Optimal Atrioventricular Delay Research Articles

Predictors of the efficacy of His bundle pacing in patients with a prolonged PR interval: A stratified analysis of the HOPE-HF randomized controlled trial.

The randomized, double-blind, placebo-controlled HOPE-HF trial assessed the benefit of atrio-ventricular (AV) delay optimization delivered using His bundle pacing. It recruited patients with left ventricular ejection fraction ≤40%, PR interval ≥200 ms, and baseline QRS ≤140 ms or right bundle branch block. Overall, there was no significant increase in peak oxygen uptake (VO2max) but there was significant improvement in heart failure specific quality of life. In this pre-specified secondary analysis, we evaluated the impact of baseline PR interval, echocardiographic E-A fusion, and the magnitude of acute high-precision haemodynamic response to pacing, on outcomes. All 167 randomized participants underwent measurement of PR interval, acute haemodynamic response at optimized AV delay, and assessment of presence of E-A fusion. We tested the impact of these baseline parameters using a Bayesian ordinal model on VO2max, quality of life and activity measures. There was strong evidence of a beneficial interaction between the baseline acute haemodynamic response and the blinded benefit of pacing for VO2 (Pr 99.9%), Minnesota Living With Heart Failure (MLWHF) (Pr 99.8%), MLWHF physical limitation score (Pr 98.9%), EQ-5D visual analogue scale (Pr 99.6%), and exercise time (Pr 99.4%). The baseline PR interval and the presence of baseline E-A fusion did not have this reliable ability to predict the clinical benefit of pacing over placebo across multiple endpoints. In the HOPE-HF trial, the acute haemodynamic response to pacing reliably identified patients who obtained clinical benefit. Patients with a long PR interval (≥200 ms) and left ventricular impairment who obtained acute haemodynamic improvement with AV-optimized His bundle pacing were likely to obtain clinical benefit, consistent across multiple endpoints. Importantly, this gradation can be reliably tested for before randomization, but does require high-precision AV-optimized haemodynamic assessment to be performed.

Impact of myocardial phenotype on atrioventricular delay optimization at rest and during exercise: insights from a virtual patient study

Abstract Background The usefulness of atrioventricular delay (AVD) optimization in cardiac resynchronization therapy (CRT) for heart failure (HF) patients with left bundle branch block (LBBB) and reduced left ventricular ejection fraction (LVEF) is still debated. Yet, studies have not explored the role of non-electrical myocardial disease substrates in determining optimal AVD settings among patients. Purpose We first hypothesized that acute response to AVD optimization might be modulated by various myocardial disease substrates. Furthermore, we hypothesized that cardiac function is more sensitive to changes in AV coupling during exercise and that this sensitivity is also modulated by underlying myocardial disease substrates. Methods We used the CircAdapt model of the human heart and circulation to simulate different types of LV remodeling that can be found in CRT candidates. First, an LBBB-like pattern of mechanical activation was imposed by delaying LV free wall (LVFW) and interventricular septal (IVS) activation relative to right ventricular free wall activation. Then, two types of LV remodeling were simulated by LV dilation with preserved or impaired myocardial contractility, resulting in LVEF <35%. To investigate the effect of diastolic dysfunction, we increased passive myocardial stiffness of the IVS and LVFW on both substrates with LV remodeling until a mean left atrial pressure (mLAP) of 14 mmHg was reached. CRT was simulated by resynchronizing IVS and LVFW. AVD optimization was conducted by gradually reducing the paced AVD from 220 ms to 40 ms in steps of 20 ms. In each simulation, the optimal paced AVD at rest (cardiac output (CO) and heart rate (HR) of 4.2 L/min and 80 bpm, respectively) was assessed using stroke volume (SV) and mLAP which is used as a measure of LV filling pressure. To investigate the relative effect of these myocardial phenotypes during AVD optimization under exercise, CO and HR were increased step-wise. Results The gain in SV by AVD optimization was larger in the simulations with healthy myocardium than in those with hypo-contractile and stiff myocardium (Figure 1: top-row). However, mLAP was comparably decreased by AVD optimization in healthy and diseased myocardium (Figure 1: bottom row). During exercise, the optimum AVD shifted to shorter values (Figure 2: top-row), and mLAP was much more sensitive to AVD, particularly in the presence of hypo-contractile and stiff myocardium (Figure 2: bottom row). Conclusion Virtual patient simulations show that both myocardial hypocontractility and stiffness dampen the effect of AVD optimization on SV. Furthermore, simulations suggest that patients benefit more from AVD optimization during exercise than during resting conditions. These mechanistic insights may help to gain more benefit from AVD optimization for patients undergoing CRT.AVD optimization at restAVD optimization during exercise

Effectiveness of dynamic atrioventricular optimization during patient exercise in cardiac resynchronization therapy

