Atrial conduction and atrial fibrillation: What can we learn from surface ECG?

Despite the advancements in pharmacological and non-pharmacological management of atrial fibrillation (AF) observed during last decades, available treatment modalities and predictors of their success are still far from optimal. Understanding of pathophysiological mechanisms underlying AF and assessment of atrial electrophysiological properties using easily available non-invasive diagnostic tools such as surface ECG are essential for further improvement of patient-tailored treatment strategies. P-wave duration is generally accepted as the most reliable non-invasive marker of atrial conduction and its prolongation has been associated with history of AF. However, patients with paroxysmal AF without structural heart disease may not have any impressive P-wave prolongation thus suggesting that the global conduction slowing is not an obligatory requirement for development of AF. In these settings, the morphology of P-wave becomes an important source of information concerning propagation of atrial activation. One of the most common morphologies, i.e. biphasic configuration of P-waves in right precordial leads has been considered a marker of left atrial enlargement but, seen in patients with structurally normal hearts, appears to be linked to an interatrial conduction defect. Recent advances in endocardial mapping technologies have linked certain P-wave morphologies with interatrial conduction patterns that may have clinical implications for invasive treatment of AF patients. The value of P-wave morphology extends beyond cardiac arrhythmias associated with atrial conduction delay and can be used for prediction of clinical outcome of wide range of cardiovascular disorders such as survival after myocardial infarction or the risk of stroke

Respiratory Modulation in Permanent Atrial Fibrillation

Several studies have shown that the autonomic nervous system (ANS) can induce changes during atrial fibrillation (AF). There is currently a lack of methods for quantifying ANS induced variations during AF. The purpose of this study is to quantify respiratory induced modulation in the f-wave frequency trend. Following qrst-cancellation, the local f-wave frequency is estimated by fitting a harmonic f-wave model signal and a quality index (SQI) is computed based on the model fit. The resulting frequency trend is filtered using a narrow bandpass filter with a center frequency corresponding to the local respiration rate. The magnitude of the respiratory induced f-wave frequency modulation is estimated by the envelope of the filtered frequency trend. The performance of the method is validated using simulations and the method is applied to analyze ECG data from eight patients with permanent AF recorded during 0.125 Hz frequency controlled respiration before and after the full vagal blockade, respectively. Results from simulated data show the magnitude of the respiratory induced f-wave frequency modulation can be estimated with an error of less than = 0.005Hz if the SQI is above 0.45. The signal quality was sufficient for analysis in 7 out of 8 patients. In 4 patients the magnitude decreased and in 3 patients there was no change

Atrial high rate episodes predict clinical outcome in patients with cardiac resynchronization therapy

OBJECTIVES: Up to 50% of patients qualified for cardiac resynchronization therapy (CRT) have documented atrial fibrillation (AF) prior to CRT-implantation. This finding is associated with worse prognosis but few studies have evaluated the importance of post-implant device-detected AF. This study aimed to assess the prognostic impact of device-detected atrial high rate episodes (AHRE), as a surrogate for atrial fibrillation (AF).DESIGN: Data was retrospectively obtained from consecutive patients receiving CRT. Baseline clinical data and data from CRT device-interrogations, performed at a median of 12.2 months after CRT-implantation, were evaluated with regard to prediction of the composite endpoint of death, heart transplant or appropriate shock therapy. Median follow-up time was 51 months post-implant.RESULTS: The study included 377 patients. Preoperative AF was present in 49% and associated with worse outcome. The cumulative burden of AHRE at 12 months post-implant was an independent predictor of the primary endpoint. During the first 12 months after CRT-implantation, AHRE were detected in 25% of the patients with no preoperative diagnosis of AF. This finding was not associated with worse outcome.CONCLUSIONS: In CRT recipients, the cumulative burden of AHRE during first year of follow-up was associated with worse long-term clinical outcome. Prospective trials are needed to determine if a rhythm control strategy is to be preferred in patients with CRT

ECG-based estimation of respiratory modulation of AV nodal conduction during atrial fibrillation

Information about autonomic nervous system (ANS) activity may be valuable for personalized atrial fibrillation (AF) treatment but is not easily accessible from the ECG. In this study, we propose a new approach for ECG-based assessment of respiratory modulation in AV nodal refractory period and conduction delay. A 1-dimensional convolutional neural network (1D-CNN) was trained to estimate respiratory modulation of AV nodal conduction properties from 1-minute segments of RR series, respiration signals, and atrial fibrillatory rates (AFR) using synthetic data that replicates clinical ECG-derived data. The synthetic data were generated using a network model of the AV node and 4 million unique model parameter sets. The 1D-CNN was then used to analyze respiratory modulation in clinical deep breathing test data of 28 patients in AF, where a ECG-derived respiration signal was extracted using a novel approach based on periodic component analysis. We demonstrated using synthetic data that the 1D-CNN can predict the respiratory modulation from RR series alone ($\rho$ = 0.805) and that the addition of either respiration signal ($\rho$ = 0.830), AFR ($\rho$ = 0.837), or both ($\rho$ = 0.855) improves the prediction. Results from analysis of clinical ECG data of 20 patients with sufficient signal quality suggest that respiratory modulation decreased in response to deep breathing for five patients, increased for five patients, and remained similar for ten patients, indicating a large inter-patient variability.Comment: 20 pages, 7 figures, 5 table

