Simple risk algorithm to predict serious bleeding in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention - RISK-PCI bleeding score

Abstract

Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI. Methods and Results: The training set included 2,096 patients enrolled in the RISK-PCI trial. The model was validated using a database of 961 patients enrolled in the ART-PCI trial. Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition. Multivariate logistic regression was used to evaluate the predictors of outcome. A sum of weighted points for specific predictors was calculated to determine the final score. The model included 5 independent predictors of 30-day bleeding: gender (female); history of peptic ulcer; creatinine clearance at admission (<60ml/min); hemoglobin at presentation (<125g/dl); and Killip class >1 heart failure at admission. The model showed good discrimination and calibration for the prediction of bleeding in the derivation set (C-statistic, 0.79; goodness of fit, P=0.12) and in the validation set (C-statistic, 0.76; goodness of fit, P=0.37). Patients were classified into 3 risk classes and the observed incidence of 30-day bleeding of 1.0%, 3.5% and 10.7% corresponded to the low-, intermediate- and high-risk classes, respectively. Conclusions: A simple risk model was developed that has a reasonably good capacity for the prediction of 30-day bleeding after PPCI.