Modeling heart rhythm using human engineered heart tissues.

Heart rate is both an indicator and modulator of cardiovascular health. Prolonged elevation in heart rate or irregular heart rhythm can trigger the onset of cardiac dysfunction, a condition termed 'tachycardia-induced cardiomyopathy'. While large animals have historically served as the primary model for studying this condition owing to their similar resting heart rates to humans, their use is limited by cost and throughput constraints.

2025 International Expert Practical Guide on the Use of the Pentaspline Pulsed Field Ablation System in Atrial Fibrillation Ablation Procedures.

Pulsed field ablation (PFA) has been developed as a largely nonthermal ablation technology with a unique biophysical profile to treat atrial fibrillation. Existing evidence has shown that PFA offers a safe and efficient atrial fibrillation ablation procedure. Among different PFA technologies, the pentaspline FARAPULSE system has been the most extensively used and investigated; however, notable variability exists in workflow, fluoroscopy time, and lesion durability.

Access to digital health technologies: personalized framework and global perspectives.

The emergence and rapid adoption of digital health technologies (DHT) present unprecedented opportunities to democratize and reduce disparities in health care by monitoring health and disease at the point of care in all patients. However, limited access to DHT is becoming a major obstacle to realizing these goals. Access to DHT is influenced not only by well-recognized social determinants of health, but also by digital determinants of health, such as digital literacy and the need for broad access to digital infrastructure, as well as commercial and economic factors.

International survey of cardiac device clinic staff determining patient-perceived challenges with remote monitoring.

Background: Regular interaction with patients with cardiac implantable electronic devices (CIEDs) provides CIED clinic personnel with unique insights into patient-related barriers and challenges to remote monitoring (RM) implementation.

Methods: Using a global network, an international survey was administered to CIED clinic personnel. Qualitative questions gathered information on perceived challenges with patient connectivity and patient-level barriers associated with RM implementation.

Non-cardiac and cardiac risk for ischemic stroke in young adults: The Stanford Y-CORE (Young Cardiovascular Outcomes and Risk Evaluation) study.

Background: The incidence of stroke is increasing in young to middle-aged adults. Assessing risk factors is important in this large population whose comorbidities may differ from older adults.

Methods: In this retrospective cohort analysis of adults aged between 20 and 50 presenting to the Stanford Healthcare system from 1 January 2000 through 31 December 2021, with no prior history of stroke or transient ischemic attack, we studied the effects of 30 risk factors on the primary endpoint of incident ischemic stroke, defined by the presence of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes for stroke and confirmed by brain imaging.

Identification of atrial myopathy and atrial fibrillation recurrence after ablation using 3D left atrial phasic strain from retrospective gated computed tomography.

Aims: Reduced left atrial (LA) mechanical function associates with atrial myopathy and adverse clinical endpoints in atrial fibrillation (AF) patients; however, conventional 2D imaging modalities are limited by atrial foreshortening and sub-optimally capture 3D LA motion.

Objectives: We set out to test the hypothesis that 3D LA motion features from 4D (3D + time) retrospective gated computed tomography (RGCT) associate with AF phenotypes and predict AF recurrence in patients undergoing catheter ablation.

Methods And Results: Sixty-nine AF patients (60.

State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.

Aims: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field.

Angiotensin-Converting Enzyme Inhibition as a Potential Risk Factor for Periprosthetic Joint Infection Following Total Knee Arthroplasty.

Background: Periprosthetic joint infection (PJI) following total knee arthroplasty (TKA) portends significant morbidity. studies demonstrating angiotensin-converting enzyme inhibitors (ACEis) may have an immunosuppressive effect. This study leveraged a large national registry to test if propensity-matched patients taking ACEis would have higher rates of PJI following TKA than patients taking angiotensin receptor blockers (ARBs).

Addressing contemporary threats in anonymised healthcare data using privacy engineering.