Prolonged repolarization in the early phase of ischemia is associated with ventricular fibrillation development in a porcine model

Background: Repolarization prolongation can be the earliest electrophysiological change in ischemia, but its role in arrhythmogenesis is unclear. The aim of the present study was to evaluate the early ischemic action potential duration (APD) prolongation concerning its causes, expression in ECG and association with early ischemic ventricular fibrillation (phase 1A VF).Methods: Coronary occlusion was induced in 18 anesthetized pigs, and standard 12 lead ECG along with epicardial electrograms were recorded. Local activation time (AT), end of repolarization time (RT), and activation-repolarization interval (ARIc) were determined as dV/dt minimum during QRS-complex, dV/dt maximum during T-wave, and rate-corrected RT–AT differences, respectively. Patch-clamp studies were done in enzymatically isolated porcine cardiomyocytes. IK(ATP) activation and Ito1 inhibition were tested as possible causes of the APD change.Results: During the initial period of ischemia, a total of 11 pigs demonstrated maximal ARIc prolongation >10 ms at 1 and/or 2.5 min of occlusion (8 and 6 cases at 1 and 2.5 min, respectively) followed by typical ischemic ARIc shortening. The maximal ARIc across all leads was associated with VF development (OR 1.024 95% CI 1.003–1.046, p = 0.025) and maximal rate-corrected QT interval (QTc) (B 0.562 95% CI 0.346–0.775, p < 0.001) in logistic and linear regression analyses, respectively. Phase 1A VF incidence was associated with maximal QTc at the 2.5 min of occlusion in ROC curve analysis (AUC 0.867, p = 0.028) with optimal cut-off 456 ms (sensitivity 1.00, specificity 0.778). The pigs having maximal QTc at 2.5 min more and less than 450 ms significantly differed in phase 1A VF incidence in Kaplan-Meier analysis (log-rank p = 0.007). In the patch-clamp experiments, 4-aminopyridine did not produce any effects on the APD; however, pinacidil activated IK(ATP) and caused a biphasic change in the APD with initial prolongation and subsequent shortening.Conclusion: The transiently prolonged repolarization during the initial period of acute ischemia was expressed in the prolongation of the maximal QTc interval in the body surface ECG and was associated with phase 1A VF. IK(ATP) activation in the isolated cardiomyocytes reproduced the biphasic repolarization dynamics observed in vivo, which suggests the probable role of IK(ATP) in early ischemic arrhythmogenesis

Signal-averaged P wave analysis for delineation of interatrial conduction – Further validation of the method

<p>Abstract</p> <p>Background</p> <p>The study was designed to investigate the effect of different measuring methodologies on the estimation of P wave duration. The recording length required to ensure reproducibility in unfiltered, signal-averaged P wave analysis was also investigated. An algorithm for automated classification was designed and its reproducibility of manual P wave morphology classification investigated.</p> <p>Methods</p> <p>Twelve-lead ECG recordings (1 kHz sampling frequency, 0.625 <it>μ</it>V resolution) from 131 healthy subjects were used. Orthogonal leads were derived using the inverse Dower transform. Magnification (100 times), baseline filtering (0.5 Hz high-pass and 50 Hz bandstop filters), signal averaging (10 seconds) and bandpass filtering (40–250 Hz) were used to investigate the effect of methodology on the estimated P wave duration. Unfiltered, signal averaged P wave analysis was performed to determine the required recording length (6 minutes to 10 s) and the reproducibility of the P wave morphology classification procedure. Manual classification was carried out by two experts on two separate occasions each. The performance of the automated classification algorithm was evaluated using the joint decision of the two experts (i.e., the consensus of the two experts).</p> <p>Results</p> <p>The estimate of the P wave duration increased in each step as a result of magnification, baseline filtering and averaging (100 ± 18 vs. 131 ± 12 ms; P < 0.0001). The estimate of the duration of the bandpass-filtered P wave was dependent on the noise cut-off value: 119 ± 15 ms (0.2 <it>μ</it>V), 138 ± 13 ms (0.1 <it>μ</it>V) and 143 ± 18 ms (0.05 <it>μ</it>V). (P = 0.01 for all comparisons).</p> <p>The mean errors associated with the P wave morphology parameters were comparable in all segments analysed regardless of recording length (95% limits of agreement within 0 ± 20% (mean ± SD)). The results of the 6-min analyses were comparable to those obtained at the other recording lengths (6 min to 10 s).</p> <p>The intra-rater classification reproducibility was 96%, while the interrater reproducibility was 94%. The automated classification algorithm agreed with the manual classification in 90% of the cases.</p> <p>Conclusion</p> <p>The methodology used has profound effects on the estimation of P wave duration, and the method used must therefore be validated before any inferences can be made about P wave duration. This has implications in the interpretation of multiple studies where P wave duration is assessed, and conclusions with respect to normal values are drawn.</p> <p>P wave morphology and duration assessed using unfiltered, signal-averaged P wave analysis have high reproducibility, which is unaffected by the length of the recording. In the present study, the performance of the proposed automated classification algorithm, providing total reproducibility, showed excellent agreement with manually defined P wave morphologies.</p

