Laboratory Testing Implications of Risk-Stratification and Management of COVID-19 Patients - Liu, Caidong; Wang, Ziyu; Wu, Wei; Xiang, Changgang; Wu, Lingxiang; Li, Jie; Hou, Weiye; Sun, Huiling; Wang, Youli; Nie, Zhenling; Gao, Yingdong; Zhang, Ruisheng; et al. (Frontiers in Medicine, 2021)
Background: To classify COVID-19 patients into low-risk and high-risk at admission by laboratory indicators. Material and methods: This is a case series of patients from a China healthcare system in Wuhan. In this retrospective cohort, 3563 patients confirmed COVID-19 pneumonia, including 548 patients in the training dataset, and 3015 patients in the testing dataset. Main Results: We first identified the significant laboratory indicators related to the severity of COVID-19 in the training dataset. Neutrophils percentage, lymphocytes percentage, creatinine, and blood urea nitrogen with AUC greater than 0.7 were included in the model. These indicators were further used to build a support vector machine model to classify patients into low-risk and high-risk at admission. Results showed that this model could stratify the patients in the testing dataset effectively (AUC=0.89). Moreover, laboratory indicators detected in the first week after admission were able to estimate the probability of death (AUC=0.95). Besides, we could diagnose COVID-19 and differentiated it from other kinds of viral pneumonia based on laboratory indicators (accuracy=0.97). Conclusions: Our risk-stratification model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage of COVID-19.