Paced Beats Research Articles

Rhythm and rate control strategies in patients with long-standing persistent atrial fibrillation treated with cardiac resynchronization: the results of the randomized Pilot-CRAfT study.

Atrial fibrillation (AF) is common in cardiac resynchronization therapy (CRT) recipients. It is a marker of impaired CRT response mainly mediated by the reduction of effectively captured biventricular paced beats (BiVp). There are no randomized trials comparing strategies to maintain high BiVp percentage. To compare the efficacy of rhythm vs rate control strategies in CRT recipients with long-standing persistent AF. We performed a randomized trial including CRT recipients with persistent AF resulting in low BiVp%. All patients received amiodarone, the rhythm control group received external electrical cardioversion (EC), and the rate control group received atrioventricular node ablation, if needed. The primary end-point was 12-month BiVp% (NCT). 43 patients were included in the analysis. The mean age was 68.4 (SD: ± 8.3) years and the mean BiVp% 82.4% ± 9.7%. AF lasted 25 ± 19 months. The mean baseline left ventricular ejection fraction (LVEF), left atrium area, and the maximal oxygen uptake (VO2max) were: 30 ± 8%, 33 ± 7 cm2, and 14 ± 5 mL/(kg*min), respectively. The EC success rate was 58%. 38% patients remained in sinus rhythm (SR) after 12 months. BiVp% increased similarly in both arms reaching 99% [95% CI 97.3-99.8] and 98% [94.0-99.0], P = 0.14 in rhythm and rate control groups, respectively. LVEF raised significantly only in the rhythm control group (ΔLVEF 4.1 (± 7.3), P = 0,018) which was driven by the patients who maintained SR. No differences in VO2max, QoL, clinical and safety end-points were observed. Despite comparable BiVp% in both groups, only restoration of SR led to improved left ventricular ejection fraction in CRT patients with long-standing AF. NCT01850277 registered on 22/04/2013.

Utility of noninvasive electrocardiographic imaging in the localization of nonpulmonary vein triggers of atrial fibrillation determined by pacing common trigger sites.

Identifying the origin of nonpulmonary vein atrial fibrillation (AF) triggers (NPVTs) after pulmonary vein isolation (PVI) can be challenging. We aimed to determine if noninvasive electrocardiographic imaging (ECGi) could localize pacing from common NPVT sites. ECGi combines measured body surface potentials with heart-torso geometry acquired from computed tomography (CT) to generate an activation map. In 12 patients with AF undergoing first time ablation, the ECGi vest was fitted for preprocedural CT scan and worn during the procedure. After PVI, we performed steady-state pacing from 15 typical anatomic NPVT sites at a cycle length of 700-800 ms. We co-registered the invasive anatomic map with the CT-based ECGi epicardial activation map to compare ECGi predicted to true pacing origin. In the study cohort (67% male, 58% persistent AF, and 67% with left atrial dilation), 148 (82%) pacing sites had both capture and adequate anatomy acquired from the three-dimensional mapping system to co-register with ECGi activation map. Median distance between true pacing sites and point of earliest epicardial activation derived from the ECGi maps for all sites was 17 mm (interquartile range, 10-22 mm). Assuming paced sites treated as regions with a radius of 2.5 cm, the earliest activation site on ECGi map falls within the region with 94% accuracy. ECGi can approximate the origin of paced beats from common NPVT sites to within a median distance of 17 mm. A rapidly identified region may then be the focus of more detailed catheter-based mapping techniques to facilitate successful localization and ablation of NPVTs.

AV synchrony maintained by a dual-chamber leadless pacemaker in real-world conditions

Abstract Background/Introduction A dual-chamber leadless pacemaker system has been developed to provide atrial and ventricular pacing and maintain atrioventricular (AV) synchrony. The device demonstrated an ability to maintain consistent AV synchrony in an in-clinic setting when tested through a series of postures and gaits under some programming restrictions. Assessing AV synchrony within real-world conditions is needed to understand the device’s performance under wider variations in activity and over a longer period. Purpose Assess a dual-chamber leadless pacemaker’s ability to maintain AV synchrony in an ambulatory environment of daily living under clinically driven programmed settings. Methods Implanted de novo subjects, who had at least 25% atrial pacing after 3-months post-implant, wore a 12-lead Holter monitor for a minimum of 24 hours during normal daily activities and completed a symptom diary. Devices were programmed to a dual chamber pacing mode and clinically appropriate settings then interrogated pre- and post-assessment. An independent Core Laboratory evaluated AV Synchrony, based on a configurable sampling window approach at repeated intervals, and defined synchronous cycles based on whether PR intervals fell within a 50 ms margin of the programmed Paced AV Delay. Results Among the 50 subjects who were administered the assessment, 48 of their Holters were analyzable (mean age 71.4 ± 10.9 years; 66.7% male), and 47 subjects had paired device interrogation data available. The analyzable population was predominantly indicated for sinus node dysfunction (83.3%) with a minority indicated for AV block (16.7%). The mean ± standard deviation of the programmed paced AV delay was 260.0 ± 47.6 ms, and mean PR interval was 241.4 ± 35.1 ms. An atrial paced beat and ventricular paced beat were each present in 69.5% and 22.5% of the evaluable cardiac cycles in the population, respectively. Mean AV Synchrony was maintained above 97% (95% CI: 95.5, 98.8) in the entire cohort and was sustained at high rates within each sub-population. Device metrics that diagnose the rate of directional implant-to-implant (i2i) communication also confirmed device data average throughput rates above 90% (Picture 1). There were no reported episodes of oversensing, undersensing, loss of capture, or pauses. Conclusion Among subjects with standard pacemaker indications, the dual-chamber leadless pacemaker system maintains very high rates of AV synchrony, exceeding i2i throughput, within real-world conditions utilizing clinically appropriate programmed settings.AV Synchrony and i2i by Indication

