• A Peer, G Falkensammer, H Alber, A Kroiss, A Griesmacher, H Ulmer, O Pachinger, and J Mair.
• Universitaetsklinik für Innere Medizin III-Kardiologie, Innsbruck Medical University, Anichstrasse 35, Innsbruck, Austria.
• Heart. 2009 Feb 1;95(4):297-303.

ObjectiveTo investigate the usefulness of N-terminal pro-brain natriuretic peptide (NT-proBNP) as a predictive marker for angiographically significant coronary artery disease (CAD) and CAD severity compared with other newer biochemical risk markers and classic risk factors in patients with clinically suspected CAD.DesignCross-sectional evaluation of NT-proBNP in a large consecutive series of patients without a history of myocardial infarction referred for elective coronary angiography (CAG) between March 2004 and January 2005. The value of NT-proBNP for predicting CAD was assessed and compared with high sensitivity C-reactive protein (hs-CRP), gamma-glutamyltransferase (GGT) and traditional risk factors.SettingTertiary care centre, Department of Cardiology, Innsbruck Medical University, Austria.Patients561 men and 287 women aged between 20-86 years (median 65 years).InterventionsNone.Main Outcome MeasuresAssociation of NT-proBNP with the severity of CAD, left ventricular dysfunction and comparison of predictive values of NT-proBNP, hs-CRP, GGT and traditional CAD risk factors.ResultsOf all tested newer biochemical risk markers NT-proBNP performed best. In a multinomial logistic regression model NT-proBNP but not hs-CRP or GGT was significantly associated with three-vessel CAD adjusted for age, sex, ventricular, renal function and classic risk factors (odds ratio = 1.667; 95% CI 1.003 to 2.772; p = 0.049). However, NT-proBNP had no additive predictive value to traditional cardiovascular risk factors for the prediction of angiographically significant CAD in a binary logistic regression model.ConclusionsThe predictive value of NT-proBNP for CAD severity is better than that of hs-CRP or GGT. However, NT-proBNP is also of limited value compared with traditional risk factors for predicting significant CAD.

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