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A Study on the Clinical Application of Causes in Patients with Unidentified Causes Using Artificial Intelligence ECG Algorithm

Predicting atrial fibrillation in patients with post-implantable cardiac monitor implementation : A prospective, Long-term follow-up study using comprehensive AI ECG analysis : multicenter prospective study

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0011697
Enrollment
92
Registered
2026-03-09
Start date
2025-11-19
Completion date
Unknown
Last updated
2026-03-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

None listed

Sponsors

Inha University Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. More than 30 years old 2. A patient is diagnosed with an image color (ESUS) to insert an image color (ICM). 3. Based on the ICM insertion date, 12 lead ECG tests within two weeks 4. According to registration date of registration rhythm (Sinus Rhythm) based on registration date 5. a patient who signed in the consent form

Exclusion criteria

Exclusion criteria: 1. Patients diagnosed with atrial fibrillation more than once on previous ECG as of enrollment date 2. Patients who are no longer able to record due to the ICM's electrical replacement interval (ERI) 3. As judged by the researchers, the ECG performed by an electrocardiogram machine that cannot be analyzed with AI ECG (SmartECG-AF) or is not compatible with digital analysis due to severe artifacts or noise

Design outcomes

Primary

MeasureTime frame
Difference in the cumulative incidence rate of atrial fibrillation events over time between the high-risk group and the control group predicted by AI ECG

Secondary

MeasureTime frame
Incidence of major adverse cardiovascular events (recurrent stroke, hospitalization for heart failure, myocardial infarction, and all-cause death)

Countries

Korea, Republic of

Contacts

Public Contacthyerim park

Inha University Hospital

rimvely1126@naver.com+82-32-890-2555

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Mar 20, 2026