[Non-invasive characterization of atrial activity immediately prior to termination of paroxysmal atrial fibrillation (corrected)].

INTRODUCTION AND OBJECTIVES Atrial activity characterization with a high degree of detail can be reached by analyzing invasive recordings. Nevertheless, electrocardiographic signal processing tools can nowadays obtain equivalent information in some cases. The aim of this work is to study the electrocardiographic alterations produced during the last instants prior to spontaneous AF termination. METHODS Fifty patients in paroxysmal AF with an episode lasting more than two hours were selected. The last minute prior to spontaneous AF termination (group S) and the central minute (group N) from each episode were analyzed. Ventricular response, f waves morphology, and atrial activity spectral and organization were studied through the use of signal processing tools. RESULTS RR intervals variability was a discriminative parameter (group S 630+/-200 ms vs. group N 740+/-100 ms; P=.034), although a low specificity was obtained (54.2%). Significative differences between both groups were not reported by the f waves morphological study. Group S presented a significative low dominant atrial frequency mean value than group N (group S 5.010+/-0.671 Hz vs. group N 6.514+/-0.804 Hz, P=4.55x10(-9)). Finally, group N showed a considerable low atrial activity organization degree than group S (group S 0.071+/-0.012 vs. group N 0.103+/-0.013, P=6.73x10(-12)). CONCLUSIONS The analysis of the electrocardiographic interval prior to spontaneous AF termination has revealed an atrial activity organization process, which cannot be observed by visual inspection of f waves morphology, but can be successfully quantified through signal processing.

[1]  L. Sörnmo,et al.  Non-invasive assessment of the atrial cycle length during atrial fibrillation in man: introducing, validating and illustrating a new ECG method. , 1998, Cardiovascular research.

[2]  D. Abásolo,et al.  Entropy analysis of the EEG background activity in Alzheimer's disease patients , 2006, Physiological measurement.

[3]  G. Nollo,et al.  Dynamic electrophysiological behavior of human atria during paroxysmal atrial fibrillation. , 1995, Circulation.

[4]  C. Israel,et al.  Prevalence, characteristics and clinical implications of regular atrial tachyarrhythmias in patients with atrial fibrillation: insights from a study using a new implantable device. , 2001, Journal of the American College of Cardiology.

[5]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[6]  Günter Schreier,et al.  Predicting initiation and termination of atrial fibrillation from the ECG , 2007, Biomedizinische Technik. Biomedical engineering.

[7]  D. Vergani,et al.  Heart rate variability and early recurrence of atrial fibrillation after electrical cardioversion. , 2001, Journal of the American College of Cardiology.

[8]  MARCELLO DISERTORI,et al.  Deterioration of Organization in the First Minutes of Atrial Fibrillation: A Beat‐to‐Beat Analysis of Cycle Length and Wave Similarity , 2007, Journal of cardiovascular electrophysiology.

[9]  J. Langberg,et al.  Non-invasive assessment of fibrillatory activity in patients with paroxysmal and persistent atrial fibrillation using the Holter ECG. , 1999, Cardiovascular research.

[10]  Hsuan-Ming Tsao,et al.  Frequency analysis in different types of paroxysmal atrial fibrillation. , 2006, Journal of the American College of Cardiology.

[11]  Robert Ploutz-Snyder,et al.  Mechanisms of Wave Fractionation at Boundaries of High-Frequency Excitation in the Posterior Left Atrium of the Isolated Sheep Heart During Atrial Fibrillation , 2006, Circulation.

[12]  A. Sahakian,et al.  Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity. , 1992, Journal of electrocardiology.

[13]  Giovanni Calcagnini,et al.  Endocardial Mapping of Atrial Fibrillation with Basket Catheter , 2006 .

[14]  Leif Sörnmo,et al.  Predicting spontaneous termination of atrial fibrillation using the surface ECG. , 2006, Medical engineering & physics.

[15]  Dong-Gu Shin,et al.  Prediction of paroxysmal atrial fibrillation using nonlinear analysis of the R-R interval dynamics before the spontaneous onset of atrial fibrillation. , 2006, Circulation journal : official journal of the Japanese Circulation Society.

[16]  Steven Swiryn,et al.  Relationship between pattern of occurrence of atrial fibrillation and surface electrocardiographic fibrillatory wave characteristics. , 2004, Heart rhythm.

[17]  F. Hornero,et al.  Analysis of the postoperative epicardial auriculogram after surgical ablation of atrial fibrillation: risk stratification of late recurrences. , 2007, The Journal of thoracic and cardiovascular surgery.

