Worldwide Survey of COVID-19-Associated Arrhythmias.

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Increased body mass index, age, and left atrial size are associated with altered intracardiac atrial electrograms in persistent atrial fibrillation patients.

BACKGROUND: There are limited studies evaluating whether atrial fibrillation (AF) patients with increased BMI, age, and left atrial (LA) size have altered intracardiac electrogram (EGM) morphology. METHODS: We analyzed left atrial intracardiac EGMs acquired during invasive electrophysiology study in 54 patients with AF. EGM correlations were assessed among AF risk factors including age, left atrial size, and BMI. RESULTS: BMI correlated positively with DF (r2 = 0.17, p = 0.009) and MP (r2 = 0.16, p = 0.01) with dominant frequency (DF) and mean spectral profile (MP) greater among obese individuals. Age was negatively associated with mean amplitude (r2 = 0.42, p < 0.001) and width (r2 = 0.32, p < 0.001); age was positively correlated with MP (r2 = 0.24, p < 0.001). LA size was negatively correlated with mean amplitude (r2 = 0.18, p = 0.03) and width (r2 = 0.23, p = 0.01); LA size was positively correlated with DF (r2 = 0.22, p = 0.01) and MP (r2 = 0.23, p = 0.01). Mean amplitude and width were decreased among subjects with a severely enlarged LA; DF and MP were increased in those with severely enlarged LA. The associations with BMI and LA size remained significant in multiple regression models that included age, male gender, time since AF diagnosis, and LVEF. CONCLUSIONS: EGM morphology of AF patients with increased BMI, older age, and an enlarged LA possessed decreased amplitude and decreased width and increased DF and MP. These findings suggest that atrial remodeling due to increased age, LA size, and BMI is associated with differences in local atrial activation, decreased refractoriness, and more heterogeneous activation. These novel findings point out clinical risk factors for atrial fibrillation that may affect electrogram characteristics.

Differences in continuous spectra of fractionated electrograms in paroxysmal versus persistent atrial fibrillation.

INTRODUCTION: Quantitative measurements are helpful to discern fractionated electrograms in paroxysmal and persistent atrial fibrillation (AF), and may be useful to detect optimal ablation sites. However, electrical activation events can be transient, leading to erroneous estimates of electrogram properties. Measurement of continuous changes in electrogram frequency content may improve analysis. METHOD: Fractionated local electrograms from 10 paroxysmal and 10 persistent AF patients were acquired from outside the pulmonary vein ostia and left atrial free wall using the distal bipolar ablation catheter electrode, and analyzed over continuous 16 second intervals. A New Spectral Estimator (NSE) updated the frequency spectrum and spectral parameters once per millisecond. The tallest spectral peak (dominant frequency or DF) was determined. Statistical tests of variability were used to determine significant differences between paroxysmal and persistent AF. RESULTS: Changes in the value of the DF over 16 seconds were caused by transient drifts in the frequency of the dominant peak, or by changes in which peak had the highest amplitude. The continuous DF and the spectral profile parameters were more highly variable in paroxysmal as compared with persistent AF patients (p<0.001). There was found to be a gradient from high to low variability of DF in paroxysmal AF, from the left superior pulmonary vein antrum to the left atrial free wall. CONCLUSIONS: The results suggest that atrial electrical activation becomes more stable and focused at a narrow frequency range in persistent as compared to paroxysmal AF. The NSE implemented for continuous update of spectral parameters, enables a rapid characterization of fractionated electrograms with high time-frequency resolution and low computational cost.

Atrial electrogram discordance during baseline vs reinduced atrial fibrillation: Potential ramifications for ablation procedures.

BACKGROUND: There are scant data comparing the electrogram (EGM) signal characteristics of atrial fibrillation (AF) at baseline vs electrically induced states during ablation procedures. OBJECTIVE: The purpose of this study was to use novel intracardiac signal analysis techniques to gain insights into the effects of catheter ablation and AF reinduction on AF EGMs in patients with persistent AF. METHODS: We collected left atrial EGMs in patients undergoing first ablation for persistent AF at 3 time intervals: (1) AF at baseline; (2) AF after pulmonary vein isolation (PVI); and (3) AF after post-PVI cardioversion and subsequent reinduction. We analyzed 2 EGM spectral characteristics: (1) dominant frequency and (2) spectral complexity; and 2 EGM morphologic characteristics: (1) morphology variation and (2) pattern repetitiveness. RESULTS: There were no differences in AF dominant frequency, dominant amplitude, spectral complexity, or metrics of EGM morphology or repetitiveness at baseline vs after PVI. However, dominant frequency, dominant amplitude, and spectral complexity differed significantly after direct current cardioversion and reinduction of AF. CONCLUSION: The frequency, spectral complexity, and local EGM morphologies of AF do not significantly change over the course of a PVI procedure in patients with persistent AF. However, reinduction of AF after direct current cardioversion results in different dominant frequency and spectral complexity, consistent with a change in the characteristics of the perpetuating source(s) of the newly induced AF. These data suggest that AF properties can vary significantly between baseline and reinduced AF, with potential clinical ramifications for outcomes of catheter ablation procedures.

