Citations

Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P < .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P < .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.

Abstract Aims Artificial intelligence electrocardiography (AI-ECG) algorithms are emerging tools for identifying individuals at risk of atrial fibrillation (AF). We evaluated the predictive performance of a validated AI-ECG algorithm for incident AF in UK Biobank participants with AF risk factors, irrespective of prevalent cardiovascular disease, and its incremental value when added to clinical predictors. Methods and results The AI-ECG tool was applied to sinus rhythm ECGs from UK-Biobank participants with risk factors for AF but no AF. Model performance was evaluated using time-dependent ROC-AUC and Harrell’s C-index. Multivariable Cox regression was used to identify clinical risk factors associated with incident AF and to quantify the contribution of AI-ECG. A total of 21 842 participants (56% male) were included. The median follow-up time was 3.7 years (IQR 0.5–5.4) The ECG-AI tool achieved a ROC-AUC of 0.73 (95% CI 0.68–0.78) at 1 and 0.69 (95% CI 0.66–0.72) at 3 years. A multivariable Cox regression model using clinical parameters achieved a ROC-AUC of 0.71 (95% CI 0.66–0.75) at 1 and 0.71 (95% CI 0.68–0.74) at 3 years. By adding ECG-AI to the clinical Cox regression model, the ROC-AUC increased to 0.75 (95%CI 0.71–0.80) at 1 and 0.74 (95% CI 0.71–0.77) at 3 years. AI-ECG showed a hazard ratio of 1.23 per decile increase (95% CI 1.18–1.27). Conclusion An AI-ECG algorithm improved the prediction of incident AF when added to a clinical parameter-based model over a median follow-up time of 3.7 years among individuals with comorbidities predisposing to AF who may benefit from targeted screening and preventive strategies.

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard‐of‐care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in‐depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype‐first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population‐based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true‐positive and false‐positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype‐first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Abstract To develop a suite of quality indicators (QIs) for the management of patients with ventricular arrhythmias (VA) and the prevention of sudden cardiac death (SCD). The Working Group comprised experts in heart rhythm management including Task Force members of the 2022 European Society of Cardiology (ESC) Clinical Practice Guidelines for the management of patients with VA and the prevention of SCD, members of the European Heart Rhythm Association, international experts, and a patient representative. We followed the ESC methodology for QI development, which involves (i) the identification of the key domains of care for the management of patients with VA and the prevention of SCD by constructing a conceptual framework of care, (ii) the development of candidate QIs by conducting a systematic review of the literature, (iii) the selection of the final set of QIs using a modified-Delphi method, and (iv) the evaluation of the feasibility of the developed QIs. We identified eight domains of care for the management of patients with VA and the prevention of SCD: (i) structural framework, (ii) screening and diagnosis, (iii) risk stratification, (iv) patient education and lifestyle modification, (v) pharmacological treatment, (vi) device therapy, (vii) catheter ablation, and (viii) outcomes, which included 17 main and 4 secondary QIs across these domains. Following a standardized methodology, we developed 21 QIs for the management of patients with VA and the prevention of SCD. The implementation of these QIs will improve the care and outcomes of patients with VA and contribute to the prevention of SCD.

Arrhythmogenic cardiomyopathy (ACM) is a primary disease of the myocardium, predominantly caused by genetic defects in proteins of the cardiac intercalated disc, particularly, desmosomes. Transmission is mostly autosomal dominant with incomplete penetrance. ACM also has wide phenotype variability, ranging from premature ventricular contractions to sudden cardiac death and heart failure. Among other drivers and modulators of phenotype, inflammation in response to viral infection and immune triggers have been postulated to be an aggravator of cardiac myocyte damage and necrosis. This theory is supported by multiple pieces of evidence, including the presence of inflammatory infiltrates in more than two-thirds of ACM hearts, detection of different cardiotropic viruses in sporadic cases of ACM, the fact that patients with ACM often fulfill the histological criteria of active myocarditis, and the abundance of anti–desmoglein-2, antiheart, and anti-intercalated disk autoantibodies in patients with arrhythmogenic right ventricular cardiomyopathy. In keeping with the frequent familial occurrence of ACM, it has been proposed that, in addition to genetic predisposition to progressive myocardial damage, a heritable susceptibility to viral infections and immune reactions may explain familial clustering of ACM. Moreover, considerable in vitro and in vivo evidence implicates activated inflammatory signaling in ACM. Although the role of inflammation/immune response in ACM is not entirely clear, inflammation as a driver of phenotype and a potential target for mechanism-based therapy warrants further research. This review discusses the present evidence supporting the role of inflammatory and immune responses in ACM pathogenesis and proposes opportunities for translational and clinical investigation.