Clinical trials

The purpose of this retrospective study is to evaluate the clinical performance of SMD-AFECG, an artificial intelligence-based medical device software that predicts the risk of atrial fibrillation occurring within 2 hours using single-lead electrocardiogram data. A total of 797 eligible electrocardiogram datasets collected through VitalDB at Seoul National University Hospital will be included. The performance of SMD-AFECG will be evaluated separately for new-onset atrial fibrillation in patients without a previous history of atrial fibrillation (NOAF) and atrial fibrillation episodes in patients with a previous history of atrial fibrillation (RAF). Two physicians blinded to the software results will review the electrocardiogram data and relevant medical records to establish the reference-standard classification. The blinded electrocardiogram datasets will then be analyzed using SMD-AFECG, and the software-generated predictions will be compared with the reference standard to evaluate the area under the receiver operating characteristic curve for NOAF and RAF.

The purpose of this retrospective study is to evaluate the clinical performance of SMD-RVECG, an artificial intelligence-based medical device software that analyzes single-lead electrocardiogram data to predict the risk of atrial fibrillation with rapid ventricular response occurring within 2 hours. A total of 348 eligible electrocardiogram datasets collected through VitalDB at Seoul National University Hospital will be included. Atrial fibrillation with rapid ventricular response is defined in this study as atrial fibrillation accompanied by an average heart rate of 110 beats per minute or greater for at least 30 seconds. Eligible datasets will be classified as positive or negative for atrial fibrillation with rapid ventricular response. Two qualified physicians blinded to the software results will review the electrocardiogram data and relevant medical records to establish the reference-standard classification. The blinded electrocardiogram datasets will then be analyzed using SMD-RVECG, and the software-generated predictions will be compared with the reference standard to evaluate clinical performance.

Background: Atrial fibrillation (AF) is the most common arrhythmia, significantly contributing to complications such as stroke, heart failure, dementia, and increased mortality. Catheter ablation is widely used for treatment, but recurrence rates range from 15-50% within 12 months post-procedure. Conventional intermittent ECG monitoring lacks sufficient sensitivity to detect asymptomatic AF recurrence effectively. Objective: To compare the recurrence rates of atrial tachyarrhythmias between a 1-day monitoring group and a 14-day monitoring group using MEMO Patch 2 after catheter ablation in AF patients. The study also evaluates the effectiveness and safety of early recurrence detection via remote monitoring. Study Population: Patients diagnosed with AF and treated with catheter ablation. Intervention: Participants will undergo three sessions of remote ECG monitoring using MEMO Patch 2 and MEMO Link (first session only), spanning approximately one year after catheter ablation. Hypothesis: Long-term monitoring with MEMO Patch 2 will be more effective than 1-day monitoring in detecting the recurrence of atrial tachyarrhythmias (including AF, atrial flutter, and atrial tachycardia) following catheter ablation.