Establishment and validation of a nomogram model containing a triglyceride-glucose index and neutrophil-to-high-density lipoprotein ratio for predicting major adverse cardiac events in patients with ST-segment elevation myocardial infarction.

Abstract

To analyze the predictive value of the triglyceride-glucose (TyG) index and neutrophil-to-high-density lipoprotein ratio (NHR) for in-hospital major adverse cardiac events (MACE) after percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI), and to establish an associated nomogram model. In this retrospective study, we collected data from consecutive STEMI patients who underwent PCI from October 2019 to June 2023 at the Second People's Hospital of Hefei and the Second Affiliated Hospital of Anhui Medical University, as training and validation sets. Stepwise regression and multivariate logistic regression analysis were performed to screen independent risk factors, and a nomogram model was constructed and evaluated for its predictive efficacy. The TyG index, NHR, urea, diastolic blood pressure, hypertension, and left ventricular ejection fraction were independent risk factors for in-hospital MACE after PCI, and were used to construct the nomogram model. The C-index of the training and validation sets were 0.799 and 0.753, respectively, suggesting that the model discriminated well. Calibration and clinical decision curves also demonstrated that the nomogram model had good predictive power. In STEMI patients, increased TyG index and NHR were closely related to the occurrence of in-hospital MACE after PCI. Our constructed nomogram model has some value for predicting the occurrence of in-hospital MACE in STEMI patients.