Evaluating ECGs with Deep Learning for Athlete Health
Official title: Deep Learning ECG Evaluation and Clinical Assessment for Competitive Sport Eligibility
Run by I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio · NCT06285084 · Data updated 2026-11-12
This study is testing a new computer program that looks at heart scans of athletes to see if it can help determine who is healthy enough to compete in sports.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 60 Years |
| Sex | All |
| Enrollment | 531 (estimated) |
| Sponsor | I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio Academic / other |
| Locations | 1 site (Milan, Lombardy) |
| Status | Recruiting |
| Started | February 2, 2024 |
| Main results expected | November 2, 2025 |
| Study ends | February 2, 2027 |
| Registry record updated | February 29, 2024 |
| Trial ID | NCT06285084 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are athletes aged 18 to 60 who require cardiac evaluations for competitive eligibility and have no history of cardiovascular disease.
✕Probably not a fit
Patients engaged in skill-based sports or those with a high clinical probability of cardiovascular disease may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to develop a Deep Learning model that analyzes electrocardiographic traces of athletes to assess their cardiovascular health and eligibility for competitive sports. Researchers will first train the model using data from 455 athletes, categorizing them as 'fit' or 'unfit' based on standard clinical evaluations. A subsequent validation cohort of 76 athletes will be used to test the model's accuracy in distinguishing between those cleared for sports and those requiring further medical assessment. The study follows established guidelines for sports participation and aims to enhance the safety of athletes in competitive environments.
Why it matters
Potential benefit: If successful, this study could improve the accuracy of cardiovascular assessments for athletes, ensuring safer participation in competitive sports.
How similar studies have gone: While the use of Deep Learning in ECG analysis is emerging, this specific application for athlete eligibility is relatively novel and has not been extensively tested in prior studies.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Athletes in need of cardiac or sports medical evaluation for the issuance of competitive eligibility. * Enlisted athletes involved in sports like soccer or those with mixed or aerobic cardiovascular demands according to the COCIS 2017 classification. * Aged 18 years or older but not exceeding 60 years. * No history of cardiovascular disease. * Signed Informed Consent. Exclusion Criteria: * Athletes engaging in skill-based sports as per the COCIS 2017 classification. * High clinical probability of cardiovascular disease, such as typical angina or heart failure. * Pregnancy and/or breastfeeding (confirmed through self-declaration).
Where it's running
-
Ospedale Galeazzi-Sant'Ambrogio
Milan, Lombardy, Italy Recruiting
Study contacts
- Study coordinator: Davide Marchetti, MD
- Email: davide.marchetti@grupposandonato.it
- Phone: +390283506734
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.