[18]  P. Toutouzas,et al.  Differences in the morphology and duration between premature P waves and the preceding sinus complexes in patients with a history of paroxysmal atrial fibrillation , 2003, Clinical cardiology.

[19]  M. Lesh,et al.  Relationship between atrial fibrillation and typical atrial flutter in humans: activation sequence changes during spontaneous conversion. , 1997, Circulation.

[20]  Federico Cantini,et al.  Noninvasive ECG as a Tool for Predicting Termination of Paroxysmal Atrial Fibrillation , 2007, IEEE Transactions on Biomedical Engineering.

[21]  Volkan Tuzcu,et al.  Decrease in the heart rate complexity prior to the onset of atrial fibrillation. , 2006, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[22]  Leif Sörnmo,et al.  Atrial fibrillatory rate and sinus rhythm maintenance in patients undergoing cardioversion of persistent atrial fibrillation. , 2006, European heart journal.

[23]  Martin Stridh,et al.  Frequency Measures Obtained from the Surface Electrocardiogram in Atrial Fibrillation Research and Clinical Decision‐Making , 2003, Journal of cardiovascular electrophysiology.

[24]  José Millet-Roig,et al.  Atrial activity extraction for atrial fibrillation analysis using blind source separation , 2004, IEEE Transactions on Biomedical Engineering.

[25]  Prashanthan Sanders,et al.  Changes in Atrial Fibrillation Cycle Length and Inducibility During Catheter Ablation and Their Relation to Outcome , 2004, Circulation.

[26]  B. Gersh,et al.  Long-Term Progression and Outcomes With Aging in Patients With Lone Atrial Fibrillation: A 30-Year Follow-Up Study , 2007, Circulation.

[27]  A. Bollmann,et al.  Frequency analysis of human atrial fibrillation using the surface electrocardiogram and its response to ibutilide. , 1998, The American journal of cardiology.

[28]  Philip Langley,et al.  Surface Atrial Frequency Analysis in Patients with Atrial Fibrillation: , 2004, Journal of cardiovascular electrophysiology.

[29]  Leif Sörnmo,et al.  Validation and Clinical Application of Time‐Frequency Analysis of Atrial Fibrillation Electrocardiograms , 2007, Journal of cardiovascular electrophysiology.

[30]  M. Allessie,et al.  High-density mapping of electrically induced atrial fibrillation in humans. , 1994, Circulation.

[31]  G. Calcagnini,et al.  Descriptors of wavefront propagation , 2006, IEEE Engineering in Medicine and Biology Magazine.

[32]  Federico Lombardi,et al.  Autonomic nervous system and paroxysmal atrial fibrillation: a study based on the analysis of RR interval changes before, during and after paroxysmal atrial fibrillation. , 2004, European heart journal.

[33]  S. Cerutti,et al.  Linear and nonlinear coupling between atrial signals , 2006, IEEE Engineering in Medicine and Biology Magazine.

[34]  I Dotsinsky,et al.  Optimization of bi-directional digital filtering for drift suppression in electrocardiogram signals , 2004, Journal of medical engineering & technology.

[35]  Jaap Haaksma,et al.  Clustering of RR Intervals Predicts Effective Electrical Cardioversion for Atrial Fibrillation , 2004, Journal of cardiovascular electrophysiology.

[36]  Steven M. Pincus.  Assessing Serial Irregularity and Its Implications for Health , 2001, Annals of the New York Academy of Sciences.

[37]  J. Jalife,et al.  Temporal Organization of Atrial Activity and Irregular Ventricular Rhythm During Spontaneous Atrial Fibrillation: , 2000, Journal of cardiovascular electrophysiology.

[38]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[39]  S Swiryn,et al.  Evidence for Transient Linking of Atrial Excitation During Atrial Fibrillation in Humans , 1992, Circulation.

[40]  P. Langley,et al.  Analysis of surface electrocardiograms in atrial fibrillation: techniques, research, and clinical applications. , 2006, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[41]  P. Platonov,et al.  Deterioration of interatrial conduction in patients with paroxysmal atrial fibrillation: electroanatomic mapping of the right atrium and coronary sinus. , 2004, Heart rhythm.

[42]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[43]  Shankar Muthu Krishnan,et al.  ECG signal conditioning by morphological filtering , 2002, Comput. Biol. Medicine.

[44]  M. Ferdjallah,et al.  Adaptive digital notch filter design on the unit circle for the removal of powerline noise from biomedical signals , 1994, IEEE Transactions on Biomedical Engineering.