Background Pulsed field ablation (PFA) is an emerging ablation technology for atrial fibrillation (AF) and associated with hemolysis. Objective This study seeks to evaluate how variations in catheter configuration could influence hemolysis intensity.Methods: Using a translational approach, hemolysis induced by a pentaspline PFA catheter was assessed in an in vitro erythrocyte concentrate model. PFA applications in flower, basket or olive configuration were delivered in erythrocyte concentrate, and hemolysis index was used to measure hemolysis. In twenty patients who underwent pulmonary vein isolation with PFA for AF using the pentaspline catheter hemolysis markers were measured before and immediately after the procedure and on the first and second post-procedural days. Results In vitro application in olive configuration led to significantly more hemolysis in erythrocyte concentrate than basket or flower configuration. After 20 applications, hemolysis index increased by 44 in the olive vs. 24 in the flower and 22.5 in the basket group. In vivo, hemolysis index increased significantly from 6.7 ± 11.77 before to 24.65 ± 6.28 immediately after PFA treatment in patients (p<0.0001). Haptoglobin decreased significantly from 1 ± 0.37 g/l before procedure to 0.53 ± 0.36 g/l on the first post-procedural day. Patients treated with olive applications demonstrated a significantly greater decrease in haptoglobin (-0.38 g/l vs. -0.55 g/l; p=0.02). No case of acute kidney injury occurred. Conclusion This study demonstrates that PFA applications with different pentaspline catheter configurations are associated with varying extents of hemolysis. The olive configuration was associated with more hemolysis than basket or flower configuration.

BACKGROUND:Optimisation of medical therapy is recommended for patients with newly diagnosed non-ischaemic cardiomyopathies (NICM) before consideration of a primary preventive implantable cardioverter-defibrillator (ICD). During this optimisation period, patients face a potentially elevated risk for sudden cardiac death (SCD) that can be countered with a wearable cardioverter-defibrillator (WCD). This systematic review aims to assess the risk for SCD in patients with newly diagnosed NICM. METHODS:A systematic review was performed in Medline, Embase and Cochrane Library last updated on March 2025. Studies with patients aged ≥18 years with newly diagnosed NICM (≤90 days) who were recipients of WCD were included. Study selection, study quality assessment and data extraction were performed by two reviewers independently. Data on percentage of patients with appropriate WCD shocks (as proxy for sustained ventricular arrhythmia, potentially leading to SCD), inappropriate WCD shocks and device implantation were pooled by random-effects model. RESULTS:50 non-controlled observational studies were included, comprising a total of 10 066 patients with NICM. The percentage of appropriate shocks was 1% (87/7708; 95% CI 1% to 2%) in patients with NICM, 2% (16/1049; 95% CI 1% to 2%) in patients with myocarditis, 3% (7/183; 95% CI 0% to 20%) in peripartum cardiomyopathy, 2% (2/102; 95% CI 0% to 7%) in Takotsubo syndrome and 1% (8/594; 95% CI 1% to 3%) for congenital/inherited or genetic cardiomyopathy. Inappropriate shocks ranged from 0% to 1%. At the end of follow-up, between 6% (Takotsubo syndrome) and 43% (congenital/inherited or genetic cardiomyopathy) of patients received an ICD. CONCLUSION:Patients with NICM face a significant risk of SCD during the drug optimisation period before deciding if they qualify for ICD implantation. Results of this meta-analysis are based on non-comparative studies; however, the assessment of an appropriate shock delivered and recorded by the WCD is highly reliable. PROSPERO REGISTRATION NUMBER:CRD42024555879.

