Many models have been devised in the past to predict adverse outcomes after PCI, but with rapid advancements in this field, a new risk-prediction model may be needed. The purpose of our study was to identify the clinical and angiographic variables associated with adverse cardiac events after percutaneous coronary intervention (PCI) and to construct a simple bedside tool for risk stratification of PCI patients.

Using our institution's database, we analyzed data from 9,494 patients who underwent PCI between January 1, 1996, and December 31, 2002 (ie, during the bare-metal stent era). Predictors of major adverse cardiac events—death, myocardial infarction, stroke, and repeat revascularization by emergent coronary artery bypass grafting or PCI—were identified by multivariate logistic regression analysis using baseline clinical, angiographic, and procedural variables. A simple integer score was constructed by multiplying the β coefficient for each variable by a constant and rounding the result to the nearest integer. The score was validated in 5,545 patients who underwent PCI between January 1, 2003, and December 31, 2006 (ie, during the drug-eluting stent era).

Multivariate regression analysis identified emergent procedure, urgent procedure, unstable angina, acute myocardial infarction, renal insufficiency, hypertension, congestive heart failure, peripheral vascular disease, type C lesion, presence of thrombus, and number of stents placed as independent predictors of adverse events after PCI. The model had good overall discrimination (area under the receiver operator characteristic curve 0.701), and the model fitted the validation cohort adequately.

Risk of complications after PCI can be assessed with this simple tool, which may permit comparisons between different operators as well as different hospitals.