Spontaneous Onset Of Atrial Fibrillation Research Articles

Structural, Pro-Inflammatory and Calcium Handling Remodeling Underlies Spontaneous Onset of Paroxysmal Atrial Fibrillation in JDP2-Overexpressing Mice.

Background: Cardiac-specific JDP2 overexpression provokes ventricular dysfunction and atrial dilatation in mice. We performed in vivo studies on JDP2-overexpressing mice to investigate the impact of JDP2 on the predisposition to spontaneous atrial fibrillation (AF). Methods: JDP2-overexpression was started by withdrawal of a doxycycline diet in 4-week-old mice. The spontaneous onset of AF was documented by ECG within 4 to 5 weeks of JDP2 overexpression. Gene expression was analyzed by real-time RT-PCR and Western blots. Results: In atrial tissue of JDP2 mice, besides the 3.6-fold increase of JDP2 mRNA, no changes could be detected within one week of JDP2 overexpression. Atrial dilatation and hypertrophy, combined with elongated cardiomyocytes and fibrosis, became evident after 5 weeks of JDP2 overexpression. Electrocardiogram (ECG) recordings revealed prolonged PQ-intervals and broadened P-waves and QRS-complexes, as well as AV-blocks and paroxysmal AF. Furthermore, reductions were found in the atrial mRNA and protein level of the calcium-handling proteins NCX, Cav1.2 and RyR2, as well as of connexin40 mRNA. mRNA of the hypertrophic marker gene ANP, pro-inflammatory MCP1, as well as markers of immune cell infiltration (CD68, CD20) were increased in JDP2 mice. Conclusion: JDP2 is an important regulator of atrial calcium and immune homeostasis and is involved in the development of atrial conduction defects and arrhythmogenic substrates preceding paroxysmal AF.

Spontaneous onset of atrial fibrillation

Most commonly, atrial fibrillation is triggered by rapid bursts of electrical impulses originating in the myocardial sleeves of pulmonary veins (PVs). However, the nature of such bursts remains poorly understood. Here, we propose a mechanism of bursting consistent with the extensive empirical information about the electrophysiology of the PVs. The mechanism is essentially non-local and involves the spontaneous initiation of non-sustained spiral waves in the distal end of the muscle sleeves of the PVs. It reproduces the experimentally observed dynamics of the bursts, including their frequency, their intermittent character, and the unusual shape of the electrical signals in the pulmonary veins that are reminiscent of so-called early afterdepolarizations (EADs).

Prediction of Paroxysmal Atrial Fibrillation Using Nonlinear Analysis of the R-R Interval Dynamics Before the Spontaneous Onset of Atrial Fibrillation

New methods based on nonlinear theory have been developed to give more insight into complex heart rate (HR) dynamics. This study was designed to test the hypothesis that altered HR dynamics, as analyzed with complexity and fractal measures, may precede the spontaneous onset of paroxysmal atrial fibrillation (PAF). Secondly, the difference in the temporal change of these measurements between the different types of atrial fibrillation (AF) was assessed. From 105 Holter tapes in which PAF was recorded, 44 PAF (>or=5 min) episodes in 33 patients (22 men, 58 +/- 12 years), preceded by sinus rhythm for more than 1 h, were selected and submitted to time-and frequency-domain HR variability analyses, along with detrended fluctuation analysis, approximate entropy (ApEn) and sample entropy (SampEn). The 60 min before the onset of AF were divided into 6 10-min periods and studied using repeated measures ANOVA. PAF episodes were divided into 3 subgroups: an increased HF component and decreased L/H ratio (vagal type, n=20); increased L/H ratio and decreased HF component (sympathetic type, n=14); and non-related type (n=10). None of the time- or frequency-domain parameters showed any significant change before AF in any type of AF. The alpha(1) showed a tendency to decrease before the onset of AF and the change in alpha(1) was divergent according to the AF type. The ApEn decreased before the onset of AF (1.005+/-0.046, 60-50 min before AF to 0.894+/-0.052, 10-0 min before AF; p=0.032). The SampEn also decreased progressively before the start of AF (1.165 +/- 0.085, 60-50 min before AF to 0.887 +/- 0.077, 10-0 min before AF, p=0.003). The decrease in both the ApEn and SampEn was irrespective of the AF type. A reduction in the ApEn and SampEn, which reflects the nonlinear complexity of HR variability, is a hallmark of altered HR dynamics preceding the spontaneous onset of AF.

