Circadian variations in atrial fibrillatory frequency in persistent human atrial fibrillation

Circadian (diurnal/nocturnal) pattern of cardiac arrhythmias

Circadian rhythms follow 24-hour biological cycle patterns controlled by internal biological or circadian clocks that optimize organismal homeostasis according to predictable environmental changes. These clocks are found in virtually all cells in the body, including cardiomyocytes. Triggers for and/or the occurrence of sudden cardiac death (SCD) and cardiac arrhythmias seem to follow such daily patterns. This review highlights data from studies exploring the role of day/night rhythms in the timing of arrhythmic events, studies describing the environmental, behavioral, and circadian mechanisms regulating cardiac electrophysiology focusing on the circadian pattern of arrhythmias and SCD. Mechanisms involved relate to circadian control of electrophysiological properties, vagal tone, and sleep disorders, as well as the potential interaction and synergism among these factors. By studying the diurnal variations of arrhythmias, therapy can be improved by optimally timing it to their circadian pattern and a person's internal body clock time. Potential treatment targets for arrhythmias with nocturnal onset may include upstream therapy for underlying comorbidities, type and timing of drug intake, pulmonary vein isolation, ablation of the ganglionated plexus, and autonomic nervous system control. Thus, specific history-taking, screening, and diagnostic workup are recommended to identify and characterize comorbidities and potential contributors to nocturnal arrhythmias, such as obesity, advanced age, diabetes, hypertension, and heart failure. In this direction, symptoms of sleep apnea may comprise snoring and excessive daytime sleepiness. Risk factors include obesity, decreased upper airway dimensions, and heart failure. Thus, one should have a low threshold for sleep testing to assess for sleep apnea. Sleep apnea treatment decreases ventricular arrhythmias and ameliorates some severe bradycardic episodes, often obviating the need for pacemaker implantation. Importantly, comorbidity treatment and lifestyle optimization remain crucial.

Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data

Objective. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor. We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.Approach. The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57 ± 12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.Main results. The mixed-effect models had a better fit to the data than fixed-effect models showing h.c. of determination (R2 = 0.49 versusR2 = 0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2 = 0.04). AFR was found to be significantly affected by previous catheter ablations (p< 0.05), episode duration (p< 0.05), and irregularity of theRRinterval series (p< 0.05).Significance. Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organizedRRintervals and after several ablation procedures.

Inverse Correlation between the Atrial Fibrillatory Rate and the Ventricular Repolarization Time: Observations at Baseline and after an Intravenous Infusion of a Combined Potassium and Sodium Current Blocker

BACKGROUND

The atrial fibrillatory rate (AFR) and the ventricular rate and repolarization (QTcF) were studied at baseline and under the influence of the combined potassium and sodium current blocker AZD7009.

METHODS

Ninety-two patients with atrial fibrillation (AF) were randomized to an intravenous infusion of AZD7009 or placebo. The atrial fibrillatory activity in lead V1 was extracted using spatiotemporal QRST cancellation. The exponential decay (ED) characterized the degree of atrial signal organization.

RESULTS

The mean (SD) AFR at baseline was 396  ±  57 (range 253-584) and 410 ± 33 (range 363-469) bpm in patients randomized to AZD7009 and placebo, respectively. The AFR decreased within the first minutes of the AZD7009 infusion and reached its minimum of 235 ± 34 bpm after 18 minutes. On placebo, the AFR was unchanged. On AZD7009, the ED decreased from 1.2 ± 0.3 to reach its lowest level at 0.7 ± 0.2 after 14 minutes. The ventricular rate did not change significantly over time. The AFR was statistically significantly related to the ventricular repolarization at baseline, the QTcF being longer at lower AFR values, and this relationship remained during and after AZD7009. In the full multivariate linear regression model, including age, sex, left ventricular ejection fraction, QRS duration, heart rate, QTcF, AF episode duration, AF history duration, and right atrial or left atrial size, only QTcF and age were statistically significantly correlated with the AFR. The correlation remained when the uncorrected QT interval was used.

