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.