Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes · 2020
Radiological Society of North America (RSNA) Expert Consensus Statement Related to Chest CT Findings in COVID-19 Versus CO-RADS: Comparison of Reporting System Performance Among Chest Radiologists and End-User Preference.
Сравнительное исследованиеСтатьяКлинические рекомендацииConsensus StatementНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
O' Neill Siobhan B, Byrne Danielle, Müller Nestor L, Jalal Sabeena, Parker William, Nicolaou Savvas, Bilawich Ana-Maria
Аннотация
PURPOSE: The RSNA expert consensus statement and CO-RADS reporting system assist radiologists in describing lung imaging findings in a standardized manner in patients under investigation for COVID-19 pneumonia and provide clarity in communication with other healthcare providers. We aim to compare diagnostic performance and inter-/intra-observer among chest radiologists in the interpretation of RSNA and CO-RADS reporting systems and assess clinician preference.
METHODS: Chest CT scans of 279 patients with suspected COVID-19 who underwent RT-PCR testing were retrospectively and independently examined by 3 chest radiologists who assigned interpretation according to the RSNA and CO-RADS reporting systems. Inter-/intra-observer analysis was performed. Diagnostic accuracy of both reporting systems was calculated. 60 clinicians participated in a survey to assess end-user preference of the reporting systems.
RESULTS: Both systems demonstrated almost perfect inter-observer agreement (Fleiss kappa 0.871, P < 0.0001 for RSNA; 0.876, P < 0.0001 for CO-RADS impressions). Intra-observer agreement between the 2 scoring systems using the equivalent categories was almost perfect (Fleiss kappa 0.90-0.92, P < 0.001). Positive predictive values were high, 0.798-0.818 for RSNA and 0.891-0.903 CO-RADS. Negative predictive value were similar, 0.573-0.585 for RSNA and 0.573-0.58 for CO-RADS. Specificity differed between the 2 systems, 68-73% for CO-RADS and 52-58% for RSNA with superior specificity of CO-RADS. Of 60 survey participants, the majority preferred the RSNA reporting system rather than CO-RADS for all options provided (66.7-76.7%; P < 0.05).
CONCLUSIONS: RSNA and CO-RADS reporting systems are consistent and reproducible with near perfect inter-/intra-observer agreement and excellent positive predictive value. End-users preferred the reporting language in the RSNA system.
METHODS: Chest CT scans of 279 patients with suspected COVID-19 who underwent RT-PCR testing were retrospectively and independently examined by 3 chest radiologists who assigned interpretation according to the RSNA and CO-RADS reporting systems. Inter-/intra-observer analysis was performed. Diagnostic accuracy of both reporting systems was calculated. 60 clinicians participated in a survey to assess end-user preference of the reporting systems.
RESULTS: Both systems demonstrated almost perfect inter-observer agreement (Fleiss kappa 0.871, P < 0.0001 for RSNA; 0.876, P < 0.0001 for CO-RADS impressions). Intra-observer agreement between the 2 scoring systems using the equivalent categories was almost perfect (Fleiss kappa 0.90-0.92, P < 0.001). Positive predictive values were high, 0.798-0.818 for RSNA and 0.891-0.903 CO-RADS. Negative predictive value were similar, 0.573-0.585 for RSNA and 0.573-0.58 for CO-RADS. Specificity differed between the 2 systems, 68-73% for CO-RADS and 52-58% for RSNA with superior specificity of CO-RADS. Of 60 survey participants, the majority preferred the RSNA reporting system rather than CO-RADS for all options provided (66.7-76.7%; P < 0.05).
CONCLUSIONS: RSNA and CO-RADS reporting systems are consistent and reproducible with near perfect inter-/intra-observer agreement and excellent positive predictive value. End-users preferred the reporting language in the RSNA system.