Goliasch_2012_Eur.Heart.J_33_2282

Aims Previous risk assessment scores for patients with coronary artery disease CAD have focused on primary prevention and patients with acute coronary syndrome However especially in stable CAD patients improved long-term risk prediction is crucial to efficiently apply measures of secondary prevention We aimed to create a clinically applicable mortality prediction score for stable CAD patients based on routinely determined laboratory biomarkers and clinical determinants of secondary prevention Methods and results We prospectively included 547 patients with stable CAD and a median follow-up of 11.3 years Independent risk factors were selected using bootstrapping based on Cox regression analysis Age left ventricular function serum cholinesterase creatinine heart rate and HbA1c were selected as significant mortality predictors for the final multivariable model The Vienna and Ludwigshafen Coronary Artery Disease VILCAD risk score based on the aforementioned variables demonstrated an excellent discriminatory power for 10-year survival with a C-statistic of 0.77 P 0.001 which was significantly better than an established risk score based on conventional cardiovascular risk factors C-statistic 0.61 P 0.001 Net reclassification confirmed a significant improvement in individual risk prediction by 34.8 95 confidence interval 21.7-48.0 compared with the conventional risk score P 0.001 External validation of the risk score in 1275 participants of the Ludwigshafen Risk and Cardiovascular Health study median follow-up of 9.8 years achieved similar results C-statistic 0.73 P 0.001 Conclusion The VILCAD score based on a routinely available set of risk factors measures of cardiac function and comorbidities outperforms established risk prediction algorithms and might improve the identification of high-risk patients for a more intensive treatment.