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AI-Powered 1-Minute ECG could spot hidden heart risks

NCT ID NCT07396792

Diagnosis Sponsor: I.M. Sechenov First Moscow State Medical University 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 This study
Registered, but not yet taking participants.
By invitation only
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study will enroll 5000 adults to see if a one-minute, single-lead ECG, analyzed by machine learning, can detect heart conditions like high blood pressure, heart failure, and diabetes. Participants will have their ECG recorded twice and compared with full medical exams. The goal is to find ECG patterns that reliably indicate disease, potentially enabling faster, cheaper screening.

What this could mean

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

Active substance
single-channel electrocardiogram (ECG) with machine learning analysis
What this could lead to
If successful, this could lead to a quick, low-cost screening tool to detect heart disease and related conditions using just a simple ECG.
What could go wrong
This is an early observational study, not a treatment trial. The AI model may not be accurate enough for real-world use, and results may not apply to people with pacemakers or tremors.

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.

Expected to start

Apr 2026

An estimate. Start dates often move.

Expected to finish

May 2028

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

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

Who is studied

All patients with or without cardiac and cardiac-associated pathologies over 18 years old

Ages

18 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: 1. The presence of written informed consent of the patient to participate in the study 2. Availability of examination data allowing for the verification or exclusion of cardiac and cardiac-associated pathology 3. Age 18 years old and older Non-inclusion criteria: 1. Patients with an implanted permanent pacemaker; 2. ECG changes that prevent spectral analysis; 3. Conditions that may impair the quality of the ECG recording (Parkinson's disease, essential tremor, etc.); 4. Conditions that make ECG recording in lead I impossible (congenital anomalies of the upper limbs, traumatic amputation of the upper limbs). 5. Lack of written informed consent from the patient to participate in the study. Exclusion Criteria: 1. Poor quality of the ECG recording on a single-channel ECG monitor 2. Insufficient examination data to verify or exclude cardiac or cardiac-associated pathology; 3. Patient's unwillingness to continue participating in the study for any reason.

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Conditions

The condition(s) this trial relates to.

abdominal obesity-metabolic syndrome anemia Arrhythmias, Cardiac cardiac rhythm disease chronic kidney disease chronic renal failure syndrome coronary artery disorder diabetes mellitus essential hypertension heart failure heart valve disorder Hypercholesterolemia hypertensive disorder metabolic syndrome X ventricular arrhythmias due to cardiac ryanodine receptor calcium release deficiency syndrome

As listed by the trial registrant

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

Arterial hypertension Chronic kidney disease (stage 3-4) Coronary artery disease Diabetes mellitus Heart failure Heart rhythm disorders Metabolic syndrome Valvular heart diseases

How to take part

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

  1. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  2. 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.

More trials for these conditions

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