AI-based ECG analysis for detecting heart attacks
Artificial Intelligence Scalable Solution for ST Myocardial Infarction (ASSIST): Cross-sectional Study
This study tests if an AI tool can quickly and accurately detect heart attacks using ECGs compared to traditional methods, helping patients get the right care faster.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 500 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Idoven 1903 S.L. Industry-sponsored |
| Locations | 5 sites (Lisbon and 4 other locations) |
| Trial ID | NCT06939738 on ClinicalTrials.gov |
What this trial studies
This observational study evaluates the performance of an AI-powered electrocardiogram (ECG) analysis platform called Willem™ in detecting Acute Myocardial Infarction (AMI). It compares the accuracy and speed of Willem™ against traditional human ECG interpretation in diagnosing AMI. The study aims to reduce delays in triage and improve diagnostic accuracy, which are critical for timely intervention in patients presenting with symptoms of acute coronary syndrome. By analyzing digitally stored 12-lead ECG traces, the study seeks to enhance the initial assessment of patients suspected of having AMI.
Who should consider this trial
Good fit: Ideal candidates include adults aged 18 and older with available digitally stored 12-lead ECG traces prior to invasive coronary angiography.
Not a fit: Patients with poor quality ECG signals or those who have had previous coronary events may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to faster and more accurate diagnoses of heart attacks, potentially saving lives.
How similar studies have performed: Other studies have shown promise in using AI for ECG analysis, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 18 years; * Available digitally stored 12-lead ECG traces prior to invasive coronary angiography; * Available angiographic and clinical data. Exclusion Criteria: * ECGs with poor signal quality; * Lack of digitally stored 12-lead ECG traces prior to coronary angiography; * Previous coronary events (AMI, coronary revascularizations); * Non-available clinical or angiographic data.
Where this trial is running
Lisbon and 4 other locations
- Unidade Local de Saúde de São José — Lisbon, Portugal (Recruiting)
- Unidade Local de Saúde de Lisboa Ocidental — Lisbon, Portugal (Recruiting)
- Germans Trias i Pujol University Hospital — Barcelona, Spain (Recruiting)
- Hospital General Universitario Gregorio Marañón — Madrid, Spain (Recruiting)
- La Paz University Hospital — Madrid, Spain (Recruiting)
Study contacts
- Principal investigator: Alfonso Jurado, MD, PhD — La Paz University Hospital
- Study coordinator: Manuel Marina-Breysse, MSc, MD
- Email: m@idoven.ai
- Phone: +34618103160
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.