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
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 92
- 试验地点
- 5
- 主要终点
- Incidence of Atrial Fibrillation (Time-to-Event)
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 30 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
研究组 & 干预措施
High Risk Group
Patients classified as having a high risk of atrial fibrillation by the SmartECG-AF AI algorithm.
Low to Intermediate Risk Group
Patients classified as having a low to intermediate risk of atrial fibrillation by the SmartECG-AF AI algorithm.
结局指标
主要结局
Incidence of Atrial Fibrillation (Time-to-Event)
时间窗: Up to 12 months
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).
次要结局
- Incidence of Major Adverse Cardiovascular Events (MACE)(Up to 12 months)
研究者
Yong-Soo Baek
Professor
Inha University Hospital