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Validation of Diagnostic Accuracy and Disease Severity Correlation of Chest Computed Tomography Severity Scores in Patients with COVID-19 Pneumonia.
Brumini, Ivan; Dodig, Doris; Zuza, Iva; Viskovic, Klaudija; Mehmedovic, Armin; Bartolovic, Nina; Susak, Helena; Cekinovic Grbesa, Durdica; Miletic, Damir.
Afiliación
  • Brumini I; Department of Diagnostic and Interventional Radiology, University Hospital Rijeka, Kresimirova 42, 51000 Rijeka, Croatia.
  • Dodig D; Department of Radiological Technology, Faculty of Health Studies, University of Rijeka, 51000 Rijeka, Croatia.
  • Zuza I; European Telemedicine Clinic S.L., C/Marina 16-18, 08005 Barcelona, Spain.
  • Viskovic K; Department of Diagnostic and Interventional Radiology, University Hospital Rijeka, Kresimirova 42, 51000 Rijeka, Croatia.
  • Mehmedovic A; University Hospital for Infectious Diseases "Dr. Fran Mihaljevic", Mirogojska 8, 10000 Zagreb, Croatia.
  • Bartolovic N; European Telemedicine Clinic S.L., C/Marina 16-18, 08005 Barcelona, Spain.
  • Susak H; Department of Diagnostic and Interventional Radiology, University Hospital Rijeka, Kresimirova 42, 51000 Rijeka, Croatia.
  • Cekinovic Grbesa D; University Hospital for Infectious Diseases "Dr. Fran Mihaljevic", Mirogojska 8, 10000 Zagreb, Croatia.
  • Miletic D; Department for Infectious Diseases, University Hospital Rijeka, Kresimirova 42, 51000 Rijeka, Croatia.
Diagnostics (Basel) ; 14(2)2024 Jan 08.
Article en En | MEDLINE | ID: mdl-38248025
ABSTRACT
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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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article