Abstract Background Cardiac resynchronization therapy (CRT) is considered the standard treatment for patients with heart failure and prolonged QRS duration. Recent studies suggest that atrioventricular delay (AVD) optimization can play a key role in QRS narrowing, thus improving CRT outcomes. For this purpose, device-based algorithms have been developed. In particular, the SyncAV algorithm continuously monitors the patient’s intrinsic AVD and dynamically adjusts the pacing AVD to allow fusion of the left ventricle pacing with intrinsic right ventricle depolarization. SyncAV optimization is usually performed in a single patient condition, i.e. at rest, and in a single operating scenario of the device, i.e. during atrial sensing. Purpose This study aims to compare QRS narrowing after AVD optimization using SyncAV in CRT-treated patients at rest, during moderate exertion, and during an increase in the atrial pacing rate. Methods This is a prospective, non-randomized, non-blinded, multicenter study. The study population consisted of patients in sinus rhythm, PR interval < 350 ms, and rest ventricular rate < 100 bpm. Within one month from the implant, patients were assessed for AVD optimization with SyncAV, selecting the offset (i.e. 10 to 40% AVD) that resulted in the shortest QRS duration (QRSd). Subsequently, patients performed moderate physical activity using a bicycle ergo-meter while a surface ECG was collected. QRSd was assessed once patients achieved a heart rate over 20 bpm to baseline heart rate, up to 100 bpm. Finally, QRSd narrowing was evaluated during a programmed increase in atrial pacing (i.e. >20 bpm of baseline atrial rate). Results Nine patients were treated with CRT and enrolled (age 67,3 ± 13,2 years; 66% male; LV ejection fraction 33,7±2,9 %; intrinsic QRSd 155,6 ± 12,7 ms) with intact atrioventricular conduction (PR interval 170,6±25,8 ms). The median SyncAV offset that provided the best QRSd reduction was 20 % (10 - 35%). Intrinsic QRSd was reduced to 132,7 ± 10,0 ms (-14,2±9,4%) with standard biventricular pacing and to 122,0 ± 11,2 ms (-21,2±8,5%) with SyncAV optimization. During exercise the mean heart rate was 88,1 bpm, the QRSd was reduced to 132,7 ± 10,0 ms (-14,2±9,4%) with standard biventricular pacing and to 124,9 ± 14,9 ms (-19,3±10,8 %) with SyncAV optimization. The mean heart rate during atrial pacing was 90 bpm with paced QRSd of 126,0 ±13,9 ms (-18,9±7,3% from baseline) with SyncAV optimization and paced PR interval of 198,2±22,7ms. Conclusion We evaluated the effectiveness of SyncAV for AVD optimization in out-of-clinic. This study demonstrates the possibility of narrowing the QRSd using SyncAV at several activity levels. Nevertheless, a deeper evaluation is needed to confirm our findings, investigating the SyncAV role in a larger population of patients.

Optimization of atrioventricular delay using Doppler ultrasound and left ventricular catheterization in patients implanted with His bundle pacing devices

Background: Currently, there is a lack of guidance on selecting the optimal method for optimizing the AV interval. Objective: To evaluate the technical characteristics of His bundle pacing and compare relation optimal ventricular conduction intervals using cardiac catheterization and echocardiogram. Method: Interventional prospective study. Result: A total of 56 patients underwent His bundle pacing (HBP) with a success rate of 78.5%. The average age was 57.8 ± 19.25, and 68.1% (30 cases) were female. Selective His pacing and non-selective respectively was successfully achieved in 22 out of 44 cases (50%) and 95.4% with pacing threshold was measured at an average of 0.82 ± 0.38 volts and 1.37 ± 0.83 volts with a pulse width of 1ms. The accuracy comparing AV optimization varied in the following order: VTImitral valve > VTIaortic valve > DFTmitral valve for AVsense optimization and VTImitral valve > DFTmitral valve > VTIaortic valve for AVpace optimization. After AV optimization, myocardial contractility increased by an additional 18.6% for AVsense and 26% for AVpace. Conclusion: His bundle pacing procedure success rate of 78.5%. AV optimization results enhancement in left ventricular contractility from 18.6 to 26%. Key words: His bundle pacing, cardiac resynchronization, heart failure, pacemaker, conduction disease, AV optimization, AV coupling.

