Deep Learning ECG Evaluation and Clinical Assessment for Competitive Sport Eligibility

The goal of this observationl study is to evaluate the possibility of building a Deep Learning (DL) model capable of analyzing electrocardiographic traces of athletes and providing information in the form of a probability stratification of cardiovascular disease. Researchers will enroll a training cohort of 455 participants, evaluated following standard clinical practice for eligibility in competitive sports. The response of the clinical evaluation and ECG traces will be recorded to build a DL model. Researchers will subsequently enroll a validation cohort of 76 participants. ECG traces will be analyzed to evaluate the accuracy of the model to discriminate participants cleared for sports eligibility versus participants who need further medical tests

NCT Number	NCT06285084
Lead Sponsor	I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio
Conditions	Sports Cardiology, Preventive Cardiology, Electrocardiogram, Artificial Intelligence
Enrollment	531 participants
Start Date	2024-02-02
Primary Completion	2025-11-02 (estimated)
Study Completion	2027-02-02 (estimated)
Updated on ClinicalTrials.gov	2024-02-29