ECG Arrhythmia Classification using Deep Learning

An electrocardiogram (ECG) is a painless, noninvasive way to help diagnose numerous common heart problems. ECG plays an important role in diagnosing various Cardiac ailments. In recent years, Deep learning techniques have shown remarkable promise in achieving accurate and automated ECG arrhythmia classification. The primary goal of the system is to develop a robust and accurate system for the automated detection and classification of arrhythmias in electrocardiogram (ECG) data. By leveraging state-of-the-art techniques such as Convolutional Neural Networks (CNNs), we analyze pattern recognition within ECG signals to detect arrhythmias. Furthermore, we address the challenge of dataset scarcity by augmenting the data through nine different image cropping methods during the training phase. The implementation of techniques like Batch Normalization and data augmentation will further enhance the model's adaptability to diverse data sources, making it an invaluable tool for healthcare professionals. The CNN will be trained and tested using the ECG Dataset obtained from the MIT-BIH Database and from it, seven types of signals of arrhythmia will be classified. These seven signals are Premature Ventricular contractions (PVC), Paced beat (PAB), Right bundle branch block beat (RBB), Left bundle branch block beat (LBB), Atrial premature contraction (APC), Ventricular escape beat (VEB) and Normal beat. This system bridges the gap between advanced technology and healthcare, offering a transformative approach to ECG arrhythmia classification that has the potential to significantly improve patient outcomes and reduce the burden of manual diagnosis

A novel technology for heart failure that utilizes the respiratory effort to shift fluids from the lung and alleviate cardiac workloads; feasibility study in sheep

Abstract Introduction Hemodynamic congestion is governed by inflow from RV and drainage through LV. However, ventricle functions are affected by the intrathoracic/pleural pressure: Negative pleural pressure (PPL) increases RV outflow while decreasing LV outflow, and vice versa at high PPL. Cardiac decompensation is associated with an increase in the respiratory effort (the peak-to-peak changes in PPL). We suggest to utilize this respiratory effort to shift fluid out of the lung and alleviate hemodynamic congestion. It is done by pacing the heart when PPL is high and the LV stroke volume is larger than the RV stroke volume. Purpose To test the feasibility of the novel technology in sheep. To verify that it is possible to modify the distribution of the heart beat within the respiratory cycle (slightly modify the rhythm according to the PPL) with insignificant effect on mean heart rate. Methods The utility was validated in sheep (N=9), under spontaneous breathing before and after induction of acute infarction by balloon inflation in the mid-LAD artery. The device senses the intracardiac electrical activity and respiratory effort and paces the right atrium when the PPL is high. The R-R interval of the paced beats was shorter than the sinus R-R interval by less than 10%. The effects of PPL and device pacing on LV and RV stroke-volumes were derived from simultaneous measurements of RV and LV pressure-volume loops, utilizing two impedance catheters (CD-Leycom) within both ventricles. Results The respiratory effort had significant effects on RV and LV outputs before and after infarction. The stroke volumes of the two ventricles were in antiphase! At low PPL the RV output increased while the LV decreased by about 10%, and the opposite occurred at high PPL. The pacing increased cardiac beating probability at high PPL. Sequential pacing for one minute increased the systolic pressure by 5 mmHg while decreasing the pulmonary artery pressure. Based on the pressure-volume loops, each paced breath cycle increased the LV outflow by 1.14 ml and decreased RV outflow by 0.36ml, yielding a shift of 1.5 ml from the lung. Interestingly, it was associated with a decrease in the sinus rate, which further decreased cardiac beating at low PPL and may represent a decrease in sympathetic tone. Conclusions Pacing only 1% of the ∼20,000 daily breath-cycles can shift 300 ml from the lung per day! The technology is agnostic of the heart-failure etiology. Preclinical studies in a model of chronic heart failure are required to further validate the novel approach.