Electrical Synchrony Optimization for Left Bundle Branch Area Pacing in Patients With Bradycardia and Heart Failure

Left bundle branch area pacing (LBBAP) has emerged as a promising physiological pacing modality. This study was designed to investigate the acute impact of the atrioventricular delay (AVD) on cardiac electrical characteristics and identify an optimal range of AVDs for LBBAP to achieve electrical atrioventricular and interventricular synchrony. Patients indicated for ventricular or biventricular pacing were studied during routine follow-ups at least 3months after LBBAP implantation. Patients were excluded if they had a complete AV block or persistent atrial fibrillation. AVD was programed from 40 to 240ms or until intrinsic conduction occurred. Optimal AVD was determined by the electrocardiography criteria, including QRS duration, reduced R-wave in lead V1, reduced notching or slurring in lateral leads, and more desirable precordial QRS transition. A total of 38 patients (age 68.7 ± 10.3years; 16 male (42%); 18 dual-chamber pacemakers and 20 cardiac resynchronization therapy devices; average follow-up period 15.1 ± 10.2months) were included. The fusion of LBBAP and intrinsic right ventricular conduction occurred in 21 patients with corresponding optimal AVD determined. A great proportion (∼85%) of the optimal AVDs ranged from 50% to 80% of the observed atrium-to-left bundle branch-sensing (A-LBBS) intervals. The linear correlation between the optimal AVD and corresponding A-LBBS interval (optimal AVD=0.84×[A-LBSs interval] - 36ms) produced R=0.86 and p <0.0001. In conclusion, AVD selection during LBBAP greatly impacted the ventricular electrical characteristics and the optimal AVD was linearly correlated with the corresponding A-LBBS interval.

Cardiac Resynchronization Therapy beyond Nominal Settings: An IEGM-Based Approach for Paced and Sensed Atrioventricular Delay Offset Optimization in Daily Clinical Practice.

Optimization of the atrioventricular (AV) delay has been performed in several landmark trials in cardiac resynchronization therapy (CRT), although it is often not performed in daily practice. Our aim was to study optimal AV delays and investigate a simple intracardiac electrogram (IEGM)-based optimization approach. 328 CRT patients with paired IEGM and echocardiography optimization data were included in our single-center observational study. Sensed (sAV) and paced (pAV) AV delays were optimized using an iterative echocardiography method. The offset between sAV and pAV delays was calculated using the IEGM method. The mean age of the patients was 69 ± 12 years; 64% were men, 48% had ischemic etiology of heart failure. During echocardiographic optimization, an offset of 73 ± 18 ms was found, differing from nominal AV settings (p < 0.001). Based on the IEGM method, the optimal offset was 75 ± 25 ms. The echocardiographic and IEGM-generated AV offset delays showed good correlation (R2 = 0.62, p < 0.001) and good agreement according to Bland-Altman plot analysis. CRT responders had a near zero offset difference between IEGM and echo optimization (-0.2 ± 17 ms), while non-responders had an offset difference of 6 ± 17 ms, p = 0.006. In conclusion, optimal AV delays are patient-specific and differ from nominal settings. pAV delay can easily be calculated from IEGM after sAV delay optimization.

Machine learning–powered, device-embedded heart sound measurement can optimize AV delay in patients with CRT

Continuous optimization of atrioventricular (AV) delay for cardiac resynchronization therapy (CRT) is mainly performed by electrical means. The purpose of this study was to develop an estimation model of cardiac function that uses a piezoelectric microphone embedded in a pulse generator to guide CRT optimization. Electrocardiogram, left ventricular pressure (LVP), and heart sounds were simultaneously collected during CRT device implantation procedures. A piezoelectric alarm transducer embedded in a modified CRT device facilitated recording of heart sounds in patients undergoing a pacing protocol with different AV delays. Machine learning (ML) was used to produce a decision-tree ensemble model capable of estimating absolute maximal LVP (LVPmax) and maximal rise of LVP (LVdP/dtmax) using 3 heart sound-based features. To gauge the applicability of ML in AV delay optimization, polynomial curves were fitted to measured and estimated values. In the data set of ∼30,000 heartbeats, ML indicated S1 amplitude, S2 amplitude, and S1 integral (S1 energy for LVdP/dtmax) as most prominent features for AV delay optimization. ML resulted in single-beat estimation precision for absolute values of LVPmax and LVdP/dtmax of 67% and 64%, respectively. For 20-30 beat averages, cross-correlation between measured and estimated LVPmax and LVdP/dtmax was 0.999 for both. The estimated optimal AV delays were not significantly different from those measured using invasive LVP (difference -5.6 ± 17.1 ms for LVPmax and +5.1 ± 6.7 ms for LVdP/dtmax). The difference in function at estimated and measured optimal AV delays was not statiscally significant (1± 3 mm Hg for LVPmax and 9 ± 57 mm Hg/s for LVdP/dtmax). Heart sound sensors embedded in a CRT device, powered by a ML algorithm, provide a reliable assessment of optimal AV delays and absolute LVPmax and LVdP/dtmax.

Variation in optimal hemodynamic atrio-ventricular delay of biventricular pacing with different endocardial left ventricular lead locations using precision hemodynamics.

