A New Nomogram Prediction Model for Left Ventricular Thrombus in Patients with Left Ventricular Aneurysm after Acute Myocardial Infarction

Background: To identify the factors influencing the development of a left ventricular thrombus (LVT) in patients with a left ventricular aneurysm (LVA) after acute myocardial infarction (AMI) and to utilize these variables to establish a new nomogram prediction model for individual assessment in LVT. Methods: We screened data on 1268 cases of LVA at the China-Japan Union Hospital of Jilin University between January 1, 2018 and December 31, 2023, and identified a total of 163 LVAs after AMI. The independent risk factors of LVT in patients with LVA after AMI were identified from univariable and multivariable logistic regression analyses and a nomogram prediction model of LVT was established with independent risk factors as predictors. We used the area under the curve (AUC) and a calibration curve to determine the predictive accuracy and discriminability of nomograms. Furthermore, decision curve analysis (DCA) was utilized to further validate the clinical effectiveness of the nomogram. Results: Multivariate logistic regression analysis identified that preoperative thrombus in myocardial infarction 0, left ventricular diameter, and anterior wall myocardial infarction were independent risk factors of LVT in patients with LVA after AMI (p < 0.05). The nomogram prediction model constructed using these variables demonstrates exceptional performance, as evidenced by well-calibrated plots, favorable results from DCA, and the AUC of receiver operating characteristic (ROC) analysis was 0.792 (95% CI: 0.710-0.874, p < 0.01). Conclusions: A new nomogram prediction model was developed to enable precise estimation of the probability of LVT in patients with LVA after AMI, thereby facilitating personalized clinical decision-making for future practice.