Xu Yuanzhen, Zhang Zhongfan, Si Daoyuan, Zhang Qian, Zhang Wenqi
Department 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.
Rev Cardiovasc Med. 2024 Oct 23;25(10):377. doi: 10.31083/j.rcm2510377. eCollection 2024 Oct.
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.
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.
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 ( < 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, < 0.01).
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.
确定急性心肌梗死（AMI）后左心室室壁瘤（LVA）患者左心室血栓（LVT）形成的影响因素，并利用这些变量建立一个新的列线图预测模型，用于LVT的个体评估。
我们筛选了2018年1月1日至2023年12月31日期间吉林大学中日联谊医院1268例LVA患者的数据，共确定了163例AMI后的LVA。通过单变量和多变量逻辑回归分析确定AMI后LVA患者LVT的独立危险因素，并以独立危险因素为预测指标建立LVT的列线图预测模型。我们使用曲线下面积（AUC）和校准曲线来确定列线图的预测准确性和辨别力。此外，采用决策曲线分析（DCA）进一步验证列线图的临床有效性。
多变量逻辑回归分析确定，心肌梗死0期术前血栓、左心室直径和前壁心肌梗死是AMI后LVA患者LVT的独立危险因素（<0.05）。使用这些变量构建的列线图预测模型表现出色，校准图良好、DCA结果良好以及受试者操作特征（ROC）分析的AUC为0.792（95%CI：0.710-0.874，<0.01）均证明了这一点。
开发了一种新的列线图预测模型，能够精确估计AMI后LVA患者发生LVT的概率，从而为未来的临床实践提供个性化决策依据。
