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Diagnostic Performance of COVID-19 Reporting and Data System Classification Across Residents and Radiologists: A Retrospective Study

Authors :
Hakan Önder
Melis Koşar Tunç
Hülya Kurtul Yıldız
Okan İnce
Naciye Kıs
Source :
Journal of Computer Assisted Tomography. 45:782-787
Publication Year :
2021
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2021.

Abstract

OBJECTIVE: The aim of the study was to evaluate the interobserver agreement and diagnostic accuracy of COVID-19 Reporting and Data System (CO-RADS), in patients suspected COVID-19 pneumonia. METHODS: Two hundred nine nonenhanced chest computed tomography images of patients with clinically suspected COVID-19 pneumonia were included. The images were evaluated by 2 groups of observers, consisting of 2 residents-radiologists, using CO-RADS. Reverse transcriptase-polymerase chain reaction (PCR) was used as a reference standard for diagnosis in this study. Sensitivity, specificity, area under receiver operating characteristic curve (AUC), and intraobserver/interobserver agreement were calculated. RESULTS: COVID-19 Reporting and Data System was able to distinguish patients with positive PCR results from those with negative PCR results with AUC of 0.796 in the group of residents and AUC of 0.810 in the group of radiologists. There was moderate interobserver agreement between residents and radiologist with κ values of 0.54 and 0.57. CONCLUSIONS: The diagnostic performance of CO-RADS for predicting COVID-19 pneumonia showed moderate interobserver agreement between residents and radiologists.

Details

ISSN :
15323145 and 03638715
Volume :
45
Database :
OpenAIRE
Journal :
Journal of Computer Assisted Tomography
Accession number :
edsair.doi.dedup.....cd836ea497a0e9f231430c25ce38c0ba
Full Text :
https://doi.org/10.1097/rct.0000000000001172