Predicting Heart Failure After a Heart Attack
Official title: Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
Funded at Yale University · NIH-11122278 · Data updated 2026-11-12
This project uses computer models to understand why some people develop heart failure after a heart attack, helping us predict who might be at risk.
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 | 2025 |
| Award (this year) | $248,615 |
| NIH project number | 5R00HL161313-04 |
| Project ID | NIH-11122278 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients who have experienced a myocardial infarction (heart attack) and are at risk for developing heart failure might be ideal candidates for future applications of this research.
✕Less likely to help
Patients without a history of heart attack or those not at risk for heart failure would not directly benefit from this specific prediction tool.
What this research studies
A heart attack can sometimes lead to heart failure, which significantly impacts many lives. After a heart attack, your heart undergoes changes in its size, shape, and how it works, a process called remodeling. While some of these changes can be helpful in the short term, others can unfortunately lead to worsening heart function and eventually heart failure. Currently, it's hard to predict which patients will experience these harmful changes. Our team is developing advanced computer models, informed by detailed heart imaging like MRI, to better understand these complex changes at a very detailed level.
Why it matters
Potential benefit: If successful, this work could lead to earlier identification of patients at high risk for heart failure after a heart attack, allowing for more timely and effective preventative treatments.
How similar studies have gone: Computational models of heart biomechanics, informed by imaging, show high potential, but this specific approach combining cell-scale and organ-scale modeling with stability theory is novel.
Where this research is happening
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Yale University
New Haven, United States Active
Researchers
- Principal investigator: Pfaller, Martin R — Yale University
- Study coordinator: Pfaller, Martin R
Related research
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Predicting heart failure after a heart attack using computer models
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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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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.