AI-driven 7-day single-lead ECG patch monitoring to detect new atrial fibrillation in older adults
Effectiveness of Artificial IntelliGence-Driven Single-LEad Long-TerM Electrocardiograms MonItoring in Detecting New-Diagnosed Atrial FIbrillation
This project will test whether AI-read 7-day single-lead ECG patches can find new atrial fibrillation in people aged 60 and older in rural China better than routine 12-lead ECG screening.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 15360 (estimated) |
| Ages | 60 Years and up |
| Sex | All |
| Sponsor | Beijing Anzhen Hospital Academic / other |
| Locations | 1 site (Zhejiang, Quzhou) |
| Trial ID | NCT06842147 on ClinicalTrials.gov |
What this trial studies
This is a cluster-randomized trial in 128 village clinics in Qujiang District, Quzhou City, comparing an enhanced screening strategy using AI-integrated 7-day single-lead ECG patches to routine care with standard 12-lead ECGs. Villages are randomized 1:1, and participants aged 60 or older in both arms receive family-centered AF education and opportunistic assessments at local clinics. The co-primary endpoints are the 1-year rate of newly diagnosed AF and a 3-year composite of all-cause death, stroke or systemic embolism, and hospitalization for heart failure. Screening is delivered through village clinics supported by township health centers within the local three-tier healthcare system.
Who should consider this trial
Good fit: Ideal candidates are residents aged 60 or older in participating villages with no prior history of atrial fibrillation who can provide informed consent and complete follow-up.
Not a fit: Patients with pacemakers/ICDs, significant cognitive impairment, an expected life expectancy under one year, or who cannot wear the patch are unlikely to gain benefit from this screening approach.
Why it matters
Potential benefit: If successful, the approach could increase AF detection in rural areas and enable earlier treatment to reduce stroke and heart-failure hospitalizations.
How similar studies have performed: Previous studies using single-lead long-term patches and AI algorithms have improved AF detection, though large cluster-randomized evaluations in rural primary-care settings remain limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: Age 60 years or older No previous history of atrial fibrillation (AF) Willing to participate in random assignment and follow-up Exclusion Criteria: Patients with a pacemaker or implanted cardioverter-defibrillator (ICD) Patients with cognitive impairment or unable to provide informed consent Patients with an estimated life expectancy of less than one year (e.g., advanced cancer or end-stage renal disease) Patients deemed unsuitable for the study by the investigator Patients who refuse to participate
Where this trial is running
Zhejiang, Quzhou
- Beijing Anzhen Hospital — Zhejiang, Quzhou, China (Recruiting)
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.