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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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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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| 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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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| Measure | Description | Time Frame |
|---|---|---|
| Distribution of AI-ECG probabilities in Athlete's | 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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Inclusion Criteria:
Exclusion Criteria:
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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.
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| Name | Affiliation | Role |
|---|---|---|
| Konstantinos Siontis, MD | Mayo Clinic | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Mayo Clinic in Rochester | Rochester | Minnesota | 55905 | United States |
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| 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. |
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| 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. |
|
| Baseline |
| 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 |
| ID | Term |
|---|---|
| D002312 | Cardiomyopathy, Hypertrophic |
| ID | Term |
|---|---|
| D009202 | Cardiomyopathies |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D001020 | Aortic Stenosis, Subvalvular |
| D001024 | Aortic Valve Stenosis |
| D000082862 | Aortic Valve Disease |
| D006349 | Heart Valve Diseases |
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| ID | Term |
|---|---|
| D004562 | Electrocardiography |
| ID | Term |
|---|---|
| D006334 | Heart Function Tests |
| D003935 | Diagnostic Techniques, Cardiovascular |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D004568 | Electrodiagnosis |
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