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NCT Number: NCT06290570

A Study of Artificial Intelligence ECG With ECG Devices to Detect Hypertrophic Cardiomyopathy Distinct From Athlete's

The purpose of this study is to evaluate the AI-ECG algorithm for HCM in detecting HCM and in differentiating it from athlete's using not only the standard 12-lead ECG, but also ECGs obtained with the Apple Watch and Alivecor KardiaMobile devices.

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This study is active but is not currently recruiting participants.

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Key information

Conditions

Hypertrophic Cardiomyopathy Aortic Stenosis, Subvalvular Aortic Valve Disease Aortic Valve Stenosis Cardiomyopathies Cardiomyopathy, Hypertrophic Cardiovascular Diseases Heart Diseases Heart Valve Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Mayo Clinic in Rochester

Rochester, Minnesota, 55905, United States

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients with clinically validated diagnoses of HCM (n=150) and athlete's (n=150) will be identified by pre-screening of the clinic appointments for each of the specialty HCM and Sports Cardiology clinics or in the CV fellows' clinic (in patients with an established diagnosis and no pending testing). All diagnoses will need to be supported by unequivocal imaging and other ancillary data per our standard of care and at the determination of clinic experts.

Exclusion criteria

  • Any exception to the above criteria.

Treatment and study plan

12-lead ECG

Diagnostic Test

A clinically performed 12-lead ECG tracing within 30 days of the appointment will be obtained from the subject medical record and will be used for AI-ECG analyses.

Apple Smart Watch Single Lead ECG

Diagnostic Test

A single lead ECG tracing will be collected using an Apple Smart Watch and tracing will be used for AI-ECG analyses.

AliveCor KardiaMobile 6-Lead ECG

Diagnostic Test

A 6-lead ECG tracing will be collected using an AliveCor KardiaMobile device and tracing will be used for AI-ECG analyses.

Primary outcomes

  1. Distribution of AI-ECG probabilities in HCM

    Time frame: Baseline

    Artificial Intelligence (AI) scores will be measured using the AI Algorithm on ECG tracings obtained from clinically indicated 12-Lead ECG, Apple Smart Watch (single-lead), and AliveCor KardiaMobile (6-Lead) in subjects with HCM. The AI scores will be utilized to generate the AI-ECG probability of accurately diagnosing HCM (labelled as true positive, true negative, false positive, false negative) and the distribution of AI-ECG probabilities will be evaluated. A higher distribution of AI-ECG probabilities (more true positives) will reflect better diagnostic performance of the AI-ECG Algorithm.

  2. Comparative diagnostic performance between tracings obtained from different devices

    Time frame: Baseline

    Artificial Intelligence (AI) scores will be measured using the AI Algorithm on ECG tracings obtained from clinically indicated 12-Lead ECG, Apple Smart Watch (single-lead), and AliveCor KardiaMobile (6-Lead). Diagnostic performance of AI Algorithm (labelled as true positive, true negative, false positive, false negative) based on tracing from each ECG form factor (12-lead, single-lead, 6-lead) will be evaluated and compared.

Secondary outcomes

  1. Distribution of AI-ECG probabilities in Athlete's

    Time frame: Baseline

    Artificial Intelligence (AI) scores will be measured using the AI Algorithm on ECG tracings obtained from clinically indicated 12-Lead ECG, Apple Smart Watch (single-lead), and AliveCor KardiaMobile (6-Lead) in subjects with Athlete's. The AI scores will be utilized to generate the AI-ECG probability of accurately diagnosing HCM (true positive, true negative, false positive, false negative) and the distribution of AI-ECG probabilities will be evaluated. A higher distribution of AI-ECG probabilities (more true positives) will reflect better diagnostic performance of the AI-ECG Algorithm.

  2. Correlation with false negative AI ECG result

    Time frame: Baseline

    Artificial Intelligence (AI) scores will be measured using the AI Algorithm on ECG tracings obtained from clinically indicated 12-Lead ECG, Apple Smart Watch (single-lead), and AliveCor KardiaMobile (6-Lead). Diagnostic performance of AI Algorithm (labelled as true positive, true negative, false positive, false negative) based on tracing from each ECG form factor (12-lead, single-lead, 6-lead) will be evaluated and the correlation of the form factor to a false negative AI ECG result will be determined.

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

Prospective Evaluation of Artificial Intelligence ECG With Consumer-Facing ECG Devices for Detection of Hypertrophic Cardiomyopathy and Distinction From Athlete's

Important dates

Study start
2024
Primary completion
2025
Study completion
2026
First posted
Mar 4, 2024
Registry last updated
Mar 19, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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