Development and Validation of the HNC-LL Score for Predicting the Severity of Coronavirus Disease 2019

Abstract

Background: The severity of coronavirus disease 2019 (COVID-19) varies widely, ranging from asymptomatic to fatal. However, there is limited information regarding the risk factors associated with severe disease. In this study, we aimed to develop a model for predicting COVID-19 severity. Methods: A total of 690 patients with confirmed COVID-19 were recruited between January 1 and March 18, 2020 from hospitals in Honghu and Nanchang, and finally, 442 patients were analyzed. Data were partitioned into the training set and test sets to develop and validate the model, respectively. Results: A predictive HNC-LL (Hypertension–Neutrophil count–C-reactive protein– Lymphocyte count– Lactate dehydrogenase) score was established based on multivariate logistic regression analysis results. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC] = 0.861, 95% confidence interval [CI]: 0.800–0.922; P Conclusions: We developed an accurate tool for predicting disease severity in patients with COVID-19. This model can potentially be used to identify patients at risk of developing severe disease in the early stage and therefore, guide treatment decisions.Funding Statement: This work was supported by the National Nature Science Foundation of China (Grant Nos. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).Declaration of Interests: The authors declare that they do not have any conflicts of interest.Ethics Approval Statement: This retrospective analysis was approved by Medical Ethics committee of Nanfang Hospital of Southern Medical University, and the requirement for informed consent was waived by the ethics committee.