PO-04-057 ATRIAL FIBRILLATION CURED BY PACEMAKER REPROGRAMMING

Atrial fibrillation (AF) is commonly detected by remote monitoring of implanted devices. A common question is whether to start anticoagulation in patients with detected AF at risk of stroke. However, the cause of AF is rarely able to be diagnosed or corrected. Repetitive non-reentrant ventriculoatrial synchrony (RNRVAS) is a pacemaker mediated arrhythmia that can occur in patients with intact ventriculoatrial (VA) conduction. Ventricular pacing with retrograde atrial activation that falls within the PVARP is followed by atrial pacing, often delivered while the atrium is refractory. Retrograde atrial activation from the next ventricular paced beat facilitates a repetitive (but non-reentrant) process. Atrial arrhythmias may occasionally result. To highlight the importance of recognizing and correcting RNRVAS as a cause of device-mediated arrhythmia. NA A 68-year-old man with hypertension and sinus node dysfunction underwent dual chamber pacemaker implant (Abbott Assurity). Device interrogation 5-years later showed repetitive episodes of AF that might warrant anticoagulation. Device tracings revealed RNRVAS: retrograde atrial activation falling in PVARP, followed by competitive sensor driven atrial pacing with non-capture, until a captured atrial event initiated AF (Figure, red arrow). Anticoagulation was deferred in favor of device reprogramming, including: 1) reduction in the lower rate; 2) reduction in paced AV delay; and 3) disabling of rate-response. The patient had no further AF episodes. RNRVAS is largely benign but may facilitate initiation of AF or other supraventricular arrhythmias that lead to symptoms or inappropriate therapy. Both RNRVAS and device-triggered AF may be underrecognized. Current devices do not have automatic diagnostic or treatment algorithms. Therefore, it is important to be aware of RNRVAS triggered AF in patients with a dual-chamber device and newly diagnosed AF. RNRVAS tends to occur with a long programmed AV delay (such as is often used to avoid ventricular pacing) and a relatively fast lower rate. Reprogramming to shorten the AV delay, decrease the lower rate or decrease the PVARP are the primary methods of correction. Awareness of pacemaker triggered AF may help avoid inappropriate initiation of anticoagulation or other therapies.

First-in-human noninvasive left ventricular ultrasound pacing: A potential screening tool for cardiac resynchronization therapy.

A screening tool to predict response to cardiac resynchronization therapy (CRT) could improve patient selection and outcomes. The purpose of this study was to investigate the feasibility and safety of noninvasive CRT via transcutaneous ultrasonic left ventricular (LV) pacing applied as a screening test before CRT implants. P-wave-triggered ultrasound stimuli were delivered during bolus dosing of an echocardiographic contrast agent to simulate CRT noninvasively. Ultrasound pacing was delivered at a variety of LV locations with a range of atrioventricular delays to achieve fusion with intrinsic ventricular activation. Three-dimensional cardiac activation maps were acquired via the Medtronic CardioInsight 252-electrode mapping vest during baseline, ultrasound pacing, and after CRT implantation. A separate control group received only the CRT implants. Ultrasound pacing was achieved in 10 patients with a mean of 81.2 ± 50.8 ultrasound paced beats per patient and up to 20 consecutive beats of ultrasound pacing. QRS width at baseline (168.2 ± 17.8 ms) decreased significantly to 117.3 ± 21.5 ms (P<.001) in the best ultrasound paced beat and to 125.8 ± 13.3 ms (P <.001) in the best CRT beat. Electrical activation patterns were similar between CRT pacing and ultrasound pacing with stimulation from the same area of the LV. Troponin results were similar between the ultrasound pacing and the control groups (P = .96), confirming safety. Noninvasive ultrasound pacing before CRT is safe and feasible, and it estimates the degree of electrical resynchronization achievable with CRT. Further study of this promising technique to guide CRT patient selection is warranted.

112 A CASE OF INCESSANT SLOW-FAST AVNRT TREATED WITH HIS BUNDLE PACING

Abstract Introduction Slow-fast AVNRT can rarely present as incessant SVT, particularly in patients with increased HV interval. We describe a case of incessant typical AVNRT, treated without transcatheter ablation. Case Presentation An 83-year-old man, with history of PAF, was admitted to our ICU complaining of dyspnea, dizziness and amaurosis. His ECG at presentation depicted sinus bradycardia, first degree AVB (PQ=400 ms) and RBBB (Fig 1A). After betablocker wash-out period, we decided to perform CSP using HBP to ensure AV synchrony and restore physiological pacing. During wash-out period, an incessant regular wide complex tachycardia with RBBB morphology and ventricular rate of 110 bpm occurred: the tracing showed a P wave immediately after the QRS, with RP &amp;lt; PR (Fig 1B). The tachycardia was incessant also in the EP lab. By means of 2 pacing leads (RV lead in the apical septum and RA lead in right appendage) and one diagnostic decapolar catheter (Inquiry, 2-2-2 Abbott) in His region, all connected to the polygraph, we performed an EPS. HV interval in sinus rhythm was 60 ms, AH 340 ms. The electrograms during tachycardia showed HVA sequence and 1:1 VA association, VA&amp;lt; 70 ms, cycle length 520 ms. Pacing from RV lead, we performed the ventricular overdrive pacing maneuver obtaining a VAV response; PPI-TCL was 280 ms and SA-VA difference was 205 ms (Fig 2A). We also noted a VA linking response to atrial overdrive pacing, and AHA response at the end of maneuver excluding JT (Fig 2B). In addition, pacing by the His catheter during tachycardia, we interrupted the arrythmia: the V signal after the last paced beat was not followed by retro-conducted A signal (Fig 2C). Finally, by administrating adenosine 12 mg the tachycardia interrupted with A as last signal recorded (Fig 2D). All these findings were consistent with an incessant typical AVNRT. We chose to treat AVRNT with sequential atrial-His pacing, placing a third lead in His region and programming the device in DDD 70-120, with selective His bundle capture, not correcting the RBBB (Fig 1C, D). Discussion In patients with poor anterograde AV nodal conduction, also slow-fast AVNRT can present as incessant tachycardia. In fact, a shorter sinus cycle length or atrial extrasystole could initiate sufficient delay in anterograde conduction to allow for recovery in conduction in the retrograde direction led to a persistent tachycardia. This case highlights the value of performing EPS diagnostic maneuvers also during PM implantations in order to personalize therapy and programming.

Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices.

Existing strategies that identify post-infarct ventricular tachycardia (VT) ablation target either employ invasive electrophysiological (EP) mapping or non-invasive modalities utilizing the electrocardiogram (ECG). Their success relies on localizing sites critical to the maintenance of the clinical arrhythmia, not always recorded on the 12-lead ECG. Targeting the clinical VT by utilizing electrograms (EGM) recordings stored in implanted devices may aid ablation planning, enhancing safety and speed and potentially reducing the need of VT induction. In this context, we aim to develop a non-invasive computational-deep learning (DL) platform to localize VT exit sites from surface ECGs and implanted device intracardiac EGMs. A library of ECGs and EGMs from simulated paced beats and representative post-infarct VTs was generated across five torso models. Traces were used to train DL algorithms to localize VT sites of earliest systolic activation; first tested on simulated data and then on a clinically induced VT to show applicability of our platform in clinical settings. Localization performance was estimated via localization errors (LEs) against known VT exit sites from simulations or clinical ablation targets. Surface ECGs successfully localized post-infarct VTs from simulated data with mean LE = 9.61 ± 2.61 mm across torsos. VT localization was successfully achieved from implanted device intracardiac EGMs with mean LE = 13.10 ± 2.36 mm. Finally, the clinically induced VT localization was in agreement with the clinical ablation volume. The proposed framework may be utilized for direct localization of post-infarct VTs from surface ECGs and/or implanted device EGMs, or in conjunction with efficient, patient-specific modelling, enhancing safety and speed of ablation planning.

Abstract 14320: Regionalization of Non-Pulmonary Vein Triggers for Atrial Fibrillation Using Non-Invasive Electrocardiographic Imaging

Introduction Ablation of non-pulmonary vein triggers (NPVTs) after pulmonary vein isolation (PVI) reduces atrial fibrillation (AF) recurrence, but localizing NPVTs can be challenging. We evaluated the potential for noninvasive electrocardiographic imaging (ECGi) to regionalize NPVTs and expedite more focused catheter-based mapping. ECGi combines measured body surface potentials with heart-torso geometry acquired from computed tomography (CT), to generate an activation map from a single recorded beat. Methods In 12 patients with AF undergoing first time AF ablation, the ECGi vest was fitted for preprocedural CT scan and then worn during procedure. Following completion of PVI, we paced from 15 atrial sites where NPVTs commonly arise (Figure 1), and evaluated the epicardial activation map generated by ECGi during steady state pacing at cycle length of 700-800 ms allowing an unobscured P wave. Merging of invasive anatomic map with CT-based ECGi map allowed comparison of ECGi activation map with true pacing location (Figure 2). Results From 180 pacing sites in our patient cohort (67% male, 58% persistent AF, 67% left atrial dilation), median distance between earliest activation site on ECGi map and pacing location was 16 mm (interquartile range, 11-22 mm), with 95% of sites within 30 mm (Figure 2). Septal pacing sites were measured to the epicardial aspect of the interatrial septum. Conclusions ECGi is able to consistently approximate the origin of paced beats from common NPVT sites and suggests the potential for rapid regionalization of NPVTs. The identified region can then be the focus of more detailed catheter-based mapping techniques to facilitate successful ablation of NPVTs.

Pacemaker-Mediated Tachycardia Interpolated Into Ventricular Tachycardia

In a 77-year-old patient with a history of inferior myocardial infarction and dual-chamber pacemaker (Effecta DR, Biotronik) implanted for carotid sinus syndrome, a routine Holter electrocardiogram recorded 3 consecutive tachycardias: irregular monomorphic ventricular tachycardia (VT), pacemaker-mediated tachycardia (PMT), and reoccurred VT (re-VT) of the same morphology as the initial one, but regular and faster than the PMT (Fig. 1).The pacemaker settings were as follows: DDD mode; pacing rate, 50 to 130 bpm; programmed atrioventricular delay, paced 145 ms and sensed 105 ms; and postventricular atrial refractory period (PVARP), 250 ms and 400 ms following premature ventricular contraction.What was the most likely mechanism of this arrhythmia?B) PMT was triggered by atrial premature beat and terminated by the re-VT (Fig. 2) Concerning the mode of the PMT initiation, the VT could not trigger PMT because its retrograde P wave (in Fig. 2, stars denote retrograde P waves; those of the VT and re-VT are marked below and those of the PMT above the middle electrocardiographic channel) occurred during the PVARP (gray horizontal marks in the ladder diagram). Given that the interrogation showed no pacemaker malfunctions and that the electrocardiogram showed no artifacts, an atrial ectopic beat (with isoelectric P wave) is the only likely trigger for PMT.Concerning the mode of PMT termination, the episode was too short to activate the device's PMT termination algorithm. Furthermore, the retrograde P wave from the last PMT beat, which appeared after 344 ms, indicates that retrograde conduction has been prolonged, but without occurrence of a block that would have stopped the PMT. Thus, the re-VT is what terminated the PMT by the first impulse following fusion (f2 in Fig. 2), which depolarized ventricles before the possible onset of the next paced beat. Retrograde conduction prolongation (by 24 ms) and programmed atrioventricular delay prolongation (by 50 ms, for Biotronik's PMT status confirmation) during the last PMT cycle provided a time for the onset of the re-VT and thus indirectly participated in the PMT termination.Based on the constant cycle length (382 ms) of the re-VT during the prolongation of ventriculoatrial conduction (from 170 to 240 ms), the re-VT was most probably microreentrant. Different retrograde conduction times of the VT (160 ms) and PMT (315 ms) might suggest the existence of a dual retrograde conduction with separate pathways for each of the 2 tachycardias, but any evidence for such speculation is lacking. In any case, this case illustrates the complexity of possible interactions between spontaneous and device-mediated arrhythmias.

