Predicting Disease Progression in Atrial Fibrillation: A Multiparametric Approach for Prognostic Marker Identification and Personalized Patient Management

NCT06647914 | Not Yet Recruiting

• 1 other identifier: PNRR-MCNT2-2023-12378472
• Study Type: observational
• Target: 322
• Locations: 0 countries
• Sites: N/A

Brief Summary

This project leverages artificial intelligence (AI) to decipher Atrial Fibrillation (AF) progression and optimize treatment strategies. By recruiting a diverse cohort of 322 AF patients, we will gather a robust multiparametric dataset including clinical, genetic, electrocardiographic, and echocardiographic data. Harnessing AI, we will extract and correlate hidden components within ECG-obtained P-wave data and echocardiographic studies with atrial fibrosis, culminating in an atrial fibrosis score (AFS). The AFS will non-invasively predict fibrosis extent and AF clinical progression, including metrics like rehospitalization, cardiac morbidity, and mortality. Ultimately, this endeavor aims to improve AF patient management, significantly reducing healthcare costs, and enhancing patient quality of life.

Conditions

Atrial Fibrillation (AF)

Outcome Measures

Primary Outcomes (1)

• A composite clinical point used to evaluate the Atrial Fibrosis Score prognostic capability

  The clinical endpoint will be composed by rehospitalization, cardiac morbidity and total mortality data

  Partecipants will be assessed at the baseline and at 6 months and 12 months time points. The AFS Prediction Model Testing will start at 9 months after the beginning of the patients enrollment.

Eligibility Criteria

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

Study Population

Patients will be recruited at the two Clinical Institution of I.R.C.C.S. Policlinico San Donato and Federico II University of Naples, with the same study protocol approved by the Institutional Board of the respective Institution.

You may qualify if:

• History of paroxysmal or persistent atrial fibrillation
• Clinical indication for Atrial Fibrosis (AF) ablation according to the 2020 ESC Guidelines

You may not qualify if:

• Age below 18 years old
• Refusal to sign consent
• Noncompliance with the study protocol

Sponsors & Collaborators

• IRCCS Policlinico S. Donato: lead
• Federico II University: collaborator
• Irccs Sdn: collaborator
• Marche Polytechnic university, Ancona, Italy: collaborator

Biospecimen

Retention: SAMPLES WITH DNA

Blood samples

MeSH Terms

Conditions

Atrial Fibrillation

Condition Hierarchy (Ancestors)

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

Central Study Contacts

Carlo Pappone, MD, PHD, FACC

CONTACT

+39-0252774260; carlo.pappone@af-ablation.org

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 24 Months
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 16, 2024
• First Posted: October 18, 2024
• Study Start: September 3, 2025
• Primary Completion: March 1, 2026
• Study Completion (Estimated): August 31, 2026
• Last Updated: October 18, 2024

Record last verified: 2024-09