It is not known whether the optimal atrioventricular (AVopt ) delay varies between left ventricular (LV) pacing site during endocardial biventricular pacing (BiVP) and may therefore needs consideration. We assessed the hemodynamic AVopt in patients with chronic heart failure undergoing endocardial LV lead implantation. AVopt was assessed during atrio-BiVPwith a "roving LV lead."Up to four locations were studied: mid-lateral wall, mid-septum (or a close alternative), site of greatest hemodynamic improvement, and LV lead implant site. The AVopt was compared to a fixed AV delay of 180 ms. Seventeen patients were included (12 male, aged 66.5 ± 12.8 years, ejection fraction 26 ± 7%, 16 left bundle branch block or high percentage of right ventricular pacing [RVP], QRS duration 167 ± 27 ms). In most locations (62/63), AVopt increased systolic blood pressure during BiVP compared with RVP (relative improvement 6 mmHg,interquartile range [IQR] 4-9 mmHg). Compared to a fixed AV delay, the hemodynamic improvement at AVopt was higher (1 mmHg, IQR 0.2-2.6 mmHg, p < .001). Within most patients (16/17), we observed a difference in AVopt between pacing sites (median paced AVopt 209 ms, IQR 117-250). Within this range, the hemodynamic impact of these differences was small (median loss 0.6 mmHg, IQR 0.1-2.6 mmHg). Within a patient, different endocardial LV lead locations have slightly different hemodynamic AVopt which are superior to a fixed AV delay. The hemodynamic consequence of applying an optimum from a different lead location is small.

Predictors of the efficacy of AV-optimised His bundle pacing in patients with a prolonged PR interval: a stratified analysis of the HOPE-HF clinical trial

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): British Heart Foundation. Background HOPE-HF was a randomised, placebo-controlled, cross-over trial of AV-optimised His bundle pacing in patients with heart failure (LVEF ≤40%), a PR interval (≥200ms) and without left bundle branch block.1,2. In this analysis we studied the impact of baseline PR interval and acute blood pressure change at the optimal AV-delay on the placebo-controlled effect of His bundle pacing on the trial endpoints of peak VO2 (primary) and patient symptoms (using the Minnesota Living with Heart Failure Questionnaire). Methods and Results 167 patients were successfully implanted and randomised to 6 month blocks of pacing and placebo. We performed a non-invasive, high-precision protocol to calculate the optimal AV delay and associated acute blood-pressure response at randomisation. To test the impact of the baseline PR interval and acute BP response on the placebo-controlled effect of AV-optimised His bundle pacing on endpoints we compared Bayesian ordinal regression models and the relative explained variance (REV) of variables in the model. There was weak evidence that His-bundle pacing improved peak VO2 across all patients (OR 1.31, 95% CrI 0.86 to 2.01, Pr(OR &amp;gt; 1)=89%). The baseline PR interval had little impact on this benefit (REV 0%), and the blood pressure response was more likely (88% vs 12%) to be predictive. However, there was strong evidence that overall AV-optimised His-bundle pacing improved patient symptoms as compared to placebo (OR 1.58, 95% CrI 1.04 to 2.40, Pr(OR&amp;gt;1)=98%). Again, the baseline PR interval had little impact on this benefit (REV 0%) and the blood pressure response was much more likely (97% vs 3%) to be predictive. Higher acute BP increments led to greater placebo-controlled improvements in MLWHF at 6-months. Conclusion An individual’s acute BP response with AV-optimised His-pacing is a powerful predictor of their placebo-controlled improvement in symptoms (MLWHF) at 6-months. This can form the basis of patient selection for future studies and clinical practice.

Lowest peak central venous pressure correlates with highest invasive arterial blood pressure as a method for optimising AV delay in post-surgical temporary pacing

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): British Heart Foundation. Background Atrioventricular (AV) delay optimisation has been performed using a variety of methods, including doppler outflow and alternating blood pressure algorithms. Patients after cardiac surgery are usually invasively monitored with arterial and central venous pressure (CVP) lines. Purpose We aimed to see if the CVP line could be used to optimise AV delays in temporary pacing for situations where the arterial line is absent or non-functional. Methods 11 patients in sinus rhythm but with temporary pacemakers after cardiac surgery were studied. Each patient underwent alternating optimisation algorithms where they were subjected to 8 transitions between a reference AV delay of 120ms and a tested AV delay ranging from 40ms to 280 ms. Testing was terminated after the AV delay occurred when native conduction occurred i.e after they began AAI pacing. All patients were paced at 80 bpm. Arterial blood pressure (ABP) and CVP were recorded from radial arterial lines and central venous lines in the internal jugular vein during the transitions. The optimal point was defined as the AV delay generating the maximum systolic blood pressure. The CVP was measured in 3 ways: peak pressure, mean pressure, and area under the curve. Central venous pressure tracings were corrected for respiration using a "fit-a-curve" function. All analysis was performed in Python. Results Individual pressure readings. There was a negative correlation between individual ABP and Peak CVP pressure readings (R= -0.539, p=0&amp;lt;0.001). A representative example for a single patient is shown in Figure 1 and for all data in Figure 2. A similar relationship, albeit less strong, was seen between ABP and Mean CVP (R= -0.281, p=0.046). There was no significant relationship between ABP and CVP AUC (R = -0.281, p=0.130). Optimum pressure settings: There was a strong correlation between the optimum AV delay as defined by the highest ABP and the optimum AVD as defined by the lowest peak CVP (R = 0.672, p=0.03). There was no significant relationship between the optimum AVD delay as defined by peak ABP and the optimum AVD defined by either mean CVP nor CVP AUC (R=0.269, p=0.452 for both). Conclusions There is an inverse relationship between individual measurements of arterial blood pressure and both peak and mean central venous pressure. The optimal AVD as defined by the highest ABP correlates with the optimal AVD as defined by the lowest peak CVP measurement. However, this method does require correction for respiratory artefact.

