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

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

Recruiting
40-85 years
All
Phase N/A

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Overview

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

Inclusion Criteria:

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

Exclusion Criteria:

  • 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

Study details
    Atrial Fibrillation (AF)
    Premature Atrial Complexes
    Atrial Arrhythmias
    Artificial Intelligence (AI)
    Electrocardiogram

NCT06847932

National Defense Medical Center, Taiwan

31 January 2026

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