Tests a 7-day AI heart-rhythm patch for finding atrial fibrillation in older adults
Tests an AI heart-rhythm patch worn for 7 days in people aged 60 or older.
Plain-language title generated from the registry record
Registry title: Effectiveness of Artificial IntelliGence-Driven Single-LEad Long-TerM Electrocardiograms MonItoring in Detecting New-Diagnosed Atrial FIbrillation
Key facts
- Where
- Zhejiang, ChinaSee the site
Where in China
- Beijing Anzhen HospitalZhejiang, ChinaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Beijing Anzhen Hospital
- Trial code
- NCT06842147
- Record updated
- 7 January 2026
- Original description
Abstract Purpose: Atrial fibrillation (AF) is a leading cause of stroke and heart failure, yet detection remains suboptimal in rural settings due to limited resources. This study evaluates whether an enhanced screening strategy using artificial intelligence (AI)-integrated 7-day single-lead electrocardiogram (ECG) patches improves AF detection and long-term clinical outcomes compared to routine care in rural China.Read full original descriptionShow less
Effectiveness of Artificial IntelliGence-Driven Single-LEad Long-TerM Electrocardiograms MonItoring in Detecting New-Diagnosed Atrial FIbrillation
Abstract Purpose: Atrial fibrillation (AF) is a leading cause of stroke and heart failure, yet detection remains suboptimal in rural settings due to limited resources. This study evaluates whether an enhanced screening strategy using artificial intelligence (AI)-integrated 7-day single-lead electrocardiogram (ECG) patches improves AF detection and long-term clinical outcomes compared to routine care in rural China.
Methods: This cluster-randomized trial will be conducted across 128 village clinics in Quzhou, Zhejiang Province. Villages are randomized 1:1 to either enhanced or routine screening. Participants aged 60 years or older (approximately 120 per village) in both arms receive family-centered AF education and opportunistic assessments. The enhanced group undergoes screening via 7-day single-lead ECG patches, while the routine group utilizes standard 12-lead ECGs.
Results: The trial features two primary endpoints. The Phase 1 endpoint is the newly diagnosed AF detection rate during a 1-year screening period. The Phase 2 endpoint is a 3-year composite outcome of all-cause mortality, stroke or systemic embolism, and hospitalization for heart failure.
Conclusion: By integrating wearable AI technology into primary care, this trial seeks to overcome diagnostic barriers in resource-limited environments. The findings will determine if prolonged digital monitoring can significantly enhance AF detection and reduce major cardiovascular events in elderly rural populations.
Inclusion: Age 60 years or older No previous history of atrial fibrillation (AF) Willing to participate in random assignment and follow-up.
Exclusion: 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.