conduction delay
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Author(s):  
ibrahim dönmez ◽  
fatma erdem ◽  
tolga memioğlu ◽  
emrah acar

Purpose:Atrial fibrillation(AF) causes structural, electrical, and cellular remodeling in the atrium. Evaluation of intra- and interatrial conduction time, which is measured by tissue doppler echocardiography, indicates structural and electrical remodeling in the atrium. The aim of this study was to evaluate the effect of pulmonary vein isolation applied with RF ablation therapy on intra- and interatrial conduction time and to investigate the structural and electrically remodeling after treatment. Methods:Fifty-two patients with symptomatic PAF despite at least one antiarrhythmic drug and without structural heart disease were included in the study. Two patients were excluded because of complications developed during and after the operation. Fifty patients (28 female; mean age: 51.68 ± 11.731; mean left atrial diameter: 36.79 ± 4.318) who underwent CARTO® 3D pulmonary vein isolation applied with the RF ablation system were followed-up. Intra- and the inter-atrial electromechanical delay was measured in all patients by tissue doppler echocardiography before and three months after RF ablation. Results:All intra- and interatrial conduction times were significantly decreased 3 months after RF ablation procedure(PA lateral p = 0.022; PA septum p = 0.002; PA tricuspid p = 0.019, interatrial conduction delay p= 0,012, intra-atrial conduction delay p = 0.029). Conclusion:The results of our study suggest that providing stable sinus rhythm by the elimination of the AF triggering mechanisms with RF ablation of pulmonary vein isolation may slow down,stop or even improve structural remodeling at substrate level secondary to AF even in patients who did not yet develop atrial fibrosis and permanent structural changes.


2021 ◽  
Vol 141 (12) ◽  
pp. 1331-1339
Author(s):  
Koji Sakai ◽  
Kenta Shimba ◽  
Kiyoshi Kotani ◽  
Yasuhiko Jimbo

2021 ◽  
Author(s):  
Priyanka Chakraborty ◽  
Shubham Kumar ◽  
Amit Naskar ◽  
Arpan Banerjee ◽  
Dipanjan Roy

Both healthy and pathological aging exhibits gradual deterioration of structure but interestingly in healthy aging adults often maintains a high level of cognitive performance in a variety of cognitively demanding task till late age. What are the relevant network measures that could possibly track these dynamic changes which may be critically relevant for maintenance of cognitive functions through lifespan and how does these measures affected by the specific alterations in underlying anatomical connectivity till day remains an open question. In this work, we propose that whole-brain computational models are required to test the hypothesis that aging affects the brain network dynamics through two highly relevant network measures synchrony and metastability. Since aging entails complex processes involving multiple timescales we test the additional hypothesis that whether these two network measures remain invariant or exhibit different behavior in the fast and slow timescales respectively. The altered global synchrony and metastability with aging can be related to shifts in the dynamic working point of the system based on biophysical parameters e.g., time delay, and inter-areal coupling constrained by the underlying structural connectivity matrix.Using diffusion tensor imaging (DTI) data, we estimate structural connectivity (SC) of individual group of participants and obtain network level synchrony, metastability indexing network dynamics from resting state functional MRI data for both young and elderly participants in the age range of 18-89 years. Subsequently, we simulate a whole-brain Kuramoto model of coupled oscillators with appropriate conduction delay and interareal coupling strength to test the hypothesis of shifting of dynamic working point with age-associated alteration in network dynamics in both neural and ultraslow BOLD signal time scales. Specifically, we investigate the age-associated difference in metastable brain dynamics across large-scale neurocognitive brain networks e.g., salience network (SN), default mode network (DMN), and central executive network (CEN) to test spatio-temporal changes in default to executive coupling hypothesis with age. Interestingly, we find that the metastability of the SN increases substantially with age, whereas the metastability of the CEN and DMN networks do not substantially vary with age suggesting a clear role of conduction delay and global coupling in mediating altered dynamics in these networks. Moreover, our finding suggests that the metastability changes from slow to fast timescales confirming previous findings that variability of brain signals relates differently in slower and faster time scales with aging. However, synchrony remains invariant network measure across timescales and agnostic to the filtering of fast signals. Finally, we demonstrate both numerically and analytically long-range anatomical connections as oppose to shot-range or mid-range connection alterations is responsible for the overall neural difference in large-scale brain network dynamics captured by the network measure metastability. In summary, we propose a theoretical framework providing a systematic account of tracking age-associated variability and synchrony at multiple time scales across lifespan which may pave the way for developing dynamical theories of cognitive aging.


Author(s):  
Weizhuo Liu ◽  
Wentao Gu ◽  
Xinping Luo ◽  
Jian Li ◽  
Nanqing Xiong

A 27-year-old female presenting palpitation without ECG documentation underwent electrophysiology study. EP study revealed atrioventricular accessory pathway with poor and unidirectional pathway conduction, and a fasciculoventricular pathway. During isoproterenol infusion, delta wave promptly became prominent, after which an antidromic AV reentrant tachycardia was induced. When the pathway was mapped, widely split double pathway potentials were observed at 12 o’clock site of tricuspid annulus during mild preexcitation, demonstrating an example of intra-pathway conduction delay, which can be reversed by isoproterenol. Ablation at the site caused accelerated pathway rhythm and eliminated the pathway, rendering the tachycardia non-inducible.


