk factors after the univariate regression analysis of the clinical characteristics and laboratory parameters (p <0.05), and LASSO regression analysis screened out seven risk factors for further study . The six independent risk factors revealed by multivariate Cox regression were myoglobin (HR 5.353 , 95% CI 2.633-10.882; p <0.001), C-reactive protein (HR 2.063 , 95% CI 1.036-4.109; p = 0.039), neutrophil count (HR 2.015 , 95% CI 1.154-3.518; p = 0.014), interleukin 6 (HR 9.753 , 95% CI 2.952-32.218; p <0.001), age (HR 2.016 , 95% CI 1.077-3.773; p = 0.028), and international normalized ratio (HR 2.595 , 95% CI 1.412-4.769; p = 0.002).

CONCLUSION: Our results suggested that inflammation-associated factors were significantly associated with in-hospital mortality in coronavirus disease-2019 patients . C-reactive protein, neutrophil count and interleukin 6 were independent factors for predicting in-hospital mortality and had a better independent predictive ability . We believe these findings may allow early identification of the patients at high risk for death, and can also assist better management of these patients . This article is protected by copyright . All rights reserved.