Literature DB >> 14760919

Echocardiographic and electrocardiographic predictors for atrial fibrillation recurrence following cardioversion.

Andreas Bollmann1, Daniela Husser, Reiko Steinert, Martin Stridh, Leif Soernmo, S Bertil Olsson, Daniela Polywka, Jochen Molling, Christoph Geller, Helmut U Klein.   

Abstract

INTRODUCTION: Identification of suitable candidates for cardioversion currently is not based on individual electrical and mechanical atrial remodeling. Therefore, this study analyzed the meaning of atrial fibrillatory rate obtained from the surface ECG (as a measure of electrical remodeling) and left atrial size (as measure of mechanical remodeling) for prediction of early atrial fibrillation (AF) recurrence following cardioversion. METHODS AND
RESULTS: Forty-four consecutive patients (26 men and 18 women, mean age 62 +/- 11 years, no antiarrhythmic medication at baseline) with persistent AF were studied. Fibrillatory rate was obtained from high-gain, high-resolution surface ECG using digital signal processing (filtering, QRST subtraction, Fourier analysis) before electrical cardioversion. Univariate and multivariate regression analysis revealed larger systolic left atrial area (Beta = 0.176, P = 0.031) obtained by precardioversion echocardiogram from the apical four-chamber view and higher atrial fibrillatory rate (Beta = 0.029, P = 0.021) to be independent predictors for AF recurrence (n = 13). Stratification based on the regression equation (electromechanical index [EMI] = 0.176 systolic left atrial area + 0.029 fibrillatory rate - 17.674) allowed identification of groups at low, intermediate, or high risk. No patient with an EMI < -1.85 had early AF recurrence, as opposed to 78% with an EMI > -0.25. Intermediate results (40% recurrence rate) were obtained when the calculated EMI ranged between -1.85 and -0.25 (P < 0.001).
CONCLUSION: Fibrillatory rate obtained from the surface ECG and systolic left atrial area obtained by echocardiography may predict early AF recurrence in patients with persistent AF. These parameters might be useful in identifying candidates with a high likelihood of remaining in sinus rhythm after cardioversion.

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Year:  2003        PMID: 14760919     DOI: 10.1046/j.1540.8167.90306.x

Source DB:  PubMed          Journal:  J Cardiovasc Electrophysiol        ISSN: 1045-3873


  15 in total

Review 1.  Atrial Remodelling : Role in Atrial Fibrillation Ablation.

Authors:  Herko Grubitzsch; Wilhelm Haverkamp
Journal:  J Atr Fibrillation       Date:  2012-12-16

Review 2.  The Role of Echocardiography as a Predictor of the Incidence and Progression of Atrial Fibrillation.

Authors:  Rui Providência; Sérgio Barra; Luís Paiva
Journal:  J Atr Fibrillation       Date:  2012-10-06

Review 3.  Role of Left Ventricular Diastolic Dysfunction in Predicting Atrial Fibrillation Recurrence after Successful Electrical Cardioversion.

Authors:  Rowlens M Melduni; Michael W Cullen
Journal:  J Atr Fibrillation       Date:  2012-12-16

4.  Noninvasive localization of maximal frequency sites of atrial fibrillation by body surface potential mapping.

Authors:  Maria S Guillem; Andreu M Climent; Jose Millet; Ángel Arenal; Francisco Fernández-Avilés; José Jalife; Felipe Atienza; Omer Berenfeld
Journal:  Circ Arrhythm Electrophysiol       Date:  2013-02-26

Review 5.  Evaluating the Atrial Myopathy Underlying Atrial Fibrillation: Identifying the Arrhythmogenic and Thrombogenic Substrate.

Authors:  Jeffrey J Goldberger; Rishi Arora; David Green; Philip Greenland; Daniel C Lee; Donald M Lloyd-Jones; Michael Markl; Jason Ng; Sanjiv J Shah
Journal:  Circulation       Date:  2015-07-28       Impact factor: 29.690

6.  A non-invasive method to predict electrical cardioversion outcome of persistent atrial fibrillation.

Authors:  Raúl Alcaraz; José Joaquín Rieta
Journal:  Med Biol Eng Comput       Date:  2008-04-24       Impact factor: 2.602

7.  Predictors of atrial fibrillation recurrence in patients with long-lasting atrial fibrillation.

Authors:  Michalis Efremidis; Ioannis P Alexanian; Dimitrios Oikonomou; Dimitrios Manolatos; Konstantinos P Letsas; Loukas K Pappas; Gerasimos Gavrielatos; Maria Vadiaka; Constantinos C Mihas; Gerasimos S Filippatos; Antonios Sideris; Fotios Kardaras
Journal:  Can J Cardiol       Date:  2009-04       Impact factor: 5.223

8.  A genotype-dependent intermediate ECG phenotype in patients with persistent lone atrial fibrillation genotype ECG-phenotype correlation in atrial fibrillation.

Authors:  Daniela Husser; Martin Stridh; Leif Sörnmo; Dan M Roden; Dawood Darbar; Andreas Bollmann
Journal:  Circ Arrhythm Electrophysiol       Date:  2009-02

9.  P Wave Duration/P Wave Voltage Ratio Plays a Promising Role in the Prediction of Atrial Fibrillation: A New Player in the Game.

Authors:  E Karacop; A Enhos; N Bakhshaliyev; R Ozdemir
Journal:  Cardiol Res Pract       Date:  2021-05-29       Impact factor: 1.866

10.  Prediction of sinus rhythm maintenance following DC-cardioversion of persistent atrial fibrillation - the role of atrial cycle length.

Authors:  Carl J Meurling; Anders Roijer; Johan E P Waktare; Fredrik Holmqvist; Carl J Lindholm; Max P Ingemansson; Jonas Carlson; Martin Stridh; Leif Sörnmo; S Bertil Olsson
Journal:  BMC Cardiovasc Disord       Date:  2006-03-13       Impact factor: 2.298

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