Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea
Byunggeon Park, Jongmin Park, Jae‐Kwang Lim, Kyung Min Shin, Jaehee Lee, Hyewon Seo, Yong Hoon Lee, Jun Heo, Won Kee Lee, Jin Young Kim, Ki Beom Kim, Sungjun Moon, Sooyoung Choi
Abstract
OBJECTIVE: Lung segmentation using volumetric quantitative computed tomography (CT) analysis may help predict outcomes of patients with coronavirus disease (COVID-19). The aim of this study was to investigate the relationship between CT volumetric quantitative analysis and prognosis in patients with COVID-19. MATERIALS AND METHODS: CT images from patients diagnosed with COVID-19 from February 18 to April 15, 2020 were retrospectively analyzed. CT with a negative finding, failure of quantitative analysis, or poor image quality was excluded. CT volumetric quantitative analysis was performed by automated volumetric methods. Patients were stratified into two risk groups according to CURB-65: mild (score of 0-1) and severe (2-5) pneumonia. Outcomes were evaluated according to the critical event-free survival (CEFS). The critical events were defined as mechanical ventilator care, ICU admission, or death. Multivariable Cox proportional hazards analyses were used to evaluate the relationship between the variables and prognosis. RESULTS: = 0.019) were associated with a lower risk of critical events in the severe pneumonia group (n = 28). CONCLUSION: CRP in the mild pneumonia group; NALP and NALPV in the severe pneumonia group; and sex, CRP, and CALP in the total cohort were independently associated with CEFS in patients with COVID-19.