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

Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development: a Randomized Control Trial

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.

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