MedTrace Logo

Deep Learning ECG Evaluation and Clinical Assessment for Competitive Sport Eligibility

NCT06285084 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 531

Last updated 2024-02-29

No results posted yet for this study

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

Sponsors & Collaborators

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

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-02-02
Primary Completion
2025-11-02
Completion
2027-02-02

Countries

  • Italy

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06285084 on ClinicalTrials.gov