A Study of Artificial Intelligence ECG With ECG Devices to Detect Hypertrophic Cardiomyopathy Distinct From Athlete's
Prospective Evaluation of Artificial Intelligence ECG With Consumer-Facing ECG Devices for Detection of Hypertrophic Cardiomyopathy and Distinction From Athlete's
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Konstantinos Siontis, MD
- Phone Number: (507) 255-1051
- Email: Siontis.Konstantinos@mayo.edu
Study Contact Backup
- Name: Shaun Crawford
- Phone Number: 507-422-5666
- Email: crawford.shaun@mayo.edu
Study Locations
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Minnesota
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Rochester, Minnesota, United States, 55905
- Mayo Clinic in Rochester
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
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.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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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).
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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.
A single lead ECG tracing will be collected using an Apple Smart Watch and tracing will be used for AI-ECG analyses.
A 6-lead ECG tracing will be collected using an AliveCor KardiaMobile device and tracing will be used for AI-ECG analyses.
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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).
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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.
A single lead ECG tracing will be collected using an Apple Smart Watch and tracing will be used for AI-ECG analyses.
A 6-lead ECG tracing will be collected using an AliveCor KardiaMobile device and tracing will be used for AI-ECG analyses.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Distribution of AI-ECG probabilities in HCM
Time Frame: Baseline
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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.
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Baseline
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Comparative diagnostic performance between tracings obtained from different devices
Time Frame: Baseline
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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.
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Baseline
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Correlation with false negative AI ECG result
Time Frame: Baseline
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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.
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Baseline
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Distribution of AI-ECG probabilities in Athlete's
Time Frame: Baseline
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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.
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Baseline
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Konstantinos Siontis, MD, Mayo Clinic
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Aortic Valve Disease
- Cardiovascular Diseases
- Heart Diseases
- Heart Valve Diseases
- Cardiomyopathies
- Aortic Stenosis, Subvalvular
- Aortic Valve Stenosis
- Cardiomyopathy, Hypertrophic
- Diagnostic Techniques and Procedures
- Diagnosis
- Diagnostic Techniques, Cardiovascular
- Heart Function Tests
- Electrodiagnosis
- Electrocardiography
Other Study ID Numbers
Other Study ID Numbers
- 23-007685
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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