Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development

Recruiting now · Not applicable

Conditions studied: Atrial Fibrillation (AF), Premature Atrial Complexes, Atrial Arrhythmias, Artificial Intelligence (AI), Electrocardiogram

In brief

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.

Key facts

Study ID

NCT06847932

Run by

National Defense Medical Center, Taiwan

People needed

14726

Starts

2025-07-01

Expected to finish

2026-10-01

Last updated by the study team

2025-11-19

Who can join

Age: 0 and older, up to 0. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Patients in the inpatient department or the outpatient department
• Patients need to have at least one electrocardiogram within one year

You may not qualify if…

• Diagnosis of atrial fibrillation/atrial flutter
• History of atrial fibrillation/atrial flutter catheter ablation
• Patients with cardiac implantable electronic devices
• Any documented electrocardiogram showed atrial fibrillation/atrial flutter and pacing rhythm
• History of received rhythm control medications for atrial arrhythmia, including Class I and Class III antiarrhythmic drugs
• Any reasons indicate for anti-coagulant agents, including vitamin K antagonist and non-vitamin K antagonist oral anticoagulant

Where it is running

• Tri-Service General Hospital — Taipei, Taiwan (enrolling)

Full record on ClinicalTrials.gov

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