Literature DB >> 17100673

Evaluating fluctuations in human atrial fibrillatory cycle length using monophasic action potentials.

Sanjiv M Narayan1, David E Krummen, Andrew M Kahn, Pamela L Karasik, Michael R Franz.   

Abstract

OBJECTIVE: To study fluctuations in intracardiac atrial fibrillation (AF) cycle length (CL).
BACKGROUND: Sites of short AF CL may be good ablation targets, and cycle lengthening predicts ablation success. However, the optimum method for measuring AF CL, and its stability, are unclear. We hypothesized that autocorrelation better estimates AF CL than spectral dominant frequency (DF), which is susceptible to double counting, using monophasic action potentials (MAPs) to separate atrial activation from artifact.
METHODS: In 28 patients with paroxysmal or persistent AF, we analyzed 49 AF epochs using MAPs at the high (HRA) and low (LRA) right atrium. We estimated AF CL over 2 seconds, 10 seconds, and 2 minutes using spectral DF and autocorrelation in MAPs and filtered bipoles.
RESULTS: In the HRA, manually measured CL was 167 +/- 25 ms. Spectral DF poorly estimated AF CL in bipolar signals (R = 0.31; P = NS), due to double counting, but accurately estimated MAP CL (R = 0.73, P < 0.001). Autocorrelation estimated MAP (R = 0.92; P < 0.001) and bipolar (R = 0.83; P < 0.001) CL, with lower errors than spectral DF (P < 0.0001). Over time, changes in DF consistently preceded reciprocal changes in organization (P < 0.001). Finally, excluding inaccurate spectra, DF and AF organization differed between HRA and LRA over 2 seconds, but correlated over 10 seconds and 2 minutes (P < 0.05).
CONCLUSIONS: AF CL is better estimated by autocorrelation than spectral DF, particularly for bipoles, and stable when measured for >10 seconds. Notably, changes in AF CL preceded reciprocal changes in organization, yet changes in organization did not precede changes in AF CL. These results may help to interpret AF CL fluctuations.

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Year:  2006        PMID: 17100673     DOI: 10.1111/j.1540-8159.2006.00525.x

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


  22 in total

1.  Clinical mapping approach to diagnose electrical rotors and focal impulse sources for human atrial fibrillation.

Authors:  Sanjiv M Narayan; David E Krummen; Wouter-Jan Rappel
Journal:  J Cardiovasc Electrophysiol       Date:  2012-04-26

Review 2.  Dynamics factors preceding the initiation of atrial fibrillation in humans.

Authors:  Sanjiv M Narayan; David E Krummen
Journal:  Heart Rhythm       Date:  2008-01-29       Impact factor: 6.343

Review 3.  Rotors as drivers of atrial fibrillation and targets for ablation.

Authors:  Amir A Schricker; Gautam G Lalani; David E Krummen; Sanjiv M Narayan
Journal:  Curr Cardiol Rep       Date:  2014-08       Impact factor: 2.931

Review 4.  Mapping and Ablation of Rotational and Focal Drivers in Atrial Fibrillation.

Authors:  Junaid Zaman; Tina Baykaner; Sanjiv M Narayan
Journal:  Card Electrophysiol Clin       Date:  2019-12

5.  Comparison of spectral estimators for characterizing fractionated atrial electrograms.

Authors:  Edward J Ciaccio; Angelo B Biviano; Hasan Garan
Journal:  Biomed Eng Online       Date:  2013-07-16       Impact factor: 2.819

6.  Atrial electromechanical cycle length mapping in paced canine hearts in vivo.

Authors:  Alexandre Costet; Ethan Bunting; Julien Grondin; Alok Gambhir; Elisa E Konofagou
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2015-07       Impact factor: 2.725

Review 7.  The role of rotors in atrial fibrillation.

Authors:  David E Krummen; Vijay Swarup; Sanjiv M Narayan
Journal:  J Thorac Dis       Date:  2015-02       Impact factor: 2.895

8.  Getting to the core of AF irregularity: are we there yet?

Authors:  Rajeev Joshi; Amir A Schricker; David E Krummen; Sanjiv M Narayan
Journal:  J Cardiovasc Electrophysiol       Date:  2012-12-17

9.  Non-invasive identification of stable rotors and focal sources for human atrial fibrillation: mechanistic classification of atrial fibrillation from the electrocardiogram.

Authors:  Aled R Jones; David E Krummen; Sanjiv M Narayan
Journal:  Europace       Date:  2013-02-28       Impact factor: 5.214

10.  Centrifugal gradients of rate and organization in human atrial fibrillation.

Authors:  David E Krummen; Kevin A Peng; John R Bullinga; Sanjiv M Narayan
Journal:  Pacing Clin Electrophysiol       Date:  2009-09-10       Impact factor: 1.976

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