Heart rate turbulence after atrial premature beats before spontaneous onset of atrial fibrillation

This study was designed to assess the temporal changes in vagal responses to atrial premature beats before spontaneous onset of atrial fibrillation (AF). Enhanced vagal activity plays a major role in the onset and perpetuation of experimental AF, but the role of vagal activation in the onset of clinical AF episodes is not so well established. We calculated heart rate turbulence after atrial premature impulses occurring 0 to 60 min before the onset of AF ("prior to AF") and compared it with the hourly means of the other hours of the 24-h electrocardiogram recordings ("non-AF hours") in 39 patients with structural heart disease and 29 patients with lone AF. Traditional heart rate variability measurements and approximate entropy (ApEn) were also analyzed. Turbulence onset (TO) was significantly less negative during the 1 h preceding AF than during the non-AF hours (0.71 +/- 1.76 vs. -0.35 +/- 1.46, p < 0.00001). Less negative TO before AF was observed among both the patients with structural heart disease (1.16 +/- 1.73 vs. 0.07 +/- 1.23; p < 0.0001) and those with lone AF (0.17 +/- 1.67 vs. -0.85 +/- 1.56; p < 0.0001). No significant difference was seen in the turbulence slope between the two periods, and none of the traditional frequency and time domain measurements differentiated between the periods; ApEn was significantly lower before AF than during the non-AF hours (p < 0.01). Altered heart rate dynamics, suggesting transient enhancement of vagal outflow after premature atrial excitation, are temporally related to spontaneous onset of clinical AF.

A17-6 Spontaneous onset of atrial fibrillation from the pulmonary vein musculature: High-resolution activation mapping with a basket catheter

A17-6 Spontaneous onset of atrial fibrillation from the pulmonary vein musculature: High-resolution activation mapping with a basket catheter

A17-6 Spontaneous onset of atrial fibrillation from the pulmonary vein musculature: High-resolution activation mapping with a basket catheter

A17-6 Spontaneous onset of atrial fibrillation from the pulmonary vein musculature: High-resolution activation mapping with a basket catheter

P2098 Spontaneous onset of atrial fibrillation from the pulmonary vein muscolature: high-resolution activation mapping with a basket catheter

P2098 Spontaneous onset of atrial fibrillation from the pulmonary vein muscolature: high-resolution activation mapping with a basket catheter

Heart rate variability and recurrence of atrial fibrillation after electrical cardioversion

BACKGROUND: Heart rate (HR) variability has been shown to predict spontaneous onset of atrial fibrillation (AF). This study was designed to test the hypothesis that HR variability after electrical cardioversion (CV) of persistent AF predicts the recurrence of AF.METHODS: Various time and frequency domain measures of HR variability, along with the non‐linear measures of HR dynamics, were analyzed from the 24‐hour ECG recordings in 78 patients with persistent AF after restoration of sinus rhythm with electrical CV.RESULTS: During the follow‐up of one month, 27 patients (35%) had recurrence of AF. The patients with AF recurrence had significantly higher standard deviation of all R‐R intervals (SDNN 117 ± 34versus100 ± 29P < 0.05), increased high‐frequency (lnHF 5.7 ± 0.6versus5.3 ± 0.7P < 0.05 ), low‐frequency (lnLF 6.2 ± 0.8versus5.6 ± 0.9P < 0.01) and very‐low‐frequency (InVLF 7.1 ± 0.8versus6.5 ± 0.8P < 0.01) power spectral components of HR variability than those who remained in sinus rhythm. Approximate entropy, a measure of complexity of HR dynamics, and the short‐term fractal scaling exponent did not differ between the groups, but the long‐term power‐law slope β was steeper among the patients who remained in sinus rhythm (P < 0.05). During the first week after the CV, increased HF power (highest tertile) was the most powerful predictor of AF recurrence with odds ratio of 2.8 (95% confidence interval 1.0 to 8.0,P < 0.05). Increased VLF power spectral component at baseline predicted best the late recurrence of AF with odds ratio of 3.3 (95% confidence interval 1.6 to 7.2,P < 0.01). No clinical or echocardiographic variable predicted the recurrence of AF.CONCLUSIONS: Increased HR variability in all major power spectral bands is associated with late recurrence of AF after electrical CV. Enhanced cardiac vagal outflow, reflected as an increased HF power spectral component, seems to predict specifically the early recurrence of AF after the CV.

