Risk Prediction Tool for Assessing the Probability of Death or Myocardial Infarction in Patients With Stable Coronary Artery Disease. The American journal of cardiology Boden, W. E., Hartigan, P. M., Mancini, J., Teo, K. K., Chaitman, B. R., Maron, D. J., Kostuk, W. J., Hartigan, J. A., Dada, M., Spertus, J. A., Bates, E. R., Weintraub, W. S., COURAGE Trial Investigators 2020


Several risk scores in acute coronary syndromes are available, but few models exist for stable coronary artery disease to guide decision-making and prognosis. A multivariate model was developed using 23 baseline candidate variables from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Therapy EvaluationTrial (n?=?2,287 patients). Discrimination of the model was evaluated by the concordance c-index. The procedure was validated using 100 random half samples. We identified 9 independent predictors of death or myocardial infarction (MI) during a 5-year follow-up. The following predictors and points contributing to the risk score were: heart failure (3), number of diseased coronary arteries (1 for each vessel), diabetes (1), age (1 for each 15 years = age 45), previous revascularization (1), current smoking (1), female (1), previous MI (1), and high-density lipoprotein cholesterol (1: 31 to 40 mg/dL; 2: <30 mg/dL). The risk tool had a potential range from 0 to 15, corresponding to 5-year event rates of 5.8% to 56%. C-indices ranged from 0.67 for the full data set to 0.62 for the validating subsamples. Respective observed versus predicted 5-year event rates for 3 predefined risk strata revealed: 30% had a low-risk score of 0 to 3 (9.3% vs 9.3%, or 1.9%/year); 59% had an intermediate-risk score of 4-6 (18.0% vs 18.1%, or 3.6%/year); and 11% had a high-risk score of 7-11 (36% vs 36.5%, or 7.2%/year). This stable coronary artery disease risk score permitted a prognostic assessment of 5-year probability of death or MI with an approximate 4-fold range in event rates from the lowest (9.3%) to the highest (36%) terciles, thus enabling better clinical practice decisions that allow physicians to tailor the intensity of treatment to the level of risk.

View details for DOI 10.1016/j.amjcard.2020.05.046

View details for PubMedID 32654755