A risk score to predict in-hospital mortality for percutaneous coronary interventions

OBJECTIVES Our purpose was to develop a risk score to predict in-hospital mortality for percutaneous coronary intervention (PCI) using a statewide population-based PCI registry. BACKGROUND Risk scores predicting adverse outcomes after PCI have been developed from a single or a small group of hospitals, and their abilities to be generalized to other patient populations might be affected. METHODS A logistic regression model was developed to predict in-hospital mortality for PCI using data from 46,090 procedures performed in 41 hospitals in the New York State Percutaneous Coronary Intervention Reporting System in 2002. A risk score was derived from this model and was validated using 2003 data from New York. RESULTS The risk score included nine significant risk factors (age, gender, hemodynamic state, ejection fraction, pre-procedural myocardial infarction, peripheral arterial disease, congestive heart disease, renal failure, and left main disease) that were consistent with other reports. The point values for risk factors range from 1 to 9, and the total risk score ranges from 0 to 40. The observed and recalibrated predicted risks in 2003 were highly correlated for all PCI patients as well as for those in the higher-risk subgroup who suffered myocardial infarctions within 24 h before the procedure. The total risk score for mortality is strongly associated with complication rates and length of stay in the 2003 PCI data. CONCLUSIONS The risk score accurately predicted in-hospital death for PCI procedures using future New York data. Its performance in other patient populations needs to be further studied.