Differences in heart rate dynamics before the spontaneous onset of long and short episodes of paroxysmal atrial fibrillation.

Altered heart rate (HR) dynamics precede the spontaneous onset of atrial fibrillation (AF), but the factors related to the perpetuation and duration of paroxysmal AF episodes are not well established. This study was designed to test the hypothesis that HR dynamics preceding the onset of (AF) may influence the duration of AF. Traditional time and frequency domain HR variability indices, along with a short-term fractal scaling exponent (alpha(1)) and approximate entropy (ApEn), were analyzed in 20-minute intervals before 92 episodes of spontaneous paroxysmal AF in 22 patients without structural heart disease. AF episodes were divided into two groups according to the duration of the arrhythmia episodes. The high-frequency (HF) spectral component in normalized units (nu) of heart rate variability was higher and low-frequency (LF) component lower before long (> 200 s, n = 41) compared to short (< 200 s, n = 51) AF episodes (HF nu; 40.1 +/- 14.8 vs 31.5 +/- 16.4, P < 0.0001 and LF nu; 59.9 +/- 14.8 vs 68.5 +/- 16.4, P < 0.0001). Short-term scaling exponent values also were lower before long compared to short AF episodes (e.g., alpha(1); 1.12 +/- 0.21 vs 1.24 +/- 0.23, P < 0.0001). Women had a larger number of long AF episodes than men, but the duration of AF was not related to any other clinical or demographic features or antiarrhythmic medication. Increased HF oscillations and decreased short-term correlation properties of R-R intervals, reflecting altered sympathovagal balance before the onset of AF, predispose to perpetuation of spontaneous arrhythmia episodes in patients with vulnerability to paroxysmal AF and without structural heart disease.

Analysis of nonlinear heart rate dynamics in cardiac arrhythmias

Analysis of heart rate dynamics by methods based on nonlinear dynamics has opened a new approach for studying the abnormalities in heart rate behavior as a predictor of cardiac arrhythmias. Recent studies have shown that the new nonlinear measures, particularly fractal analysis methods of heart rate dynamics, perform better than traditional analysis methods as a predictor of sudden cardiac death in post-infarction populations. Altered short-term fractal properties of heart rate dynamics have also been shown to precede the onset of ventricular tachyarrhythmias. Reduced approximate entropy, a measure of complexity of heart rate variability has been observed to precede the spontaneous onset of atrial fibrillation. These findings support the notion that some nonlinear methods, such as fractal and complexity measures, give important new information for the prediction of the onset of cardiac arrhythmias.¶ This article provides a review of our current knowledge of the usefulness of newer dynamic measures of heart rate fluctuation both in risk stratification and as predictors of spontaneous onset of cardiac arrhythmias.

Nonlinear Analysis of Heart Rate Variability: Fractal and Complexity Measures of Heart Rate Behavior

Many new methods of analyzing heart rate (HR) variability have been developed to describe the features in HR behavior that cannot be detected by traditional time‐ and frequency‐domain methods. Some of the new methods, such as analysis of fractal correlation properties and complexity of HR dynamics, have provided clinically useful information in various patient populations. Importantly, some fractal analysis methods are better risk predictors of mortality than traditional HR variability measures, and analysis of complexity of HR dynamics has been shown to predict the spontaneous onset of atrial fibrillation. New analysis methods based on nonlinear dynamics are a promising tool for better understanding of normal and abnormal HR behavior. More work will be needed to establish the clinical applicability of traditional and new analysis methods of HR variability.