The echocardiogram should be performed in the patients with atrial fibrillation to detect cardiac structurally abnormality and assess left ventricular systolic and diastolic functions. Parameters that reflect left atrium (LA) size such as LA dimension and LA volume have been proposed as predictors of success of the radiofrequency catheter ablation. The transthoracic echocardiogram can provide useful information to guide the management of atrial fibrillation, but cannot exclude thrombus in the left atrial appendage (LAA). The transesophageal echocardiography must be used to rule out intra LA thrombus especially prior to cardioversion and the radiofrequency catheter ablation. The smoke-like echo and sludge in the LA or LAA and the decreased LAA flow velocity are associated with high risk for LA thrombus.
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Heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF) are increasingly prevalent cardiovascular conditions, particularly among the elderly population. These two conditions share common risk factors and often coexist, leading to a complex interplay that alters the clinical course of each other. The pathophysiology of HFpEF is multifaceted and intricately linked, with atrial disease serving as a common pathophysiological pathway.
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Second Department of Internal Medicine, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan.
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Division of Respirology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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January 2025
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, PR China. Electronic address:
Background And Objective: Atrial fibrillation (AF) is a significant cause of life-threatening heart disease due to its potential to lead to stroke and heart failure. Although deep learning-assisted diagnosis of AF based on ECG holds significance in clinical settings, it remains unsatisfactory due to insufficient consideration of noise and redundant features. In this work, we propose a novel multiscale feature-enhanced gating network (MFEG Net) for AF diagnosis.
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