Establishment and evaluation of predictive model for acute heart failure after PCI in patients with STEMI

Objective: To establish a predictive model for acute heart failure (AHF) occurrence in patients with ST-segment elevation myocardial infarction (STEMI) following percutaneous coronary intervention (PCI) and evaluate its clinical performance. Methods: = 319) based on AHF occurrence. Logistic regression analysis identified independent risk factors for model construction. Model performance was assessed using receiver operating characteristic (ROC) curves with optimal threshold determination via maximum Youden index. Statistical validation included Omnibus and Hosmer-Lemeshow tests. Results: < 0.0001). Clinical decision curve analysis demonstrated net clinical benefit when threshold probability ranged from 0.1 to 0.99. Conclusion: Systolic blood pressure, total bilirubin, LVEF, neutrophils, and urea nitrogen are independent factors affecting AHF occurrence after PCI in STEMI patients. This exploratory predictive model demonstrates potential for assessing AHF risk in STEMI patients following PCI and may provide valuable clinical decision support for risk stratification and patient management. However, external validation in independent, multicenter populations is essential before clinical implementation.