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

Study acronym: PAMP FA
StatusUnknown
PhaseNot specified
Started
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Record status
This record was last updated October 18, 2024 (before its estimated March 1, 2026 completion). Its status may not reflect the trial's current state.

Record History

  1. Changed Registry marked status Unknown (sponsor has not verified the record since Sep 2024); last known: Not Yet Recruiting
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
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.
Trial Details
NCT Number NCT06647914
Lead Sponsor IRCCS Policlinico S. Donato
Collaborators: Federico II University, Irccs Sdn, Marche Polytechnic university, Ancona, Italy
Conditions Atrial Fibrillation (AF)
Enrollment 322 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov