About
AF is a common heart condition affecting millions of Europeans, significantly impacting quality of life and increasing the risk of stroke and mortality. Despite advancements in medical technology, current treatments often fail to prevent AF recurrence. PERSUADE wants to address this critical challenge by focusing on the underlying causes of AF, specifically targeting the atrial fibrotic substrate. Through a combination of cutting-edge research and clinical expertise, the project aims to develop personalized and effective treatment strategies for AF patients.
Background
Modifications of the atrial substrate can lead to the development of atrial fibrillation (AF), a condition affecting over 10 million Europeans and approximately 0.5% of the global population, equating to more than 37 million individuals worldwide. With its prevalence surging by 33% in the last two decades and a projected increase of over 60% by 2050, AF is rapidly approaching pandemic proportions.
This significant rise in AF cases is accompanied by a substantial increase in stroke risk, mortality rates, and a decline in quality of life. Consequently, AF imposes a considerable societal burden, resulting in substantial financial costs primarily attributed to hospitalization and stroke-related complications. In the United States alone, annual incremental costs of AF care are estimated to reach $26 billion, while in various European countries, AF-related expenditures account for between 0.28% and 2.60% of total healthcare spending.
A deeper understanding of the underlying pathophysiological mechanisms of AF is crucial for improving our ability to identify and target effective treatments. Such advancements would not only enhance therapeutic strategies but also optimize the timing and cost-effectiveness of interventions.
Objectives
- Data harmonization: design structured and standardized approach towards data acquisition, annotation, analysis and integration for objective analyses.
- Creation of multi-center databases, which can be utilized to feed artificial intelligence algorithms.
- Uncover new substrates that are responsible for driving persistent AF, for both patients with and without cardiovascular comorbidities and explicitly addressing the role of the sex of patients from a large data set from different clinical sites using the state-of-the-art computational tools in a secure manner, without compromising patient privacy.
- Identify the main mechanisms underlying AF by studying the synergies at different scales from ionic models up to tissue, and how these interactions relate with the proposed ablation therapy in the presence and absence of anti-arrhythmic drug.
- Identification of biomarkers on clinical recordings linked to therapy outcome based on simulations and AI based tools
- Proof of principle: clinical testing of the new ablation therapy based on hidden/concealed slow conduction on a small sample size of 30 patients with persistent AF.
Approach
WP1 aims to overcome the current limitations due to the lack of standardization in data collection, annotation and processing of AF patients in various medical centers. WP1 will focus on the harmonization of the multi-center dataset and provide a unified platform performing the harmonized (pre-)processing of all available data, which can be used by all consortium partners.
WP2 intents to provide in-silico analysis of the electric behavior of the atria. Data provided by work packages WP1 and WP5 will be used to model the electrical impulse propagation within the atrium. Different mechanistic scenarios will be tested to better characterize regions of slow conduction, and how they relate with ablation in the presence and absence of pharmacological treatment.
WP3 plans to extract quantitative (bio)markers from clinical recordings linked with the therapy response, able to automatically identify potential targets for AF ablation. WP3 will focus on the identification of (bio)markers from clinical and simulated EGMs linked with the underlying pathological mechanism identified in WP2. AI models will be then used in for patient stratification and therapy guidance.
WP4 will oversee patient stratification, selection and recurrence risk assessment. This WP will provide subpopulation-specific risk assessments, stratified on sex, cardiovascular comorbidity burden and AF subtype. We will develop subgroup-specific risk models using data from WP1, WP2 and WP3
WP5 will develop a new technique for functional analysis of electrical activity based on uncovering hidden conduction abnormalities with pacing maneuvers. Based on the clinical protocol proposed on this WP, an electrophysiological study will be performed in patients undergoing PVI procedures.
The results of this study may have an immediate impact on the treatment of persistent atrial fibrillation and it can be extended to those centres that perform the pulmonary vein ablation technique, which is currently the first arrhythmia in number of interventions.
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This project has received funding from the European Union under the umbrella of the Partnership Fostering a European Research Area for Health (ERA4Health) (GA°101095426 of the EU Horizon Europe Research and Innovation Programme)
National and regional funding organizations