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 radiofrequency catheter ablation in real time.

Temporal stability in the spectral representation of complex fractionated atrial electrograms.

BACKGROUND: Although local electrograms during atrial fibrillation (AF) are often spectrally analyzed over 8-second (8s) intervals, changes may be common over intervals as short as 2s. We sought to determine whether averaged 2s measurements of electrogram spectral parameters were similar to 8s measurements, and whether the 2s intervals could provide an estimate of the temporal stability of the signal frequency content in paroxysmal versus persistent AF. METHODS: Complex fractionated atrial electrograms (CFAEs) were acquired outside the pulmonary vein ostia and from free wall sites in nine paroxysmal and 10 longstanding persistent AF patients. Using a 2s sliding calculation window, a frequency spectrum was computed every 100 ms over an interval of 8.4 seconds (82 spectra in total). The dominant frequency (DF), the dominant amplitude (DA), and the mean spectral profile (MP) were measured. The 2s measurements were compared to single 8.4-second interval measurements. Coefficients of variation (COV) were computed from the 82 spectra for each CFAE recording to determine temporal variability of parameters. RESULTS: Over the sliding 2s computation intervals, as for fixed 8.4-second computation intervals, mean DA and DF were significantly higher in longstanding persistent AF while MP was significantly higher in paroxysmal AF (P ≤ 0.001). The COV was significantly higher for the DF parameter in paroxysmal AF (P < 0.001) and significantly higher for the MP parameter in persistent AF (P < 0.02). CONCLUSIONS: For both paroxysmal and persistent AF data, the 2s sliding window averages provide similar results to single 8.4-second intervals, and information regarding temporal stability was additionally obtained in the process.

The dominant morphology of fractionated atrial electrograms has greater temporal stability in persistent as compared with paroxysmal atrial fibrillation.

BACKGROUND: Measurements of both the dominant frequency (DF) and the time series morphology of complex fractionated atrial electrograms (CFAE) are useful to distinguish persistent from paroxysmal atrial fibrillation (AF). In this study, an algorithm was devised to extract morphologic components according to frequency, and its usefulness for distinguishing CFAE was shown. METHOD: CFAE of length 16s were obtained at two sites each from the four pulmonary vein ostia (PV), and from anterior and posterior left atrial free wall (FW), in nine paroxysmal and 10 longstanding persistent AF patients. The DF was computed for each of two 8s CFAE segments in each 16s recording. Each CFAE segment was then transformed into a set of basis vectors, which represent electrogram morphology at each frequency. The dominant morphology (DM) is defined as the ensemble average of sequential signal segments, with the segment length equal to the period at the DF. The DMs of the two 8s pairs were correlated. Normalized correlation coefficients were tabulated for all data, and separately for PV and FW. The means and coefficients of variation of the DM correlation coefficients were then plotted, and a linear discriminant function was used to classify persistent versus paroxysmal AF data. For comparison with DM results, CFE-mean and interval confidence level (ICL) were also calculated for persistent versus paroxysmal AF data. RESULTS: Mean correlation of the DM, 1st 8s versus 2nd 8s data, was 0.62+0.22 for persistent versus 0.50+0.19 for paroxysmal CFAE for all recording sites (p<0.001). At single anatomical locations, correlation was greater in persistents than paroxysmals at all sites, but achieved significance only at the left superior (p<0.001) and right superior (p<0.05) PV. Spatial variation in correlation coefficient was greater in paroxysmal than persistent AF (not significant). Using the means of DF correlation coefficients, 17/19 patients were classified correctly. The CFE-mean parameter averaged 89.01±20.99 ms in persistents versus 93.96±33.81 ms in paroxysmals (p<0.05), while ICL averaged 94.54±18.52 deflections/8s for persistents versus 90.70±19.28 deflections/8s for paroxysmals (p<0.05). CONCLUSIONS: In CFAE recordings, the DM parameter was found to have greater temporal morphologic variation in paroxysmal as compared with persistent AF data (p<0.001). In contrast, only moderate significance between paroxysmal versus persistent AF data was found when using the of CFE-mean and ICL parameters (p<0.05). The DM parameter may thus be useful as a new measure to discern both temporal and spatial variations in CFAE in paroxysmal versus persistent AF recordings.

Computational method for high resolution spectral analysis of fractionated atrial electrograms.