2021 ◽  
Vol 15 ◽  
Author(s):  
S. Kamyar Tavakoli ◽  
André Longtin

Neural circuits operate with delays over a range of time scales, from a few milliseconds in recurrent local circuitry to tens of milliseconds or more for communication between populations. Modeling usually incorporates single fixed delays, meant to represent the mean conduction delay between neurons making up the circuit. We explore conditions under which the inclusion of more delays in a high-dimensional chaotic neural network leads to a reduction in dynamical complexity, a phenomenon recently described as multi-delay complexity collapse (CC) in delay-differential equations with one to three variables. We consider a recurrent local network of 80% excitatory and 20% inhibitory rate model neurons with 10% connection probability. An increase in the width of the distribution of local delays, even to unrealistically large values, does not cause CC, nor does adding more local delays. Interestingly, multiple small local delays can cause CC provided there is a moderate global delayed inhibitory feedback and random initial conditions. CC then occurs through the settling of transient chaos onto a limit cycle. In this regime, there is a form of noise-induced order in which the mean activity variance decreases as the noise increases and disrupts the synchrony. Another novel form of CC is seen where global delayed feedback causes “dropouts,” i.e., epochs of low firing rate network synchrony. Their alternation with epochs of higher firing rate asynchrony closely follows Poisson statistics. Such dropouts are promoted by larger global feedback strength and delay. Finally, periodic driving of the chaotic regime with global feedback can cause CC; the extinction of chaos can outlast the forcing, sometimes permanently. Our results suggest a wealth of phenomena that remain to be discovered in networks with clusters of delays.


2021 ◽  
Vol 12 ◽  
Author(s):  
Mattias Karlsson ◽  
Frida Sandberg ◽  
Sara R. Ulimoen ◽  
Mikael Wallman

During atrial fibrillation (AF), the heart relies heavily on the atrio-ventricular (AV) node to regulate the heart rate. Thus, characterization of AV-nodal properties may provide valuable information for patient monitoring and prediction of rate control drug effects. In this work we present a network model consisting of the AV node, the bundle of His, and the Purkinje fibers, together with an associated workflow, for robust estimation of the model parameters from ECG. The model consists of two pathways, referred to as the slow and the fast pathway, interconnected at one end. Both pathways are composed of interacting nodes, with separate refractory periods and conduction delays determined by the stimulation history of each node. Together with this model, a fitness function based on the Poincaré plot accounting for dynamics in RR interval series and a problem specific genetic algorithm, are also presented. The robustness of the parameter estimates is evaluated using simulated data, based on clinical measurements from five AF patients. Results show that the proposed model and workflow could estimate the slow pathway parameters for the refractory period, RminSP and ΔRSP, with an error (mean ± std) of 10.3 ± 22 and −12.6 ± 26 ms, respectively, and the parameters for the conduction delay, Dmin,totSP and ΔDtotSP, with an error of 7 ± 35 and 4 ± 36 ms. Corresponding results for the fast pathway were 31.7 ± 65, −0.3 ± 77, 17 ± 29, and 43 ± 109 ms. These results suggest that both conduction delay and refractory period can be robustly estimated from non-invasive data with the proposed methodology. Furthermore, as an application example, the methodology was used to analyze ECG data from one patient at baseline and during treatment with Diltiazem, illustrating its potential to assess the effect of rate control drugs.


2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Issam Damin Nayef Alhamaideh ◽  
Tariq Emad Hawash Al-Bkoor ◽  
Adnan Tahir

Objective: The incidence of new onset arrhythmia after conventional aortic valve replacement (AVR) is relatively high whereby atrial fibrillation (AF) in particular (30-40%). Arrhythmias increase postoperative morbidity, mortality and consequently health costs. The need for a reliable method for early detection and discrimination between low and high risk patients is therefore indispensable. For this reason this study examined the possible correlation between electrophysiological abnormalities on continuous ECG recordings and the initiation of arrhythmia directly after surgery. Methods and Results: Both ECG and clinical data was collected from the hospitals filing system for all patient (n=107) who underwent surgical Aortic Valve Replacement (AVR) for non-rheumatic aortic valve stenosis or insufficiency for the period from January 2010 to December 2018.  Continuous ECG data was converted into ISHNE-format and analyzed by using Synescope™ software. Data showed that one minute prior to arrhythmia, AF in particular, an increase of both supraventricular premature beats (SVPB) and missed beats (MB) was detected (n=33; P<0,05). However there was no correlation between arrhythmia and the overall SVPB incidence (n=33). Twenty-one out of 33 AVR patients developed a de novo intraventricular conductance delay directly after cardioplegic arrest, which persisted in 7 cases. Conclusions: Although there is an increase of both SVPB and MB prior to arrhythmia startup, it is still questionable what is the true predictive value of these findings are. Additionally it appeared that a temporarily intraventricular conduction delay (IVCD) is a common finding after AVR.


