CT lung lesions as predictors of early death or ICU admission in COVID-19 patients

Objective: The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients. Methods: We studied 572 patients diagnosed with COVID-19 (confirmed using polymerase chain reaction) for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0-10%, 11 -25%, 26-50%, 51-75% and >75%. The primary endpoint was severe disease, defined by death or admission to the intensive care unit in the 7 days following first admission. Results: The mean patient age was 66.0 +/- 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 patients (36.0%). The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24-4.46; p < 0.01). Most patients with lung involvement >50% (66/95, 69.5%) developed severe disease compared to patients with lung involvement of 26-50% (70/171, 40.9%) and <= 25% (70/306, 22.9%) (p < 0.01 and p < 0.01, respectively). None of the patients with normal CT (0/14) had severe disease. Conclusion: Chest CT findings at admission are associated with outcome in COVID-19 patients. (C) 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.