Effect of Direct Slow Pathway Capture Mapping–Guided Ablation on Typical Atrioventricular Nodal Re-Entrant Tachycardia

BackgroundDirect slow pathway capture (DSPC) mapping is a novel electrophysiological technique for detecting antegrade slow pathway input sites. However, the effect of DSPC mapping–guided ablation on atrioventricular nodal re-entrant tachycardia (AVNRT) is unknown. ObjectivesThis study aimed to evaluate the efficacy and safety of DSPC mapping–guided ablation in typical AVNRT patients. MethodsA multicenter retrospective study was conducted in 301 consecutive typical AVNRT patients. The outcomes in patients who underwent DSPC mapping–guided ablation (DSPC group) and those who underwent conventional anatomical ablation (conventional group) were compared. The conventional group was established before introducing DSPC mapping–guided ablation. Positive DSPC sites were defined as sites with a return cycle atrioventricular prolongation of ≥20 ms with high-output (10-20 V) pacing during tachycardia or the last paced beat of the atrial extrastimulation. ResultsAmong 116 patients in the DSPC group, 102 (88%) had positive DSPC sites, and 86 (74%) had a successful ablation at that site. Of the remaining 30 patients, 27 had a successful anatomical ablation. The DSPC group had a significantly lower frequency of radiofrequency applications and shorter total application time than the conventional group (median: 5.5 [IQR: 3-11] times vs 9 [IQR: 5-15] times, and 168 [IQR: 108-266] seconds vs 244 [IQR: 158-391] seconds, respectively; P < 0.01). Moreover, the DSPC group had a numerically lower incidence of permanent pacemaker implantations and AVNRT recurrences than the conventional group (0% vs 1.6%; P = 0.17, and 1.7% vs 3.2%; P = 0.43, respectively). ConclusionsDSPC mapping–guided ablation was associated with a lower operative time, which can reduce the risk of AV conduction injury in typical AVNRT.

Cardiac arrhythmia classification by time–frequency features inputted to the designed convolutional neural networks

The electrocardiogram (ECG) plays a vital auxiliary role in medical diagnosis, but due to the very low amplitude of the ECG signals, it is challenging and time-consuming to conduct artificial visual evaluation of the ECG signals. In recent years, medical aid research methods through ECG have emerged one after another. However, most of them have defects such as poor model generalization ability and obvious individual differences. This paper constructs two-way multiplex convolutional neural networks (CNNs) based on time–frequency features to classify normal cardiac rhythm (NOR) and seven cardiac arrhythmias including atrial premature contraction (APC), ventricular premature beat (PVC), left bundle branch block (LBBB), right bundle branch block (RBBB), signal quality change (∼), ventricular fused heart beat (FVN), and pacing heart beat (/). Firstly, the preprocessing steps of the original rough ECG signal are arranged in a unique order, including wavelet transform, threshold denoising, normalization, chopping, mel-frequency cepstral coefficients (MFCC). Secondly, a 12-layer one-dimensional CNN model with block representation and a 11-layer auxiliary-two-dimensional CNN architecture are designed for the time-domain feature and the frequency-domain feature, respectively, where the focal loss function is defined to solve the problem of data categories imbalance. Finally, the experimental results show that the proposed algorithm presents excellent performances in processing variable length ECGs, the average accuracy of time-domain model is 99.1 %, and the classification accuracy of APC in frequency-domain model is 96.3 %.

Heart rate distribution in dogs with third degree atrioventricular block and rate responsive pacemakers

IntroductionIn dogs, single lead ventricular pacing, ventricular sensing, inhibition response, rate adaptive (VVIR) pacemakers are routinely used to treat third degree atrioventricular block. The objectives of this study were to investigate the heart rate distribution in dogs with VVIR pacemakers, and report changes when activity settings were adjusted. AnimalsEighteen client-owned dogs with VVIR pacemakers for third degree atrioventricular block. Materials and methodsThis observational study consisted of a review of medical records of dogs with VVIR pacemakers. For dogs with >50% of paced beats at the lower pacing rate, the activity daily living (ADL) and exertion responses were increased. Re-evaluations were performed after 6–12 months. ResultsHeart rate distribution similar to healthy dogs was absent for all dogs. In nine dogs, the ADL and exertion responses were increased to the highest level. Of these, three dogs showed no improvement in heart rate distribution; for two dogs, one with an epicardial pacemaker, several activity settings were adjusted and pacing at higher heart rates was observed at re-evaluation. Four dogs died or were lost to follow-up. Clinical signs had resolved for all dogs after pacemaker implantation. ConclusionDefault activity settings of VVIR pacemakers do not result in heart rate distribution equivalent to healthy dogs. Increasing the ADL and exertion response settings to the highest levels did not improve the pacemaker rate response. Further investigations into the role of dog size, generator positioning, pacemaker settings, and whether rate responsiveness is required for dogs' quality and quantity of life are warranted.

