< Back to previous page

Publication

Radiological findings in low-dose CT for COVID-19 pneumonia in 182 patients Correlation of signs and severity with patient outcome

Journal Contribution - Journal Article

To characterize computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia and their value in outcome prediction.Chest CTs of 182 patients with a confirmed diagnosis of COVID-19 infection by real-time reverse transcription polymerase chain reaction were evaluated for the presence of CT-abnormalities and their frequency. Regarding the patient outcome each patient was categorized in 5 progressive stages and the duration of hospitalization was determined. Regression analysis was performed to find which CT findings are predictive for patient outcome and to assess prognostic factors for the hospitalization duration.Multivariate statistical analysis confirmed a higher age (OR = 1.023, P  =  .025), a higher total visual severity score (OR = 1.038, P  =  .002) and the presence of crazy paving (OR = 2.160, P  =  .034) as predictive parameters for patient outcome. A higher total visual severity score (+0.134 days; P  =  .012) and the presence of pleural effusion (+13.985 days, P  =  0.005) were predictive parameters for a longer hospitalization duration. Moreover, a higher sensitivity of chest CT (false negatives 10.4%; true positives 78.6%) in comparison to real-time reverse transcription polymerase chain reaction was obtained.An increasing percentage of lung opacity as well as the presence of crazy paving and a higher age are associated with a worse patient outcome. The presence of a higher total visual severity score and pleural effusion are significant predictors for a longer hospitalization duration. These results are underscoring the value of chest CT as a diagnostic and prognostic tool in the pandemic outbreak of COVID-19, to facilitate fast detection and to preserve the limited (intensive) care capacity only for the most vulnerable patients.
Journal: Medicine
ISSN: 0025-7974
Issue: 9
Volume: 101
Publication year:2022
Accessibility:Open