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Diagnostic Performance of COVID-19 Reporting and Data System Classification Across Residents and Radiologists: A Retrospective Study #MMPMID34176881
Kosar Tunc M; Kis N; Ince O; Kurtul Yildiz H; Onder H
J Comput Assist Tomogr 2021[Sep]; 45 (5): 782-787 PMID34176881show ga
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 kappa 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.
|Aged[MESH]
|COVID-19/*diagnostic imaging[MESH]
|Female[MESH]
|Humans[MESH]
|Internship and Residency/*statistics & numerical data[MESH]
J+Comput+Assist+Tomogr 2021 ; 45 (5): 782-787
