Identifying patients with refusal of percutaneous coronary intervention for acute myocardial infarction: a classification and regression tree analysis

AbstractThe purpose of the present study is to develop and validate a prediction tool to identify patients who refuse to receive percutaneous coronary intervention (PCI) rapidly. We developed a risk stratification model using the derivation cohort of 288 patients with ST segment elevation myocardial infarction (STEMI) in our hospital and validated it in a prospective cohort of 115 patients. There were 52 (18.1%) patients and 18 (15.7%) patients who refused PCI among derivation and validation cohort, respectively. A classification and regression tree (CART) analysis and multivariate logistic regression were used for statistical analysis. The decision-making factors for refusal of PCI were also investigated. The CART analysis and logistic regression both showed that self-rated mild symptom was the most significant predictor of not choosing PCI. The model generated three risk groups. The high-risk group included: self-rated mild symptoms; self-rated severe symptom, glomerular filtration rate  <  60 ml/min/1.73m2. The intermediate-risk group included: self-rated severe symptom, glomerular filtration rate  ≥ 60 ml/min/1.73m2 and age  ≥ 75 years. The low-risk group included: self-rated severe symptom, glomerular filtration rate ≥ 60 ml/min/1.73m2 and age  <  75 years. The prevalence for refusal of PCI of the three groups were 45%–44%, 18% and 4%, respectively. The sensitivity was 88% and the negative predictive value was 96%. And similar results were ob...
Source: Internal and Emergency Medicine - Category: Emergency Medicine Source Type: research