Hemodynamic optimization of cardiac resynchronization therapy by heart sound sensor in pulse generator

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): EU-HORIZON 2020-International Training Network H2020-MSCA-ITN-2017. Background Continuous ambulatory AV-optimization for Cardiac Resynchronization Therapy (CRT) is mainly performed by electrical means. Objective Develop an estimation model of cardiac function that uses feedback from a piezoelectric transducer embedded in an internal pulse generator to guide CRT optimization. Methods During implantation procedures measurements were performed of left ventricular pressure (LVP) and heart sound waveforms, the latter using the piezoelectric alarm transducer of the device in 22 CRT patients at atrioventricular (AV)-delays of 60-330 ms. Post-hoc, machine learning (ML) was employed to produce models that use heart-sound based features to estimate cardiac function in terms of maximum LVP (LVPmax) and the maximum positive derivative of LVP (LVdP/dtmax). Polynomial curve fitting was used to compare estimated and measured AV-delays with highest LVPmax and LVdP/dtmax. Results The figure displays the concept of the study and an example of the measured and estimated optimization curve. With a dataset of ~30,000 beats, ML provided three most suitable features. Using LVPmax, ML-based estimated optimal AV-delays were not significantly different from measured ones (-5.6 ± 17.1ms for LVPmax and +5.1 ± 46.7ms for LVdP/dtmax). The difference in function between the estimated and measured optimal AV-delays was small and not statically significant (1 ± 3mmHg for LVPmax and 9 ± 57mmHg/s for LVdP/dtmax). Conclusion Heart sound sensors in devices in combination with ML provide a reliable assessment of absolute LVPmax and LVdP/dtmax and may be used for continuous optimization of AV-delays in CRT patients.

CI-452767-3 MACHINE LEARNING-POWERED, DEVICE-EMBEDDED HEART SOUND MEASUREMENT CAN OPTIMIZE AV DELAY IN CRT PATIENTS

Continuous ambulatory optimization of atrioventricular (AV) delay for cardiac resynchronization therapy (CRT) is mainly performed by electrical means. Development of an estimation model of cardiac function that uses a piezoelectric transducer embedded in an internal pulse generator to guide CRT optimization in patients. Electrocardiogram, left ventricular pressure (LVP) and heart sounds were simultaneously collected during the implantation procedures. A piezoelectric alarm transducer embedded in a modified CRT device facilitated recording heart sound in 22 patients undergoing a pacing protocol with AV delays varying from 60 to 330 ms. Post-hoc, machine learning was employed to produce a decision tree ensemble model capable of estimating maximal LVP (LVPmax) and maximal rate of rise of LVP (LVdP/dtmax) using heart-sound based features. To gauge the applicability of machine learning in AV delay optimization, polynomial curves were fitted to invasively measured and estimated values. The figure illustrates the concept of the study and an example of the invasively measured and heart sound-estimated AV delay optimization curves. In the dataset of ∼30,000 heartbeats, machine learning indicated S1 amplitude, S2 amplitude and S1 integral (or energy) as the most prominent features for AV delay optimization in terms of LVPmax and LVdP/dtmax. Machine learning facilitated categorical beat by beat estimation for absolute values of LVPmax (10 mmHg bin size) and LVdP/dtmax (100 mmHg/s bin size). The right panel illustrates the similar absolute values for LVPmax using 30 second averages. Estimated optimal AV delays using ∼30 second recordings were not significantly different from those measured using invasive LVP (difference: -5.6 ± 17.1 ms for LVPmax and +5.1 ± 46.7 ms for LVdP/dtmax). The difference in function between the estimated and measured optimal AV delays was small and not statically significant (1 ± 3mmHg for LVPmax and 9 ± 57mmHg/s for LVdP/dtmax). Heart sound sensors embedded in a CRT device, powered by a machine learning algorithm provide a reliable assessment of both optimal AV delays and absolute LVPmax and LVdP/dtmax in a clinical environment.

