학술논문
Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.
Document Type
article
Author
Mohamed, Mahmoud; Bosserdt, Maria; Wieske, Viktoria; Dubourg, Benjamin; Alkadhi, Hatem; Garcia, Mario; Leschka, Sebastian; Zimmermann, Elke; Shabestari, Abbas; Nørgaard, Bjarne; Meijs, Matthijs; Øvrehus, Kristian; Diederichsen, Axel; Knuuti, Juhani; Halvorsen, Bjørn; Mendoza-Rodriguez, Vladymir; Wan, Yung-Liang; Bettencourt, Nuno; Martuscelli, Eugenio; Buechel, Ronny; Mickley, Hans; Sun, Kai; Muraglia, Simone; Kaufmann, Philipp; Herzog, Bernhard; Tardif, Jean-Claude; Schütz, Georg; Laule, Michael; Newby, David; Achenbach, Stephan; Haase, Robert; Biavati, Federico; Mézquita, Aldo; Schlattmann, Peter; Dewey, Marc; Budoff, Matthew
Source
European Radiology. 34(4)
Subject
Language
Abstract
OBJECTIVES: Coronary computed tomography angiography (CCTA) has higher diagnostic accuracy than coronary artery calcium (CAC) score for detecting obstructive coronary artery disease (CAD) in patients with stable chest pain, while the added diagnostic value of combining CCTA with CAC is unknown. We investigated whether combining coronary CCTA with CAC score can improve the diagnosis of obstructive CAD compared with CCTA alone. METHODS: A total of 2315 patients (858 women, 37%) aged 61.1 ± 10.2 from 29 original studies were included to build two CAD prediction models based on either CCTA alone or CCTA combined with the CAC score. CAD was defined as at least 50% coronary diameter stenosis on invasive coronary angiography. Models were built by using generalized linear mixed-effects models with a random intercept set for the original study. The two CAD prediction models were compared by the likelihood ratio test, while their diagnostic performance was compared using the area under the receiver-operating-characteristic curve (AUC). Net benefit (benefit of true positive versus harm of false positive) was assessed by decision curve analysis. RESULTS: CAD prevalence was 43.5% (1007/2315). Combining CCTA with CAC improved CAD diagnosis compared with CCTA alone (AUC: 87% [95% CI: 86 to 89%] vs. 80% [95% CI: 78 to 82%]; p