Related Experiment Video
Updated: Jun 9, 2026
Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
Published on: October 28, 2020
A prediction model for left ventricular mass in patients at high cardiovascular risk
Matthijs F L Meijs1, Yvonne Vergouwe, Maarten J M Cramer
1Department of Cardiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, The Netherlands.
Insights
We developed a prediction model to identify high cardiovascular risk patients with large left ventricular (LV) mass. This tool aids in early detection and prevention of cardiovascular disease.
Area of Science:
- Cardiology
- Medical Imaging
- Predictive Analytics
Background:
- Left ventricular (LV) mass is linked to cardiovascular risk.
- Regression of LV mass improves prognosis.
- Early identification of large LV mass is crucial for risk stratification.
Purpose of the Study:
- To develop a predictive model for LV mass in hypertensive patients at high cardiovascular risk.
- To enable early identification of individuals with increased LV mass.
- To support clinical decision-making in cardiovascular disease prevention.
Main Methods:
- Analysis of data from 536 hypertensive patients with atherosclerotic disease or risk factors.
- LV mass measurement using cardiac MRI.
- Development of a prediction rule via multivariable linear regression and stepwise backward elimination.
- Internal validation using bootstrap sampling.
Main Results:
- Key predictors for LV mass included sex, height, BMI, systolic blood pressure, and prior abdominal aortic aneurysm.
- The prediction model achieved an R² of 45% after internal validation.
- This R² is significantly higher than previously reported models.
- Electrocardiography data offered minimal improvement (R²=47%).
Conclusions:
- A novel prediction model for LV mass in high-risk hypertensive patients has been developed.
- External validation is needed before clinical implementation.
- The model has the potential to aid in early LV mass estimation and cardiovascular disease prevention.
Background:
Left ventricular (LV) mass has a continuous relation with cardiovascular risk, and regression of LV mass induced by pharmacological treatment is associated with improved prognosis. Therefore, early identification of patients with a large LV mass is desired. We developed a model to predict LV mass in individual hypertensives at high cardiovascular risk.
Design And Methods:
We analyzed data of 536 hypertensives with symptomatic extracardiac atherosclerotic disease or marked risk factors for atherosclerosis from a cross-sectional study in a tertiary referral center. LV mass was measured by cardiac MRI. We developed the prediction rule with multivariable linear regression analysis and stepwise backward elimination. Internal validation was assessed with bootstrap sampling to obtain an estimate of model performance (R²) that may be expected for new patients.
Results:
Important predictors for LV mass included sex, height, body mass index, systolic blood pressure, and previous aneurysm of the abdominal aorta. R² of the prediction model was 45% after internal validation, which was considerably higher than the R² of previously reported models (range 1-38%). Addition of electrocardiography data showed limited improvement of the model performance (R²=47%).
Conclusion:
We present a prediction model for LV mass in hypertensives at high cardiovascular risk. After external validation, this model may be used in clinical practice to estimate LV mass for early identification of large LV mass. The predictions of the model may support appropriate medical care in the prevention of cardiovascular disease.
