关键词: 新型冠状病毒感染(COVID-19), 院内死亡, 影响因素, 风险预测模型, 老年

Abstract: Objective To study the factors affecting hospital death in elderly patients with novel coronavirus infection/disease 2019(COVID-19), and to build a risk prediction model. Methods According to the diagnostic criteria of Diagnosis and Treatment Protocol for COVID-19 Infection (Trial 10th Edition). Totally 775 elderly patients (≥60 years old) diagnosed as COVID-19 infection in the emergency department and fever clinic of the First Hospital of Changsha were selected as the research objects. General data and serum biomarkers of patients were collected. After treatment, the patients' data were divided into survival group and hospital death group. Binary Logistic regression was used to screen the independent influencing factors of death, and ROC curve was used to analyze the predictive value of related indicators on hospital death. Results After treatment, 712 patients (91.9%) survived and 63 patients (8.3%) died in hospital. Binary Logistic regression analysis showed that: ≥90 years old [OR=5.065, 95% CI (1.427,17.974)], type 2 diabetes mellitus [OR=3.757, 95% CI (1.649,8.559)], COPD[OR=5.625,95% CI (2.357,13.421)], monocyte ratio [OR=0.908,95% CI (0.857,0.963)], plasma fibringen [OR=1.376,95% CI (1.053,1.800)] and lactate dehydrogenase [OR=1.005,95% CI (1.001,o1.008)] were independent factors of in-hospital death (P＜0.05). The predictive value of diabetes mellitus + COPD + age + monocyte ratio + plasma fibrinogen + lactate dehydrogenase was proved in hospital death from COVID-19 infected patients: the area under the curve(AUC) was 0.883 (95% CI: 0.827,0.940,P＜ 0.001), the critical value ≥0.710 suggested the risk of death in hospital, the specificity was 0.851, the sensitivity was 0.857. Conclusions The hospital mortality of the elderly after COVID-19 infection is higher and closely related to type 2 diabetes, COPD, monocyte ratio, plasma fibrinogen and lactate dehydrogenase.

Key words: novel coronavirus infection(COVID-19), nosocomial death, influencing factor, risk prediction model, the aged