Predicting clinical outcome with computed tomography severity score in COVID-19

Abstract

Introduction: COVID-19 is a major public health burden in the world, and chest computed tomography (CT) is the ideal imaging modality to diagnose and monitor disease progression. Objectives: The objective was to review the common and uncommon chest CT findings of patients with COVID-19 and to correlate the CT findings with short-term prognosis. Methods: All patients who had laboratory-confirmed COVID-19 infection and underwent CT scan were reviewed. The imaging features and the distribution of abnormality were evaluated. A CT severity score (CT-SS) system out of 40 was used. Mann–Whitney U-test and Chi-square or Fisher's exact test were used for analysis. Two-sided P < 0.05 was considered statistically significant. A receiver operating characteristic curve analysis was performed to calculate the CT-SS cutoff for hospital admission and intensive care unit (ICU) admission. Results: A total of 149 individuals were eligible. The most common imaging features were ground-glass opacities (GGO) (88%), septal thickening (70%), and reticulations (50%). The least common imaging features were pneumothorax (1%) and vascular enlargement (1%). The most common distributions of GGO were bilateral (92%) and multifocal (95%), with peripheral (100%) and lower lobe predominance (77%). A higher CT-SS had a significant association with longer hospital stay and ICU admission, with CT-SS of 18 and 10 being optimal cutoff, respectively. Conclusion: Our study is one of the few studies to correlate the imaging finding with clinical outcomes in the south Indian population. The common findings in our study were consistent with the literature. CT-SS plays an important role in predicting prognosis.