Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

Petersson, Richard; Sandberg, Frida; Platonov, Pyotr G.; Holmqvist, Fredrik

doi:10.1016/j.jelectrocard.2010.10.033

Cited by 9 publications

(4 citation statements)

References 23 publications

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“…Furthermore, f-waves detected from the surface ECG may represent less localized atrial signals compared to an invasive electrophysiology study using bipolar electrodes that detect electrical activity within a very small distance, and the 12-leads can reflect signals obtained from various axes and directions of the atrium. Due to these advantages, previous studies have compared the characteristics of f-waves and the clinical outcome of rhythm control after cardioversion findings, and recent reports have noted that the AF rate (AFR) 27 , AF signal entropy (AFSE) 28,29 , and harmonic decay 27 are independent factors of AF recurrences within 4 weeks after cardioversion.…”

Section: Discussionmentioning

confidence: 99%

Early differentiation of long-standing persistent atrial fibrillation using the characteristics of fibrillatory waves in surface ECG multi-leads

Park

Lee

Leshem

et al. 2019

Sci Rep

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We characterized the f-waves in atrial fibrillation (AF) in the surface ECG by quantifying the amplitude, irregularity, and dominant rate of the f-waves in leads II, aVL, and V 1 , and investigated whether those parameters of the f-waves could discriminate long-standing persistent AF (LPeAF) from non-LPeAF. A total of 224 AF patients were enrolled: 112 with PAF (87 males), 48 with PeAF (38 males), and 64 with LPeAF (47 males). The f-waves in surface ECG leads V 1 , aVL, and II, which reflect well electrical activity in the right atrium (RA), the left atrium (LA), and both atria, respectively, were analyzed. The f-waves for LPeAF had lower amplitudes in II and aVL, increased irregularity and a higher dominant rate in II and V 1 compared to PAF and PeAF (all p < 0.02). In a multivariate analysis, a low amplitude in lead II (<34.6 uV) and high dominant rate in lead V 1 (≧390/min) (p < 0.00 1 ) independently discriminated LPeAF from the other AF types. The f-waves combined with both a low amplitude in lead II and high dominant rate in lead V 1 were significantly associated with LPeAF (OR 6.27, p < 0.001). Characteristics of the f-waves on the surface ECG could discriminate LPeAF from other types of AF.

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Section: Discussionmentioning

confidence: 99%

Early differentiation of long-standing persistent atrial fibrillation using the characteristics of fibrillatory waves in surface ECG multi-leads

Park

Lee

Leshem

et al. 2019

Sci Rep

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“…Another study showed that a longer AF cycle length on lead V1 was associated with favourable acute and long-term outcome after catheter ablation 16. Although these results seem promising, some studies using DF or SampleEn showed a lower predictive value for outcome after DCC for persistent AF 23 31. In another study low DF correlated with successful DCC but not with recurrence of AF during 6 months follow-up 32.…”

Section: Ecg Guiding Rhythm Control Strategiesmentioning

confidence: 99%

The ECG as a tool to determine atrial fibrillation complexity

Lankveld

Zeemering

Crijns

et al. 2014

Heart

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The use of the ECG for atrial fibrillation (AF) in clinical daily practice is still limited to its diagnosis. Recent research shows however that ECG-derived parameters can also be used to assess the spatiotemporal properties of AF. Specifically, the complexity of the f-waves in the ECG reflects the complexity of the fibrillatory conduction during AF and therefore can be used for quantification of the degree of electrophysiological alterations in the atria. This information might be useful for guiding AF therapy and might form the basis for classification of AF. This review focuses on technical and mathematical aspects of ECG-based atrial complexity assessment and its potential ability to guide treatment strategies.

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“…Spectral analysis has been used, among others, to identify sites of high-frequency activity maintaining AF [27]. On the other hand, entropy measurements have been used either to predict spontaneous termination of paroxysmal AF [21] or as a predictor for sinus rhythm maintenance following electrical cardioversion [1,24]. Entropy can be described as a statistical analysis technique to characterize time-domain non-linear dynamics, and can be employed to retrieve information related to the irregularity or disorganization of a signal.…”

Section: Introductionmentioning

confidence: 99%

Entropy at the right atrium as a predictor of atrial fibrillation recurrence outcome after pulmonary vein ablation

Cervigón¹,

Moreno

Quintanilla

et al. 2016

Biomedical Engineering / Biomedizinische Technik

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Atrial fibrillation (AF) recurrence rates after successful ablation procedures are still high and difficult to predict. This work studies the capability of entropy measured from intracardiac recordings as an indicator for recurrence outcome. Intra-atrial recordings from 31 AF patients were registered previously to an ablation procedure. Four electrodes were located at the right atrium (RA) and four more at the left atrium (LA). Sample entropy measurements were applied to these signals, in order to characterize different non-linear AF dynamics at the RA and LA independently. In a 3 months follow-up, 19 of them remained in sinus rhythm, whereas the other 12 turned back to AF. Entropy values can be associated to a proarrhythmic indicator as they were higher in patients with AF recurrence (1.11±0.15 vs. 0.91±0.13), in persistent patients (1.03±0.19 vs. 0.96±0.15), and at the LA with respect to the RA (1.03±0.23 vs. 0.89±0.15 for paroxysmal AF patients). Furthermore, entropy values at the RA arose as a more reliable predictor for recurrence outcome than at the LA. Results suggest that high entropy values, especially at the RA, are associated with high risk of AF recurrence. These findings show the potential of the proposed method to predict recurrences post-ablation, providing additional insights to the understanding of arrhythmia.

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Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

Cited by 9 publications

References 23 publications

Early differentiation of long-standing persistent atrial fibrillation using the characteristics of fibrillatory waves in surface ECG multi-leads

Early differentiation of long-standing persistent atrial fibrillation using the characteristics of fibrillatory waves in surface ECG multi-leads

The ECG as a tool to determine atrial fibrillation complexity

Entropy at the right atrium as a predictor of atrial fibrillation recurrence outcome after pulmonary vein ablation

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