Atrial fibrillatory rate as predictor of recurrence of atrial fibrillation in horses treated medically or with electrical cardioversion

Background The recurrence rate of atrial fibrillation (AF) in horses after cardioversion to sinus rhythm (SR) is relatively high. Atrial fibrillatory rate (AFR) derived from surface ECG is considered a biomarker for electrical remodelling and could potentially be used for the prediction of successful AF cardioversion and AF recurrence. Objectives Evaluate if AFR was associated with successful treatment and could predict AF recurrence in horses. Study design Retrospective multicentre study. Methods Electrocardiograms (ECG) from horses with persistent AF admitted for cardioversion with either medical treatment (quinidine) or transvenous electrical cardioversion (TVEC) were included. Bipolar surface ECG recordings were analysed by spatiotemporal cancellation of QRST complexes and calculation of AFR from the remaining atrial signal. Kaplan-Meier survival curve and Cox regression analyses were performed to assess the relationship between AFR and the risk of AF recurrence. Results Of the 195 horses included, 74 received quinidine treatment and 121 were treated with TVEC. Ten horses did not cardiovert to SR after quinidine treatment and AFR was higher in these, compared with the horses that successfully cardioverted to SR (median [interquartile range]), (383 [367-422] vs 351 [332-389] fibrillations per minute (fpm), P < .01). Within the first 180 days following AF cardioversion, 12% of the quinidine and 34% of TVEC horses had AF recurrence. For the horses successfully cardioverted with TVEC, AFR above 380 fpm was significantly associated with AF recurrence (hazard ratio = 2.4, 95% confidence interval 1.2-4.8, P = .01). Main limitations The treatment groups were different and not randomly allocated, therefore the two treatments cannot be compared. Medical records and the follow-up strategy varied between the centres. Conclusions High AFR is associated with failure of quinidine cardioversion and AF recurrence after successful TVEC. As a noninvasive marker that can be retrieved from surface ECG, AFR can be clinically useful in predicting the probability of responding to quinidine treatment as well as maintaining SR after electrical cardioversion

Age-related changes in P wave morphology in healthy subjects

<p>Abstract</p> <p>Background</p> <p>We have previously documented significant differences in orthogonal P wave morphology between patients with and without paroxysmal atrial fibrillation (PAF). However, there exists little data concerning normal P wave morphology. This study was aimed at exploring orthogonal P wave morphology and its variations in healthy subjects.</p> <p>Methods</p> <p>120 healthy volunteers were included, evenly distributed in decades from 20–80 years of age; 60 men (age 50+/-17) and 60 women (50+/-16). Six-minute long 12-lead ECG registrations were acquired and transformed into orthogonal leads. Using a previously described P wave triggered P wave signal averaging method we were able to compare similarities and differences in P wave morphologies.</p> <p>Results</p> <p>Orthogonal P wave morphology in healthy individuals was predominately positive in Leads X and Y. In Lead Z, one third had negative morphology and two-thirds a biphasic one with a transition from negative to positive. The latter P wave morphology type was significantly more common after the age of 50 (P < 0.01). P wave duration (PWD) increased with age being slightly longer in subjects older than 50 (121+/-13 ms vs. 128+/-12 ms, P < 0.005). Minimal intraindividual variation of P wave morphology was observed.</p> <p>Conclusion</p> <p>Changes of signal averaged orthogonal P wave morphology (biphasic signal in Lead Z), earlier reported in PAF patients, are common in healthy subjects and appear predominantly after the age of 50. Subtle age-related prolongation of PWD is unlikely to be sufficient as a sole explanation of this finding that is thought to represent interatrial conduction disturbances. To serve as future reference, P wave morphology parameters of the healthy subjects are provided.</p

Risk Prediction of Atrial Fibrillation Based on Electrocardiographic Interatrial Block

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144584/1/jah33160_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144584/2/jah33160-sup-0001-SupInfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144584/3/jah33160.pd