Schnabel, Renate B 
ORCID: 0000-0001-7170-9509, Marinelli, Elena Andreassi, Arbelo, Elena, Boriani, Giuseppe, Boveda, Serge, Buckley, Claire M ORCID: 0000-0002-3174-7022, Camm, A John, Casadei, Barbara ORCID: 0000-0002-6801-1617, Chua, Winnie, Dagres, Nikolaos et al (show 66 more authors)
(2023)
Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference.
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 25 (1).
pp. 6-27.
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Abstract
Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Humans, Atrial Fibrillation, Early Diagnosis, Consensus, Cognition, Artificial Intelligence, Stroke |
| Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 02 Oct 2023 10:39 |
| Last Modified: | 02 Oct 2023 10:39 |
| DOI: | 10.1093/europace/euac062 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3173290 |
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