Diagnostic performance and interobserver agreement of CO-RADS: evaluation of classification in radiology practice.
Diagn Interv Radiol
; 27(5): 615-620, 2021 Sep.
Статья
в английский
| MEDLINE | ID: covidwho-1329195
ABSTRACT
PURPOSE:
We aimed to evaluate the use of the COVID-19 reporting and data system (CO-RADS) among radiologists and the diagnostic performance of this system.METHODS:
Four radiologists retrospectively evaluated the chest CT examinations of 178 patients. The study included 143 patients with positive reverse transcriptase-polymerase chain reaction (RT-PCR) test results and 35 patients whose RT-PCR tests were negative but whose clinical and/or radiological findings were consistent with COVID-19. Fleiss' kappa (κ) values were calculated, and individual observers' scores were compared. To investigate diagnostic efficiency, receiver operating characteristic (ROC) curves were calculated for each interpreter.RESULTS:
The interpreters were in full agreement on 574 of 712 (80.6%) evaluations. The common Fleiss' κ value of all the radiologists combined was 0.712 (95% confidence interval [CI] 0.692-0.769). A reliable prediction on the basis of RT-PCR and clinical findings indicated the mean area under the curve (AUC) of Fleiss' κ value as 0.89 (95% CI 0.708-0.990). General interpreter agreement was found to range from moderate to good.CONCLUSION:
The interpreter agreement for CO-RADS categories 1 and 5 was reasonably good. We conclude that this scoring system will make a valuable contribution to efforts in COVID-19 diagnosis. CO-RADS can also be of significant value for the diagnosis and treatment of the disease in cases with false-negative PCR results.
Полный текст:
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Коллекция:
Международные базы данных
база данных:
MEDLINE
Основная тема:
Radiology
/
COVID-19
Тип исследования:
Диагностическое исследование
/
Экспериментальные исследования
/
Наблюдательное исследование
/
Прогностическое исследование
Пределы темы:
Люди
Язык:
английский
Журнал:
Diagn Interv Radiol
Тематика журнала:
Диагностическая визуализация
/
Лучевая диагностика
Год:
2021
Тип:
Статья
Аффилированная страна:
Dir.2021.201032
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