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

NCT07722039 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 348

Last updated 2026-07-23

No results posted yet for this study

Summary

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.

Conditions

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

Interventions

DEVICE

SMD-RVECG

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.

Sponsors & Collaborators

  • Seoul National University Hospital

    collaborator OTHER

  • Korea Medical Device Development Fund

    collaborator OTHER

  • HUINNO Co., Ltd

    lead INDUSTRY

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-10-01
Primary Completion
2026-11-30
Completion
2026-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07722039 on ClinicalTrials.gov