Automated quantification and identification of decremental response after extrastimulus: validation of a novel software

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Junta de Andalucia Background Automatic identification of myocardial electrograms (EGMs) with decremental conduction (DC) is a promising field in catheter ablation procedures, allowing the identification of the critical isthmus of tachycardias with re-entry mechanisms. In this work, a novel artificial intelligence (AI)-based software was developed for the automatic analysis of delays between evoked responses in the coronary sinus (CS), allowing signal quantification. Methods Atrioventricular (AV) and ventriculoatrial (VA) conduction was analysed in coronary sinus signals obtained from patients undergoing electrophysiological study. A simple pacing (S=400-600ms) and extra-stimulus protocol (S2=ERP + 20-60ms) were used in all cases. An AI-based algorithm was developed for EGM delineation with the objective of localising the onsets and offsets of each independent local and far field activations. The algorithm consisted in several steps. Firstly, an AI-based QRS detector was employed (Figure 1A). Secondly, the located QRS’ were used alongside another AI model to delineate the EGMs corresponding to all bipolar electrodes in the CS (Figure 1B). Thirdly, majority voting is performed on the delineations to obtain an overall prediction for all CS electrodes (Figure 1C). Fourthly, the predictions are cleaned and a rule-based algorithm is employed to automatically exclude faulty registries (e.g. loss of capture or AV/VA block after S2). Finally, the determination of decremental response is performed by computing the time difference between the last paced beat and the S2 extrastimulus. This was measured using the onsets of morphologically similar activations in the trace, correcting for misalignments. A decremental response was defined as a difference &amp;gt;10 ms between the AV/VA interval during the S1 drive and the same interval immediately after the S2. Four experts validated results of the automated analysis. Results 321 tracings from 50 patients were analysed. 81 tracings were automatically excluded due to loss of capture or AV/VA block after S2. The AV/VA interval was automatically annotated in 236 EGMs. 192 tracings exhibited decremental conduction properties, whereas 48 tracings showed non-decremental AV or VA conduction due to accessory pathways. Automatic analysis accurately classified 191 tracings as decremental (93.75% sensitivity, 91.47% specificity) and 45 tracings as non-decremental (85.42% sensitivity, 98.53% specificity). Conclusions AI-based algorithms are able to produce objective quantifications over real-world data, discriminating between local and far field signals and accurately identifying EGMs with decremental evoked response. Automated data analysis can accelerate research and reduce clinical workload. Moreover, a quantification-based approach can be employed in many other applications. Validation of this software on ventricular signals could facilitate ventricular tachycardia substrate ablation procedures.

Non-invasive delineation of ventricular tachycardia substrates for cardiac stereotactic body radiotherapy: utility of in-silico pace-mapping

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): EPSRC Background Cardiac stereotactive body radiotherapy (CSBRT) is an emerging, non-invasive ablation modality that targets ventricular tachycardia (VT) substrates in patients with limited conventional treatment options. Success of CSBRT hinges primarily on the correct identification of VT targets, which requires non-invasive planning. Current non-invasive, pre-procedure strategies employ multi-electrode electrocardiographic imaging (ECGi). Given its significant cost and potential challenges in detecting endocardial, intramural and/or septal VT sites, there is a need to optimise VT delineation strategies for CSBRT; patient-specific simulations may show promise at guiding such planning non-invasively. Purpose We aim to perform non-invasive, in-silico pace-mapping on an image-based computational model to identify VT substrates for CSBRT. We intend to show the utility of our fast computational pipeline - relying on CT imaging data only - to provide further insights on inaccessible, scar-related VT episodes. Methods A detailed computational torso model of a CSBRT candidate with incessant VT was generated from CT imaging data. Extracellular content volumes (ECVs) were used to identify different tissue types (healthy, border zone and non-conducting), and scale model tissue conductivities accordingly. In-silico pace-mapping was performed by simulating ~360 paced beats across the LV, and computing corresponding 12-lead ECGs within a fast electrophysiological (EP) simulation environment combining reaction-eikonal and lead field methods. QRS complexes from simulated paced beats were used to construct the virtual correlation pace-map against the measured QRS of the clinically-induced VT, along with a ‘reference-less’ virtual pace-map constructed from neighbouring paced-beat QRSs (within a 20 mm radius). An epicardial activation map of the clinically-induced VT was reconstructed from ECGi measurement, and used for comparison against our virtual pace-maps. Results Correlations between simulated paced-beat QRS complexes and the clinically-induced VT QRS were higher in mid-apical, infero-septal segments - segment 9 (85.71%), 10 (87.95%) and 15 (89.58%) - identifying septal origin and pathway of the induced re-entrant circuit. A possible septal VT isthmus was also identified by a high gradient in the virtual reference-less pace-map in segment 9 (&amp;gt; 2.5%/mm). Our in-silico predictions were in agreement with the clinical regions identified for CSBRT (segment 9 and 15), and provided additional information on the 3D and septal dynamics of the VT episode. Conclusions Our in-silico pace-mapping study successfully localised VT substrates in a patient unable to receive standard ablative procedures, and provided further clinical insight on the induced VT dynamics. Our rapid in-silico pace-mapping approach may be utilised to support optimal identification of VT target volumes for CSBRT.

