Aortic StenosisNCT06749145
Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study
A study testing Portable 1-lead electrocardiogram, Point-of-care ultrasound and AI-ECG risk algorithm in people with Aortic Stenosis, run by Yale University at 3 sites in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 70 years and olderHealthy volunteers can take part
- Conditions the study is for
- Aortic Stenosis
- What is being tested?
- Portable 1-lead electrocardiogram, Point-of-care ultrasound and AI-ECG risk algorithm
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 410 participants
- Where
- 3 sitesUnited States
- Study dates
- 16 Sep 2025to 31 Aug 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 70 years and older
- All sexes
- Healthy volunteers accepted
- Older adult
Who may be able to join
- Age 70 years or older
- Attending a routine outpatient primary care clinic at one of the three enrollment sites
Who cannot join
- 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
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- 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 locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States3 sites
The Methodist Hospital Research Institute
Houston, Texas, 77030
Yale New Haven Health System
New Haven, Connecticut, 06519
Icahn School of Medicine at Mount Sinai
New York, New York, 10029
About this study
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.
- Conditions
- Aortic Stenosis
- Being tested
- Portable 1-lead electrocardiogram, Point-of-care ultrasound, AI-ECG risk algorithm, AI-POCUS
- Keywords
- aortic stenosis, artificial intelligence
- Medical subject headings
- Aortic Valve Stenosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Portable 1-lead electrocardiogramDiagnostic test
Portable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device.
Point-of-care ultrasoundDiagnostic test
Point-of-care ultrasound performed with the FDA-approved VScan Air device.
AI-ECG risk algorithmOther
Artificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram
AI-POCUSOther
Artificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos.
| Study group | Role | What they receive |
|---|---|---|
| Intervention | Experimental | 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. Receives: Diagnostic Test: Portable 1-lead electrocardiogram; Diagnostic Test: Point-of-care ultrasound; Other: AI-ECG risk algorithm; Other: AI-POCUS |
| Control | Sham comparator | The control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS). Receives: Diagnostic Test: Portable 1-lead electrocardiogram; Diagnostic Test: Point-of-care ultrasound |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of participants diagnosed with advanced aortic stenosis (AS) by transthoracic echocardiogram (TTE)
The number of participants diagnosed with advanced AS by TTE at 12 months. Diagnosis of advanced AS is defined as diagnosis of moderate or severe AS as documented in the participant's electronic health record (EHR) at 12 months and adjudication of outcome via review of echocardiographic reports and videos performed by blinded members of the echocardiographic lab at the coordinating center.
Measured: Until 12 months from the baseline visit
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Dec 2024
- Study start16 Sep 2025
- Primary completion31 Aug 2028 (estimated)
- Study completion31 Aug 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Aortic StenosisStudies of the same condition, open and under way.
- More trials run by Yale UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind
- Who is masked
- Participant, Investigator, Outcomes assessor
- Enrolment
- 410 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Yale University
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute on Aging (NIA), Icahn School of Medicine at Mount Sinai, The Methodist Hospital Research Institute
- Responsible party
- Sponsor
- Investigators
- Rohan Khera, MD, MS, Principal investigator, Yale University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06749145
- Sponsor's protocol ID
- 2000038634
- Other IDs
- R01AG089981
- Status last verified
- Oct 2026
- First submitted
- 19 Dec 2024
- Last updated
- 6 Oct 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes: A de-identified dataset will be made available following publication of primary results.
Study at a glance
From the registry record, last updated by the sponsor on 6 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study
- ClinicalTrials.gov ID
- NCT06749145
- Acronym / sponsor ID
- 2000038634
- Conditions
- Aortic Stenosis
- Keywords
- aortic stenosis, artificial intelligence
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 410 participants (estimated)
- Lead sponsor
- Yale UniversityUniversity, hospital or other
- Collaborators
- National Institute on Aging (NIA), Icahn School of Medicine at Mount Sinai, The Methodist Hospital Research Institute
- Study start
- 16 Sep 2025 (actual)
- Primary completion
- 31 Aug 2028 (estimated)
- Study completion
- 31 Aug 2028 (estimated)
- First posted
- 27 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind (participant, investigator, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intervention | Experimental | Diagnostic Test: Portable 1-lead electrocardiogram, Diagnostic Test: Point-of-care ultrasound, Other: AI-ECG risk algorithm, Other: AI-POCUSThe 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. |
| Control | Sham comparator | Diagnostic Test: Portable 1-lead electrocardiogram, Diagnostic Test: Point-of-care ultrasoundThe control arm will undergo a portable 1-lead electrocardiogram (ECG), with 10% randomly assigned to undergo point-of-care ultrasound (POCUS). |
Who may qualify
- Ages
- 70 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Older adult
Key inclusion criteria (2 listed)
- Age 70 years or older
- Attending a routine outpatient primary care clinic at one of the three enrollment sites
Key exclusion criteria (10 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Portable 1-lead electrocardiogramPortable 1-lead electrocardiogram (ECG) performed with the FDA-approved AliveCor KardiaMobile device. | Diagnostic test | Control, Intervention |
| Point-of-care ultrasoundPoint-of-care ultrasound performed with the FDA-approved VScan Air device. | Diagnostic test | Control, Intervention |
| AI-ECG risk algorithmArtificial intelligence (AI) risk algorithm for aortic stenosis using a 1-lead electrocardiogram | Other | Intervention |
| AI-POCUSArtificial intelligence (AI) risk algorithm for aortic stenosis using cardiac ultrasound plax videos. | Other | Intervention |
Primary outcome
Number of participants diagnosed with advanced aortic stenosis (AS) by transthoracic echocardiogram (TTE)
Time frame: Until 12 months from the baseline visit
The number of participants diagnosed with advanced AS by TTE at 12 months. Diagnosis of advanced AS is defined as diagnosis of moderate or severe AS as documented in the participant's electronic health record (EHR) at 12 months and adjudication of outcome via review of echocardiographic reports and videos performed by blinded members of the echocardiographic lab at the coordinating center.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Oct 2026.
- Individual participant dataSharing planned: Yes. A de-identified dataset will be made available following publication of primary results.
Related trials for Aortic Stenosis
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Trial of the F2 Filter and Delivery System for Embolic Protection During TAVR
Aortic Stenosis Treated With TAVI, Aortic Diseases
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Human Experimental Models of Pain (HEMP)
Acute Pain
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Intravascular Lithotripsy in High Risk Calcified Iliac Anatomy for Transfemoral TAVR
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Not yet recruiting
NHLBI SESAME (SEptal Scoring Along Midline Endocardium) Multi-Center Prospective Study Using Improvised Off-Label Devices
Hypertrophic Cardiomyopathy, Left Ventricular Outflow Obstruction
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Exercise and Diet Supplements for Older Patients Undergoing TAVI: the IRON-TAVI Trial
Aortic Stenosis Disease, Aortic Stenosis Symptomatic
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Rohan Khera, MD, MS principal investigator
Yale University
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Portable 1-lead electrocardiogram, Point-of-care ultrasound and AI-ECG risk algorithm in people with Aortic Stenosis, run by Yale University at 3 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 6 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the 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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Oct 2026.