Related Experiment Video
Updated: Jun 2, 2025
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
Identifying risk factors and constructing a predictive model for heart failure combined with intracardiac thrombus in
Peizhu Dang1, Haiyang Wang2, Xiaowei Huo1
1Department of Cardiovascular Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China.
Insights
This study developed a nomogram to predict cardiogenic composite endpoints (intracardiac thrombosis and heart failure) in non-compaction cardiomyopathy patients. The model, using diabetes mellitus, LVESD, and EF, shows good predictive value.
Area of Science:
- Cardiology
- Medical Prediction Models
Background:
- Non-compaction cardiomyopathy (NCM) is associated with significant cardiogenic risks.
- Predicting composite endpoints like intracardiac thrombosis (ICT) and heart failure (HF) in NCM patients is crucial for management.
Purpose of the Study:
- To develop and validate a nomogram prediction model for the cardiogenic composite endpoint (ICT + HF) in NCM patients.
- To identify independent predictors for this composite endpoint.
Main Methods:
- Retrospective analysis of clinical data from 976 NCM patients (Jan 2018 - May 2024).
- Data split into training and validation cohorts.
- Logistic regression used to identify predictors; nomogram developed and validated for accuracy and clinical utility.
Main Results:
- Diabetes mellitus (DM), left ventricular end-systolic diameter (LVESD), and ejection fraction (EF) were identified as independent predictors.
- The nomogram achieved an AUC of 0.747 (training) and 0.803 (validation).
- Good calibration and clinical utility demonstrated via calibration curves and decision curve analysis.
Conclusions:
- A validated nomogram effectively predicts the cardiogenic composite endpoint in NCM patients.
- The model provides robust clinical predictive value, aiding in risk stratification and management.
- Identified predictors (DM, LVESD, EF) offer insights into NCM-related cardiogenic risks.
Abstract:
This study aims to develop a nomogram prediction model for assessing the cardiogenic composite endpoint, which includes intracardiac thrombosis (ICT) combined with heart failure (HF) in patients with non-compaction cardiomyopathy (NCM) patients. We retrospectively analyzed clinical data from NCM patients (January 2018 to May 2024), who were randomly assigned to training and validation cohorts. Independent predictors were identified using logistic regression, and a nomogram model was developed. The model's discriminative ability, accuracy, and clinical applicability were subsequently validated. A total of 976 patients were included, of whom 54 had ICT and 191 had HF. Diabetes mellitus (DM), left ventricular end-systolic diameter (LVESD), and ejection fraction (EF) were identified as independent predictors for the composite endpoint. The nomogram demonstrated good performance, with an area under the curve (AUC) of 0.747 (95% CI: 0.707-0.787) in the training group and 0.803 (95% CI: 0.752-0.854) in the validation group. The calibration curve for the training group showed an average absolute error of 0.028, with a Hosmer-Lemeshow test P-value of 0.076. Decision curve analysis and clinical impact curves further indicated that the clinical net benefit was maximized at a threshold probability of 0.05-0.61. This study establishes and validates a nomogram for predicting cardiogenic composite endpoint in NVM patients, demonstrating robust clinical predictive value.
