Chahal, C. Anwar A.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, contributing to significant morbidity and mortality worldwide. The relationship between physical exercise and AF is complex, with studies showing both beneficial and potentially adverse effects. Moreover, evidence suggests a U-shaped association between exercise intensity and AF risk. Moderate exercise has been shown to reduce AF burden by improving cardiovascular risk factors, enhancing autonomic regulation, and mitigating atrial fibrosis. In contrast, excessively high-intensity endurance exercise may increase AF risk, particularly in young athletes, due to atrial stretching, dilation, fibrosis, autonomic imbalances, and heightened inflammation. The current guidelines emphasize exercise as a core lifestyle intervention for AF management, recommending moderate-intensity aerobic activity for optimal outcomes. This review examines the current evidence on the effects of exercise on AF, identifies knowledge gaps, and proposes potential future research directions.

Arrhythmogenic cardiomyopathies (ACMs) are a phenotypically and etiologically heterogeneous group of myocardial disorders characterized by fibrotic or fibro-fatty replacement of ventricular myocardium, electrical instability, and an elevated risk of sudden cardiac death. Initially identified as a right ventricular disease, ACMs are now recognized to include biventricular and left-dominant forms. Genetic causes account for a substantial proportion of cases and include desmosomal variants, non-desmosomal variants, and familial gene-elusive forms with no identifiable pathogenic mutation. Nongenetic etiologies, including post-inflammatory, autoimmune, and infiltrative mechanisms, may mimic the phenotype. In many patients, the disease remains idiopathic despite comprehensive evaluation. Cardiac magnetic resonance imaging has emerged as a key tool for identifying non-ischemic scar patterns and for distinguishing arrhythmogenic phenotypes from other cardiomyopathies. Emerging classifications propose the unifying concept of scarring cardiomyopathies based on shared structural substrates, although global consensus is evolving. Risk stratification remains challenging, particularly in patients without overt systolic dysfunction or identifiable genetic markers. Advances in tissue phenotyping, multi-omics, and artificial intelligence hold promise for improved prognostic assessment and individualized therapy.

Abstract Aims Left ventricular hypertrophy (LVH) regionality carries diagnostic and prognostic importance. Mean absolute deviation of maximum segmental wall thickness (MadWT) is a novel left ventricular wall thickness (LVWT) heterogeneity biomarker from cardiovascular magnetic resonance imaging (CMR). Objectives To compare MadWT to indexed LV mass (LVMi), maximum (MaxWT) and mean (MeanWT) wall thickness to predict incident cardiovascular disease (CVD) and differentiate physiological from pathological LVH in highly physically active individuals. Methods and results Deep learning-assisted analysis of 44 930 UK Biobank CMR scans produced WT indices. Cox regression modelled major adverse cardiovascular events (MACE), heart failure (HF), arrhythmia, and all-cause death against LVWT indices. In the top 1% most physically active biomarker differences between propensity score matched hypertensive and non-hypertensive groups were compared. Over median (Q1, Q3) follow-up of 5.7 (4.9, 7.1) years, MadWT, MaxWT, MeanWT, and LVMi were associated with greater risk of MACE, HF, arrhythmia (P < 0.05), but not all-cause death (P > 0.05). After adjusting for CMR biomarkers, including LVMi, MadWT remained independently prognostic of the greatest number of endpoints, including MACE, HF, and arrhythmia [HR 1.13 (1.04–1.23); HR 1.15 (1.01–1.32); and HR 1.26 (1.18–1.35) respectively]. In the top 1% most physically active by three metrics, MadWT was the only significantly different biomarker between hypertensive and non-hypertensive participants (P < 0.05). Conclusion MadWT is important prognostically beyond LV mass and may be useful when differentiating physiological from hypertensive LVH. Although findings require confirmation in athletic and diseased cohorts, MadWT is readily translatable to deep learning-assisted clinical CMR reporting, especially in early unexplained LVH.

