AI-Based Prediction of Atrial Fibrillation in ESUS Patients With ICM
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age30+
SponsorInha University Hospital
About this trial
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.
Eligibility criteria
Qualifiers
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.
Disqualifiers
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.
Trial design
Treatments tested in this trial
- Not listed
Trial groups
92 Participants
are grouped into 2 trial groupsSponsors and collaborators
Inha University Hospital
Lead sponsor
DeepCardio Co., Ltd.
Collaborator
Source ClinicalTrials.gov