CONCLUSIONS

The QTcF was inversely correlated with AFR, both at baseline and during administration of AZD7009. The AFR was not correlated with the ventricular rate.

Association between atrial fibrillatory rate and heart rate variability in patients with atrial fibrillation and congestive heart failure

BACKGROUND

Even if atrial fibrillatory rate (AFR) has been related to clinical outcome in patients with atrial fibrillation (AF), its relation with ventricular response has not been deeply studied. The aim of this study was to investigate the relation between AFR and RR series variability in patients with AF.

METHODS

Twenty-minute electrocardiograms in orthogonal leads were processed to extract AFR, using spatiotemporal QRST cancellation and time frequency analysis, and RR series in 127 patients (age 69 ± 11 years) with congestive heart failure (NYHA II-III) enrolled in the MUSIC study (MUerte Subita en Insufficiencia Cardiaca). Heart rate variability and irregularity were assessed by time domain parameters and entropy-based indices, respectively and their correlation with AFR investigated.

RESULTS

Variability measures seem not to be related to AFR, while irregularity measures do. A significant correlation between AFR and variability parameters of heart rate variability during AF was found only in patients not treated with antiarrhythmics drugs (correlation = 0.56 P < 0.05 for pNN50), while this correlation was lost in patients taking rate- or rhythm-control drugs. A significant positive correlation between AFR and indices of RR irregularity was found, showing that a higher AFR is related to a less organized RR series (correlation = 0.33 P < 0.05 for regularity index for all patients, correlation increased in subgroups of patients treated with the same drug).

CONCLUSIONS

These results suggest that a higher AFR is associated with a higher degree of irregularity of ventricular response that is observed regardless of the use of rate-controlling drugs.

Quantification of anaesthetic effects on atrial fibrillation rate by partial least-squares

The mechanism underlying atrial fibrillation (AF) remains poorly understood. Multiple wandering propagation wavelets drifting through both atria under hierarchical models are not understood. Some pharmacological drugs, known as antiarrhythmics, modify the cardiac ionic currents supporting the fibrillation process within the atria and may modify the AF propagation dynamics terminating the fibrillation process. Other medications, theoretically non-antiarrhythmic, may slightly affect the fibrillation process in non-defined mechanisms. We evaluated whether the most commonly used anaesthetic agent, propofol, affects AF patterns. Partial least-squares (PLS) analysis was performed to reduce significant noise into the main latent variables to find the differences between groups. The final results showed an excellent discrimination between groups with slow atrial activity during the propofol infusion.

Spectral profiles of complex fractionated atrial electrograms are different in longstanding and acute onset atrial fibrillation atrial electrogram spectra

Spectral Profiles of CFAE.

BACKGROUND

Spectral analysis of complex fractionated atrial electrograms (CFAE) may be useful for gaining insight into mechanisms underlying paroxysmal and longstanding atrial fibrillation (AF). The commonly used dominant frequency (DF) measurement has limitations.

METHOD

CFAE recordings were acquired from outside the 4 pulmonary vein ostia and at 2 left atrial free wall sites in 10 paroxysmal and 10 persistent AF patients. Two consecutive 8s-series were analyzed from recordings >16s in duration. Power spectra were computed for each 8s-series in the range 3-12 Hz and normalized. The mean and standard deviation of normalized power spectra (MPS and SPS, respectively) were compared for paroxysmal versus persistent CFAE. Also, the DF and its peak amplitude (ADF) were compared for pulmonary vein sites only. Power spectra were computed using ensemble average and Fourier methods.

RESULTS

No significant changes occurred in any parameter from the first to second recording sequence. For both sequences, MPS and SPS were significantly greater, and DF and ADF were significantly less, in paroxysmals versus persistents. The MPS and ADF measurements from ensemble spectra produced the most significant differences in paroxysmals versus persistents (P < 0.0001). DF differences were less significant, which can be attributed to the relatively high variability of DF in paroxysmals. The MPS was correlated to the duration of uninterrupted persistent AF prior to electrophysiologic study (P = 0.01), and to left atrial volume for all AF (P < 0.05).

