NCT06290570

Brief Summary

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.

Trial Health

75
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
183

participants targeted

Target at P50-P75 for all trials

Timeline
7mo left

Started May 2024

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
active not recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress78%
May 2024Dec 2026

First Submitted

Initial submission to the registry

February 26, 2024

Completed
7 days until next milestone

First Posted

Study publicly available on registry

March 4, 2024

Completed
2 months until next milestone

Study Start

First participant enrolled

May 7, 2024

Completed
1.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 25, 2025

Completed
1.4 years until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2026

Expected
Last Updated

March 19, 2026

Status Verified

March 1, 2026

Enrollment Period

1.1 years

First QC Date

February 26, 2024

Last Update Submit

March 17, 2026

Conditions

Outcome Measures

Primary Outcomes (2)

  • Distribution of AI-ECG probabilities in HCM

    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.

    Baseline

  • Comparative diagnostic performance between tracings obtained from different devices

    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.

    Baseline

Secondary Outcomes (2)

  • Distribution of AI-ECG probabilities in Athlete's

    Baseline

  • Correlation with false negative AI ECG result

    Baseline

Study Arms (2)

Hypertrophic Cardiomyopathy (HCM)

Subjects with clinically validated diagnoses of HCM will be enrolled and have a clinically indicated 12-Lead ECG obtained as well as ECG tracings collected using an Apple Smart Watch (single-lead) and AliveCor KardiaMobile (6-Lead).

Diagnostic Test: 12-Lead ECGDiagnostic Test: Apple Smart Watch Single Lead ECGDiagnostic Test: AliveCor KardiaMobile 6-Lead ECG

Athlete's

Athlete's will be enrolled and have a clinically indicated 12-Lead ECG obtained as well as ECG tracings collected using an Apple Smart Watch (single-lead) and AliveCor KardiaMobile (6-Lead).

Diagnostic Test: 12-Lead ECGDiagnostic Test: Apple Smart Watch Single Lead ECGDiagnostic Test: AliveCor KardiaMobile 6-Lead ECG

Interventions

12-Lead ECGDIAGNOSTIC_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.

Athlete'sHypertrophic Cardiomyopathy (HCM)

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

Athlete'sHypertrophic Cardiomyopathy (HCM)

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

Athlete'sHypertrophic Cardiomyopathy (HCM)

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Outpatients scheduled for appointments in the sports cardiology or HCM clinic at Mayo Clinic in Rochester, MN will be approached to participate in the study.

You may qualify if:

  • 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.

You may not qualify if:

  • Any exception to the above criteria.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Mayo Clinic in Rochester

Rochester, Minnesota, 55905, United States

Location

MeSH Terms

Conditions

Cardiomyopathy, Hypertrophic

Interventions

Electrocardiography

Condition Hierarchy (Ancestors)

CardiomyopathiesHeart DiseasesCardiovascular DiseasesAortic Stenosis, SubvalvularAortic Valve StenosisAortic Valve DiseaseHeart Valve Diseases

Intervention Hierarchy (Ancestors)

Heart Function TestsDiagnostic Techniques, CardiovascularDiagnostic Techniques and ProceduresDiagnosisElectrodiagnosis

Study Officials

  • Konstantinos Siontis, MD

    Mayo Clinic

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

February 26, 2024

First Posted

March 4, 2024

Study Start

May 7, 2024

Primary Completion

June 25, 2025

Study Completion (Estimated)

December 1, 2026

Last Updated

March 19, 2026

Record last verified: 2026-03

Data Sharing

IPD Sharing
Will not share

Locations