Clinical Validation of SMD-RVECG for Predicting Atrial Fibrillation With Rapid Ventricular Response Within 2 Hours

Sponsor
HUINNO Co., Ltd
Study ID
NCT07722039
Status
Not Yet Recruiting

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Conditions

  • Atrial Fibrillation (AF)
  • Atrial Fibrillation With Rapid Ventricular Response

Eligibility Criteria

Sex
ALL
Age
19 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • SMD-RVECG — DEVICE
    SMD-RVECG is an artificial intelligence-based software as a medical device designed to analyze continuous single-lead electrocardiogram data and estimate the risk of atrial fibrillation with rapid ventricular response occurring within 2 hours. The software generates a risk score ranging from 0 to 100 based on electrocardiogram signal characteristics. In this retrospective study, blinded electrocardiogram datasets identified only by screening numbers will be analyzed using SMD-RVECG. The software-generated risk scores, peak values, and corresponding times will be recorded and compared with the reference-standard classifications. The software will not be used to guide the clinical care of the patients whose data are included.

Study Details

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.

Key Dates

First listed
Jul 23, 2026
Start date
Oct 1, 2026
Status verified
Jul 2026
Primary completion
Nov 30, 2026
Completion
Dec 31, 2026

Study Design

Enrollment
348 participants (estimated)

Arms

  • Arm: AF With RVR Positive Group
    Electrocardiogram datasets from patients with atrial fibrillation in which rapid ventricular response occurred. Rapid ventricular response is defined as an average heart rate of 110 beats per minute or greater for at least 30 seconds. The dataset includes electrocardiogram data preceding the first onset of rapid ventricular response and data following the episode in accordance with the protocol. These datasets will be retrospectively analyzed using SMD-RVECG.
  • Arm: AF With RVR Negative Group
    Electrocardiogram datasets from patients with atrial fibrillation in which rapid ventricular response did not occur during the predefined assessment period. The dataset includes electrocardiogram data from the 3 hours preceding a selected index time corresponding to a similar time during hospitalization as the onset time used for positive cases. These datasets will be retrospectively analyzed using SMD-RVECG.

Primary Outcome Measure

AUROC of SMD-RVECG for Predicting Atrial Fibrillation With Rapid Ventricular Response Within 2 Hours [ Time Frame: During retrospective analysis of the predefined electrocardiogram dataset for each case, up to 3 hours ]

Central Contacts

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