The rapid expansion of interventional electrophysiology (EP) and cardiac implantable electronic device (CIED) therapies has outpaced the capacity of traditional apprenticeship-based training to deliver standardized, equitable, and patient-safe skill acquisition across Europe. This scientific statement of European Heart Rhythm Association (EHRA) of the European Society of Cardiology (ESC) synthesizes the current landscape of digitally assisted learning for EP/CIED, provides a structured framework for implementation, and defines the responsibilities of scientific societies in establishing trustworthy, competency-based pathways. The document first reviews the technical principles and available digital modalities, emphasizing alignment of tool selection with learning objectives and staged progression. It then contrasts these capabilities with real-world uptake, highlighting fragmented access and strong reliance on industry-mediated training, alongside the emergence of neutral access models such as the EHRA Simulation Village. A central suggestion is the adoption of proficiency-based progression supported by protocolized evaluation: predefined and validated performance metrics, benchmarking against expert standards, deliberate practice with structured feedback, and summative assessment prior to patient procedures. Key implementation challenges include resource disparities and geographic inequities, limits in simulation fidelity for team-based and contextual decision-making, governance of industry relationships, and the need for protected educational time. Pragmatic solutions include tiered certification tracks, hybrid models combining digital and supervised clinical training, regional simulation hubs, minimum simulator specifications, ongoing curriculum updates, and coordinated stakeholder collaboration. Priority research needs are defined around clinical outcome validation, optimal curriculum design, technology development, and implementation science.

Artificial intelligence (AI) is gaining importance in the field of cardiology. By analyzing complex multimodal data AI can support the diagnostic processes, risk stratification and making decisions. In cardiac imaging AI-based procedures improve the objective image analysis and facilitate the detection of specific cardiac diseases. The AI-assisted analysis in electrocardiography (ECG) not only enables reliable identification of established diagnoses but also enables the detection of patterns not yet identifiable for the human eye and therefore opens up opportunities for the establishment of new diagnostics and risk stratification. Large language models (LLM) represent a subdomain of AI. In cardiology they show particular potential for knowledge-based and text-based tasks, such as clinical documentation, support in drafting medical reports and patient education. Based on the current evidence, publicly available LLM are not appropriate for image interpretation, clinical decision-making or for supporting peer-review processes. Key challenges for the clinical implementation of AI include data protection and data security, regulatory requirements, currently limited evidence from randomized clinical trials, the limited option for validation of self-learning algorithms, limited transparency and the need for structured training programs for both physicians and patients. Irrespective of the degree of AI assistance, physician oversight remains crucial.

Abstract This study demonstrates the successful production and injection of human induced pluripotent stem cell cardiomyocyte aggregates into infarcted cynomolgus monkey hearts, resulting in substantial, structured human grafts three months after cell transplantation. Transient graft-induced arrhythmias decreased over time. Both the arrhythmogenicity and the substantial heart function recovery in vivo notably seemed to correlate with induced pluripotent stem cell clone-dependent contractile and electrophysiological cardiomyocyte properties in vitro. Overexpression of a red fluorescent reporter protein led to a dysregulated conduction and contraction machinery in yet engraftment competent cardiomyocytes, providing an important tool to mechanistically understand and improve induced pluripotent stem cell-based heart repair in preclinical models. We demonstrate the logistically important, temporal uncoupling of cardiomyocyte production from transplantation. Cardiomyocyte aggregate transplantation yielded results comparable to the reported transplantation of 10-20-fold higher numbers of dissociated human embryonic stem cell- cardiomyocytes and suggests a higher degree of cell/ tissue maturation in cardiac grafts. Our study promotes reduced cell production costs, highlights the need for an in vitro potency assay, and shows a pragmatic new avenue for the clinical translation of human induced pluripotent stem cell-based heart repair.

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy but are associated with a growing spectrum of cardiovascular immune-related adverse events. Among these, arrhythmias represent a rare yet potentially life-threatening complication. ICI-induced arrhythmias encompass a wide clinical spectrum, including atrial arrhythmias, conduction disturbances and malignant ventricular arrhythmias. This review summarizes the current evidence on the incidence, clinical presentation, pathophysiological mechanisms and management of ICI-associated arrhythmias. We discuss the limitations of available data, which are largely derived from case reports, small series and retrospective registries, and highlight the implications for clinical practice. Improved understanding of ICI-induced arrhythmias is essential to balance oncological efficacy with cardiovascular safety in this, rapidly expanding, patient population.