ABSTRACTBackgroundLate gadolinium enhancement (LGE) on cardiovascular magnetic resonance (CMR) imaging is a well‐established indicator of myocardial fibrosis in hypertrophic cardiomyopathy (HCM). However, its association with electrocardiographic (ECG) abnormalities and the risk of atrial fibrillation (AF) remains uncertain.ObjectivesTo investigate the association between the presence and burden of LGE with ECG characteristics, including precordial voltage, depolarization and repolarization abnormalities, and the incidence of AF in adults with HCM.MethodsWe conducted a retrospective cohort study of 144 adults with HCM with CMR and 12‐lead ECG within 30 days of each other. LGE was quantified as a percentage of LV mass and categorized as absent, < 5%, or ≥ 5%. ECG parameters, including QRS voltage, repolarization abnormalities, and LVH criteria, were analyzed. Incident AF was assessed during a median follow‐up of 6.6 years.ResultsLGE was present in 96 (67%) patients, with 21 (22%) having ≥ 5% LGE. There were no significant differences in precordial voltage between patients with and without LGE across Sokolow‐Lyon, Cornell, and Romhilt‐Estes criteria. However, T‐wave inversion was more common in leads I (41% vs. 19%, p = 0.009), aVL (50% vs. 31%, p = 0.033), and V4 (41% vs. 23%, p = 0.035) in patients with LGE. Patients with ≥ 5% LGE had a significantly lower median LVEF (64% vs. 74%, p = 0.003). Additionally, LGE presence was not associated with an increased risk of incident AF (HR 1.8, 95% CI 0.6–5.3, p = 0.308).ConclusionIn contrast to pediatric HCM, LGE is associated with specific ECG repolarization abnormalities, particularly T‐wave inversion in lateral leads, but does not significantly affect precordial voltage in adults.

BACKGROUND: This study aimed to evaluate the prevalence of pathogenic/likely pathogenic cardiomyopathy variant carriers in a multiancestry US population and examine the risk of adverse clinical outcomes. METHODS: This retrospective cohort study included multiancestry US adults aged ≥18 years with sequencing data from the All of Us Research Program. Pathogenic/likely pathogenic variants in cardiomyopathy genes were identified using the ClinVar database. The primary outcome was heart failure. Secondary outcomes included cardiomyopathy and arrhythmia. Outcomes were identified from electronic health records. Interval-censored Cox models, taking age on the timescale, were used to assess the risk of outcomes in pathogenic/likely pathogenic variant carriers with noncarriers as the reference group. RESULTS: Among 167 435 individuals (median age, 55.2 [39.5–66.3] years; 61.7% female; 40.7% non-European ancestry) included, the prevalence of pathogenic/likely pathogenic cardiomyopathy variant carriers was 0.7% in the overall population and 0.8%, 0.8%, 0.5%, and 1.2% among European, African, East Asian, and South Asian ancestry individuals, respectively. Over their lifetime, there were 12 867 heart failure events (205 in carriers and 12 662 in noncarriers), with an incidence rate of 3.05 (95% CI, 2.66–3.49) per 1000 person-years in carriers and 1.37 (95% CI, 1.35–1.40) in noncarriers (adjusted hazard ratio, 2.30 [95% CI, 2.04–2.60]). Cardiomyopathy occurred in 5164 (161 in carriers and 5003 in noncarriers), with an incidence rate of 2.38 (95% CI, 2.04–2.78) per 1000 person-years among carriers and 0.54 (95% CI, 0.53–0.56) in noncarriers (adjusted hazard ratio, 4.31 [95% CI, 3.73–4.97]). There were 19 405 arrhythmia events (263 in carriers and 19 142 in noncarriers), with an incidence rate of 3.93 (95% CI, 3.48–4.44) per 1000 person-years among carriers and 2.09 (95% CI, 2.06–2.12) in noncarriers (adjusted hazard ratio, 2.12 [95% CI, 1.78–2.53]). CONCLUSIONS: Pathogenic/likely pathogenic cardiomyopathy variant carriers have an increased risk of heart failure, cardiomyopathy, and arrhythmias. Despite the modest overall prevalence, the associated risks suggest potential benefits of targeted genetic screening for early detection and management.

Abstract Arrhythmogenic cardiomyopathy (ACM) is addressed in international guidelines and expert consensus statements. To assist clinicians in their routine practice and support decision-making, we performed a systematic review of the most relevant guidelines and recommendations for ACM diagnosis and management. Our search, covering MEDLINE, EMBASE, and resources from scientific societies over the last 10 years, identified two guidelines and three consensus statements that met rigorous inclusion criteria for detailed analysis. In the examined documents, key areas of agreement included the critical role of cardiac imaging for initial diagnosis and ongoing monitoring, genetic testing in index patients, ventricular arrhythmia management, catheter ablation indications, heart failure treatment strategies, and exercise recommendations. However, significant differences were found in definitions and diagnostic criteria for ACM, interpretation of phenocopies, management of family members, and criteria for implantable cardioverter defibrillator implantation. Additional discrepancies emerged regarding the role of multidisciplinary teams, non-cardiac surgical considerations, atrial fibrillation management, and reproductive issues. Crucially, there remain considerable gaps in evidence, especially in areas such as the management and follow-up of patients with potential or borderline ACM diagnoses, as well as the care of their relatives. The clinical implications of genetic findings, along with the clinical management of left-dominant, biventricular phenotypes, and hot phases of disease, are also insufficiently addressed. Furthermore, a critical shortfall is the lack of externally validated risk assessment tools to guide clinical decision-making. