Abstract
PURPOSE: The aim of this study was to investigate if CT performed in the early disease phase can predict the course of COVID-19 pneumonia in a German cohort. METHOD: All patients with RT-PCR proven COVID-19 pneumonia and chest CT performed within 10 days of symptom onset between March 1st and April 15th 2020 were retrospectively identified from two tertiary care hospitals. 12 CT features, their distribution in the lung and the global extent of opacifications were evaluated. For analysis of prognosis two compound outcomes were defined: positive outcome was defined as either discharge or regular ward care; negative outcome was defined as need for mechanical ventilation, treatment on intensive care unit, extracorporeal membrane oxygenation or death. Follow-up was performed until June 19th. For statistical analysis uni- und multivariable logistic regression models were calculated. RESULTS: 64 patients were included in the study. By univariable analysis the following parameters predicted a negative outcome: consolidation (p = 0.034), crazy paving (p = 0.004), geographic shape of opacification (p = 0.022), dilatation of bronchi (p = 0.002), air bronchogram (p = 0.013), vessel enlargement (p = 0.014), pleural effusion (p = 0.05), bilateral disease (p = 0.004), involvement of the upper lobes (p = 0.004, p = 0.015) or the right middle lobe (p < 0.001) and severe extent of opacifications (p = 0.002). Multivariable analysis revealed crazy paving and severe extent of parenchymal involvement to be independently predictive for a poor outcome. CONCLUSIONS: Easy to assess CT features in the early phase of disease independently predicted an adverse outcome of patients with COVID-19 pneumonia.