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Development and validation of a risk model for intracardiac thrombosis in patients with dilated cardiomyopathy: a
Yuan Huang1, Long-Chang Li2, Yu-Xin Li3,4,5
1Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Insights
A new nomogram helps assess intracardiac thrombosis risk in non-ischemic dilated cardiomyopathy patients. Key factors include d-dimer, WBC, CRP, and NT-proBNP, improving individualized risk evaluation.
Area of Science:
- Cardiology
- Thrombosis Research
- Medical Informatics
Background:
- Intracardiac thrombosis is a serious complication in non-ischemic dilated cardiomyopathy (NIDCM).
- Accurate risk stratification is crucial for timely intervention and improved patient outcomes.
- Existing risk assessment tools may not be sufficiently individualized for NIDCM patients.
Purpose of the Study:
- To develop and validate an individualized nomogram for predicting intracardiac thrombosis risk.
- To identify key clinical predictors of intracardiac thrombosis in NIDCM.
- To provide a clinically useful tool for risk assessment.
Main Methods:
- Retrospective study of 564 NIDCM patients.
- Multivariable logistic regression to identify risk factors.
- Nomogram construction and validation using bootstrapping and decision curve analysis.
Main Results:
- Identified d-dimer, white blood cell count, high-sensitivity C-reactive protein, pulse pressure, stroke history, hematocrit, and NT-proBNP as significant risk factors.
- The nomogram demonstrated good discrimination (AUC=0.833) and calibration.
- The model showed clinical utility across a wide range of risk thresholds.
Conclusions:
- A novel, validated nomogram effectively assesses intracardiac thrombosis risk in NIDCM patients.
- This tool facilitates individualized risk stratification and clinical decision-making.
- The nomogram integrates key biomarkers and clinical factors for enhanced predictive accuracy.
Abstract:
Intracardiac thrombosis is a severe complication in patients with non-ischemic dilated cardiomyopathy. This study aims to develop and validate an individualized nomogram to evaluate the risk of intracardiac thrombosis in patients with non-ischemic dilated cardiomyopathy. This retrospective study included patients diagnosed with dilated cardiomyopathy at first admission. Clinical baseline characteristics were acquired from electronic medical record systems. Multiple methods were applied to screen the key variables and generate multiple different variable combinations. Multivariable logistic regression was used to build the models, and the optimal model was chosen by comparing the discrimination. Then we checked the performance of the model in different thrombus subgroups. Finally, the model was presented using a nomogram and evaluated from the perspectives of discrimination, calibration, and clinical usefulness. Internal validation was performed by extracting different proportions of data for Bootstrapping. Ultimately, 564 eligible patients were enrolled, 67 of whom developed an intracardiac thrombosis. Risk factors included d-dimer, white blood cell count, high-sensitivity C-reactive protein, pulse pressure, history of stroke, hematocrit, and NT-proBNP in the optimal model. The model had good discrimination and calibration, and the area under the curve (AUC) was 0.833 (0.782-0.884), and the model's performance in each subgroup was stable. Clinical decision curve analysis showed that the model had clinical application value when the high-risk threshold was between 2% and 78%. The AUC of interval validation (30% and 70% data resampling) was 0.844 (0.765-0.924) and 0.833 (0.775-0.891), respectively. This novel intracardiac thrombosis nomogram could be conveniently applied to facilitate the individual intracardiac thrombosis risk assessment in patients with non-ischemic dilated cardiomyopathy.
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