Development of a risk prediction model for severe patients with COVID-19

Pengqiang Du,Su Shen,Rufei Ma,Quncheng Zhang, Hongwei Zhao, Mingyue Chen, Ming Ni, Qingli Shen,Xingang Li

Authorea (Authorea)(2020)

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摘要
An outbreak of COVID-19 has spread worldwide, and it is urgent to evaluate risk factors associated with severe cases. We aimed to identify risk factors for severe patients with COVID-19. A total of 52 patients with COVID-19 admitted to Henan Provincial People’s Hospital were enrolled in this study, and patients’ information was extracted from electronic medical records. The severity of symptoms of COVID-19 was divided into “mild” and “severe.” Univariate analysis was used to select potential risk factors. A risk model was constructed using multivariable logistic regression analysis. Advanced age (OR = 1.098, 95% CI = 1.020-1.183) and number of comorbidities (OR = 6.067, 95% CI = 1.078-34.143) were significant risk factors for severe patients with COVID-19. The comorbidities included hypertension, diabetes, cardiovascular disease, respiratory disease, and past surgical history. A risk score was developed based on this model, and the developed risk prediction model had good discriminative power and was well-calibrated. This study indicates that advanced age and comorbidities are risk factors for severe patients with COVID-19. More attention should be paid to high-risk patients during hospitalization.
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关键词
risk prediction model,severe patients
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