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Development and Validation of a Mortality Prediction Model for Left Ventricular Thrombus
Song Lei1,2, Chenyu Yu1, Li Li3
1Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China.
Pacing and Clinical Electrophysiology : PACE
|August 8, 2025
Summary
A new model predicts mortality in patients with left ventricular thrombus (LVT), identifying key risk factors like high BNP and tumors. This tool aids in assessing risk and optimizing treatment for LVT complications.
Area of Science:
- Cardiology
- Internal Medicine
- Medical Informatics
Background:
- Left ventricular thrombus (LVT) is a serious complication associated with significant risks of systemic embolism and mortality.
- Current anticoagulant therapies have limitations, and optimal management strategies for LVT patients remain unclear.
- Accurate risk stratification is crucial for guiding clinical decisions and improving outcomes in LVT patients.
Purpose of the Study:
- To develop and validate a predictive model for assessing all-cause mortality risk in patients diagnosed with left ventricular thrombus.
- To identify independent predictors of mortality in LVT patients to inform clinical management.
- To provide a tool for risk assessment and treatment optimization in LVT patient populations.
Main Methods:
- Retrospective cohort study of 459 LVT patients diagnosed between June 2018 and June 2023.
- Patients were randomly divided into training (n=322) and validation (n=137) sets.
- Logistic regression analysis was used to identify independent predictors and construct a nomogram-based risk prediction model.
Main Results:
- The developed nomogram model demonstrated good predictive performance with an AUC of 0.846 in the training set and 0.791 in the validation set.
- Key independent predictors of mortality included elevated B-type natriuretic peptide (BNP), lower albumin levels, absence of antithrombotic therapy, and presence of malignant tumors.
- Elevated BNP (OR 3.359) and malignant tumors (OR 6.199) were associated with increased mortality risk, while antithrombotic therapy (OR 0.468) and higher albumin levels (OR 0.930) were protective.
Conclusions:
- A novel, validated nomogram-based model effectively predicts all-cause mortality in left ventricular thrombus patients.
- The model identifies critical risk factors, enabling better risk stratification and personalized treatment strategies.
- This tool is particularly valuable for risk assessment and treatment optimization in Asian populations, especially in China, though further external validation is warranted.
