Ibutilide Increases the Variability and Complexity of Atrial Fibrillation Electrograms: Antiarrhythmic Insights Using Signal Analyses

Introduction Intravenous ibutilide is used to convert atrial fibrillation (AF) to sinus rhythm (SR) due to its Class III antiarrhythmic mechanisms. However, the effects of ibutilide on local electrograms (EGMs) during AF have not been elucidated. Methods and Results We used EGM analysis techniques to characterize how ibutilide administration changes the frequency, morphology, and repeatability of AF EGM signals, thereby providing insight into ibutilide's antiarrhythmic mechanism of action. AF recordings were collected from 21 patients with AF, both before and after ibutilide administration. The effects of ibutilide on the following AF EGM parameters were assessed: (1) dominant frequency (DF), (2) variations in EGM amplitude and overall morphology, (3) repetition of EGM patterns, and (4) complexity of the AF frequency spectra. When comparing pre- versus post-ibutilide administration EGMs, DF decreased from 5.45 Hz to 4.02 Hz (P < 0.0001). There was an increase in the variability of both AF EGM amplitudes (P = 0.003) and overall AF EGM morphologies (P = 0.003). AF EGM pattern repetitiveness decreased (P = 0.01), and the AF frequency spectral profile manifested greater complexity (P = 0.02). Conclusions Novel EGM signal analysis techniques reveal that ibutilide administration causes increased complexity in the atrial electrical activation pattern with decreasing rate. These findings may be explained by the progressive destabilization of higher frequency, more homogeneous primary drivers of AF over the course of ibutilide administration, and/or less uniform propagation of atrial activation, until AF maintenance becomes more difficult and either transforms to atrial tachycardia or terminates to SR

Software algorithm and hardware design for real-time implementation of new spectral estimator

Background: Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method: Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results: The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150˟ faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions: The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radio frequency catheter ablation in real time

Comparison of spectral estimators for characterizing fractionated atrial electrograms

Background: Complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF) are commonly assessed using the discrete Fourier transform (DFT), but this can lead to inaccuracy. In this study, spectral estimators derived by averaging the autocorrelation function at lags were compared to the DFT. Method: Bipolar CFAE of at least 16 s duration were obtained from pulmonary vein ostia and left atrial free wall sites (9 paroxysmal and 10 persistent AF patients). Power spectra were computed using the DFT and three other methods: 1. a novel spectral estimator based on signal averaging (NSE), 2. the NSE with harmonic removal (NSH), and 3. the autocorrelation function average at lags (AFA). Three spectral parameters were calculated: 1. the largest fundamental spectral peak, known as the dominant frequency (DF), 2. the DF amplitude (DA), and 3. the mean spectral profile (MP), which quantifies noise floor level. For each spectral estimator and parameter, the significance of the difference between paroxysmal and persistent AF was determined. Results: For all estimators, mean DA and mean DF values were higher in persistent AF, while the mean MP value was higher in paroxysmal AF. The differences in means between paroxysmals and persistents were highly significant for 3/3 NSE and NSH measurements and for 2/3 DFT and AFA measurements (p<0.001). For all estimators, the standard deviation in DA and MP values were higher in persistent AF, while the standard deviation in DF value was higher in paroxysmal AF. Differences in standard deviations between paroxysmals and persistents were highly significant in 2/3 NSE and NSH measurements, in 1/3 AFA measurements, and in 0/3 DFT measurements. Conclusions: Measurements made from all four spectral estimators were in agreement as to whether the means and standard deviations in three spectral parameters were greater in CFAEs acquired from paroxysmal or in persistent AF patients. Since the measurements were consistent, use of two or more of these estimators for power spectral analysis can be assistive to evaluate CFAE more objectively and accurately, which may lead to improved clinical outcome. Since the most significant differences overall were achieved using the NSE and NSH estimators, parameters measured from their spectra will likely be the most useful for detecting and discerning electrophysiologic differences in the AF substrate based upon frequency analysis of CFAE

A new LMS algorithm for analysis of atrial fibrillation signals

Background A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE). Method Equations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Results Based on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 ± 0.49μV2/sample for the new LMS algorithm versus 0.72 ± 0.35μV2/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 ± 0.95μV2/sample for the new LMS algorithm versus 0.62 ± 0.55μV2/sample for Widrow-Hoff LMS. There were no significant differences in estimation error for paroxysmal versus persistent data. From all trials, the mean convergence time was approximately 1 second for both algorithms. The new LMS algorithm was useful to enhance the electrocardiogram F wave by subtraction of an adaptively weighted prototypical reference signal from the aVF lead. The extrinsic weighting over 25 s demonstrated that time-varying functions such as patient respiration could be identified and monitored. Conclusions A new LMS algorithm was derived and used for normalization of the extrinsic features in CFAE and for electrocardiogram monitoring. The weighting at convergence provides an estimate of the degree of similarity between two signals in terms of x-axis and y-axis shift and scale. The algorithm is computationally efficient with low estimation error. Based on the results, proposed applications include monitoring of extrinsic and intrinsic features of repetitive patterns in CFAE, enhancement of the electrocardiogram F wave and monitoring of time-varying signal properties, and to quantitatively characterize mechanistic differences in paroxysmal versus persistent AF

Improved frequency resolution for characterization of complex fractionated atrial electrograms