PO-02-014 IMPACT OF RIGHT VENTRICULAR ELECTRICAL ACTIVATION (INTRINSIC AND PACED) IN HEART FAILURE PATIENTS WITH LBBB

The appropriately timed incorporation of the intrinsic right bundle branch (RBB) conduction during biventricular (RV & LV) pacing – “triple fusion”- may improve electrical resynchronization and response to CRT. However, the relative contribution of these wavefronts, optimal programming, and impact upon left ventricular activation remains poorly understood. To characterize intrinsic RBB and paced RV activation in heart failure patients with LBBB. CRT Patients with Strauss-type LBBB were studied. Right ventricular electrical activation was estimated from the onset of the r wave to the nadir of the S wave (rS interval) in leads V1 and V2. QRS duration was taken as the earliest onset to the terminal deflection in any lead. Paced QRS was measured during RV only pacing and nominal BiV (BiVNom; paced and sensed AV delay of 140/110 ms). The optimal AV delay was determined by the narrowest QRS duration achieved during simultaneous BiV pacing (BiVOpt) while adjusting the paced AV delay from 60% to 95% of the PR interval (in increments of 5%). This protocol was repeated while withholding RV pacing (LV-onlyOpt). All measurements were performed in each patient. Thirty patients (53% Male, 33% ICM, 68±8 yrs, EF 24±7%, qRV 25±8 ms, qLV 123±21 ms, and QRSd 170±18 ms) were evaluated. The PR interval was 208±39 ms (range 117-328 ms). The qlV/ QRS was 73±9%, indicating optimized LV lead position. Compared to BiVNom, BiVOpt was achieved at longer AVD (80±7% vs 56±7% of PR interval) but resulted in more rapid RBB electrical activation (59±14 ms vs 90±20 ms) and narrower QRS duration (130±13 ms vs 146±16 ms); all P < 0.05 vs BiVNom. Withholding RV pacing (LV-onlyOpt) did not impact RBB activation or AV delay programming compared to BiVOpt, but still reduced QRS duration compared to BiVNom (139±14 ms vs 146±16 ms; P<0.05). Incorporation of RV pacing during biventricular pacing with longer AVD programming facilitates intrinsic RBB conduction to improve electrical resynchronization without committing the LV to this wavefront.

Optimizing diastolic filling by pacing in nonobstructive hypertrophic cardiomyopathy

Treatment options for symptomatic patients with nonobstructive hypertrophic cardiomyopathy (nHCM) are limited. The purpose of this study was to determine the effect of sequential atrioventricular (AV) pacing, from different right ventricular (RV) sites with varying AV delays, on the diastolic function and functional capacity of patients with nHCM. Twenty-one patients with symptomatic nHCM and normal left ventricular (LV) systolic function were prospectively enrolled. Inclusion criteria included PR interval >150 ms, E/e' ≥15, and an indication for implantable cardioverter-defibrillator (ICD) implantation. Doppler echocardiographic study was performed during dual-chamber pacing at various AV intervals. Pacing was performed at 3 RV sites: RV apex (RVA), RV midseptum (RVS), and RV outflow tract (RVO). The site and sensed AV delay (SAVD) at which optimal diastolic filling occurred were chosen based on diastolic filling period and E/e'. During ICD implantation, the RV lead was implanted at the site identified by the pacing study. Devices were programmed in DDD mode at the optimal SAVD. During follow-up, diastolic function and functional capacity were assessed. Among the 21 patients (age 47.8 ± 7.7 years; 81.0% male), baseline E/A and E/e' were 2.4 ± 0.6 and 17.2 ± 2.2, respectively. There was an improvement in diastolic function (E/e') in 18 patients (responders) when pacing from the RVA (12.9 ± 3.4; P <.001) than from the RVS (16.6 ± 2.3) and RVO (16.9 ± 2.2). Among responders, optimal diastolic filling occurred at SAVD of 130-160 ms with RVA pacing. Nonresponders had longer duration of symptoms (P = .006), lower LV ejection fraction (P = .037), and higher late gadolinium enhancement burden (P <.001). During 13.5 ± 1.5 months of follow-up, there was an improvement (Δ) in diastolic function (E/e' -4.1 ± 0.5), functional capacity (New York Heart Association functional class -1.5 ± 0.3), and reduction in N-terminal pro-brain natriuretic peptide level (-55.6 ± 12.3 pg/mL) compared to baseline. Pacing at an optimized AV delay from the RVA improves diastolic function and functional capacity in a subset of patients with nHCM.

