Analysis of Predictive Factors for Moderate-Stage COVID-19 Outcome and Maximal Extent of Lung Injury

Background: As the coronavirus disease 2019 (COVID-19) epidemic continues to spread, it is important to predict the clinical classification of COVID-19 and evaluate the progression of lung injury. Objectives: To investigate the predictive factors of theoutcomeof moderate-stage coronavirus disease 2019 (COVID-19)andmaximal extent of lung injury. Patients and Methods: This study was a retrospective analysis of 97 patients with moderate-stage COVID-19 diagnosed in our hospital. We divided the patients into two groups according to disease progression: one group for moderate stage and another for both severe stage and critically severe stage COVID-19. We then analyzed the independent factors influencing changes in the course of the disease in moderate-stage patients using binary logistic regression. Next, we assessed the computed tomography (CT) score of maximal lung injury using follow-up images of the patients. We used multiple linear regression (MLR) to analyze the independent variables, and to predict the CT score of maximal lung injury in COVID-19 patients. Results: The results were obtained using multivariate logistic regression analysis, and the independent factors affecting clinical classification were baseline CT score (P = 0.008), high-sensitivity C-reactive protein (hs-CRP) (P = 0.001), and diabetes (P = 0.04). MLR revealed that the factors predicting the extent of maximal lung injury in COVID-19 patients were age (P = 0.014), neutrophil percentage (P = 0.038), lymphocyte percentage (P = 0.031), hs-CRP (P = 0.010), and baseline CT score (P 0.001). The optimal cut-off value of hs-CRP was 18.5, and the baseline CT score was 8.5. Conclusion: Age, baseline CT score, hs-CRP, neutrophil percentage, and lymphocyte percentage could predict the CT score of maximal lung injury, and hs-CRP 18.5, baseline CT score 9, and diabetes were independent factors of severe/critically severe COVID-19.