Novel risk scoring system for predicting acute respiratory distress syndrome among hospitalized patients with coronavirus disease 2019 in Wuhan, China

Abstract

Abstract Background The mortality rate from acute respiratory distress syndrome (ARDS) is high among hospitalized patients with coronavirus disease 2019 (COVID-19). Hence, risk evaluation tools are required to immediately identify high-risk patients upon admission for early intervention. Methods A cohort of 220 consecutive patients with COVID-19 were included in this study. To analyze the risk factors of ARDS, data obtained from approximately 70% of the participants were randomly selected and used as training dataset to establish a logistic regression model. Meanwhile, data obtained from the remaining 30% of the participants were used as test dataset to validate the effect of the model. Results Lactate dehydrogenase, blood urea nitrogen, D-dimer, procalcitonin, and ferritin levels were included in the risk score system and were assigned a score of 25, 15, 34, 20, and 24, respectively. The cutoff value for the total score was > 35, with a sensitivity of 100.00% and specificity of 81.20%. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow test were 0.967 (95% confidence interval [CI]: 0.925–0.989) and 0.437(P Value = 0.437). The model had excellent discrimination and calibration during internal validation. Conclusions The novel risk score may be a valuable risk evaluation tool for screening patients with COVID-19 who are at high risk of ARDS.