Diagnostic reliability of AV synchrony self-diagnostics in leadless VDD pacemakers

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Leadless pacemakers (PMs) capable of atrio-ventricular (AV) synchronous pacing have been introduced recently. These devices provide mechanical atrial sensing by detection of the atrial contraction via an accelerometer. Atrial tracking may be disturbed by external influences such as body motions and higher heart rates in real life. To track the amount of AV synchronous pacing, the device statistic classifies all sensed and paced QRS complexes according to presumed AV synchrony. The reliability of this self-diagnostics to estimate the true degree of AV synchrony, however, is insufficiently studied. Purpose To investigate the informative value of the device statistics offered by leadless VDD PMs regarding true AV snychrony. Methods We prospectively included all patients who received a leadless VDD PM between 07/2020 and 05/2021 at our center in this observational study. During the regular outpatient follow-ups, device interrogation was performed, which included evaluation of the PM statistics. True AV synchrony (defined as a QRS complex preceded by a p-wave within 300ms) was analyzed repeatedly during follow-up using Holter ECGs. Results We analysed 34 Holter ECGs from 20 outpatients (816 hours of ECG in total). Patients had a median age of 80 years (interquartile range 76-86 years), 55% were females. For Holter ECG sequences that showed high degree or complete AV-Block (&amp;gt;80% ventricular pacing), the percentage of paced beats that were presumed to be AV synchronous by the device statistic (ratio "AM-VP"/total VP) correlated well with AV synchrony as assessed using Holter-ECGs (Kendall’s τ=0.312, p&amp;lt;0.001). AV synchrony in the Holter ECG was different in patients with &amp;lt;66.6% presumed AV synchrony than in patients with &amp;gt;66.6% presumed AV synchrony (p&amp;lt;0.001, figure). For Holter ECG sequences with mostly preserved intrinsic AV conduction (&amp;lt;20% ventricular pacing), the ratio "AM-VP"/total VP was not predictive for true AV synchrony (Kendall’s τ=0.07, p=n.s.). In this situation, however, "VS only" (Kendall’s τ=0.110, p=0.005) correlated with true AV synchrony (due to AV conduction mode switch) and "VP only" showed an inverse correlation with AV synchrony (Kendall’s τ=-0.215, p&amp;lt;0.001). Conclusion Leadless PMs provide device statistics that show a correlation with true AV synchrony. The clinical setting as well as the device programming (e.g. AV conduction mode switch) significantly influence the predictive value of the different parameters of the device’s statistics.

Automated detection of scar-related ventricular tachycardia origins from implanted device electrograms: a combined computational-AI platform

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): EPSRC Background Existing strategies that identify ventricular tachycardia (VT) ablation targets either employ invasive and time-consuming electrophysiological (EP) mapping, or non-invasive modalities that utilise standard electrocardiogram (ECG) signals. Success of these pre-procedure ablation approaches in localising re-entrant VTs often relies on VT induction, which could be avoided by utilising recordings of clinical VT episodes stored as electrograms (EGMs) in implanted devices. Such a non-invasive approach that localises VT substrates from EGMs may aid ablation planning, enhancing safety and speed. Purpose Our goal is to automate scar-related VT localisation by utilising EGM recordings of VT episodes from implanted devices. To achieve this, deep-learning algorithms will be trained on computational data to return VT sites of origin from implanted device EGMs. Ultimately, we intend to utilise this computational-artificial intelligence (AI) framework to detect ablation targets of clinical VT episodes and guide pre-procedure ablation planning non-invasively. Methods A comprehensive library of ECGs and EGMs from simulated paced beats (~15000) and scar-related VTs (500) was generated across five detailed torso models within a fast EP computational environment, combining reaction-eikonal and lead field methods. ECG (or EGM) traces from simulated paced beats were used to initially pre-train two convolutional neural network (CNN) long short-term (LSTM) attention-based architectures. Subsequently, signals of the in-silico, re-entrant VTs were used to re-train the networks to output the sites of origin of these episodes in a standardised ventricular coordinate space. Finally, the retrained CNN architectures were tested on re-entrant VTs of unseen models, and median localisation errors (LEs) were estimated against known VT origins from simulations. Results The performance of the networks to localise scar-related VT episodes was asserted for each torso model. When a torso model was only seen during initial training on simulated paced beats, implanted device EGMs and ECGs successfully localised VT sources with LEs 10.04 – 16.36 mm and 10.05 – 12.79 mm, respectively. When a torso model was not seen during pacing or VT training, recreating potential clinical application settings where ECGs or EGMs of clinical VTs would be the only inputs to the networks, LEs ranged 12.42 - 22.79 mm and 12.41 - 19.68 mm for EGM and ECG-based testing, respectively. Conclusions Our study successfully detected VT ablation substrates with accuracy that could be beneficial in clinical ablation settings. The proposed computational-AI framework may be used to automate the localisation of scar-related VTs from clinical ECGs or EGM recordings from implanted devices, ultimately aiding ablation planning.

