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अमूर्त

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, Qiang Tong, De-Hua Yu, Sheng-Ming Dai, Ran Cui

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.