Browsing by Author "Shah, Dipen (7402371395)"

Atrial fibrillation (AF) is the commonest cardiac rhythm disorder. Evaluation of patients with AF requires an electrocardiogram, but imaging techniques should be considered for defining management and driving treatment. The present document is an expert consensus from the European Association of Cardiovascular Imaging (EACVI) and the European Heart Rhythm Association. The clinical value of echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), and nuclear imaging in AF patients are challenged. Left atrial (LA) volume and strain in echocardiography as well as assessment of LA fibrosis in CMR are discussed. The value of CT, especially in planning interventions, is highlighted. Fourteen consensus statements have been reached. These may serve as a guide for both imagers and electrophysiologists for best selecting the imaging technique and for best interpreting its results in AF patients. © 2016 Published on behalf of the European Society of Cardiology.

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Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and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. © 2022 The Author(s). Published by Oxford University Press on behalf of European Society of Cardiology.