CONCLUSIONS

The MPS and ADF measurements introduced in this study are probably superior to DF for discerning power spectral differences in paroxysmal versus longstanding CFAE. (J Cardiovasc Electrophysiol, Vol. 23, pp. 971-979, September 2012).

Atrial fibrillatory rate and irregularity of ventricular response as predictors of clinical outcome in patients with atrial fibrillation

Atrial fibrillation (AF) remains the most common arrhythmia encountered in clinical practice. Electrocardiogram (ECG)-based predictors of clinical outcome, however, have mostly been studied during sinus rhythm, whereas noninvasive risk stratification of patients with AF remains largely unexplored. Advances in ECG signal processing have led to the development of noninvasive methods of atrial fibrillatory rate (AFR) assessment using spatiotemporal QRST cancellation and time frequency analysis that demonstrated its predictive value for the outcome of pharmacologic and catheter-based interventions for AF. Recently, the prognostic value of AFR was evaluated in patients with congestive heart failure and indicated that reduced AFR may be an independent predictor of total and congestive heart failure-related mortality. A high degree of irregularity of the RR intervals during AF and its dependence on the modulation of the atrioventricular conduction rather than sinus node automaticity hampers the use of conventional heart rate variability approach in patients with AF. However, RR irregularity measures that can be applied to short-time ECG recordings appear to be promising predictors of clinical outcome.

Vagal modulation of heart rate variability during atrial fibrillation in pigs

Atrial fibrillation (AF) is the most common sustained cardiac dysrhythmia and is associated with an increased risk for sudden cardiac death. The ventricular rhythm is irregular and displays both non-linear and linear patterns; however, it has not been determined whether vagally derived patterns are manifest within the irregular rhythm. Moreover, indices of increased vagal control are associated with reduced risk of sudden cardiac death. In this study, we sought to determine whether the ventricular rhythm pattern during AF is, in part, modulated by vagal activity. Vagal oscillations were forced at 0.15 Hz by neck suction in 12 pigs with sustained AF with and without glycopyrrolate (0.15 microg/kg, intravenously) vagal blockade. Vagal activity was evaluated using time- and frequency-domain heart rate variability measures. The standard deviation of RR intervals (SDRRI) was significantly increased during vagal activation compared with baseline (P = 0.006). Moreover, SDRRI correlated significantly with spectral power at 0.15 Hz during baseline (r = 0.90, P < .001) and vagal activation (r = 0.86, P < 0.05). Glycopyrrolate blocked the increase in SDRRI (P < 0.001) and blunted spectral power at 0.15 Hz (P < 0.05). These results indicate that: (1) power spectral analysis may be used to assess parasympathetic regulation during AF, and (2) vagal oscillations produce an entrainment of the ventricular rhythm during AF in pigs.

Circadian variation in dominant atrial fibrillation frequency in persistent atrial fibrillation

Circadian variation in atrial fibrillation (AF) frequency is explored in this paper by employing recent advances in signal processing. Once the AF frequency has been estimated and tracked by a hidden Markov model approach, the resulting trend is analyzed for the purpose of detecting and characterizing the presence of circadian variation. With cosinor analysis, the results show that the short-term variations in the AF frequency exceed the variation that may be attributed to circadian. Using the autocorrelation method, circadian variation was found in 13 of 18 ambulatory ECG recordings (Holter) acquired from patients with long-standing persistent AF. Using the ensemble correlation method, the highest AF frequency usually occurred during the afternoon, whereas the lowest usually occurred during late night. It is concluded that circadian variation is present in most patients with long-standing persistent AF though the short-term variation in the AF frequency is considerable and should be taken into account.

