Relationship Between Cardiometabolic Index and Post-PCI Coronary Microvascular Dysfunction in Acute STEMI Patients.

Background: Coronary microvascular dysfunction (CMD) significantly impacts outcomes in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI). The cardiometabolic index (CMI), an indicator combining lipid and anthropometric parameters, has been linked to cardiovascular risk, but its association with CMD remains unclear. This study aims to investigate the relationship between CMI and the occurrence of CMD following PCI in STEMI patients and to assess its predictive value using Least Absolute Shrinkage and Selection Operator (LASSO)-based feature selection and multiple machine learning algorithms. Methods: This retrospective cohort study enrolled STEMI patients who underwent primary PCI with stent implantation and post-procedural coronary microvascular function assessment between January 2021 and December 2024. Patients were categorized into CMD and non-CMD groups based on noninvasive microvascular resistance indices. Logistic regression, restricted cubic spline analysis, and machine learning models (Random Forest (RF), LightGBM, XGboost and K-Nearest Neighbors) were employed to evaluate the predictive value of CMI for post-PCI CMD. Results: A total of 702 STEMI patients were included, and CMD was observed in 52.1% of patients. Compared to the first CMI tertile (T1) group, T2 and T3 group had increased odds of CMD (T2: adjusted odds ratio (aOR) 2.41, 95% confidence interval (CI) 1.60-3.63; T3: aOR 3.40, 95% CI 2.17-5.32). There was a non-linear relationship between CMI and CMD ( Conclusion: A higher CMI level is an independent risk factor for CMD of STEMI patients after PCI, and its predictive value enhanced when integrated into RF model.