Right ventricular cardiac resynchronization therapy in patients with right ventricular conduction delay and heart failure

Right ventricular cardiac resynchronization therapy in patients with right ventricular conduction delay and heart failure

Heart sound–derived systolic time intervals for atrioventricular delay optimization in cardiac resynchronization therapy

Phonocardiography (PCG) can be used to determine systolic time intervals (STIs) from ventricular pacing spike to the first heart sound (VS1) and from the first to the second heart sound (S1S2). The purpose of this study was to investigate the relations between STIs and hemodynamics during atrioventricular (AV) delay optimization of biventricular pacing (BiVP) in animals and patients. Five pigs with AV block underwent BiVP, while PCG was collected from an epicardial accelerometer. In 21 patients undergoing cardiac resynchronization therapy device implantation, PCG was recorded with a pulse generator-embedded microphone. Optimal AV delays derived from shortest VS1 and longest S1S2 were compared with AV delays derived from highest left ventricular pressure (LVP), maximal rate of rise in LVP, and stroke work. In pigs, VS1 and S1S2 predicted the AV delays with optimal hemodynamics (highest LVP, maximal rate of rise in LVP, and stroke work) by a median error of 2-28 ms, resulting in a median loss of <2% of pump function. In patients, VS1 and S1S2 predicted the optimal AV delay by errors of 32.5 and 37.5 ms, respectively, resulting in 0.2%-0.9% lower LVP and stroke work, which were reduced to 21 and 24 ms in 8 patients with a full-capture AV delay of >180 ms. During BiVP with varying AV delays, close relations exist between PCG-derived STIs and hemodynamic parameters. AV delays advised by PCG-derived STIs cause only a minimal loss of pump function compared with those based on invasive hemodynamic measurements. ClinicalTrials.gov Identifier: NCT01832493.

Leadless biventricular left bundle and endocardial lateral wall pacing versus left bundle only pacing in left bundle branch block patients.

Biventricular endocardial (BIV-endo) pacing and left bundle pacing (LBP) are novel delivery methods for cardiac resynchronization therapy (CRT). Both pacing methods can be delivered through leadless pacing, to avoid risks associated with endocardial or transvenous leads. We used computational modelling to quantify synchrony induced by BIV-endo pacing and LBP through a leadless pacing system, and to investigate how the right-left ventricle (RV-LV) delay, RV lead location and type of left bundle capture affect response. We simulated ventricular activation on twenty-four four-chamber heart meshes inclusive of His-Purkinje networks with left bundle branch block (LBBB). Leadless biventricular (BIV) pacing was simulated by adding an RV apical stimulus and an LV lateral wall stimulus (BIV-endo lateral) or targeting the left bundle (BIV-LBP), with an RV-LV delay set to 5ms. To test effect of prolonged RV-LV delays and RV pacing location, the RV-LV delay was increased to 35ms and/or the RV stimulus was moved to the RV septum. BIV-endo lateral pacing was less sensitive to increased RV-LV delays, while RV septal pacing worsened response compared to RV apical pacing, especially for long RV-LV delays. To investigate how left bundle capture affects response, we computed 90% BIV activation times (BIVAT-90) during BIV-LBP with selective and non-selective capture, and left bundle branch area pacing (LBBAP), simulated by pacing 1cm below the left bundle. Non-selective LBP was comparable to selective LBP. LBBAP was worse than selective LBP (BIVAT-90: 54.2 ± 5.7ms vs. 62.7 ± 6.5, p < 0.01), but it still significantly reduced activation times from baseline. Finally, we compared leadless LBP with RV pacing against optimal LBP delivery through a standard lead system by simulating BIV-LBP and selective LBP alone with and without optimized atrioventricular delay (AVD). Although LBP alone with optimized AVD was better than BIV-LBP, when AVD optimization was not possible BIV-LBP outperformed LBP alone, because the RV pacing stimulus shortened RV activation (BIVAT-90: 54.2 ± 5.7ms vs. 66.9 ± 5.1ms, p < 0.01). BIV-endo lateral pacing or LBP delivered through a leadless system could potentially become an alternative to standard CRT. RV-LV delay, RV lead location and type of left bundle capture affect leadless pacing efficacy and should be considered in future trial designs.

Impact of long-term optimizing atrioventricular delay using device-based algorithms on cardiac resynchronization therapy

Sub-optimal atrioventricular delay (AVD) is one of the main causes of non-responder for cardiac resynchronization therapy (CRT). Recently, device-based algorithms (DBAs) that provide optimal AVD based on intracardiac electrograms, have been developed. However, their long-term effectiveness is still unknown. This study aims to investigate the effect of optimizing AVD using DBAs over a long period, on the prognosis of patients undergoing CRT. A total of 118 patients who underwent CRT at our hospital between April 2008 and March 2018, were retrospectively reviewed; 61 of them with optimizing AVD using DBAs were classified into the treated group (group 1), and the remaining 57 were classified into the control group (group 2). The median follow-up period was 46.0 months. The responder and survival rate in group 1 were significantly better than those in group 2 (group 1 vs. group 2: responder rate = 64% vs. 46%, p = 0.046; survival rate: 85.2% vs. 64.9%, p = 0.02). Moreover, investigating only the non-responder population showed that group 1 had an improved survival rate compared to group 2 (group 1 vs. group 2 = 72.7% vs. 45.1%, p = 0.02). Optimizing AVD using DBAs was a significant contributor to the improved survival rate in CRT non-responders in multivariate analysis (HR 3.6, p = 0.01). In conclusion, the long-term optimizing AVD using DBAs improved the survival rate in CRT and the prognosis of CRT non-responders, as well.