Electrophysiological characteristics associated with symptoms in pacemaker patients with paroxysmal atrial fibrillation

PURPOSE

The purpose of this study is to identify the electrophysiological factors affecting symptoms in paroxysmal atrial fibrillation (PAF) using patients with paroxysmal atrial fibrillation and pacemakers with advanced atrial fibrillation (AF) diagnostics.

METHODS

Seventy-nine patients (age 71.0 +/- 8.2, 54.4% male) with symptomatic PAF and AF burden of 1% to 50% with DDDRP pacemakers implanted were assessed for 6 months. Patients recorded symptom onset and duration and these were correlated with device-derived electrophysiological data.

RESULTS

Of 2,638 AF episodes, 333 were symptomatic and 2,305 asymptomatic, with 194 non-atrial tachyarrhythmia symptomatic episodes giving a sensitivity of 12.6% and a positive predictive value of 63.2% for specific AF symptoms. Symptomatic AF episodes were 3.8 times more common diurnally than nocturnally (p < 0.001). Diurnally, symptomatic AF was significantly associated with a shorter AF cycle length (CL; p = 0.04), faster ventricular rate (p = 0.004), shorter PR interval (p < 0.001), faster preceding heart rate (p = 0.001) and increased early recurrence of AF (p < 0.04). Nocturnally, a significantly longer AF CL (p = 0.04) and PR interval (p < 0.001) prior to AF onset predicted symptomatic AF.

CONCLUSIONS

Symptoms in PAF are predicted by changes in AF episode duration, ventricular rate during AF, preceding sinus heart rate, AV nodal conduction and AF cycle length but not ventricular irregularity. Excess diurnal sympathetic tone and excess nocturnal vagal tone predispose to symptomatic PAF. These findings may have relevance for therapies for symptom control of PAF.

Analysis of atrial fibrillation: from electrocardiogram signal processing to clinical management

The analysis of atrial fibrillation in non-invasive ECG recordings has received considerable attention in recent years, spurring the development of signal processing techniques for more advanced characterization of the atrial waveforms than previously available. The present paper gives an overview of different approaches to the extraction of atrial activity in the ECG and to the characterization of the resulting atrial signal with respect to its spectral properties. So far, the repetition rate of the atrial waves is the most studied parameter and its significance in clinical management is briefly considered, including the identification of pathomechanisms and prediction of therapy efficacy.

Atrial fibrillatory rate and risk of left atrial thrombus in atrial fibrillation

AIMS

In atrial fibrillation (AF), a relation between electrocardiogram (ECG) fibrillatory wave amplitude and thrombus formation has been sought for long with conflicting results. In contrast, the possible relation between atrial fibrillatory rate obtained from the surface ECG and left atrial thrombus formation in patients with AF is unknown and was consequently evaluated in this study.

METHODS AND RESULTS

One-hundred and twenty-five patients (mean age 64 +/- 12 years, 72% male) with persistent non-valvular AF (mean duration 28 +/- 80 days) undergoing transesophageal echocardiography were studied. In all patients, standard 12-lead ECG recordings were acquired before the examination. Atrial fibrillatory rate was determined using spatiotemporal QRST cancellation and time-frequency analysis of lead V1. Atrial fibrillatory rate measured 401 +/- 63 fibrillations per minute (fpm, range 235-566 fpm) and was related with age (R = -0.326, P < 0.001), ventricular rate (R = -0.202, P = 0.024), gender (407 +/- 62 in males vs. 387 +/- 64 fpm in females, P = 0.038) but not AF duration (R = 0.088, P = 0.374), presence of lone AF (408 +/- 66 vs. 394 +/- 58 fpm, P = 0.228), or beta-blocker or calcium channel blocker treatment (398 +/- 63 vs. 405 +/- 62 fpm, P = 0.556). Age was the only independent predictor of fibrillatory rate (B = -1.714, P < 0.001). In patients with left atrial thrombus (n = 10), spontaneous echo contrast (SEC) was more frequently present (70 vs. 29 %, p = 0.007) and left atrial appendage (LAA) outflow velocity was lower (26 +/- 20 vs. 37 +/- 15 cm/s, P = 0.012) than in patients without thrombus (n = 115). In contrast, mean fibrillatory rate, which showed a weak inverse correlation with LAA velocity (R = -0.118, P = 0.048) was not different between both groups (380 +/- 56 vs. 403 +/- 63 fpm, P = 0.226). Similarly, presence of thrombus and SEC combined was not related with fibrillatory rate.

