• Xiaofeng Wang, Xingxing Hu, Weijun Tan, Peter Mazzone, Eduardo Mireles-Cabodevila, Xiaozhen Han, Pingyue Huang, Weihua Hu, Raed Dweik, and Zhenshun Cheng.
• Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH.
• AJR Am J Roentgenol. 2021 Jul 1; 217 (1): 83-92.

AbstractBACKGROUND. Chest CT findings have the potential to guide treatment of hospitalized patients with coronavirus disease (COVID-19). OBJECTIVE. The purpose of this study was to assess a CT visual severity score in hospitalized patients with COVID-19, with attention to temporal changes in the score and the role of the score in a model for predicting in-hospital complications. METHODS. This retrospective study included 161 inpatients with COVID-19 from three hospitals in China who underwent serial chest CT scans during hospitalization. CT examinations were evaluated using a visual severity scoring system. The temporal pattern of the CT visual severity score across serial CT examinations during hospitalization was characterized using a generalized spline regression model. A prognostic model to predict major complications, including in-hospital mortality, was created using the CT visual severity score and clinical variables. External model validation was evaluated by two independent radiologists in a cohort of 135 patients from a different hospital. RESULTS. The cohort included 91 survivors with nonsevere disease, 55 survivors with severe disease, and 15 patients who died during hospitalization. Median CT visual lung severity score in the first week of hospitalization was 2.0 in survivors with non-severe disease, 4.0 in survivors with severe disease, and 11.0 in nonsurvivors. CT visual severity score peaked approximately 9 and 12 days after symptom onset in survivors with nonsevere and severe disease, respectively, and progressively decreased in subsequent hospitalization weeks in both groups. In the prognostic model, in-hospital complications were independently associated with a severe CT score (odds ratio [OR], 31.28), moderate CT score (OR, 5.86), age (OR, 1.09 per 1-year increase), and lymphocyte count (OR, 0.03 per 1 × 109/L increase). In the validation cohort, the two readers achieved C-index values of 0.92-0.95, accuracy of 85.2-86.7%, sensitivity of 70.7-75.6%, and specificity of 91.4-91.5% for predicting in-hospital complications. CONCLUSION. A CT visual severity score is associated with clinical disease severity and evolves in a characteristic fashion during hospitalization for COVID-19. A prognostic model based on the CT visual severity score and clinical variables shows strong performance in predicting in-hospital complications. CLINICAL IMPACT. The prognostic model using the CT visual severity score may help identify patients at highest risk of poor outcomes and guide early intervention.

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