Deep Learning ECG Evaluation and Clinical Assessment for Competitive Sport Eligibility

NCT06285084 | Recruiting

• 1 other identifier: VALETUDO Trial (L4195)
• Study Type: observational
• Target: 531
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Sports Cardiology; Preventive Cardiology; Electrocardiogram; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• DL model accuracy

  The accuracy of the DL model in recognizing the ECGs of athletes deemed fit or unfit will be evaluated by comparing the results with those obtained from the assessment performed by the sports physician (gold standard). Participants will categorize the athletes into true positives, false positives, true negatives, and false negatives. To define the ability of the DL model to discriminate between ECGs of athletes deemed fit or unfit, the receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) will be calculated.

  From first medical evaluation with ECG until the final medical decision on competitive sports eligibility, up to 12 months

Study Arms (2)

Training Cohort

455 Athletes already evaluated for sports participation clearance, whom ECG and clinical evaluation (cleared - not cleared for competitive sports participation) will be fed into the DL model

Validation Cohort

76 Athletes evaluated using standard sports eligibility clearance tests and our DL model

Eligibility Criteria

• Age: 18 Years - 60 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Adults requiring medical evaluation for competitive sports eligibility

You may qualify if:

• 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.

You may not qualify if:

• 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).

Sponsors & Collaborators

• I.R.C.C.S Ospedale Galeazzi-Sant'Ambrogio: lead

Study Sites (1)

Ospedale Galeazzi-Sant'Ambrogio

Milan, Lombardy, 20157, Italy

RECRUITING

Central Study Contacts

Davide Marchetti, MD

CONTACT

+390283506734; davide.marchetti@grupposandonato.it

Daniele Andreini, MD, PhD

CONTACT

+390283506734; daniele.andreini@unimi.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 5, 2024
• First Posted: February 29, 2024
• Study Start: February 2, 2024
• Primary Completion: November 2, 2025
• Study Completion (Estimated): February 2, 2027
• Last Updated: February 29, 2024

Record last verified: 2024-02

Locations

IT (1)