BACKGROUND AND AIMS:Stereotactic arrhythmia radioablation (STAR) is increasingly used for refractory ventricular tachycardia (VT), yet prospective multicentre outcome data remain limited. Here, the planned interim analysis of the prospective Standardized Treatment and Outcome Platform for Stereotactic Therapy Of Re-entrant tachycardia by a Multidisciplinary (STOPSTORM) registry is reported. METHODS:STOPSTORM is a European prospective, international, multicentre registry of patients treated with STAR. The primary efficacy endpoint was the change in sustained VT episode burden comparing the 6 months before versus the 6 months after STAR. The primary safety endpoint was the occurrence of serious adverse events (SAEs) adjudicated as possibly or probably treatment-related. Overall survival was assessed using time-to-event methods. RESULTS:Across 28 centres, 193 patients were included (mean age 68±9 years; 88% male; 53% non-ischaemic cardiomyopathy). Median follow-up was 19 months. Among 107 evaluable patients with ≥6-month follow-up, the median VT episode burden was reduced by 80% after STAR. Among patients surviving ≥6 months, 72% were free from implantable cardioverter-defibrillator (ICD) shock. In the full cohort, 12 SAEs were adjudicated as possibly or probably treatment-related, including pericardial effusion, coronary events, and early post-treatment ventricular arrhythmia. Overall survival probability was 77% at 12 months. CONCLUSIONS:In the largest prospective multicentre cohort reported to date, STAR was associated with a substantial reduction in VT burden and ICD shocks, with a low frequency of possibly or probably treatment-related SAEs.

Cardiac implantable device procedures in patients with congenital heart defects often pose a major challenge due to the often very complex anatomy and should be planned and performed by an interdisciplinary team in centers suitable for this. This review article gives a practical guide on how a pacemaker or defibrillator implantation can be successfully performed in patients with complex congenital heart defects based on representative case examples.

Atrial fibrillation (AF) is increasingly diagnosed early, close to its first occurrence due to: (i) increased public awareness with self-screening; (ii) health care initiatives including population screening and opportunistic case finding; and (iii) increased use and surveillance of implantable cardiac devices. At its onset, AF is often low burden, and cardiovascular co-morbidities may be absent or at an early stage. Thus, the management of recent-onset AF has become an issue of growing importance. Professional guidelines have traditionally focused on anticoagulant thromboprophylaxis, generally recommending a cautious approach to rhythm control, and priority has been given to rate control to alleviate symptoms. In recent guidelines, the importance of managing lifestyle and co-morbidities has increased. The AF-SCREEN collaboration proposes that a vigorous approach to active management of recent-onset AF may be warranted. This includes addressing co-morbidities and promoting healthy lifestyles to prevent the emergence or progression of AF and associated cardiovascular disease, as well as the initiation of active rhythm control ± anticoagulation to prevent AF-related morbidity and mortality, including stroke and heart failure (HF). Intuitively, intervention early after AF onset would be beneficial since lifestyle and co-morbidity management, plus rhythm control and anticoagulation, are important contributors to improved outcomes in patients with established AF, but robust evidence is lacking for recent-onset AF. There is a delicate balance between achieving favourable outcomes such as preventing strokes, HF and AF progression vs the complications and potential adverse effects of interventions. Given the serious long-term consequences, innovative approaches are necessary to determine the value and risks of initiating active therapy very early in the course of AF. More data are needed to guide the best management of recent-onset AF, bearing AF burden in mind. Long-term studies using large national databases linked to electronic medical records and rhythm monitoring devices offer excellent opportunities. Shorter-term studies focusing on reducing AF burden to slow AF progression and studies focusing on outcomes such as HF could be used in both randomized clinical trials and observational cohort studies.

BACKGROUND:Stereotactic arrhythmia radioablation (STAR) targets are typically defined by electroanatomical mapping and imaging-based substrate characterization, yet their spatial relationship to mechanically derived deformation abnormalities remains incompletely understood. OBJECTIVE:To evaluate the spatial association between CT-derived end-diastolic-end-systolic (ED-ES) radial deformation abnormalities and clinically defined STAR targets. METHODS:In nine patients undergoing STAR, three-dimensional left ventricular shells were reconstructed from ECG-gated contrast-enhanced CT. Radial deformation between ED and ES was estimated from the inter-phase displacement field, and abnormal regions defined by a patient-specific threshold at the lower 10th percentile of voxel-wise radial deformation. STAR targets were transferred from voltage maps onto the CT geometry. Spatial relationships were assessed using centroid distance, mean surface distance, volumetric overlap, and segment-level concordance. RESULTS:Eleven abnormal radial deformation regions and 11 STAR targets were identified. At the segment level, radial deformation discriminated target-positive segments (AUC 0.80, 95% CI 0.73-0.88) significantly better than longitudinal deformation (AUC 0.71, 95% CI 0.66-0.76; DeLong p < 0.001). Median centroid distance between abnormal regions and STAR targets was 20.4 mm (IQR 15.4-33.7) and median mean surface distance 6.0 mm (IQR 2.8-9.7). Partial volumetric overlap occurred in 9 of 11 deformation-defined regions, and 10 of 11 STAR targets overlapped at least one deformation-defined abnormality. Abnormal radial deformation was present in 18 of 21 target-positive segments (86%) versus 41 of 129 target-negative segments (32%). CONCLUSIONS:CT-derived ED-ES radial deformation abnormalities show substantial spatial association with clinically defined STAR targets, alongside partial discordance, and may complement substrate characterization in patients undergoing STAR.