CONCLUSION

Atrial fibrillatory rate obtained from surface ECG lead V1 is not a risk marker for left atrial thrombus formation in AF.

Exercise testing for non-invasive assessment of atrial electrophysiological properties in patients with persistent atrial fibrillation

AIMS

Experimental studies suggest that the autonomic nervous system modulates atrial refractoriness and conduction velocity in atrial fibrillation (AF). These modulatory effects are, however, difficult to assess in the clinical setting. This study sought to non-invasively characterize in patients with persistent AF, the influence of autonomic modulation induced by exercise on atrial fibrillatory rate as marker of atrial refractoriness and to identify clinical and electrocardiographic predictors of atrial rate response.

METHODS AND RESULTS

In 24 patients (16 males, mean age 60 +/- 13 years) with persistent AF (16 +/- 25 months), continuous ECGs were recorded during bicycle exercise testing. Fibrillatory rate (in fibrillations per minute, fpm) was assessed at baseline and immediately after termination of exercise with spatiotemporal QRST cancellation and time-frequency analysis. Ventricular response was characterized by time-domain HRV indices. Exercise had no influence on mean fibrillatory rate (409 +/- 42 vs. 414 +/- 43 fpm, P = NS). Seven patients responded to exercise with an increase in fibrillatory rate (26 +/- 10 fpm, P < 0.001 and three with a decrease (-21 +/- 8 fpm, P < 0.001), while the remaining 14 patients did not show a response. Responders' HRV indices changed in response to exercise similarly to that of non-responders. Their baseline fibrillatory rate was, however, lower than that of non-responders (387 +/- 18 vs. 425 +/- 48 fpm, P = 0.028). No other clinical or echocardiographic variable was associated with fibrillatory rate response. Twelve weeks after cardioverson, responders were more likely to remain in sinus rhythm than non-responders (88 vs. 46 %, P = 0.04).

CONCLUSIONS

Exercise-induced autonomic activation produces changes in atrial electrophysiological properties that can be detected by time-frequency analysis. Higher baseline fibrillatory rates are associated with an impaired atrial response to exercise that suggests advanced electrical remodelling and reduced sensitivity to autonomic stimuli.

Analysis of surface electrocardiograms in atrial fibrillation: techniques, research, and clinical applications

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice. Neither the natural history of AF nor its response to therapy is sufficiently predictable by clinical and echocardiographic parameters. The purpose of this article is to describe technical aspects of novel electrocardiogram (ECG) analysis techniques and to present research and clinical applications of these methods for characterization of both the fibrillatory process and the ventricular response during AF. Atrial fibrillatory frequency (or rate) can reliably be assessed from the surface ECG using digital signal processing (extraction of atrial signals and spectral analysis). This measurement shows large inter-individual variability and correlates well with intra-atrial cycle length, a parameter which appears to have primary importance in AF maintenance and response to therapy. AF with a low fibrillatory rate is more likely to terminate spontaneously and responds better to antiarrhythmic drugs or cardioversion, whereas high-rate AF is more often persistent and refractory to therapy. Ventricular responses during AF can be characterized by a variety of methods, which include analysis of heart rate variability, RR-interval histograms, Lorenz plots, and non-linear dynamics. These methods have all shown a certain degree of usefulness, either in scientific explorations of atrioventricular (AV) nodal function or in selected clinical questions such as predicting response to drugs, cardioversion, or AV nodal modification. The role of the autonomic nervous system for AF sustenance and termination, as well as for ventricular rate responses, can be explored by different ECG analysis methods. In conclusion, non-invasive characterization of atrial fibrillatory activity and ventricular response can be performed from the surface ECG in AF patients. Different signal processing techniques have been suggested for identification of underlying AF pathomechanisms and prediction of therapy efficacy.

