Validation of Diagnostic Accuracy and Disease Severity Correlation of Chest Computed Tomography Severity Scores in Patients with COVID-19 Pneumonia

被引:2
作者
Brumini, Ivan [1 ,2 ]
Dodig, Doris [3 ]
Zuza, Iva [1 ]
Viskovic, Klaudija [4 ]
Mehmedovic, Armin [4 ]
Bartolovic, Nina [1 ]
Susak, Helena [4 ]
Grbesa, Durdica Cekinovic [5 ]
Miletic, Damir [1 ]
机构
[1] Univ Hosp Rijeka, Dept Diagnost & Intervent Radiol, Kresimirova 42, Rijeka 51000, Croatia
[2] Univ Rijeka, Fac Hlth Studies, Dept Radiol Technol, Rijeka 51000, Croatia
[3] European Telemed Clin SL, C Marina 16-18, Barcelona 08005, Spain
[4] Univ Hosp Infect Dis Dr Fran Mihaljevic, Mirogojska 8, Zagreb 10000, Croatia
[5] Univ Hosp Rijeka, Dept Infect Dis, Kresimirova 42, Rijeka 51000, Croatia
关键词
COVID-19; pneumonia; SARS-CoV-2; thorax; CT;
D O I
10.3390/diagnostics14020148
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The aim of our study was to establish and compare the diagnostic accuracy and clinical applicability of published chest CT severity scoring systems used for COVID-19 pneumonia assessment and to propose the most efficient CT scoring system with the highest diagnostic performance and the most accurate prediction of disease severity. This retrospective study included 218 patients with PCR-confirmed SARS-CoV-2 infection and chest CT. Two radiologists blindly evaluated CT scans and calculated nine different CT severity scores (CT SSs). The diagnostic validity of CT SSs was tested by ROC analysis. Interobserver agreement was excellent (intraclass correlation coefficient: 0.982-0.995). The predominance of either consolidations or a combination of consolidations and ground-glass opacities (GGOs) was a predictor of more severe disease (both p < 0.005), while GGO prevalence alone was not. Correlation between all CT SSs was high, ranging from 0.848 to 0.971. CT SS 30 had the highest diagnostic accuracy (AUC = 0.805) in discriminating mild from severe COVID-19 disease compared to all the other proposed scoring systems (AUC range 0.755-0.788). In conclusion, CT SS 30 achieved the highest diagnostic accuracy in predicting the severity of COVID-19 disease while maintaining simplicity, reproducibility, and applicability in complex clinical settings.
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页数:12
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