Predictors of COVID-19 Disease Course and Pulmonary Insult

Abstract

Background: The novel coronavirus disease COVID-19 first appeared in Wuhan, Hubei. It is crucial to identify patients who are susceptible to severe forms of the disease. Imaging has an important role in the confirmation and treatment of COVID-19 pneumonia. Aim: To assess the predictors of the COVID-19 disease course and pulmonary insult. Methods: Our retrospective investigation included 115 patients with COVID-19, with a median age of 49.1-66.3 years old, at King Hussein Medical Center, Amman, Jordan. Patients were assigned into one of two groups based on the disease course: group I (n=63) included patients with moderate disease and group II (n=52) included patients with severe disease. Computed tomography (CT) scores of pulmonary insult were determined. Baseline CT findings showed ground-glass opacity, consolidation, crazy-paving pattern and reticular shadow. Each lung region was scored using the five-grade scale to calculate the CT score. Independent factors of moderate COVID-19 were evaluated using binary logistic regression. Multivariate logistic regression was used to predict the CT score in COVID-19. Results: The independent factors for the COVID-19 disease course were baseline CT score (P < 0.05) and C-reactive protein (CRP) (P< 0.05). The factors for pulmonary insult were age, neutrophil, lymphocyte and CRP levels and CT score (P < 0.05). The cut-off value for CRP was 19.0 and the cut-off value for CT score was 9.0. Conclusion: Age, baseline CT score, CRP, neutrophil and lymphocyte percentages may predict the CT score of pulmonary insult. A CRP value of more than 19 and baseline CT score of more than 9 were independent factors of severe COVID-19 disease. Keywords: COVID-19, moderate, severe, pulmonary insult, computed tomography score, neutrophil, lymphocyte, CRP, age.