Comparison of Coronary Artery Disease Consortium 1 and 2 Scores and Duke Clinical Score to Predict Obstructive Coronary Disease by Invasive Coronary Angiography. Issue 4 (5th February 2016)

• Record Type: Journal Article
• Authors: Almeida, João; Fonseca, Paulo; Dias, Tiago; Ladeiras‐Lopes, Ricardo; Bettencourt, Nuno; Ribeiro, José; Gama, Vasco
• Is Part Of: Clinical cardiology. Volume 39:Issue 4(2016)
• Page Start: 223
• Page End: 228
• Publication Date: 2016-02-05
• Subjects: Cardiology -- Periodicals; 616.12005
• DOI: 10.1002/clc.22515
• Languages: English
• ISSNs: 0160-9289

Abstract

ABSTRACT: Background: The first step in evaluating a patient with suspected stable coronary artery disease (CAD) is the determination of the pretest probability. The European Society of Cardiology guidelines recommend the use of the CAD Consortium 1 score (CAD1), which contrary to CAD Consortium 2 (CAD2) score and Duke Clinical Score (DCS), does not include modifiable cardiovascular risk factors. Hypothesis: Using scores that include modifiable risk factors (DCS and CAD2) enhances prediction of CAD. Methods: We retrospectively included all patients referred to invasive coronary angiography for suspected CAD from January/2008–December/2012 (N = 2234). Pretest probability was calculated using 3 models (CAD1, DCS, and CAD2), and they were compared using the net reclassification improvement. Results: Mean patient age was 63.7 years, 67.5% were male, and the majority (66.9%) had typical angina. Coronary artery disease was diagnosed in 58.5%, and the area under the curve was 0.685 for DCS, 0.664 for CAD1, and 0.683 for CAD2, with a statistically significant difference between CAD1 and the others ( P < 0.001). The net reclassification improvement was 20% for DCS, related to adequate reclassification of 32% of patients with CAD to a higher risk category, and 5% for CAD2, at the cost of adequate reclassification of 34% of patients without CAD to a lower risk category. Conclusions: Prediction of CAD using scores that include modifiable cardiovascular risk factors seems to improve accuracy. Our results suggest that, in high‐prevalence populations, DCS may better identify patients at higher risk and CAD2 those at lower risk for CAD.