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AI turns routine heart tracings into an early warning for a silent valve disease

NCT ID NCT07827105

Diagnosis Sponsor: AccurKardia, Inc. Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only This study
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Sep 18, 2026 · Last updated Sep 18, 2026

Summary

Researchers test whether an AI algorithm called AK-AVS can spot moderate-to-severe aortic stenosis, a narrowing of the heart's aortic valve, in older adults who have not been diagnosed. The study reviews about 4,000 routine electrocardiograms (ECGs) already collected during primary care, urgent care, or emergency visits for people aged 65 and older. When the algorithm flags a possible sign of aortic stenosis, those patients are invited for a symptom questionnaire, a physical exam, and a heart ultrasound to confirm whether the condition is present.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
an AI-based ECG algorithm for detecting aortic stenosis
What this could lead to
If it works, routine heart tracings could flag hidden aortic valve narrowing earlier, so people get a heart ultrasound and treatment before symptoms worsen.
What could go wrong
The algorithm may miss cases or raise false alarms, and this study only checks how well it reads existing ECGs. It cannot show whether earlier detection improves health.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 4,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Aug 2026

Expected to finish

Mar 2027

An estimate. End dates often move.

Lead sponsor

A company

The lead sponsor is a pharmaceutical, biotech, or medical-device company.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Participants will be drawn from patients 65 years of age or older with 12-lead ECGs on file at a primary care outpatient office, urgent care facility, or emergency department. Eligible ECGs, acquired within the prior 6 months, will be identified through electronic health record review and randomly selected by the principal investigator for AK-AVS screening.

Ages

65 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * ECGs from primary care or ER visits * ECGs must include all relevant parameters for AK-AVS intake * Patients aged 65 and older at the time of the ECG Subgroup analysis: * Patients with Insulin Resistance (pre-diabetic), Diabetes Mellitus, and Chronic Kidney Disease * Patients with hypertension Exclusion Criteria: * ECG Poor Quality (as indicated by cardiology information system) * Patients already seen by cardiology, to effectively exclude: Pacemaker / Paced rhythm Ejection fraction (EF) less than 40% Left ventricular hypertrophy (LVH) Prior diagnosis of Aortic Stenosis Prior diagnosis of heart failure Prior myocardial infraction (MI) Prior cardiac surgery

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Conditions

The condition(s) this trial relates to.

aortic valve stenosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Aortic stenosis

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    The full official record for this study. This one lists no contact details, but it is the first place any would appear.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • UC Irvine Health

    Orange, California, 92868, United States

More trials for these conditions

Other studies related to the condition(s) this trial covers.