An observational study in Embolic Stroke of Undetermined Source, sponsored by Inha University Hospital. Recruiting at 5 sites in South Korea. Open to participants aged 30 Years and older. Per ClinicalTrials.gov, last updated 2026-01-16.
Sponsored by Inha University Hospital · Observational
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.
Embolic Stroke of Undetermined Source (ESUS) accounts for a significant proportion of ischemic strokes, and occult Atrial Fibrillation (AF) is considered a major etiology. While Implantable Cardiac Monitors (ICMs) are the gold standard for long-term rhythm monitoring, identifying patients at the highest risk for AF remains a clinical challenge.
This multicenter, prospective study aims to validate the clinical utility of an artificial intelligence-based electrocardiogram analysis algorithm, "SmartECG-AF," in this specific population. The algorithm analyzes 12-lead ECGs recorded during sinus rhythm to detect subtle signs of electrical remodeling associated with paroxysmal AF.
Enrolled patients with ESUS who have undergone ICM implantation will have their baseline ECGs analyzed by the SmartECG-AF algorithm. Based on the AI-generated probability score, patients will be stratified into a "High Risk" group and a "Low to Intermediate Risk" group. The study will longitudinally track these patients to compare the time-to-event for ICM-detected AF between the two groups. Additionally, the study will evaluate the correlation between the AI risk score and the incidence of Major Adverse Cardiovascular Events (MACE), providing evidence for AI-guided risk stratification in cryptogenic stroke management.
Patients diagnosed with Embolic Stroke of Undetermined Source (ESUS) aged 30 years or older who have received or are scheduled to receive an Implantable Cardiac Monitor (ICM). Participants are recruited from five tertiary referral hospitals in South Korea (Inha University Hospital, Jeju National University Hospital, Korea University Guro Hospital, Korea University Ansan Hospital, and Ajou University Hospital).
Exclusion Criteria:
Patients classified as having a high risk of atrial fibrillation by the SmartECG-AF AI algorithm.
Patients classified as having a low to intermediate risk of atrial fibrillation by the SmartECG-AF AI algorithm.
Incidence of Atrial Fibrillation (Time-to-Event)
Comparison of the cumulative incidence rate of atrial fibrillation (AF) events between the High Risk group and the Low to Intermediate Risk group (classified by SmartECG-AF). AF occurrence is confirmed by reviewing data recorded on the Implantable Cardiac Monitor (ICM).
Time frame: Up to 12 months
Incidence of Major Adverse Cardiovascular Events (MACE)
Evaluation of the composite rate of major clinical events including recurrent stroke, hospitalization for heart failure, myocardial infarction, and all-cause death (cardiovascular and non-cardiovascular). The study will analyze the correlation between the occurrence of these events and the AI-predicted risk levels.
Time frame: Up to 12 months
Plan to share: No — Individual participant data will not be shared to protect participant privacy and confidentiality. The informed consent form signed by participants does not include authorization for the release of individual raw data to third parties.
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Inha University Hospital