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.