Künstliche Intelligenz (KI) gewinnt in der Kardiologie zunehmend an Bedeutung. Durch die Analyse komplexer, multimodaler Daten kann KI bei Diagnostik, Risikostratifizierung und Therapieplanung unterstützen. In der kardialen Bildgebung verbessern KI-basierte Verfahren die objektive Bildauswertung sowie die Detektion spezifischer kardialer Erkrankungen. Die KI-gestützte Elektrokardiogramm(EKG)-Analyse kann neben der zuverlässigen Erkennung etablierter Diagnosen auch bisher für das menschliche Auge nichterkennbare Muster identifizieren und eröffnet damit ganz neue diagnostische und risikostratifizierende Möglichkeiten. Large Language Models (LLM) stellen einen KI-Teilbereich dar. In der Kardiologie zeigen sie insbesondere Potential bei wissens- und textbasierten Aufgaben wie klinischer Dokumentation, der Unterstützung bei der Arztbriefschreibung sowie in der Patientenedukation. Für die Bildinterpretation, komplexe Therapieentscheidungen oder für die Unterstützung wissenschaftlicher Begutachtungsprozesse sind öffentlich zugängliche LLM nach aktuellem Kenntnisstand nicht geeignet. Zentrale Herausforderungen für den klinischen Einsatz von KI umfassen unter anderem Datenschutz und Datensicherheit, regulatorische Anforderungen, die bislang begrenzte Evidenz aus randomisierten Studien, die eingeschränkte Validierbarkeit selbstlernender Algorithmen, fehlende Transparenz sowie den Bedarf an strukturierten Aus- und Weiterbildungsformaten für ÄrztInnen und PatientInnen. Unabhängig vom Grad der Automatisierung bleibt die ärztliche Kontrolle unverzichtbar.

Photoplethysmography (PPG) is a noninvasive optical technique for assessing cardiovascular physiology that has evolved into a widely used tool embedded in modern consumer wearables. By detecting changes in blood volume through light absorption, PPG provides both heart rate and rhythm information, as well as insights into broader physiological states. While electrocardiography (ECG) remains the gold standard for arrhythmia diagnosis, PPG offers a scalable and accessible alternative for continuous monitoring. Technically, PPG signals consist of a pulsatile component reflecting arterial blood flow and a baseline component from static tissues. These signals correlate closely with ECG-derived heart rate and can be used to derive additional metrics such as heart rate variability and vascular indices. Numerous studies have demonstrated the high accuracy of PPG for heart rate measurement, though performance can be affected by motion artifacts, skin tone, and reduced signal amplitude at high heart rates. PPG has shown strong performance in detecting atrial fibrillation, with high sensitivity and specificity in both algorithm-based and physician-interpreted analyses. However, ECG confirmation remains necessary for diagnosis given variability in study quality and limitations in distinguishing other arrhythmias. Clinically, PPG is valuable for atrial fibrillation screening, symptom-rhythm correlation, and remote monitoring, particularly in hybrid systems combining PPG with ECG. Future developments include expanded arrhythmia detection, machine learning integration, and contactless monitoring technologies. Despite its promise, widespread clinical adoption is currently limited by the lack of standardized technical frameworks and validation protocols. Overall, PPG represents a powerful adjunct to ECG, with significant potential to enhance patient-centered cardiovascular care.