BACKGROUND: The discrete Fourier transform (DFT) is often used as a spectral estimator for analysis of complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF). However, time resolution can be unsatisfactory, as the frequency resolution is proportional to rate/time interval. In this study we compared the DFT to a new spectral estimator with improved time-frequency resolution. METHOD: Recently, a novel spectral estimator (NSE) based upon signal averaging was derived and implemented computationally. The NSE is similar to the DFT in that both estimators model the autocorrelation function to form the power spectrum. However, as derived in this study, NSE frequency resolution is proportional to rate/period(2) and thus unlike the DFT, is not directly dependent on the window length. We hypothesized that the NSE would provide improved time resolution while maintaining satisfactory frequency resolution for computation of CFAE spectral parameters. Window lengths of 8s, 4s, 2s, 1s, and 0.5s were used for analysis. Two criteria gauged estimator performance. Firstly, a periodic electrogram pattern with phase jitter was embedded in interference. The error in detecting the frequency of the periodic pattern was determined. Secondly, significant differences in spectral parameters for paroxysmal versus persistent AF data, which have known dissimilarities, were determined using the DFT versus NSE methods. The parameters measured were the dominant amplitude, dominant frequency, and mean spectral profile. RESULTS: At all time resolutions, the error in detecting the frequency of the repeating electrogram pattern was less for NSE than for DFT (p<0.001). The DFT was accurate to 2s time resolution/0.5 Hz frequency resolution, while the NSE was accurate to 0.5s time resolution/0.05 Hz frequency resolution. At all time resolutions, significant differences in the dominant amplitude spectral parameter for paroxysmal versus persistent CFAE were greater using NSE than DFT (p<0.0001). For three of five time resolutions, the NSE had greater significant differences than DFT for discriminating the dominant frequency and mean spectral profile parameters between AF types. CONCLUSIONS: The results suggest that the NSE has improved performance versus DFT for measurement of CFAE spectral properties.

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

UNLABELLED: 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).

Identification of recurring patterns in fractionated atrial electrograms using new transform coefficients.

BACKGROUND: Identification of recurrent patterns in complex fractionated atrial electrograms (CFAE) has been used to differentiate paroxysmal from persistent atrial fibrillation (AF). Detection of the atrial CFAE patterns might therefore be assistive in guiding radiofrequency catheter ablation to drivers of the arrhythmia. In this study a technique for robust detection and classification of recurrent CFAE patterns is described. METHOD: CFAE were obtained from the four pulmonary vein ostia, and from the anterior and posterior left atrium, in 10 patients with paroxysmal AF and 10 patients with longstanding persistent AF (216 recordings in total). Sequences 8.4 s in length were analyzed (8,192 sample points, 977 Hz sampling). Among the 216 sequences, two recurrent patterns A and B were substituted for 4 and 5 of the sequences, respectively. To this data, random interference, and random interference + noise were separately added. Basis vectors were constructed using a new transform that is derived from ensemble averaging. Patterns A and B were then detected and classified using a threshold level of Euclidean distance between spectral signatures as constructed with transform coefficients. RESULTS: In the presence of interference, sensitivity to detect and distinguish two patterns A and B was 96.2%, while specificity to exclude nonpatterns was 98.0%. In the presence of interference + noise, sensitivity was 89.1% while specificity was 97.0%. CONCLUSIONS: Transform coefficients computed from ensemble averages can be used to succinctly quantify synchronized patterns present in AF data. The technique is useful to automatically detect recurrent patterns in CFAE that are embedded in interference without user bias. This quantitation can be implemented in real-time to map the AF substrate prior to and during catheter ablation.

A new transform for the analysis of complex fractionated atrial electrograms.

BACKGROUND: 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. METHOD: 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.

Differences in repeating patterns of complex fractionated left atrial electrograms in longstanding persistent atrial fibrillation as compared with paroxysmal atrial fibrillation.

BACKGROUND: Complex fractionated atrial electrograms (CFAE) are morphologically more uniform in persistent longstanding as compared with paroxysmal atrial fibrillation (AF). It was hypothesized that this may result from a greater degree of repetitiveness in CFAE patterns at disparate left atrial (LA) sites in longstanding AF. METHODS AND RESULTS: CFAEs were obtained from recording sites outside the 4 pulmonary vein (PV) ostia and at a posterior and an anterior LA site during paroxysmal and longstanding persistent AF (10 patients each, 120 sequences total). To quantify repetitiveness in CFAE, the dominant frequency was measured from ensemble spectra using 8.4-second sequences, and repetitiveness was calculated by 2 novel techniques: linear prediction and Fourier reconstruction methods. Lower prediction and reconstruction errors were considered indicative of increasing repetitiveness and decreasing randomness. In patients with paroxysmal AF, CFAE pattern repetitiveness was significantly lower (randomness higher) at antral sites outside PV ostia as compared with LA free wall sites (P < 0.001). In longstanding AF, repetitiveness increased outside the PV ostia, especially outside the left superior PV ostium, and diminished at the LA free wall sites. The result was that in persistent AF, there were no significant site-specific differences in CFAE repetitiveness at the selected LA locations used in this study. Average dominant frequency magnitude was 5.32 ± 0.29 Hz in paroxysmal AF and higher in longstanding AF, at 6.27 ± 0.13 Hz (P < 0.001), with the frequency of local activation approaching a common upper bound for all sites. CONCLUSIONS: In paroxysmal AF, CFAE repetitiveness is low and randomness high outside the PVs, particularly the left superior PV. As evolution to persistent longstanding AF occurs, CFAE repetitiveness becomes more uniformly distributed at disparate sites, possibly signifying an increasing number of drivers from remote PVs.

