AI-Based Prediction of Atrial Fibrillation in ESUS Patients With ICM

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

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07347691

Acronym

SMART-ESUS

Enrollment

Registered

2026-01-16

Start date

2025-11-19

Completion date

2028-05-01

Last updated

2026-01-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Embolic Stroke of Undetermined Source

Keywords

Implantable Cardiac Monitor, Artificial Intelligence, Deep Learning, Electrocardiography, Risk Prediction, Cryptogenic Stroke

Brief summary

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.

Detailed description

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

30 Years to No maximum

Healthy volunteers

Inclusion criteria

* 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 criteria

* 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.

Design outcomes

Primary

Measure	Time frame	Description
Incidence of Atrial Fibrillation (Time-to-Event)	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).

Secondary

Measure	Time frame	Description
Incidence of Major Adverse Cardiovascular Events (MACE)	Up to 12 months	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.

Countries

South Korea

Contacts

CONTACTYong-Soo Baek, MD, PhD

existsoo@inha.ac.kr+82-32-890-2200

CONTACTHyoung Seok Lee, MD

hyoungseok_lee@inha.ac.kr+82-32-890-3575

PRINCIPAL_INVESTIGATORYong-Soo Baek, MD, PhD

Inha University Hospital

Outcome results