Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study

Yale University

Status: Invitation-only

Conditions: Aortic Stenosis

Treatments: Other: AI-POCUS; Other: AI-ECG risk algorithm; Diagnostic Test: Portable 1-lead electrocardiogram; Diagnostic Test: Point-of-care ultrasound

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT06749145

R01AG089981 (U.S. NIH Grant/Contract)

2000038634

Details and patient eligibility

About

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.

Enrollment: 410 estimated patients

Sex: All

Ages: 70+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Age 70 years or older
• Attending a routine outpatient primary care clinic at one of the three enrollment sites

Exclusion criteria

• Opted out of research studies
• 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.

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

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410 participants in 2 patient groups

Intervention

Experimental group

Description:

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.

Treatment:

Diagnostic Test: Point-of-care ultrasound

Diagnostic Test: Portable 1-lead electrocardiogram

Other: AI-ECG risk algorithm

Other: AI-POCUS

Control

Sham Comparator group

Description:

The control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS).

Treatment:

Diagnostic Test: Point-of-care ultrasound

Diagnostic Test: Portable 1-lead electrocardiogram