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Clinical Validation of SMD-AFECG for Predicting New-Onset Atrial Fibrillation Within 2 Hours Using Single-Lead ECG Data
Sponsor: HUINNO Co., Ltd
Summary
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.
Official title: A Retrospective, Single-Center, Single-Arm, Superiority Confirmatory Study to Evaluate the Clinical Validity of SMD-AFECG, Artificial Intelligence Software to Predict the Risk of Atrial Fibrillation, Including First Episode Within 2 Hours, Using Single-Lead-Based Electrocardiogram Analysis
Key Details
Gender
All
Age Range
19 Years - Any
Study Type
OBSERVATIONAL
Enrollment
797
Start Date
2026-10-01
Completion Date
2026-12-31
Last Updated
2026-07-23
Healthy Volunteers
No