Right ventricular lead sensing latency in pacemaker therapy

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Pacemaker’s ventricular sensing function relies on the analysis of the intracardiac electrogram (EGM) including the timing of the intrinsic detection. The phenomenon of ventricular sensing latency refers to the gap of time by which the intrinsic signal gets delayed to be detected compared with the surface electrogram (ECG). A pacing system analyzer (PSA) unit is needed to record the EGM during pacemaker operation, which is expected to correspond to those taken following implantation. Purpose We sought to determine the latency period for sensing EGM by the right ventricular (RV) lead, either through the PSA or through the implanted pacemaker on the same patient. Methods Patients without significant heart disease and intrinsic atrioventricular conduction underwent conventional dual-chamber Medtronic or Abbott pacemaker implantation with the RV lead positioned on mid-septum. Real time sensing data was obtained through PSA and after pacemaker implantation. The RV lead sensing latency was defined as the time interval Q-VS measured from the beginning of QRS on ECG to the released ventricular sensed (VS) event marker on either device. Results Of 157 patients, 105 had narrow QRS (&amp;lt;120 ms) and 52 had wide QRS (≥120 ms) of right bundle branch block (RBBB). Both narrow QRS and RBBB patients had longer sensing latency through PSA (50.9 ± 24.2 ms and 67.8 ± 32.9 ms, respectively) than through pacemaker (18.2 ± 12.8 ms and 31.2 ± 14.8 ms, respectively, both p&amp;lt;0.001). RBBB patients had longer sensing latency compared with narrow QRS patients, either through PSA or through pacemaker (p&amp;lt;0.001). The sensing latency of Medtronic recipients was longer than those of Abbott in narrow QRS, but not in RBBB (p=0.03 and p=0.08, respectively). Conclusion We demonstrated longer RV lead sensing latency (1) through PSA than through the implanted pacemaker, (2) in RBBB than in narrow QRS, (3) in Medtronic pacemakers compared with Abbott pacemakers. Knowledge of the RV lead sensing latency helps optimization of atrioventricular delay and reduces unnecessary ventricular pacing.

Acute Hemodynamic Effects of Simultaneous and Sequential Multi-Point Pacing in Heart Failure Patients With an Expected Higher Rate of Sub-response to Cardiac Resynchronization Therapy: Results of Multicenter SYNSEQ Study.

The aim of the SYNSEQ (Left Ventricular Synchronous vs. Sequential MultiSpot Pacing for CRT) study was to evaluate the acute hemodynamic response (AHR) of simultaneous (3P-MPP syn) or sequential (3P-MPP seq) multi-3-point-left-ventricular (LV) pacing vs. single point pacing (SPP) in a group of patients at risk of a suboptimal response to cardiac resynchronization therapy (CRT). Twenty five patients with myocardial scar or QRS ≤ 150 or the absence of LBBB (age: 66 ± 12 years, QRS: 159 ± 12 ms, NYHA class II/III, LVEF ≤ 35%) underwent acute hemodynamic assessment by LV + dP/dtmax with a variety of LV pacing configurations at an optimized AV delay. The change in LV + dP/dt max (%ΔLV + dP/dt max) with 3P-MPP syn (15.6%, 95% CI: 8.8%-22.5%) was neither statistically significantly different to 3P-MPP seq (11.8%, 95% CI: 7.6-16.0%) nor to SPP basal (11.5%, 95% CI:7.1-15.9%) or SPP mid (12.2%, 95% CI:7.9-16.5%), but higher than SPP apical (10.6%, 95% CI:5.3-15.9%, p = 0.03). AHR (defined as a %ΔLV + dP/dt max ≥ 10%) varied between pacing configurations: 36% (9/25) for SPP apical, 44% (11/25) for SPP basal, 54% (13/24) for SPP mid, 56% (14/25) for 3P-MPP syn and 48% (11/23) for 3P-MPP seq.Fifteen patients (15/25, 60%) had an AHR in at least one pacing configuration. AHR was observed in 10/13 (77%) patients with a LBBB but only in 5/12 (42%) patients with a non-LBBB (p = 0.11). To conclude, simultaneous or sequential multipoint pacing compared to single point pacing did not improve the acute hemodynamic effect in a suboptimal CRT response population.Clinical Trial RegistrationClinicalTrials.gov, identifier: NCT02914457.