Observational Study of Sinus Rhythm Mapping in Pulmonary Vein Isolation Naive Patients With Atrial Fibrillation

NCT06098664 | Unknown

• 1 other identifier: Z-2023039
• Study Type: observational
• Target: 60
• Locations: 1 country
• Sites: 1

Brief Summary

Atrial fibrillation (AF) initially starts in a paroxysmal form, which is mainly based on the presence of triggers. Progression of AF is accompanied by structural and electrical remodelling which can typically be described as a progressive change in electrophysiological properties of the myocardium caused by cardiovascular comorbidities and AF itself. This results in complex electrical conduction disorders, which is defined as electropathology. The aim of our study is to evaluate whether an artificial intelligence (AI)-enabled ECG algorithm (on an ECG in Sinus Rhythm) can predict electropathology in patients with AF who undergo a first PVI.

Conditions

Atrial Fibrillation

Keywords

Artificial Intelligence; Deep Neural Network; Electrocardiogram; Pulmonary Vein Isolation

Outcome Measures

Primary Outcomes (1)

• Low voltage area

  Proportion of low voltage area in the left atrium. (Defined as a threshold 0.5mV)

  During atrial voltage mapping, prior to PVI procedure.

Secondary Outcomes (8)

• Transition zone voltage area

  During atrial voltage mapping, prior to PVI procedure.

• Conduction delay

  During atrial voltage mapping, prior to PVI procedure.

• Conduction delay score

  During atrial voltage mapping, prior to PVI procedure.

• Conduction time from sinus node to Bachman bundle

  During atrial voltage mapping, prior to PVI procedure.

• Total LA conduction time

  During atrial voltage mapping, prior to PVI procedure.

Study Arms (3)

Low score group (DNN-score = 0 - 10%)

The inclusions will be stratified to the deep neural network (DNN) score. The study will enrol 20 patients in each group.

Diagnostic Test: AI-enabled ECG score for Atrial Fibrillation (DNN score); Diagnostic Test: Atrial voltage map in sinus rhythm

Medium score group (DNN-score = 10 - 50%)

The inclusions will be stratified to the deep neural network (DNN) score. The study will enrol 20 patients in each group.

Diagnostic Test: AI-enabled ECG score for Atrial Fibrillation (DNN score); Diagnostic Test: Atrial voltage map in sinus rhythm

High score group (DNN-score = 50 - 100%)

The inclusions will be stratified to the deep neural network (DNN) score. The study will enrol 20 patients in each group.

Diagnostic Test: AI-enabled ECG score for Atrial Fibrillation (DNN score); Diagnostic Test: Atrial voltage map in sinus rhythm

Interventions

AI-enabled ECG score for Atrial Fibrillation (DNN score) DIAGNOSTIC_TEST

A 12-lead ECG, performed within 24 hours before the Pulmonary Vein Isolation (PVI) procedure, will be used to calculate the DNN score. (DNN score details: https://doi.org/10.1016/j.jacep.2023.04.008)

High score group (DNN-score = 50 - 100%); Low score group (DNN-score = 0 - 10%); Medium score group (DNN-score = 10 - 50%)

Atrial voltage map in sinus rhythm DIAGNOSTIC_TEST

An atrial voltage map will be constructed prior to the PVI procedure.

High score group (DNN-score = 50 - 100%); Low score group (DNN-score = 0 - 10%); Medium score group (DNN-score = 10 - 50%)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All patients scheduled for a PVI will be consecutively screened and enrolled in the study. The inclusions will be stratified to the DNN score.

You may qualify if:

• Provide signed and dated informed consent.
• First PVI-procedure
• Age is 18 years or higher.
• lead ECG available in SR during the last 14 days.

You may not qualify if:

• Mitral insufficiency of grade 3 or 4.
• Participating in another study that may interfere with participation in this study

Sponsors & Collaborators

• Ziekenhuis Oost-Limburg: lead

Study Sites (1)

Ziekenhuis Oost-Limburg

Genk, Limburg, 3600, Belgium

RECRUITING

MeSH Terms

Conditions

Atrial Fibrillation

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Henri M.P.B.C. Gruwez, MD

CONTACT

+3289212051; henri.gruwez@zol.be

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical professor

Study Record Dates

• First Submitted: October 19, 2023
• First Posted: October 24, 2023
• Study Start: June 26, 2023
• Primary Completion: November 1, 2023
• Study Completion: December 1, 2023
• Last Updated: October 24, 2023

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share

Locations

BE (1)