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

Hypertrophic Cardiomyopathy Clinical Trial

Official title:

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06290570
• Other study ID #: 23-007685
• Status: Not yet recruiting
• Start date: April 2024
• Est. completion date: September 2025

Study information

• Verified date: April 2024
• Source: Mayo Clinic
• Contact: Heart Rhythm Services Research Team
• Phone: (507) 255-0774
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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 heart using not only the standard 12-lead ECG, but also ECGs obtained with the Apple Watch and Alivecor KardiaMobile devices.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 300
• Est. completion date: September 2025
• Est. primary completion date: September 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients with clinically validated diagnoses of HCM (n=150) and athlete's heart (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.

Related Conditions & MeSH terms

• Cardiomyopathies
• Cardiomyopathy, Hypertrophic
• Hypertrophic Cardiomyopathy
• Hypertrophy

Intervention

Diagnostic Test:
• 12-Lead ECG
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
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
A 6-lead ECG tracing will be collected using an AliveCor KardiaMobile device and tracing will be used for AI-ECG analyses.

Locations

Country	Name	City	State
United States	Mayo Clinic in Rochester	Rochester	Minnesota

Sponsors (1)

Lead Sponsor	Collaborator
Mayo Clinic

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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
Primary	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	Distribution of AI-ECG probabilities in Athlete's Heart	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 Heart. 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.	Baseline
Secondary	Correlation with false negative AI ECG result	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.	Baseline