AI-Guided Heart Rhythm Monitoring to Find Hidden Atrial Fibrillation After Stroke
Tests AI-guided heart rhythm monitoring for hidden atrial fibrillation in adults after ischemic stroke.
Plain-language title generated from the registry record
Registry title: AI-Assisted Workflow for Occult Atrial Fibrillation Detection After Ischemic Stroke: A Prospective Randomized Trial
Key facts
- Where
- Taipei, TaiwanSee the site
Where in Taiwan
- National Taiwan University HospitaTaipei, TaiwanNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- National Taiwan University Hospital
- Trial code
- NCT07540065
- Record updated
- 20 April 2026
- Original description
We hypothesize that an AI-guided AF risk stratification approach, particularly when combined with intensified rhythm monitoring using wearable devices and extended ECG patches, will significantly increase AF detection rates compared with standard care. By enabling earlier identification of patients who may benefit from anticoagulation therapy, this strategy has the potential to improve clinical outcomes while minimizing unnecessary exposure to anticoagulant-related bleeding risks. Ultimately, this trial seeks to provide robust clinical evidence supporting the integration of AI-assisted ECG analysis into routine post-stroke care, advancing precision medicine and optimizing resource allocation for patients with ischemic stroke.Read full original descriptionShow less
AI-Assisted Workflow for Occult Atrial Fibrillation Detection After Ischemic Stroke: A Prospective Randomized Trial
We hypothesize that an AI-guided AF risk stratification approach, particularly when combined with intensified rhythm monitoring using wearable devices and extended ECG patches, will significantly increase AF detection rates compared with standard care. By enabling earlier identification of patients who may benefit from anticoagulation therapy, this strategy has the potential to improve clinical outcomes while minimizing unnecessary exposure to anticoagulant-related bleeding risks. Ultimately, this trial seeks to provide robust clinical evidence supporting the integration of AI-assisted ECG analysis into routine post-stroke care, advancing precision medicine and optimizing resource allocation for patients with ischemic stroke.
Inclusion: 18 years or older who are acutely hospitalized due to ischemic stroke; A 12-lead electrocardiogram upon admission showing sinus rhythm.
Exclusion: Previous diagnosis of atrial fibrillation or flutter; Pre-existing cardiac implantable electronic device (IVD); Known contraindications to non-vitamin K antagonist oral anticoagulants due to comorbidities, including but not limited to end-stage renal disease, severe mitral stenosis due to rheumatic heart disease, or metallic heart valves; Diagnosis of atrial fibrillation during hospitalization; Expected inability to attend regular outpatient follow-ups after discharge, or to undergo multiple 14-day ECG recordings; Requires long-term anticoagulant use for other reasons, including but not limited to chronic pulmonary embolism; Unwilling to sign a participant consent form.