Different characteristics of complex fractionated atrial electrograms in acute paroxysmal versus long-standing persistent atrial fibrillation.

BACKGROUND: Complex fractionated atrial electrograms (CFAEs) may represent a phenomenon associated with sources of atrial fibrillation (AF) and are being used increasingly as targets of catheter ablation. However, current methods have limited efficacy for characterizing CFAEs important to substrate arrhythmogenicity and do not measure electrogram morphology. OBJECTIVE: The purpose of this study was to develop a methodology for quantifying the degree of morphologic heterogeneity in CFAE deflections, and to determine whether there are differences in this measurement between paroxysmal and persistent AF patients. METHODS: Two successive bipolar CFAEs of length 8.4 seconds each were acquired during AF from two sites each at the ostia of the four pulmonary veins (PVs) and from the anterior and posterior left atrial free wall in patients with paroxysmal AF (N = 10) and long-standing persistent AF (N = 10). Extrinsic and intrinsic features of electrogram shape were used to characterize fractionation in CFAE sequences. The extrinsic parameters were the amplitude, upslope, downslope, and width of each deflection. The intrinsic parameter was the voltage profile as characterized by the sum of absolute values. These measurements were compared to the mean interval between CFAE deflections, a standard fractionation indicator. RESULTS: The variability of intrinsic/extrinsic morphologic parameters was higher in paroxysmal than persistent AF at the left superior PV (P < or =.003), the posterior left atrial free wall, anterior left atrial free wall, left inferior PV, and right superior PV (P <.05 for most parameters), and the right inferior PV (not significant). Mean CFAE deflection intervals were longer at all locations in paroxysmal AF but were significant only at the left superior PV and posterior left atrial free wall (P <.05). Quantitative morphologic parameters were not well correlated with dominant frequency (r(2) <0.32); thus, our new measures are robust to changes in activation rate. CONCLUSION: A novel method for quantifying CFAEs, independent of activation rate, has been developed. The method demonstrates greater significance in the difference between CFAE morphology in paroxysmal and long-standing AF compared with mean interval between CFAE deflections. The differences identified suggest that CFAE morphology may evolve as AF persists.

Atrial flutter catheter ablation in adult patients with repaired tetralogy of Fallot: mechanisms and outcomes of percutaneous catheter ablation in a consecutive series.

BACKGROUND: Prior investigators note successful ablation of both typical cavotricuspid isthmus-dependent and scar-related macroreentrant right atrial flutters (AFL) in adult patients with repaired tetralogy of Fallot (TOF). However, an analysis of the mechanisms (including a description of a uniform approach to diagnose such mechanisms), and clinical outcomes of catheter ablation in a consecutive series of adult patients with AFL late after surgical TOF repair has not been previously reported. METHODS: Background clinical data and follow-up were evaluated in a consecutive series of TOF patients evaluated from September 2001 to June 2008. RESULTS: We report a prevalence of sustained, symptomatic AFL in patients with repaired TOF equal to 20% (28/140 patients), and of recurrent, drug-refractory and/or severely symptomatic AFL to be 11% (16/140 patients). The AFLs manifested variable cycle lengths ranging from 215 to 525 ms. Underlying mechanisms were: (1) cavotricuspid (CTI)-dependent, counterclockwise atrial flutter (n=8 patients); (2) non-CTI-dependent macroreentrant scar-related AFL (n=6 patients); and (3) both CTI- and non-CTI-dependent macroreentrant AFL (n=2 patients). Recurrent arrhythmias occurred in six patients, five of whom were successfully treated with repeat ablation. After a mean follow-up of 23 months, 15 of 16 patients were alive and free of sustained AFL. CONCLUSIONS: AFL late after surgical TOF repair occurs in 20% of such patients. In more than half of these patients, the AFLs are drug-refractory and/or severely symptomatic. Despite the presence of congenital heart disease treated with prior cardiac surgery and AFLs with variable atrial cycle lengths, the CTI-dependent mechanism underlies approximately half of the sustained, symptomatic AFLs.