Patients with persistent atrial fibrillation taking oral verapamil exhibit a lower atrial frequency on the ECG

BACKGROUND

While there is agreement that verapamil attenuates the AF- induced refractory period shortening when given before AF induction, controversy exists regarding its effects when given after the onset of persistent AF. This study aimed to compare atrial fibrillatory frequency obtained from the surface ECG in patients with persistent atrial fibrillation (AF) with oral verapamil treatment to those without this treatment.

METHODS AND RESULTS

Surface ECG recordings were performed in 57 patients (34 male, 23 female, mean age 59 +/- 11 years) with persistent AF (> 7 days). The frequency content of the fibrillatory baseline was quantified using digital signal processing (filtering, QRST complex averaging and subtraction, Fourier transformation). In 27 patients with verapamil treatment (120 or 240 mg/day for at least 7 days) mean fibrillatory frequency measured 6.4 +/- 0.2 Hz, compared to 7.0 +/- 0.4 Hz (P = 0.012) in 30 patients without verapamil. In a subset of 20 randomly selected patients (10 with, 10 without verapamil treatment) a 24-hour Holter ECG recording was performed and fibrillatory frequency determined at 4 PM, 10 PM, 4 AM, and 10 AM. While there was a significant frequency reduction in the verapamil treated patients at night (P = 0.011), it remained constant over time in the other patients.

CONCLUSION

In patients with persistent AF, fibrillatory frequency assessed by spectral analysis of the surface ECG is lower in patients taking verapamil.

Comparison of atrial signal extraction algorithms in 12-lead ECGs with atrial fibrillation

Analysis of atrial rhythm is important in the treatment and management of patients with atrial fibrillation. Several algorithms exist for extracting the atrial signal from the electrocardiogram (ECG) in atrial fibrillation, but there are few reports on how well these techniques are able to recover the atrial signal. We assessed and compared three algorithms for extracting the atrial signal from the 12-lead ECG. The 12-lead ECGs of 30 patients in atrial fibrillation were analyzed. Atrial activity was extracted by three algorithms, Spatiotemporal QRST cancellation (STC), principal component analysis (PCA), and independent component analysis (ICA). The amplitude and frequency characteristics of the extracted atrial signals were compared between algorithms and against reference data. Mean (standard deviation) amplitude of QRST segments of V1 was 0.99 (0.54) mV, compared to 0.18 (0.11) mV (STC), 0.19 (0.13) mV (PCA), and 0.29 (0.22) mV (ICA). Hence, for all algorithms there were significant reductions in the amplitude of the ventricular activity compared with that in V1. Reference atrial signal amplitude in V1 was 0.18 (0.11) mV, compared to 0.17 (0.10) mV (STC), 0.12 (0.09) mV (PCA), and 0.18 (0.13) mV (ICA) in the extracted atrial signals. PCA tended to attenuate the atrial signal in these segments. There were no significant differences for any of the algorithms when comparing the amplitude of the reference atrial signal with that of the extracted atrial signals in segments in which ventricular activity had been removed. There were no significant differences between algorithms in the frequency characteristics of the extracted atrial signals. There were discrepancies in amplitude and frequency characteristics of the atrial signal in only a few cases resulting from notable residual ventricular activity for PCA and ICA algorithms. In conclusion, the extracted atrial signals from these algorithms exhibit very similar amplitude and frequency characteristics. Users of these algorithms should be observant of residual ventricular activities which can affect the analysis of the fibrillatory waveform in clinical practice.

Relationship between pattern of occurrence of atrial fibrillation and surface electrocardiographic fibrillatory wave characteristics

OBJECTIVES

The purpose of this study was to assess whether surface ECG fibrillatory (f)-wave characteristics reflect clinical variables, especially pattern of occurrence.

