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Recruiting NCT07217236

Proactive Risk Evaluation for Cardiac Implantable Electronic Device Strategy Using AI-ECG

No phase Interventional Artificial Intelligence (AI) Cardiac Implantable Electrical Devices Conduction Disorder of the Heart

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI-ECG driven ECG monitoring.
Who it may be relevant to
Registry conditions: Artificial Intelligence (AI), Cardiac Implantable Electrical Devices, Conduction Disorder of the Heart. Basic parameters: 65 years — 90 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Taiwan
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Evaluation of an Artificial Intelligence-Enhanced Electrocardiogram Strategy Versus Standard Care to Identify Patients Requiring Cardiac Implantable Electronic Devices: A Randomized Controlled Trial

Overview

The goal of this clinical trial is to learn whether an artificial intelligence-enhanced electrocardiogram (AI-ECG) strategy improves timely intervention of patients requiring cardiac implantable electronic devices (CIEDs), compared with standard clinical care.

Detailed description

This is a randomized controlled trial designed to evaluate the impact of an AI-ECG strategy on the identification of patients requiring CIEDs. The ECGs of eligible participants will be analyzed by a previously validated deep learning algorithm. Those classified as high-risk by the AI-ECG system will be allocated at random into either the intervention group or the control group.

In the intervention group, the physicians will be alerted by the AI-ECG system, and the participants will be proactively contacted to receive ambulatory continuous ECG monitoring for up to 7 days. In the control group, the participants will continue with usual clinical care, and treating physicians will not have access to the AI-ECG results before the end of this study. To ensure accuracy, the reference standards for device indications will be performed by a panel of experienced cardiologists without access to the AI-generated reports.

Interventions

  • Diagnostic test AI-ECG driven ECG monitoring
    Participants identified as high-risk for CIED implantation by the AI-ECG system will receive a continuous cardiac rhythm monitor for up to 7 days.

Primary outcome measures

  • CIED implantation [Time frame: Within 180 days after randomization]
Secondary outcome measures (6)
  • Number of High-Grade Atrioventricular Block [Time frame: Within 90 days after randomization]
  • Number of Complete Atrioventricular Block [Time frame: Within 90 days after randomization]
  • Number of Sick Sinus Syndrome [Time frame: Within 90 days after randomization]
  • Number of Ventricular Arrhythmia [Time frame: Within 90 days after randomization]
  • Adverse Events Related to Continuous ECG Monitoring [Time frame: Within 90 days after randomization.]
  • Number of CIED-Related Complications [Time frame: Within 90 days after randomization.]

Eligibility criteria

Inclusion criteria

  • At least one 12-lead ECG within 1 year

Exclusion criteria

  • Diagnosis of sick sinus syndrome
  • Diagnosis of high-grade or complete atrioventricular block
  • Diagnosis of ventricular tachycardia or ventricular fibrillation
  • Post CIED implant
  • Heart rate below 40 beats per minute by 12-lead ECG

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Screening

Study locations

Taiwan · 1 center
  • Tri-Service General Hospital — Taipei

Identifiers

NCT: NCT07217236 · TSGH-AIECG-CIED

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