Effectiveness of Artificial IntelliGence-Driven Single-LEad Long-TerM Electrocardiograms MonItoring in Detecting New-Diagnosed Atrial FIbrillation

NCT ID: NCT06842147

Last Updated: 2026-01-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

15360 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-03-01

Study Completion Date

2028-07-30

Brief Summary

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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.

Detailed Description

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Effectiveness of Artificial IntelliGence-Driven Single-Lead Long-Term Electrocardiograms Monitoring In Detecting New-Diagnosed Atrial FIbrillation (GEMINI) trial is a parallel, two-stage cluster randomized trial being conducted in 128 villages in Qujiang District, Quzhou City, Zhejiang Province. Village clinics serve as the primary health care units and provide essential services to rural residents, with one clinic allocated to each administrative village in China. Each village clinic is staffed by a village doctor with basic medical training (certificate-level) and operates under the supervision of physicians based at 8 township health centers. These township health centers are, in turn, overseen by a single district-level hospital, forming a three-tier hierarchical healthcare system . This decentralized structure, designed to address the shortage of specialist resources at the village level, enables consistent outreach and sustained medical engagement across rural populations. In this study, the villages (clusters) were randomly assigned to either the enhanced screening group (intervention arm) or the routine screening group (control arm). The coprimary outcomes are the 1-year detection rate of newly diagnosed AF (Phase 1) and a 3-year composite of all-cause mortality, stroke or systemic embolism, and hospitalization for heart failure (Phase 2).

Conditions

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Atrial Fibrillation (AF)

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Long-term Screening Group

This group will use the 7-day single-lead ECG monitoring device, a standard 12-lead ECG, family-centered AF education and opportunistic screening.

Group Type EXPERIMENTAL

7-day single-lead long-term ECG monitoring device.

Intervention Type DEVICE

Participants in the long-term screening group will undergo baseline data collection and a 12-lead ECG at baseline, followed using a 7-day single-lead long-term ECG monitoring device. This device continuously collects dynamic ECG data for seven days and allows participants to view and store ECGs through the accompanying software (registration number: 20192070163).

Standard Screening Group

This group will receive a standard 12-lead ECG, family-centered AF education and opportunistic screening.

Group Type ACTIVE_COMPARATOR

Standard Screening Group

Intervention Type DEVICE

Patients in the standard screening group will undergo baseline data collection and a standard 12-lead ECG at the start of the study, with follow-up including opportunistic ECG checks as needed. Those diagnosed with AF will receive anticoagulation and antiarrhythmic therapy according to clinical guidelines.

Interventions

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7-day single-lead long-term ECG monitoring device.

Participants in the long-term screening group will undergo baseline data collection and a 12-lead ECG at baseline, followed using a 7-day single-lead long-term ECG monitoring device. This device continuously collects dynamic ECG data for seven days and allows participants to view and store ECGs through the accompanying software (registration number: 20192070163).

Intervention Type DEVICE

Standard Screening Group

Patients in the standard screening group will undergo baseline data collection and a standard 12-lead ECG at the start of the study, with follow-up including opportunistic ECG checks as needed. Those diagnosed with AF will receive anticoagulation and antiarrhythmic therapy according to clinical guidelines.

Intervention Type DEVICE

Eligibility Criteria

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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
Minimum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Beijing Anzhen Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Beijing Anzhen Hospital

Zhejiang, Quzhou, China

Site Status RECRUITING

Countries

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China

Facility Contacts

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Song Zuo, MD

Role: primary

+8618801427775

Role: backup

Other Identifiers

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Beijing An Zhen Hospital

Identifier Type: -

Identifier Source: org_study_id

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