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| http://dx.doi.org/10.1016/j.hrthm.2024.02.028 | DOI Listing |
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Contrastive pretraining improves deep learning classification of endocardial electrograms in a preclinical model.
Heart Rhythm O2
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Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah.
Background: Rotors and focal ectopies, or "drivers," are hypothesized mechanisms of persistent atrial fibrillation (AF). Machine learning algorithms have been used to identify these drivers, but the limited size of current driver data sets constrains their performance.
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Intracardiac electrogram-based atrial pace mapping for detecting the earliest activation site in atrial arrhythmias.
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Overcoming Uncertainties in Electrogram-Based Atrial Fibrillation Mapping: A Review.
Cardiovasc Eng Technol
February 2024
School of Electrical and Mechanical Engineering, The University of Adelaide, Adelaide, SA, 5000, Australia.
In clinical rhythmology, intracardiac bipolar electrograms (EGMs) play a critical role in investigating the triggers and substrates inducing and perpetuating atrial fibrillation (AF). However, the interpretation of bipolar EGMs is ambiguous due to several aspects of electrodes, mapping algorithms and wave propagation dynamics, so it requires several variables to describe the effects of these uncertainties on EGM analysis. In this narrative review, we critically evaluate the potential impact of such uncertainties on the design of cardiac mapping tools on AF-related substrate characterization.
View Article and Find Full Text PDFClinical outcomes of automatic algorithms in cardiac resynchronization therapy: Systematic review and meta-analysis.
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October 2023
Emory University Adult Congenital Heart Center, Atlanta, Georgia.
Background: Algorithms to automatically adjust atrioventricular (AV) and interventricular (VV) intervals in cardiac resynchronization therapy (CRT) devices are common, but their clinical efficacy is unknown.
Objective: The purpose of this study was to evaluate automatic CRT algorithms in patients with heart failure for the reduction of mortality, heart failure hospitalizations, and clinical improvement.
Methods: We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) in patients with CRT using automatic algorithms that change AV and VV intervals dynamically without manual input, on a beat-to-beat basis.
Evaluation of Criteria for Left Bundle Branch Capture.
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June 2022
Cardiac Electrophysiology, Geisinger Heart Institute, Geisinger Commonwealth School of Medicine, MC 36-10, 1000 E Mountain Blvd, Wilkes-Barre, PA 18711, USA. Electronic address:
Left bundle branch pacing (LBBP) provides electrical and mechanical synchrony at low and stable pacing output and effectively corrects distal conduction system disease. The criteria for differentiating LBBP from LV septal pacing has not been validated in large trials. There are several electrocardiography-based and intracardiac electrogram-based criteria to confirm LBB capture.
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