Computed Tomography and Clinical Features for Diagnosis of COVID-19 Pneumonia and Differentiating from Common Viral Pneumonia

Abstract

Introduction: HRCT chest has high sensitivity in diagnosis of corona virus disease 2019 (COVID-19) in a screening population, but it is thought to be nonspecific. The study aimed to determine the predictive features of computed tomography (CT) and clinical features for diagnosing COVID-19 pneumonia and differentiating it from non-COVID -19 viral pneumonia. Methodology: A retrospective study was done on 21 patients with confirmed COVID-19 pneumonia (group 1). In addition, 16 patients with confirmed cases of other common viral pneumonia (group 2) during the first and second wave to analyse characteristics of COVID-19 pneumonia were included in the study. Patients with laboratory confirmed RTPCR test positive and undergone CT scan were included. Results: The factors including size of ground glass opacity (GGO), GGO with reticular and/or interlobular septal thickening, vascular enlargement, “tree-in-bud” opacity, centrilobular nodules, and stuffy or runny nose were associated with group 2 (COVID-19) of viral pneumonia. Only GGO with reticular and/or interlobular septal thickening, centrilobular nodules, and stuffy or runny nose remained independent risk factors in multinomial logistic regression analysis for COVID-19 pneumonia. Conclusion: GGO with reticular and/or interlobular septal thickening, absence of centrilobular nodules on computed tomography, and absence of stuffy or runny nose are presented in patients with COVID-19 pneumonia.

Keywords

• Computed tomography, COVID-19 pneumonia, Ground glass opacities.