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A New Nomogram Prediction Model for Left Ventricular Thrombus in Patients with Left Ventricular Aneurysm after Acute
Yuanzhen Xu1, Zhongfan Zhang1, Daoyuan Si1
1Department of Cardiology, China-Japan Union Hospital of Jilin University, Jilin Provincial Molecular Biology Research Center for Precision Medicine of Major Cardiovascular Disease, 130033 Changchun, Jilin, China.
Insights
This study identified key factors for left ventricular thrombus (LVT) development in patients with left ventricular aneurysm (LVA) post-myocardial infarction. A new nomogram model accurately predicts LVT risk, aiding personalized patient care.
Area of Science:
- Cardiology
- Medical Diagnostics
- Predictive Modeling
Background:
- Left ventricular aneurysm (LVA) following acute myocardial infarction (AMI) increases the risk of left ventricular thrombus (LVT) formation.
- Identifying LVT risk factors is crucial for preventing adverse cardiovascular events.
Purpose of the Study:
- To determine factors influencing LVT development in LVA patients post-AMI.
- To develop a predictive nomogram model for individualized LVT risk assessment.
Main Methods:
- Retrospective analysis of 163 LVA patients post-AMI.
- Logistic regression to identify independent risk factors for LVT.
- Nomogram construction and validation using AUC, calibration curves, and DCA.
Main Results:
- Preoperative thrombus, left ventricular diameter, and anterior wall myocardial infarction were identified as independent LVT risk factors.
- The developed nomogram showed good discriminative ability (AUC=0.792) and calibration.
- Decision curve analysis confirmed the clinical utility of the nomogram.
Conclusions:
- A novel nomogram model accurately predicts LVT probability in LVA patients post-AMI.
- This tool supports personalized clinical decision-making and risk stratification.
- The model can aid in optimizing management strategies for these high-risk patients.
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.