Dubious effect of the high biventricular paced beats percentage itself on the cardiac resynchronization efficacy in patients with atrial fibrillation. The randomized Pilot-CRAfT Study results

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Institute of Cardiology statutory grant Background The presence of atrial fibrillation (AF) in cardiac resynchronization therapy (CRT) recipients is common and AF is a marker of poorer CRT response. The negative influence of AF on CRT efficacy is belived to be mediated mainly by the drop of effectively captured biventricular paced beats percentage (BiVp%). According to observational trials, the minimal BiVp associated with better outcomes is 95-98%, however there is lack of randomized trials to confirm this findings. Purpose The purpose of the study was to assess the influence of BiVp% itself on the clinical outcomes in the population CRT patients with atrial fibrillation in a prospective, randomized cohort. Methods The study included the prospective Pilot-CRAfT study participants that is patients with CRT and permanent or persistent AF lasting for ≥6 months that were randomly assigned to rhythm or rate control strategy. We divided the whole study population according to their BiVp at the 12 month follow-up with two borderline BiVp values (BiVp &amp;gt;98% vs &amp;lt;98% and &amp;gt;95% vs &amp;lt;95%) and analysed the echocardiographic indices, exercise tolerance and quality of life between the prespecified groups. Results The study included 43 CRT patients (97,7% males) aged 68,4 (SD: ±8,3) years with mean BiVp% 82,4% ±9,7% at baseline. The mean baseline left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDD) and maximal oxygen uptake (VO2max) were: 30 ±8%, 65 ±8 mm, 14 ±5 mL/(kg*min), respectively. In both of the study arms the BiVp% raised significantly reaching 98,1 ±2,3% and 96,3 ±3,9% in the rhythm control and the rate control arms respectively (P=0,093). As a result the were overall 21 patients with BiVp &amp;gt;98% and 29 patients with BiVp &amp;gt;95% at the end of the study. The BiVp groups &amp;gt;98% vs &amp;lt;98% and &amp;gt;95% vs &amp;lt;95% did not differ as to baseline characteristics and we have not observed any differences in the mean LVEF, mean LVEDD, mean VO2max, and quality of life in the prespecified BiVp% groups at the end of the follow up. Moreover no linear correlations between the BiVp% and LVEF, LVEDD, VO2max values were observed. However, in the rate control group patients with AVNA performed had lower LVEDD at the end of the study (57,7 ±3,0 vs 65,4 ±7,0 p=0,007) and significant decrease in the LVEDD after AVNA was observed (-8,6 95%CI [-14,9; -2,3]). Conclusions The BiVp &amp;gt;98% or &amp;gt;95% alone does not seem to warrant good response to cardiac resynchronization in patients with persistent atrial fibrillation as assessed in the prospective randomized cohort. However, performing AVNA in this group of patients may be beneficial in terms of LVEDD decrease.

C4 PERMANENT HIS BUNDLE PACING USING STYLET–DRIVEN LEAD IN PATIENTS WITH RIGHT ATRIOMEGALY: A SINGLE–CENTER EXPERIENCE

Abstract Background His bundle pacing (HBP) is becoming an increasing widespread approach for physiological pacing. However, successful HBP procedure could be hampered by limited implantation tools especially in challenging anatomies. We aimed to report our experience with HBP technique using a novel stylet–driven lead system in patients with right atriomegaly. Methods Consecutive patients with right atrium (RA) volume &amp;gt;25 mL/m2 in men and &amp;gt;21 mL/m2 in women who underwent permanent HBP for standard indications were enrolled from March 2020 to March 2021. The tool of first choice for HBP attempt was a stylet–driven lead (Solia S 60, Biotronik) delivered via a dedicated introducer sheath (Selectra 3D, Biotronik). The acute, 1–month and 6–month procedural success rate was assessed. Results We enrolled 24 patients (median age 75 [70–79] years, 85% men) with an average RA volume of 50.7±7.8 mL/m2. At implant, conduction system pacing using stylet–driven lead was achieved in 21 patients (87%): 12 (50%) selective HBP, 6 non–selective HBP (25%) and 3 left bundle branch area pacing (12.5%). In the 3 failures, HBP was further attempted with a different system with final procedural success in 2 cases. In the successful cases, there was a significant reduction of QRS duration between paced and spontaneous beats (152.5 (130–167.5) ms vs 130 (122.5– 137.5) ms, p = 0.003). No lead dislodgment nor significant pacing threshold increase was observed at 1–month (1.30±0.76 V@0.4 vs. 1.32±0.80 V@0.4ms, p &amp;gt; 0.9) and 6–month follow–up (1.30±0.76 V@0.4 vs. 1.38±0.97 V@0.4ms, p = 0.66). Conclusions In our experience, the novel stylet–driven lead system showed high implant success rates and capture threshold stability also in patients with right atriomegaly.