Predicting Illness Severity and Short-Term Outcomes of COVID-19: A Retrospective Cohort Study in China
Chuming Chen, Haihui Wang, Zhichao Liang, Ling Peng, Fang Zhao, Liuqing Yang, Mengli Cao, Weibo Wu, Xiao Jiang, Peiyan Zhang, Yinfeng Li, Li Chen, Shiyan Feng, Jianming Li, Lingxiang Meng, Huishan Wu, Fuxiang Wang, Quanying Liu, Yingxia Liu
Abstract
Among 417 COVID-19 patients in Shenzhen, demographic characteristics, clinical manifestations and baseline laboratory tests showed significant differences between mild-moderate cohort and severe-critical cohort.Based on these differences, a convenient mathematical model was established to predict the illness severity of COVID-19. The model includes four parameters: age, BMI, CD4(+) lymphocytes and IL-6 levels. The AUC of the model is 0.911.The high risk factors for developing to severe COVID-19 are: age ≥ 55 years, BMI > 27 kg / m(2), IL-6 ≥ 20 pg / ml, CD4(+) T cell ≤ 400 count / μ L.Among 249 discharged COVID-19 patients, those who recovered after 20 days had a lower count of platelet, a higher level of estimated glomerular filtration rate, and higher level of interleukin-6 and myoglobin than those who recovered within 20 days.