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Development of a risk prediction model for left ventricular thrombosis in STEMI patients
Jingjing Wang1, Ping Ma2, QingBin Xu2
1Department of Critical Care Medicine, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, Yinchuan, China.
Insights
This study developed a risk model to predict left ventricular thrombus (LVT) in patients with ST-segment elevation myocardial infarction (STEMI). The model uses seven clinical factors to identify high-risk individuals, aiding in early intervention.
Area of Science:
- Cardiology
- Medical Diagnostics
- Predictive Modeling
Background:
- Left ventricular thrombus (LVT) is a serious complication of ST-segment elevation myocardial infarction (STEMI).
- Accurate risk stratification is crucial for timely intervention and improved patient outcomes.
- Existing models may not fully capture the complex factors contributing to LVT formation in STEMI patients.
Purpose of the Study:
- To develop and validate a robust risk prediction model for LVT formation in patients experiencing acute STEMI.
- To identify key clinical variables associated with LVT development in this patient population.
- To create a practical tool for clinicians to stratify LVT risk.
Main Methods:
- Retrospective analysis of STEMI patients (October 2017-October 2020) categorized into LVT (n=50) and no-LVT (n=130) groups based on echocardiography.
- Logistic regression analyses (single-factor, Lasso, multi-factor) to identify risk factors.
- Development of a nomogram-based risk prediction model with internal validation using cross-validation, k-fold, leave-one-out, and bootstrap methods.
Main Results:
- A multivariate logistic regression model identified seven independent predictors of LVT: MCV, D-dimer, CRP, LVEF, A wave velocity, pericardial effusion, and anterior wall infarction.
- The model demonstrated strong predictive performance with a C-index of 0.966 and an Area Under the ROC Curve (AUC) of 96.6% (internal validation).
- Model accuracy ranged from 0.899 to 0.926 across different validation techniques.
Conclusions:
- MCV, D-dimer, CRP, LVEF, A wave velocity, pericardial effusion, and anterior wall infarction are significant independent predictors of LVT in acute STEMI.
- The developed risk prediction model exhibits excellent discrimination and calibration, suitable for preliminary risk stratification of LVT in STEMI patients.
- The nomogram provides a user-friendly visualization for assessing individual patient risk.
Purpose:
To develop a risk prediction model for left ventricular thrombus (LVT) formation in patients with acute ST-segment elevation myocardial infarction (STEMI).
Patients And Methods:
We performed a retrospective analysis of patients with STEMI in our hospital between October 2017 to October 2020. According to transthoracic echocardiography, these patients were included in the LVT group (n = 50) or no-LVT group (n = 130). Clinical data were collected from both groups. The comparison between groups, single-factor logistic regression analysis, Lasso regression analysis and multi-factor logistic regression analysis were performed successively to screen the risk factors and to establish risk prediction models. After evaluation and internal verification, we obtained an optimal risk prediction model. A nomogram was constructed to visualize the optimal model.
Results:
The risk prediction model contained seven variables including MCV (OR = 1.251, 95% CI = 1.021-1.531, P = 0.030), D-Dimer (OR = 9.798, 95% CI = 2.630-36.503, P = 0.001), CRP (OR = 1.033, 95% CI = 1.011-1.055, P = 0.003), LVEF (OR = 0.903, 95% CI = 0.819-0.995, P = 0.040), A wave velocity (OR = 0.044, 95% CI = 0.002-0.906, P = 0.043), pericardial effusion (OR = 16.926, 95% CI = 2.767-103.522, P = 0.002) and anterior wall infarction (OR = 12.275, 95% CI = 2.136-70.548, P = 0.005). The C-index value was 0.966 and the area under the ROC curve was 96.6% (95% CI = 0.9399-0.9914). Simple cross-validation, k-fold, leave-one-out, and bootstrap analyses were used to internally verify the model. The accuracy of the model were 0.926, 0.9, 0.9, and 0.899, and Kappa values were 0.807, 0.744, 0.744, and 0.739. The area under the ROC curve was 94.7%, as verified by bootstrapping.
Conclusion:
MCV, D-dimer level, CRP level, LVEF, A-wave velocity, pericardial effusion, and anterior wall infarction were independently related to the occurrence of LVT in STEMI at the acute stage. The multivariate logistic regression risk prediction model developed in this study demonstrates good discrimination and calibration, enabling preliminary risk stratification for LVT in patients with acute STEMI.
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