Screening for valvular heart disease with a single-lead ECG
Official title: Screening of Valvular Heart Disease Using Single-channel Electrocardiogram Analyzed With Machine Learning Models
Run by I.M. Sechenov First Moscow State Medical University · NCT07099417 · Data updated 2026-11-12
This project will test whether a one-minute single-lead ECG can detect valve problems in adults by comparing ECG recordings to echocardiogram results.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 1200 (estimated) |
| Sponsor | I.M. Sechenov First Moscow State Medical University Academic / other |
| Locations | 1 site (Moscow) |
| Status | Recruiting |
| Started | January 1, 2025 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | August 1, 2025 |
| Trial ID | NCT07099417 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18 and older who can give written informed consent and can attend outpatient or inpatient evaluation at the Sechenov University center are eligible, provided they do not have pacemakers or prosthetic valves and can produce an adequate ECG and echocardiogram.
✕Probably not a fit
Patients with pacemakers, prosthetic valves, movement disorders that impair ECG quality, poor echocardiographic windows, or acute illnesses that prevent completion of tests are unlikely to benefit from this screening approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a prospective, controlled, single-center observational study enrolling at least 1,200 adults at Sechenov University. Each participant will receive a standard echocardiogram read independently by two experts, followed immediately by a one-minute single-lead (lead I) ECG recorded with a CardioQvark device. ECG signals will be deidentified and stored remotely, then analyzed using spectral methods including continuous wavelet transform and machine-learning model development with a 1,000-patient training set and 200-patient test set. The aim is to identify ECG parameters and build models that correlate with echocardiographic findings of valvular stenosis or regurgitation.
Why it matters
Potential benefit: If successful, this could enable a fast, low-cost screening tool to flag patients who need further echocardiographic evaluation for valve disease.
How similar studies have gone: Using single-lead ECGs and machine learning to detect structural heart problems is relatively novel: there are preliminary pilot studies suggesting signal-based detection is possible, but large-scale validation for valvular disease is limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * The presence of written informed consent of the patient to participate in the study * Age from 18 years * Outpatient treatment and / or hospitalization in a research center Exclusion Criteria: * Reluctance of the patient to participate in the study * Poor quality ECG recording on a single-channel ECG monitor * Poor visualization of the heart during echocardiographic study * Acute psychotic reactions that arose during research * An exacerbation of chronic diseases requiring treatment tactics for the patient and preventing his further participation in the study. Non-inclusion criteria: * Poor quality ECG recording on a single-channel ECG monitor * Conditions that can impair ECG recording quality (Parkinson's disease, essential tremor) * Mental illness * Patients with a pacemaker installed * Patients with prosthetic valves
Where it's running
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I.M. Sechenov First Moscow State Medical University (Sechenov University)
Moscow, Russia Recruiting
Study contacts
- Principal investigator: Natalia Kuznetsova, Dr. — I.M. Sechenov First Moscow State Medical University (Sechenov University)
- Study coordinator: Natalia Kuznetsova, Dr.
- Email: kuznetsova_n_o@staff.sechenov.ru
- Phone: +79164778724
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.