Predicting heart failure after a heart attack using computer models
Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
This study looks at how having a heart attack can affect your heart's shape and function, helping us figure out who might be at risk of heart failure afterward, using both computer models and real-life tests on people and animals.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-11103557 on NIH RePORTER |
What this research studies
This research investigates how heart attacks can lead to heart failure by analyzing the changes in heart structure and function that occur afterward. It uses advanced computer models to simulate the heart's biomechanics and growth patterns, informed by detailed imaging techniques. By understanding these changes, the research aims to identify patients at risk of developing heart failure after a heart attack. The approach involves both animal and human studies to validate the predictions made by the models.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals who have recently experienced a myocardial infarction.
Not a fit: Patients who have not had a heart attack or those with pre-existing heart failure may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to better predictions and interventions for patients at risk of heart failure after a heart attack.
How similar studies have performed: Other research has shown promise in using computational models to predict cardiac outcomes, suggesting that this approach could be effective.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Pfaller, Martin R — Yale University
- Study coordinator: Pfaller, Martin R
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.