Comparison of Coronary Artery Disease Consortium 1 and 2 Scores and Duke Clinical Score to Predict Obstructive Coronary Disease by Invasive Coronary Angiography

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Almeida, J (Author) Other; Fonseca, P (Author) Other; Dias, T (Author) Other; Ladeiras-Lopes R (Author) FMUP; Bettencourt, N (Author) FMUP; Ribeiro, J (Author) Other; Gama, V (Author) Other

Journal

Title: Clinical Cardiology

Vol. 39

Pages: 223-228

ISSN: 0160-9289

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 16 Citations

Other information

Authenticus ID: P-00K-ED1

DOI: 10.1002/clc.22515

Abstract (EN): BackgroundThe 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. HypothesisUsing scores that include modifiable risk factors (DCS and CAD2) enhances prediction of CAD. MethodsWe 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. ResultsMean 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. ConclusionsPrediction 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6