Cyber-attacks on healthcare entities and leaks of personal identifiable information (PII) are a growing threat. However, it is now possible to learn sensitive characteristics of an individual without PII, by combining advances in artificial intelligence, analytics, and online repositories. We discuss privacy threats and privacy engineering solutions, emphasizing the selection of privacy enhancing technologies for various healthcare cases.

Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.

Reducing electrophysiological (EP) signal noise is essential for diagnosis, mapping, and ablation, yet traditional approaches are suboptimal. This study tests the hypothesis that generative artificial intelligence (AI), specifically Variational Autoencoders (VAEs), can effectively denoise these signals by forming robust internal representations of 'clean' signals. Utilizing a dataset of 5706 time series from 42 patients with ischemic cardiomyopathy at risk of cardiac sudden death, we set out to apply a β-VAE model to denoise and reconstruct intra-ventricular monophasic action potential (MAP) signals, which have verifiable morphology.

A call for transparency, improved reporting, and interpretation of trials using surrogate end points in cardiac electrophysiology.

In this call for transparency, we aim to disseminate knowledge about recent CONSORT-Surrogate and SPIRIT-Surrogate checklists. SPIRIT-Surrogate is an extension of the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist, developed as a consensus document and designed as a reporting guideline for randomized controlled trial (RCT) protocols using surrogate end points as the primary end points. CONSORT-Surrogate is an extension of the Consolidated Standards of Reporting Trials (CONSORT) checklist, a consensus-driven reporting guideline for RCTs using surrogate end points as the primary end points.

Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

Background: It is difficult to identify patients with atrial fibrillation (AF) most likely to respond to ablation. While any arrhythmia patient may recur after acutely successful ablation, AF is unusual in that patients may have long-term arrhythmia freedom despite a lack of acute success. We hypothesized that acute and chronic AF ablation outcomes may reflect distinct physiology and used machine learning of multimodal data to identify their phenotypes.

Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram.

Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to identify novel ECG features using deep learning to enhance WMA detection, referencing echocardiography as the gold standard. We collected ECG and echocardiogram data from 35,210 patients in California and labeled WMA using unstructured language parsing of echocardiographic reports.

Atrial fibrillation nomenclature, definitions, and mechanisms: Position paper from the international Working Group of the Signal Summit.

The international Working Group of the Signal Summit is a consortium of experts in the field of cardiac electrophysiology dedicated to advancing knowledge on understanding and clinical application of signal recording and processing techniques. In 2023, the working group met in Reykjavik, Iceland, and laid the foundation for this manuscript. Atrial fibrillation (AF) is the most common arrhythmia in adults, with a rapidly increasing prevalence worldwide.

Prediction of sudden cardiac death using artificial intelligence: Current status and future directions.

Sudden cardiac death (SCD) remains a pressing health issue, affecting hundreds of thousands each year globally. The heterogeneity among people who suffer a SCD, ranging from individuals with severe heart failure to seemingly healthy individuals, poses a significant challenge for effective risk assessment. Conventional risk stratification, which primarily relies on left ventricular ejection fraction, has resulted in only modest efficacy of implantable cardioverter-defibrillators for SCD prevention.

Factors of engagement in research after graduation from EP fellowship: An HRS survey.

Background: The declining number of electrophysiologists pursuing academic research careers could have a negative impact on innovation for patients with heart rhythm disorders in the coming decades.

Objective: The objective of this study was to explore determinants of research engagement after graduation from electrophysiology (EP) fellowship programs and to evaluate associated barriers and opportunities.

Methods: A mixed methods survey of EP fellows and early-career electrophysiologists was conducted, drawing from Heart Rhythm Society members.

Mechanistic Insights From Trials of Atrial Fibrillation Ablation: Charting a Course for the Future.

Success rates for catheter ablation of atrial fibrillation (AF), particularly persistent AF, remain suboptimal. Pulmonary vein isolation has been the cornerstone for catheter ablation of AF for over a decade. While successful for most patients, pulmonary vein isolation alone is still insufficient for a substantial minority.