Background: The dominant frequency of the Fourier power spectrum is useful to analyze complex fractionated atrial electrograms (CFAE), but spectral resolution is limited and uniform from DC to the Nyquist frequency. Herein the spectral resolution of a recently described and relatively new spectral estimation technique is compared to the Fourier radix-2 implementation. Methods: In 10 paroxysmal and 10 persistent atrial fibrillation patients, 216 CFAE were acquired from the pulmonary vein ostia and left atrial free wall (977 Hz sampling rate, 8192 sample points, 8.4 s duration). With these parameter values, in the physiologic range of 3–10 Hz, two frequency components can theoretically be resolved at 0.24 Hz using Fourier analysis and at 0.10 Hz on average using the new technique. For testing, two closely-spaced periodic components were synthesized from two different CFAE recordings, and combined with two other CFAE recordings magnified 2×, that served as interference signals. The ability to resolve synthesized frequency components in the range 3–4 Hz, 4–5 Hz, …, 9–10 Hz was determined for 15 trials each (105 total). Results: With the added interference, frequency resolution averaged 0.29 ± 0.22 Hz for Fourier versus 0.16 ± 0.10 Hz for the new method (p < 0.001). The misalignment error of spectral peaks versus actual values was ±0.023 Hz for Fourier and ±0.009 Hz for the new method (p < 0.001). One or both synthesized peaks were lost in the noise floor 13/105 times using Fourier versus 4/105 times using the new method. Conclusions: Within the physiologically relevant frequency range for characterization of CFAE, the new method has approximately twice the spectral resolution of Fourier analysis, there is less error in estimating frequencies, and peaks appear more readily above the noise floor. Theoretically, when interference is not present, to resolve frequency components separated by 0.10 Hz using Fourier analysis would require an 18.2 s sequence duration, versus 8.4 s with the new method

A new transform for the analysis of complex fractionated atrial electrograms

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction. A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE. Results: The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%. Conclusions: The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study

Correlating perceived arrhythmia symptoms and QoL in the elderly with Heart Failure in an urban clinic: A prospective, single center study

Aims and objectives To determine the relationship between quality of life and perceived self-reported symptoms in an older, ambulatory, urban population living with heart failure. Background While arrhythmias in older individuals with heart failure are well documented, the association between perceived arrhythmia symptoms and quality of life is not well-defined. Design Prospective, cross-sectional single-centre study. Methods A single-centre, prospective study was conducted with heart failure patients recruited from an urban outpatient cardiology clinic in the United States. Fifty-seven patients completed a baseline quality of life survey with 42 of these completing the six-month follow-up survey. Quality of life was evaluated with the SF-36v2™ and frequency of symptoms with the Atrial Fibrillation Severity Scale. Subjects wore an auto triggered cardiac loop monitor (LifeStar AF Express®) for two weeks to document arrhythmias. Data analysis utilised Spearman's rank correlation and logistic regression. Results Baseline and six-month quality of life measures did not correlate with recorded arrhythmias. However, perceptions of diminished general health correlated significantly with symptoms of exercise intolerance, lightheadedness/dizziness, palpitations and chest pain/pressure. By multivariable logistic regression, more severe perceived episodes, symptoms of exercise intolerance and lightheadedness/dizziness were independently associated with diminished quality of life. Conclusion Quality of life was significantly worse in patients with perceptions of severe arrhythmic episodes and in those with symptoms of dizziness and exercise intolerance. Relevance to clinical practice The findings of this study indicate that symptomatic heart failure patients suffer from poor quality of life and that interventions are needed to improve quality of life and decrease symptom severity. Nurses who care for heart failure patients play an essential role in symptom evaluation and management and could significantly improve overall quality of life in these patients by carefully evaluating symptomatology and testing interventions and educational programmes aimed at improving quality of life

Healthcare Utilization and Quality of Life Improvement after Ablation for Paroxysmal AF in Younger and Older Patients

Background Atrial fibrillation (AF) prevalence increases significantly with age. Little is known about the effect of AF ablation on quality of life and healthcare utilization in the elderly. The objective of this study was to quantify the healthcare utilization and quality of life benefits of catheter ablation for AF, for patients ≥65 years compared to patients <65 years. Methods Two multicenter U.S. registry studies enrolled patients with paroxysmal AF. Baseline characteristics and acute outcomes were collected for 736 patients receiving catheter ablation with the Navistar® ThermoCool® SF Catheter (Biosense Webster, Inc., Diamond Bar, CA, USA). Healthcare utilization and quality of life outcomes were collected through 1 year postablation for 508 patients. Results The rates of acute pulmonary vein isolation were high and similar between patients ≥65 years and <65 years (97.5% vs 95.8%, P = 0.2130). Length of stay for the index procedure was similar between age groups with 82.2% of the older group and 83.2% of the younger group having one-day hospitalization. Disease-specific quality of life instrument scores improved significantly and similarly for older and younger patients at 1 year postablation, compared to baseline. AF-related hospitalizations and emergency department visits were similar or lower in older patients compared to younger patients, as reported at 1 year postablation. Conclusion For older patients undergoing catheter ablation for paroxysmal AF, healthcare utilization parameters were lower or not significantly different than for younger patients, and quality of life outcomes were similarly improved. These findings support the use of catheter ablation as a treatment option in older patients with paroxysmal AF