Erschienen in:
01.01.2013 | Original Paper
Analysis of electrical and mechanical left atrial properties in patients with persistent atrial fibrillation
verfasst von:
Anna Degiovanni, Miriam Bortnik, Gabriele Dell’Era, Virginia Bolzani, Eraldo Occhetta, Giorgio Bellomo, Paolo Marino
Erschienen in:
The International Journal of Cardiovascular Imaging
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Ausgabe 1/2013
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Abstract
The study of left atrial (LA) mechanical function during atrial fibrillation (AFib) can provide valuable information, particularly if such profiling is related to the cavity electrical substrate and conveys prognostic information. To assess if there is any relation between LA mechanical and electrical asynchrony and if such evaluation can be of interest in stratifying AFib patients. 50 patients with persistent AFib who underwent electrical cardioversion (CV) were evaluated with pre-CV atrial electrograms (AEGs). Electrical asynchrony was classified according to Wells’ patterns of AEGs, ranging from most organized (I) to most dispersed (III) one. LA mechanical asynchrony was addressed by transthoracic 2D-speckle-tracking echo and quantified according to time-to-peak standard deviation (TP-SD) of wall strains and their peak values (PS) before CV, after 24 h, at 1 month. Pre-CV a linear, inverse relation between TP-SD and PS (p < 0.001) and a direct linear relation between TP-SD and Wells’ classes (p = 0.04) were observed. With sinus rhythm TP-SD decreased (p = 0.023) and PS increased (p < 0.001), suggesting improved LA mechanical milieu. A multivariate analysis, testing the effects of baseline variables in predicting post-CV recurrence of AFib, revealed that amount of TP-SD variation pre/24 h post-CV was the only independent predictor at 6 months (p = 0.046). Speckle tracking-derived LA parameters can describe LA wall forces during AFib, categorizing the asynchronous mechanistic profile of AFib that correlates with the degree of the dispersed LA electrical activity. The amount of changes in LA mechanical asynchrony pre/post-CV seems to have prognostic relevance in predicting SR maintenance.