AI heart tracing to predict irregular heartbeat after unexplained stroke
Studies an AI tool reading heart tracings to predict atrial fibrillation after stroke.
Plain-language title generated from the registry record
Registry title: AI-Based Prediction of Atrial Fibrillation in ESUS Patients With ICM
Key facts
- Where
- Ansan, Incheon, Jeju City, Seoul, and Suwon, South KoreaSee the 5 sites
Where in South Korea
- Korea University Ansan HospitalAnsan, South KoreaTaking people
- Inha University HospitalIncheon, South KoreaTaking people
- Jeju National University HospitalJeju City, South KoreaTaking people
- Korea University Guro HospitalSeoul, South KoreaTaking people
- Ajou University HospitalSuwon, South KoreaTaking people
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
- Inha University Hospital
- Trial code
- NCT07347691
- Record updated
- 16 January 2026
- Original description
This study investigates patients with Embolic Stroke of Undetermined Source (ESUS) who have received an Implantable Cardiac Monitor (ICM). The main purpose is to evaluate the predictive value of an Artificial Intelligence ECG analysis tool, named SmartECG-AF.Read full original descriptionShow less
Predicting Atrial Fibrillation in Patients With Post-implantable Cardiac Monitor Implementation : A Prospective, Long-term Follow-up Study Using Comprehensive AI ECG Analysis : Multicenter Prospective Study
This study investigates patients with Embolic Stroke of Undetermined Source (ESUS) who have received an Implantable Cardiac Monitor (ICM). The main purpose is to evaluate the predictive value of an Artificial Intelligence ECG analysis tool, named SmartECG-AF.
Participants will be classified into two groups based on the AI analysis: a "High Risk" group and a "Low to Intermediate Risk" (control) group. The study aims to compare the incidence rate of atrial fibrillation (AF) events over time between these two groups. Additionally, the study will analyze the relationship between the AI-predicted risk levels and the occurrence of major cardiovascular events during the follow-up period.
Inclusion: Patients aged 30 years or older; Patients diagnosed with Embolic Stroke of Undetermined Source (ESUS) who have undergone or are scheduled for Implantable Cardiac Monitor (ICM) implantation; Patients who have undergone at least one 12-lead ECG examination within 2 weeks before or after the date of ICM implantation; Patients maintaining Sinus Rhythm on ECG at the time of enrollment; Patients who have voluntarily signed the informed consent form.
Exclusion: Patients diagnosed with Atrial Fibrillation (AF) at least once prior to the date of enrollment; Patients whose ICM battery status is at Elective Replacement Interval (ERI), making recording impossible; Patients whose ECGs cannot be analyzed by the AI algorithm (SmartECG-AF) due to severe artifacts or noise, or are incompatible with digital analysis.