Using ECGs to find hidden heart attacks in people with chest pain
Electrocardiographic Detection of Non-ST Elevation Myocardial Events for Accelerated Classification of Chest Pain Encounters (ECG-SMART 2)
This project is creating smart ECG tools to quickly spot heart attacks that don't show the classic ST-elevation in people who come to the emergency room with chest pain.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project ID | NIH-11292312 on NIH RePORTER |
What this research studies
The team collected thousands of 12-lead ECGs linked to outcomes from multiple hospitals and ambulances to train computer models. They used machine learning to find ECG patterns tied to non-ST-elevation coronary events and checked that these patterns make clinical sense. Now they plan to build a bedside, real-time decision support system and test it prospectively in clinical settings. The work includes external validation at other hospitals and a technical setup to deliver ECG alerts to clinicians during patient care.
Who could benefit from this research
Good fit: Adults who present with chest pain or suspected acute coronary syndrome in participating emergency departments or prehospital (ambulance) systems would be the ideal candidates.
Not a fit: People whose conditions are already clearly identified by standard ECGs (for example classic ST-elevation heart attacks) or whose chest pain is due to clearly non-cardiac causes may not gain additional benefit from this tool.
Why it matters
Potential benefit: If successful, this could help doctors find and treat heart attacks sooner in people whose ECGs do not show the classic ST-elevation, reducing missed diagnoses and delays in care.
How similar studies have performed: Prior retrospective work using the project's large ECG database showed promising algorithm performance, but real-time bedside deployment and prospective validation remain new steps.
Where this research is happening
Rochester, United States
- University of Rochester — Rochester, United States (Active)
Researchers
- Principal investigator: Al-Zaiti, Salah S — University of Rochester
- Study coordinator: Al-Zaiti, Salah S
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.