Risk Factors and a Prognostic Scoring System for Severe Disease in Patients with COVID-19: A Retrospective Cohort Study

Sen Yang, Le Ma, Yu-Lan Wang, Q. Tong, De-Hua Yu, S. Dai, R. Cui
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Abstract

Background: The corona virus disease 2019 (COVID-19) has made a big threat on the global public health. The aim of the study is to comprehensively explore the risk factor for severe disease events (intensive care, invasive ventilation, or death) in patients with COVID-19, and to establish a prognostic scoring system. Methods: Patients with laboratory-confirmed COVID-19 admitted to the Wuhan Leishenshan Hospital from February 13 to March 14, 2020, was retrospectively analyzed. Demographic data, symptoms, laboratory values at baseline, comorbidities, treatments and clinical outcomes were extracted. The LASSO and multivariate logistic regression models were developed to explore the risk factors for critical-ill events. A risk model was established via nomogram. Results: 463 COVID-19 patients were included, of whom 397 were non-critically ill and 66 were critically ill. The LASSO identified four risk factors (hypersensitive cardiac troponin I [cTnI], Blood Urea Nitrogen [BUN], haemoglobin, and Interleukin-6 [IL-6]) contributing to the critical-ill events. Multivariable regression showed increasing odds of in-hospital critical-ill events associated with hypersensitive cTnI greater than 0.04 ng/mL (OR, 95% CI: 20.98, 3.51-125.31), BUN greater than 7.6 mmol/L (OR, 95% CI: 5.22, 1.52-17.81), decreased haemoglobin (OR, 95% CI: 1.06, 1.04-1.10), and higher IL-6 (OR, 95% CI: 1.05, 1.02-1.08) on admission. The risk model constructed by the selected four risk factors showed high calibration (Hosmer-Lemeshow, p=1.00). Conclusion: Elevated hypersensitive cTnI, BUN, IL-6, and decreased hemoglobin were risk factors of critical-ill events. The risk model could help clinicians with early identification of patients with COVID-19 who will progress to severe disease.
COVID-19重症患者的危险因素和预后评分系统:一项回顾性队列研究
背景:2019冠状病毒病(COVID-19)已对全球公共卫生构成重大威胁。本研究旨在全面探讨COVID-19患者重症事件(重症监护、有创通气或死亡)的危险因素,并建立预后评分系统。方法:对武汉市雷神山医院2020年2月13日至3月14日收治的新型冠状病毒肺炎实验室确诊患者进行回顾性分析。提取了人口统计学数据、症状、基线实验室值、合并症、治疗和临床结果。采用LASSO和多元logistic回归模型探讨危重事件的危险因素。通过nomogram方法建立了风险模型。结果:纳入463例新冠肺炎患者,其中非危重症397例,危重症66例。LASSO确定了导致危重事件的四个危险因素(心肌肌钙蛋白I (cTnI)、血尿素氮(BUN)、血红蛋白和白细胞介素6 (IL-6))。多变量回归显示,入院时与超敏cTnI大于0.04 ng/mL (OR, 95% CI: 20.98, 3.51-125.31)、BUN大于7.6 mmol/L (OR, 95% CI: 5.22, 1.52-17.81)、血红蛋白降低(OR, 95% CI: 1.06, 1.04-1.10)和IL-6升高(OR, 95% CI: 1.05, 1.02-1.08)相关的住院危重事件的几率增加。选取的4个危险因素构建的风险模型具有较高的校正性(Hosmer-Lemeshow, p=1.00)。结论:超敏cTnI、BUN、IL-6升高、血红蛋白降低是危重事件发生的危险因素。该风险模型可以帮助临床医生早期识别将发展为严重疾病的COVID-19患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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