Predicting long-term outcomes after primary PCI in Acute ST-segment elevation myocardial infarction patients with single-vessel disease

Abstract

Abstract Background This study aimed to develop a predictive nomogram for long-term outcomes in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI) for single-vessel disease, integrating the cholesterol-to-lymphocyte ratio (CLR) index with clinical data.Methods From April 2016 to December 2021, 1264 patients with acute STEMI were enrolled. They were divided into development (949 patients) and validation (315 patients) cohorts. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified potential risk factors, and multivariate Cox regression determined independent risk factors for the nomogram. The model was transformed into a web-based calculator for ease of use. Its performance was evaluated using ROC curve analysis, calibration curves,and C-index. In addition, individual risk assessment based on the model is conducted.Results The nomogram included age, diabetes, heart rate, and CLR index as variables. In the development cohort, ROC analysis yielded AUCs of 0.816, 0.812, and 0.751 for predicting major adverse cardiac events (MACEs) at 2, 3, and 4 years, respectively. In the validation cohort, the AUCs were 0.852, 0.773, and 0.806. The C-index was 0.76 in the development cohort and 0.79 in the validation cohort. Kaplan-Meier analysis indicated a higher likelihood of MACEs in the high-risk group.Conclusions This predictive model, incorporating CLR index and electronic health record (EHR) data, reliably and accurately forecasts adverse cardiac events post-primary PCI in patients with acute STEMI and single-vessel disease, aiding in improved risk stratification and management.