Rationale and design of the randomized multicentre His Optimized Pacing Evaluated for Heart Failure (HOPE‐HF) trial

Keene, Daniel; Arnold, Ahran; Shun-Shin, Matthew; Howard, James P.; Sohaib, SM Afzal; Moore, Philip; Tanner, Mark; Quereshi, Norman; Muthumala, Amal; Chandresekeran, Badrinathan; Foley, Paul; Leyva, Francisco; Adhya, Shaumik; Falaschetti, Emanuela; Tsang, Hon Ki; Vijayaraman, Pugal; Cleland, John G.F.; Stegemann, Berthold; Francis, Dárrel P.; Whinnett, Zachary I.

doi:10.1002/ehf2.12315

Cited by 41 publications

(37 citation statements)

References 37 publications

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“…Baseline patient demographics together with relevant clinical information (QRS duration, NYHA class, LV function, presence of IHD) were recorded. Patients identified as being recruited into blinded randomized controlled trials, including the HOPE-HF double-blind randomized crossover trial, 7 were excluded from this analysis. Where patients were noted to have multiple indications, only one was recorded-this was the one with the strongest pacing indication.…”

Section: Methodsmentioning

confidence: 99%

His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: Insights from a large international observational study

Keene

Arnold

Jastrzębski

et al. 2019

Cardiovasc electrophysiol

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Background His‐bundle pacing (HBP) provides physiological ventricular activation. Observational studies have demonstrated the techniques’ feasibility; however, data have come from a limited number of centers. Objectives We set out to explore the contemporary global practice in HBP focusing on the learning curve, procedural characteristics, and outcomes. Methods This is a retrospective, multicenter observational study of patients undergoing attempted HBP at seven centers. Pacing indication, fluoroscopy time, HBP thresholds, and lead reintervention and deactivation rates were recorded. Where centers had systematically recorded implant success rates from the outset, these were collated. Results A total of 529 patients underwent attempted HBP during the study period (2014‐19) with a mean follow‐up of 217 ± 303 days. Most implants were for bradycardia indications. In the three centers with the systematic collation of all attempts, the overall implant success rate was 81%, which improved to 87% after completion of 40 cases. All seven centers reported data on successful implants. The mean fluoroscopy time was 11.7 ± 12.0 minutes, the His‐bundle capture threshold at implant was 1.4 ± 0.9 V at 0.8 ± 0.3 ms, and it was 1.3 ± 1.2 V at 0.9 ± 0.2 ms at last device check. HBP lead reintervention or deactivation (for lead displacement or rise in threshold) occurred in 7.5% of successful implants. There was evidence of a learning curve: fluoroscopy time and HBP capture threshold reduced with greater experience, plateauing after approximately 30‐50 cases. Conclusion We found that it is feasible to establish a successful HBP program, using the currently available implantation tools. For physicians who are experienced at pacemaker implantation, the steepest part of the learning curve appears to be over the first 30‐50 cases.

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Section: Methodsmentioning

confidence: 99%

His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: Insights from a large international observational study

Keene

Arnold

Jastrzębski

et al. 2019

Cardiovasc electrophysiol

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150

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“…HBP can preserve physiological activation in patients with an intact conduction system and even can correct bundle branch block (BBB) to restore normal ventricular activation. [2][3][4][5][6] The electrocardiogram (ECG) is a key tool for identifying successful pacing. Conventional ventricular pacing produces characteristic, easily discernible changes in the 12-lead ECG.…”

Section: Introductionmentioning

confidence: 99%

Discriminating electrocardiographic responses to His-bundle pacing using machine learning

Arnold¹,

Howard²,

Gopi

et al. 2020

Cardiovascular Digital Health Journal

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BACKGROUND His-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts. OBJECTIVE The purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation. METHODS We identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset. RESULTS The CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network's performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P ,.0001), with an overall accuracy of 75%. The CNN's accuracy in the 17-patient testing set was 67% for S-HBP, 71% for NS-HBP, and 84% for MOC. CONCLUSION We demonstrated proof of concept that a neural network can be trained to automate discrimination between HBP ECG responses. When a larger dataset is trained to higher accuracy, automated AI ECG analysis could facilitate HBP implantation and follow-up and prevent complications resulting from incorrect HBP ECG analysis.

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“…One acute hemodynamic study showed that AV‐optimized HBP could improve systolic heart function in these patients, similar to the improvement from biventricular pacing . The His Optimized Pacing Evaluated for Heart Failure (HOPE‐HF) trial that is also expected to end in 2019 is a randomized crossover study of 160 patients that aims to evaluate the performance of HBP on patients with long PR interval (over 200 ms), LVEF less than 40%, and either narrow QRS (≤140 ms) or right bundle branch block …”

Section: Discussionmentioning

confidence: 99%

“…22 The His Optimized Pacing Evaluated for Heart Failure (HOPE-HF) trial that is also expected to end in 2019 is a randomized crossover study of 160 patients that aims to evaluate the performance of HBP on patients with long PR interval (over 200 ms), LVEF less than 40%, and either narrow QRS (≤140 ms) or right bundle branch block. 23 As a result, the His bundle is an ideal site for physiological pacing because of the engagement of the normal stimulation through the His-Purkinje conduction system. For heart failure patients, HBP could achieve cardiac resynchronization by correcting left bundle branch block (LBBB) via pacing the His-Purkinje system.…”

Section: Discussionmentioning

confidence: 99%

Permanent His bundle pacing in heart failure patients: A systematic review and meta‐analysis

Zhang

Zou

Wang

et al. 2018

Pacing Clinical Electrophis

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Background Cardiac resynchronization therapy (CRT) is the standard‐of‐care therapy for the patients with heart failure and left ventricular (LV) dyssynchrony. However, approximately 30% of the patients show no response. Recent studies have shown that His bundle pacing (HBP) could be an alternative for the patients with CRT indications. The purpose of this study was to evaluate the efficacy of HBP in patients with heart failure. Methods We searched PubMed and Embase databases for studies evaluating HBP in patients with heart failure and LV dyssynchrony. The successful rate of implantation, QRS duration, pacing threshold, LV function at baseline and follow‐up, and mortality rates were extracted and summarized. Results Eleven studies including 494 patients were included in this analysis. The overall successful rate for implantation was 82.4%. The main indications for HBP were CRT candidates and cardiomyopathy with atrial fibrillation undergoing atrioventricular node ablation. Permanent HBP resulted in narrow QRS duration of 116.3 ± 13.9 ms after implantation. LV functions, including echocardiographic parameters and clinical outcomes, significantly improved at follow‐up (P < 0.001). However, there was a trend of increased capture and bundle branch block correction thresholds at follow‐up compared to baseline (P = 0.01 and 0.02, respectively). During a mean follow‐up of 23.7 months, 5.9% of the patients experienced heart failure‐related hospitalization and the mortality rate was 9.1%. Conclusion Permanent HBP has shown promising results for heart failure patients in small observational studies. Randomized controlled trials are needed to assess the efficacy of HBP in these patients.

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Rationale and design of the randomized multicentre His Optimized Pacing Evaluated for Heart Failure (HOPE‐HF) trial

Cited by 41 publications

References 37 publications

His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: Insights from a large international observational study

His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: Insights from a large international observational study

Discriminating electrocardiographic responses to His-bundle pacing using machine learning

Permanent His bundle pacing in heart failure patients: A systematic review and meta‐analysis

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