Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study
NCT ID: NCT06749145
Last Updated: 2025-11-13
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ENROLLING_BY_INVITATION
NA
410 participants
INTERVENTIONAL
2025-09-16
2028-08-31
Brief Summary
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Detailed Description
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Conditions
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Keywords
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
TRIPLE
Study Groups
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Intervention
The 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.
Portable 1-lead electrocardiogram
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device.
Point-of-care ultrasound
Point-of-care ultrasound performed with the FDA-approved VScan Air device.
AI-ECG risk algorithm
Artificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram
AI-POCUS
Artificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos.
Control
The control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS).
Portable 1-lead electrocardiogram
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device.
Point-of-care ultrasound
Point-of-care ultrasound performed with the FDA-approved VScan Air device.
Interventions
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Portable 1-lead electrocardiogram
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device.
Point-of-care ultrasound
Point-of-care ultrasound performed with the FDA-approved VScan Air device.
AI-ECG risk algorithm
Artificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram
AI-POCUS
Artificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos.
Eligibility Criteria
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Inclusion Criteria
* Attending a routine outpatient primary care clinic at one of the three enrollment sites
Exclusion Criteria
* Non-English speaking
* Urgent or emergent visits, defined as a visit for an illness or injury that needs attention quickly or is life-threatening
* Any echocardiogram within 12 months of clinic visit
* Prior history of moderate or severe AS
* Prior history of aortic valve replacement or repair, including transcatheter and surgical AVR with either a bioprosthetic or mechanical valve
* Presence of implantable cardiac devices, including permanent cardiac pacer, implantable cardioverter-defibrillator, or left ventricular assist device
* Prior heart transplant
* History of dementia
* Documented life expectancy of \<1 year or current participation in hospice services.
70 Years
ALL
Yes
Sponsors
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Yale University
OTHER
National Institute on Aging (NIA)
NIH
Icahn School of Medicine at Mount Sinai
OTHER
The Methodist Hospital Research Institute
OTHER
Responsible Party
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Principal Investigators
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Rohan Khera, MD, MS
Role: PRINCIPAL_INVESTIGATOR
Yale University
Locations
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Yale New Haven Health System
New Haven, Connecticut, United States
Icahn School of Medicine at Mount Sinai
New York, New York, United States
The Methodist Hospital Research Institute
Houston, Texas, United States
Countries
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Other Identifiers
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2000038634
Identifier Type: -
Identifier Source: org_study_id