Predicting heart failure after a heart attack using computer models
Official title: Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
Funded at Yale University · NIH-11103557 · Data updated 2026-11-12
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 start | July 1, 2024 |
| Project end | June 30, 2027 |
| Funding year | 2024 |
| Award (this year) | $249,000 |
| NIH project number | 4R00HL161313-03 |
| Project ID | NIH-11103557 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have recently experienced a myocardial infarction.
✕Less likely to help
Patients who have not had a heart attack or those with pre-existing heart failure may not benefit from this research.
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.
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 gone: 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
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Pfaller, Martin R — Yale University
- Study coordinator: Pfaller, Martin R
Related research
Other NIH-funded projects on the same topics.
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Predicting Heart Failure Risk After a Heart Attack with Computer Models
A patient-focused look at how advanced computer models of the heart, built from MRI scans, could predict who might develop heart failure after a heart attack.
-
Predicting Heart Failure After a Heart Attack
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AI-supported heart failure diagnosis and management in Rwanda
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An NIH-funded project will test whether AI-enhanced, easy-to-use heart ultrasound can help non-experts diagnose and manage heart failure in Rwanda.
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HF endotypes in heart failure using ethical multi-modal AI and molecular data
A patient-friendly project that uses advanced AI and multiple kinds of health data to identify distinct heart failure subtypes that could guide personalized care.
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A new therapy combines three genetic approaches delivered by a virus to help the heart heal after a heart attack.
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.