BACKGROUND

In clinically stable patients, f waves have fairly constant quantitative characteristics. Both electrophysiologic and structural remodeling might modify f waves.

METHODS

We analyzed f waves from 238 patients (120 men and 118 women; age range 30-97 years, mean 77 +/- 12) with atrial fibrillation identified by retrospective chart review as paroxysmal, persistent, or permanent fibrillation. Analysis was performed in the time and frequency domains on ECGs after QRS-T cancellation. Student's t-test and multivariate analysis were used for comparison.

RESULTS

The f waves of 12 patients taking rhythm control drugs had lower frequency ("slower" fibrillation) than the f waves of patients not taking such drugs (5.3 +/- 0.6 vs 6.0 +/- 0.7 Hz, P < .001). Of the 226 remaining patients, 59 were paroxysmal, 30 were persistent, and 72 were permanent; 65 had an unknown pattern. Paroxysmal and persistent patients were younger than permanent (74 +/- 12 and 72 +/- 15 vs 80 +/- 9 years, P < .002 for both). Paroxysmal, persistent, and permanent patients had different f-wave frequencies of 5.7 +/- 0.7, 6.1 +/- 0.8, and 6.2 +/- 0.6 Hz, respectively (P = .01 for paroxysmal vs persistent and P < .001 for paroxysmal vs permanent). Patients older than 77 years (mean age) had lower f wave frequency than those younger 77 years (6.0 +/- 0.7 vs 6.2 +/- 0.7 Hz, P = .01). Using multivariate analysis, the overall pattern-frequency relationship was significant (p = .014). There was a statistically significant inverse correlation between frequency and age (R = .27, slope = -0.017 Hz/year, P < .001).

CONCLUSIONS

ECG f-wave frequency reflects specific clinical variables, with higher frequency in permanent than paroxysmal fibrillation but lower frequency in older than younger patients. These findings are consistent with the idea that fibrillatory waves are modified by both electrophysiologic and structural remodeling.

Analysis of the surface electrocardiogram for monitoring and predicting antiarrhythmic drug effects in atrial fibrillation

Specific antiarrhythmic therapy with class I and III drugs for atrial fibrillation (AF) conversion and prevention of its recurrence is frequently utilized in clinical practice. Besides being only moderate effective, the utilization of antiarrhythmic drugs may be associated with serious side effects. In the clinical setting it is difficult to directly evaluate the effects of antiarrhythmic drugs on the individual patient's atrial electrophysiology, thereby predicting their efficacy in restoring and maintaining sinus rhythm. Analysis of the surface electrocardiogram in terms of P-wave signal averaged ECG during sinus rhythm and spectral characterization of fibrillatory waves during AF for evaluation of atrial antiarrhythmic drug effects is a new field of investigation. Both techniques provide reproducible parameters for characterizing atrial electrical abnormalities and seem to contain prognostic information regarding antiarrhythmic drug efficacy. Further research is needed which elucidates the most challenging clinical questions in AF management whom to place on antiarrhythmic drug treatment and what antiarrhythmic drug to prescribe. Analysis of the surface ECG might have the potential to answer these questions.

Surface ECG vector characteristics of organized and disorganized atrial activity during atrial fibrillation

BACKGROUND

The aim of this study was to examine atrial organization from vectorcardiograms (VCGs) derived from the surface ECG of atrial fibrillatory waves.

METHODS

We retrieved ECGs recorded during ventricular asystole from 22 patients with AF undergoing ablation of the AV junction. The synthesized VCG of each f-wave cycle of each ECG and its plane of best fit, described by azimuth and elevation angles relative to the frontal plane, were computed.

RESULTS

Fifteen of the 22 ECGs had at least 30% of the planes in a single 30-degree region of azimuth angles. Of these 15, 12 had the greatest percentage of planes with azimuth angles within 30 degrees of the sagittal plane; two were near the frontal plane; and one near the right anterior oblique plane.

