Computed tomography-quantitative evaluation (CT-QE) score of patients with COVID-19 pneumonia: a simple and practical approach

Abstract

Introduction: A simple visual score based on chest computed tomography (CT) findings is desirable for defining prognosis in patients with COVID-19 pneumonia. This study evaluated the diagnostic performance of chest CT using a visual quantification score of lung involvement that predicts the clinical outcome and management area of patients with COVID-19 pneumonia. We also compared the accuracy of this score with clinical severity scores and inflammatory markers. Materials and methods: A chest CT quantitative evaluation (CT-QE) ranging from 0 to 15 points was created. Scores were found to be correlated with the patient management areas such as home, hospital ward, and intensive care unit (ICU). Receiver operating characteristic (ROC) curves were compared with the diagnostic performance of the CT-QE score with clinical severity scales and inflammatory markers to predict clinical outcomes. Results: A total of 178 patients with COVID-19 pneumonia were included. The CT-QE score (AUC, 0.78) had a higher accuracy for adverse clinical outcomes than the CURB-65 score (AUC, 0.65) and the P/F ratio (AUC, 0.69) (p < 0.001). Furthermore, the CT-QE score (AUC, 0.86) outperformed CRP (AUC, 0.77), D-dimer (AUC, 0.73), and ferritin (AUC, 0.76) (p < 0.001) in predicting the clinical outcomes. The CT-QE score was 6-9 points for hospital ward management (p < 0.001) and ≥ 10 points for admission to the ICU or death (p < 0.001). Conclusion: The CT-QE score is a simple and practical visual quantification tool based on chest CT findings for prognosis, which predicts the clinical outcome and management area in patients with COVID-19 pneumonia.