A simple prognostic classification model for postprocedural complications after percutaneous coronary intervention for acute myocardial infarction (from the New York State percutaneous coronary intervention database).

摘要

Previous postprocedural complications risk scores have shown very good performance. However, the need for real-time risk score computation makes their implementation in an emergency situation challenging. Therefore, we developed an easy-to-use prognostic classification model for postprocedural complications after early percutaneous coronary intervention for acute myocardial infarction. The model was developed on the New York State percutaneous coronary intervention database for 1999 to 2000 (consisting of 5,385 procedures) and was validated using the subsequent 2001 to 2002 database (consisting of 7,414 procedures). Tree-structured prognostic classification identified 4 key presenting features: cardiogenic shock, congestive heart failure, age, and diabetes. In the validation database, the model identified patient groups with postprocedural complications rates ranging from 1.0% to 22.8%, >22-fold increased risk. The performance of this model was similar to the Mayo Clinic and another recently published risk scores with a discrimination capacity of 78% (95% confidence interval, 75%, 80%). In conclusion, patients undergoing percutaneous coronary intervention for acute myocardial infarction can be readily stratified into distinct prognostic classes using the tree-structured model.