Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study
Part of paid clinical trials in New Haven, Connecticut.
- Sponsor
- Yale University
- Study ID
- NCT06749145
- Status
- Enrolling By Invitation
Conditions
- Aortic Stenosis
Eligibility Criteria
- Sex
- ALL
- Age
- 70 Years - N/A
- Healthy Volunteers
- Accepted
Interventions
- Portable 1-lead electrocardiogram — DIAGNOSTIC_TESTPortable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device.
- Point-of-care ultrasound — DIAGNOSTIC_TESTPoint-of-care ultrasound performed with the FDA-approved VScan Air device.
- AI-ECG risk algorithm — OTHERArtificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram
- AI-POCUS — OTHERArtificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos.
Study Details
The DETECT-AS Diagnostic Study will assess the performance of artificial intelligence (AI) risk predictions to detect aortic stenosis using results from portable electrocardiogram (ECG) and cardiac ultrasound devices.
Key Dates
- Start date
- Sep 16, 2025
- Status verified
- Nov 2025
- Primary completion
- Aug 31, 2028
- Completion
- Aug 31, 2028
Study Design
- Enrollment
- 410 participants (estimated)
- Allocation
- RANDOMIZED
- Intervention model
- PARALLEL
- Primary purpose
- DIAGNOSTIC
Arms
- Experimental: InterventionThe intervention arm will undergo sequential screening for aortic stenosis using portable 1-lead electrocardiograms (ECGs), followed by point-of-care ultrasound (POCUS), if indicated, by artificial intelligence (AI)-based risk algorithms.
- Sham Comparator: ControlThe control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS).
Primary Outcome Measure
Number of participants diagnosed with advanced aortic stenosis (AS) by transthoracic echocardiogram (TTE) [ Time Frame: Until 12 months from the baseline visit ]
Locations (3)
| Facility | City | State | ZIP | Site coordinators |
|---|---|---|---|---|
| Yale New Haven Health System | New Haven | Connecticut | 06519 | - |
| Icahn School of Medicine at Mount Sinai | New York | New York | 10029 | - |
| The Methodist Hospital Research Institute | Houston | Texas | 77030 | - |
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