2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
J Duchenne ◽  
S Calle ◽  
A Puvrez ◽  
F Rega ◽  
F Timmermans ◽  
...  

Abstract Introduction Recent cross-sectional studies suggest a relationship between persisting left bundle branch block (LBBB) and the extent of left ventricular (LV) electro-mechanical alterations over time. When patients are referred for cardiac resynchronization therapy (CRT), temporal data during the sub-clinical phase of disease is often missing. A longitudinal study using an animal model would provide a better understanding of the relationship between the onset of LBBB and the electro-mechanical changes. Purpose To investigate the sequential alterations in LV structure and function that develop over time in an animal model of LBBB. Methods Thirteen sheep were subjected to rapid DDD pacing (180 bpm; leads on right atrium and right ventricular free wall) in order to induce a LBBB-like conduction delay. All animals underwent an 8-week pacing protocol, whereas 4 of them were subjected to 16 weeks of pacing in total. Echocardiographic speckle tracking was used to assess circumferential strain of the septal and lateral wall. Septal and lateral wall thickness were measured at end-diastole. Cardiac magnetic resonance imaging was used to determine LV volumes and ejection fraction (LVEF). Examinations took place at baseline (before and after start of pacing), and after 8 and 16 weeks of pacing. All examinations were performed at a physiologic heart rate of 110 bpm. Results At baseline, DDD pacing induced an increase in QRS duration (+85%, p&lt;0.0001) and LBBB-like mechanical dyssynchrony, with mild early-systolic notching and preserved systolic shortening of the septal wall. The lateral wall demonstrated early pre-stretch followed by increasing systolic shortening. No acute changes in LV end-diastolic volume, LVEF or septal or lateral wall thickness were observed (all p&gt;0.05). After 8 weeks of DDD pacing, mechanical dyssynchrony worsened: septal notching increased, followed by reduced systolic shortening. After 16 weeks, the initial septal shortening was followed by profound stretching throughout systole. Lateral wall systolic shortening was reduced compared to baseline. QRS duration increased further by +12% (week 8) and +20% (week 16) (all p&lt;0.001). End-diastolic volumes had increased by +39% (week 8) and +72% (week 16), whereas LVEF had decreased by −48% (week 8) and −56% (week 16) (all p&lt;0.001). Septal wall thickness had reduced by −24% (week 8) and −33% (week 16), while lateral wall thickness had increased by +21% (week 8) and +30% (week 16) (all p&lt;0.05). Conclusion A persisting LBBB-like conduction delay induces sequential changes in LV deformation patterns, and triggers morphological and electrical remodelling. These changes are similar to those observed in patients with LBBB and different degrees of LV dysfunction. Our data suggest a continuum due to the progression of LBBB-induced LV disease. In the clinic, patients with mild dysfunction should be closely monitored in order to treat dyssynchrony as soon as guideline indications are reached. FUNDunding Acknowledgement Type of funding sources: Other. Main funding source(s): This work was supported by a KU Leuven research grant


2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Gupta ◽  
S Mahajan ◽  
A Malik ◽  
S Mehta ◽  
N Patel

Abstract Introduction Transcatheter Aortic Valve Replacement (TAVR) has emerged as the standard of care for patient with severe aortic stenosis. Conduction abnormalities leading to permanent pacemaker (PPM) implantation is one of the most common complication after TAVR. Newer generation valves (NGV) such as Sapien S3, XT and Evolut are widely being used in real time practice. The aim of this analysis is to compare the predictors associated with increased risk of PPM implantation after TAVR in newer generation valves (NGV) as compared to older generation valves (OGV). Methods A comprehensive literature search was performed in PubMed, Embase, and Cochrane to identify relevant trials. Summary effects were calculated using a DerSimonian and Laird random-effects model as odds ratio with 95% confidence intervals for all the clinical endpoints. Results 18 observational studies with 16,004 patients were identified. The incidence of PPM implantation after TAVR in our analysis was 8.9%. For the NGV, right bundle branch block (RBBB) and atrioventricular (AV) block were independent predictors of PPM insertion after TAVR. Baseline heart rate, presence of atrial fibrillation, and baseline intraventricular conduction delay were not significant predictors. However, for the OGV, risk of PPM implantation after TAVR was higher in presence of RBBB, depth of implant, valve size/annulus size, presence of atrial fibrillation and post-procedure AV block. Conclusions Our analysis identified 2 factors that were significantly associated with increased risk of PPM insertion after TAVR in NGV compared to 6 factors with OGV. With the increasing physician expertise with TAVI and use of NGV, the incidence of post TAVR PPM insertion has reduced but baseline RBBB and AV conduction block still continue to be significant predictors of increased PPM insertion after TAVR. FUNDunding Acknowledgement Type of funding sources: None.


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