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Personalized accelerated physiologic pacing.

ABSTRACT: Heart failure with preserved ejection fraction (HFpEF) is increasingly prevalent with a high socioeconomic burden. Pharmacological heart rate lowering was recommended to improve ventricular filling in HFpEF. This article discusses the misperceptions that have resulted in an overprescription of beta-blockers, which in all likelihood have untoward effects on patients with HFpEF, even if they have atrial fibrillation or coronary artery disease as a comorbidity. Directly contradicting the lower heart rate paradigm, faster heart rates provide haemodynamic and structural benefits, amongst which lower cardiac filling pressures and improved ventricular capacitance may be most important. Safe delivery of this therapeutic approach is feasible with atrial and ventricular conduction system pacing that aims to emulate or enhance cardiac excitation to maximize the haemodynamic benefits of accelerated pacing. This conceptual framework was first tested in the myPACE randomized controlled trial of patients with pre-existing pacemakers and preclinical or overt HFpEF. This article provides the background and path towards this treatment approach.

SUBMITTER: Meyer M

PROVIDER: S-EPMC10637836 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Personalized accelerated physiologic pacing.

Meyer Markus M Infeld Margaret M Habel Nicole N Lustgarten Daniel D

European heart journal supplements : journal of the European Society of Cardiology 20231109 Suppl G

Heart failure with preserved ejection fraction (HFpEF) is increasingly prevalent with a high socioeconomic burden. Pharmacological heart rate lowering was recommended to improve ventricular filling in HFpEF. This article discusses the misperceptions that have resulted in an overprescription of beta-blockers, which in all likelihood have untoward effects on patients with HFpEF, even if they have atrial fibrillation or coronary artery disease as a comorbidity. Directly contradicting the lower hear ...[more]

PMID: 37970518

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Project description:ImportancePatients with heart failure with preserved ejection fraction (HFpEF) with a pacemaker may benefit from a higher, more physiologic backup heart rate than the nominal 60 beats per minute (bpm) setting.ObjectiveTo assess the effects of a moderately accelerated personalized backup heart rate compared with 60 bpm (usual care) in patients with preexisting pacemaker systems that limit pacemaker-mediated dyssynchrony.Design, setting, and participantsThis blinded randomized clinical trial enrolled patients with stage B and C HFpEF from the University of Vermont Medical Center pacemaker clinic between June 2019 and November 2020. Analysis was modified intention to treat.InterventionsParticipants were randomly assigned to personalized accelerated pacing or usual care and were followed up for 1 year. The personalized accelerated pacing heart rate was calculated using a resting heart rate algorithm based on height and modified by ejection fraction.Main outcomes and measuresThe primary outcome was the serial change in Minnesota Living with Heart Failure Questionnaire (MLHFQ) score. Secondary end points were changes in N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, pacemaker-detected physical activity, atrial fibrillation from baseline, and adverse clinical events.ResultsOverall, 107 participants were randomly assigned to the personalized accelerated pacing (n = 50) or usual care (n = 57) groups. The median (IQR) age was 75 (69-81) years, and 48 (48%) were female. Over 1-year follow-up, the median (IQR) pacemaker-detected heart rate was 75 (75-80) bpm in the personalized accelerated pacing arm and 65 (63-68) bpm in usual care. MLHFQ scores improved in the personalized accelerated pacing group (median [IQR] baseline MLHFQ score, 26 [8-45]; at 1 month, 15 [2-25]; at 1 year, 9 [4-21]; P < .001) and worsened with usual care (median [IQR] baseline MLHFQ score, 19 [6-42]; at 1 month, 23 [5-39]; at 1 year, 27 [7-52]; P = .03). In addition, personalized accelerated pacing led to improved changes in NT-proBNP levels (mean [SD] decrease of 109 [498] pg/dL vs increase of 128 [537] pg/dL with usual care; P = .02), activity levels (mean [SD], +47 [67] minutes per day vs -22 [35] minutes per day with usual care; P < .001), and device-detected atrial fibrillation (27% relative risk reduction compared with usual care; P = .04) over 1-year of follow-up. Adverse clinical events occurred in 4 patients in the personalized accelerated pacing group and 11 patients in usual care.Conclusions and relevanceIn this study, among patients with HFpEF and pacemakers, treatment with a moderately accelerated, personalized pacing rate was safe and improved quality of life, NT-proBNP levels, physical activity, and atrial fibrillation compared with the usual 60 bpm setting.Trial registrationClinicalTrials.gov Identifier: NCT04721314.

Project description:Introduction: The 30-50% non-response rate to cardiac resynchronization therapy (CRT) calls for improved patient selection and optimized pacing lead placement. The study aimed to develop a novel technique using patient-specific cardiac models and machine learning (ML) to predict an optimal left ventricular (LV) pacing site (ML-PS) that maximizes the likelihood of LV ejection fraction (LVEF) improvement in a given CRT candidate. To validate the approach, we evaluated whether the distance DPS between the clinical LV pacing site (ref-PS) and ML-PS is associated with improved response rate and magnitude. Materials and methods: We reviewed retrospective data for 57 CRT recipients. A positive response was defined as a more than 10% LVEF improvement. Personalized models of ventricular activation and ECG were created from MRI and CT images. The characteristics of ventricular activation during intrinsic rhythm and biventricular (BiV) pacing with ref-PS were derived from the models and used in combination with clinical data to train supervised ML classifiers. The best logistic regression model classified CRT responders with a high accuracy of 0.77 (ROC AUC = 0.84). The LR classifier, model simulations and Bayesian optimization with Gaussian process regression were combined to identify an optimal ML-PS that maximizes the ML-score of CRT response over the LV surface in each patient. Results: The optimal ML-PS improved the ML-score by 17 ± 14% over the ref-PS. Twenty percent of the non-responders were reclassified as positive at ML-PS. Selection of positive patients with a max ML-score >0.5 demonstrated an improved clinical response rate. The distance DPS was shorter in the responders. The max ML-score and DPS were found to be strong predictors of CRT response (ROC AUC = 0.85). In the group with max ML-score > 0.5 and DPS< 30 mm, the response rate was 83% compared to 14% in the rest of the cohort. LVEF improvement in this group was higher than in the other patients (16 ± 8% vs. 7 ± 8%). Conclusion: A new technique combining clinical data, personalized heart modelling and supervised ML demonstrates the potential for use in clinical practice to assist in optimizing patient selection and predicting optimal LV pacing lead position in HF candidates for CRT.

Dataset Information

Personalized accelerated physiologic pacing.

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Personalized accelerated physiologic pacing.

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