CONCLUSIONS

Varying degrees of organization were observed from VCGs of fibrillatory waves with the more organized examples having planes predominately near the sagittal plane.

Atrial Fibrillatory Wave Characteristics on Surface Electrogram:

INTRODUCTION

Fibrillatory waves on the surface ECG have been scrutinized to allow inferences about underlying mechanisms and pathophysiology, based on the premise that fibrillatory waves do not vary "randomly" but provide a consistent reflection of the underlying state of the atria in an individual patient. This premise is untested.

METHODS AND RESULTS

Ten standard ECGs were recorded over a 24-hour period in each of 20 clinically stable inpatients with atrial fibrillation. After QRS-T cancellation, the remainder fibrillatory waves were analyzed. Interpatient versus intrapatient differences in fibrillatory wave characteristics were evaluated by analysis of variance (ANOVA). The fibrillatory wave peak-to-peak amplitude of all the patients ranged from 0.06 to 0.35 mV, whereas 1 SD of the amplitude for each patient ranged from 0.004 to 0.053 mV. Short-term peak frequencies of all the patients ranged from 4.6 to 8.0 Hz, whereas 1 SD for each patient varied from 0.2 to 0.5 Hz. For these and all other parameters tested, interpatient differences were significantly greater compared to intrapatient differences (P < 0.0001).

CONCLUSION

Fibrillatory wave characteristics are repeatable from ECG to ECG over 24 hours for clinically stable patients, whereas substantial differences are present between patients. Further study of the relationship of such characteristics to pathophysiology and management decisions is valid and warranted.

Circadian variation of arrhythmia onset patterns in patients with persistent atrial fibrillation

BACKGROUND

The circadian onset patterns and cycle lengths of atrial tachyarrhythmias (AT) were determined in a group of patients with persistent atrial fibrillation.

METHODS

Fifteen patients, mean age 63 +/- 14 years and 80% male, were implanted with the Jewel AF atrial defibrillator (Medtronic, Minneapolis, Minn) for persistent atrial fibrillation only. Onset times of AT and median onset atrial cycle lengths were determined from device memory.

RESULTS

Over a follow-up period of 23.3 +/- 7 months, 227 episodes of persistent AT were treated by patient-activated atrial defibrillation. The peak onset of persistent AT was nocturnal, with 74% of episodes initiating between 8 pm and 8 am. Eighty-seven percent of the patients experienced an additional 403 paroxysmal AT episodes. These episodes showed a "double-peaked" pattern with the least number of episodes occurring between midnight and 8 am. The mean onset atrial cycle length of persistent AT was significantly shorter than the paroxysmal AT episodes (200 +/- 37 ms vs 240 +/- 39 ms, P <.005). The atrial cycle lengths at arrhythmia onset of both paroxysmal and persistent AT episodes also demonstrated circadian variation.

CONCLUSION

There is a circadian distribution of onsets for persistent AT with predominance at night. Patients with persistent AF have >1 type of atrial arrhythmia with differences in the onset patterns and atrial cycle lengths, suggesting different triggers and onset mechanisms.

A theoretical model of the role of brain stem nuclei in alcohol-mediated arrhythmogenesis in older adults

Uncertainty about the mechanism of alcohol-mediated arrhythmogenesis and the effect of alcohol use on arrhythmic risk among older adults is an increasing concern in light of population aging and recent reports that moderate alcohol consumption may protect older adults against coronary artery disease. In this review, a theoretical model of the role of brain stem nuclei in alcohol-mediated arrhythmogenesis in older adults is developed. The model is based on the hypothesis that the effects of alcohol on central autonomic pathways of cardiac control may alter the threshold for alcohol-mediated arrhythmogenesis among older adults. Findings from multiple lines of research including cellular, electrophysiological, epidemiological, experimental, and clinical studies in human, animal, and in vitro models were synthesized in developing the model. Suggestions for future research on the topic of alcohol-mediated arrhythmogenesis in older adults are offered.