Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development: a Randomized Control Trial
Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY
Our study aimed to use an AF-predict AI-ECG alert system to help physicians identify patients who need to wear a continuous cardiac rhythm monitor for new diagnoses of atrial fibrillation (AF), atrial flutter (AFL), or atrial arrhythmia with high AF risk, including premature atrial complexes (PAC) ≥ 500/24hr, burst PACs \> 20 beats, non-sustained AF/AFL.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 1 month
Maximum Age: 2 months
Healthy Volunteers: f
View:
• Patients in the inpatient department or the outpatient department
• Patients need to have at least one electrocardiogram within one year
Locations
Other Locations
Taiwan
Tri-Service General Hospital
RECRUITING
Taipei
Contact Information
Primary
Chin Lin, PhD
xup6fup@mail.ndmctsgh.edu.tw
+886-2-8792-3100 Ext. 18574
Backup
ChiaoChin Lee, MD
chiaochinlee@hotmail.com
+886919614672
Time Frame
Start Date: 2025-07-01
Estimated Completion Date: 2026-10-01
Participants
Target number of participants: 14726
Treatments
Experimental: AF-predict AI-ECG alert system
All the patients' ECGs will receive AF-predict AI-ECG analysis. According to the AI-ECG analysis results, those with at least one high-risk ECG within one year will be called back and asked to undergo a continuous cardiac rhythm monitor for up to 7 days. Otherwise, the physicians can review the AI-ECG analysis results for all the patients in the intervention group.
No_intervention: Standard of care
Patients will receive the standard care, and their ECGs will not be analyzed by AI-ECG before the end of the study.
Related Therapeutic Areas
Sponsors
Leads: National Defense Medical Center, Taiwan