Un Woo Lee1, Shin Ahn2, Yo Sep Shin1, Youn-Jung Kim1, Seung Mok Ryoo1, Chang Hwan Sohn1, Won Young Kim1, Sang-Hun Lee3. 1. Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. 2. Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. Electronic address: ans1023@gmail.com. 3. Department of Emergency Medicine, Dongsan Medical Center, Keimyung University School of Medicine, Daegu, Republic of Korea.
Abstract
OBJECTIVE: Current guidelines recommend the use of the updated Diamond-Forrester (DF) method and Coronary Artery Disease (CAD) Consortium models to assess the pretest probability of obstructive CAD. The present study aimed to compare the performance of these models among patients with chest pain evaluated in an emergency department (ED). METHODS: We compared three scores (DF, CAD consortium basic, and clinical) among 1247 consecutive patients with chest pain who underwent coronary computed tomographic angiography (CTA). Invasive angiography was performed to confirm the stenosis for those who showed obstructive CAD on CTA, if clinically indicated. Primary outcome was the presence of obstructive CAD (≧50% stenosis). RESULTS: Overall, 426 (34.2%) patients were diagnosed with obstructive CAD. The expected prevalence of CAD was underestimated by the CAD consortium clinical model (23.4%) and overestimated by the DF model (53.1%). For the prediction of obstructive CAD, the CAD consortium clinical model had superior area under the receiver-operating curve (0.754), followed by the CAD consortium basic (0.736), and finally, the DF model (0.718). Whereas the CAD consortium models more accurately classified patients without any CAD or nonobstructive CAD as low-risk patients, the DF model more accurately classified high-risk patients with obstructive CAD. The net reclassification improvement of CAD consortium basic and clinical models were 24.7% and 27.9%, respectively. CONCLUSIONS: Compared with the DF model, the CAD consortium clinical model appears to improve the prediction of low-risk patients with <15% probability of having obstructive CAD. However, this model needs caution when using in high-risk population.
OBJECTIVE: Current guidelines recommend the use of the updated Diamond-Forrester (DF) method and Coronary Artery Disease (CAD) Consortium models to assess the pretest probability of obstructive CAD. The present study aimed to compare the performance of these models among patients with chest pain evaluated in an emergency department (ED). METHODS: We compared three scores (DF, CAD consortium basic, and clinical) among 1247 consecutive patients with chest pain who underwent coronary computed tomographic angiography (CTA). Invasive angiography was performed to confirm the stenosis for those who showed obstructive CAD on CTA, if clinically indicated. Primary outcome was the presence of obstructive CAD (≧50% stenosis). RESULTS: Overall, 426 (34.2%) patients were diagnosed with obstructive CAD. The expected prevalence of CAD was underestimated by the CAD consortium clinical model (23.4%) and overestimated by the DF model (53.1%). For the prediction of obstructive CAD, the CAD consortium clinical model had superior area under the receiver-operating curve (0.754), followed by the CAD consortium basic (0.736), and finally, the DF model (0.718). Whereas the CAD consortium models more accurately classified patients without any CAD or nonobstructive CAD as low-risk patients, the DF model more accurately classified high-risk patients with obstructive CAD. The net reclassification improvement of CAD consortium basic and clinical models were 24.7% and 27.9%, respectively. CONCLUSIONS: Compared with the DF model, the CAD consortium clinical model appears to improve the prediction of low-risk patients with <15% probability of having obstructive CAD. However, this model needs caution when using in high-risk population.
Authors: Antonio Esposito; Marco Francone; Daniele Andreini; Vitaliano Buffa; Filippo Cademartiri; Iacopo Carbone; Alberto Clemente; Andrea Igoren Guaricci; Marco Guglielmo; Ciro Indolfi; Ludovico La Grutta; Guido Ligabue; Carlo Liguori; Giuseppe Mercuro; Saima Mushtaq; Danilo Neglia; Anna Palmisano; Roberto Sciagrà; Sara Seitun; Davide Vignale; Gianluca Pontone; Nazario Carrabba Journal: Radiol Med Date: 2021-06-23 Impact factor: 3.469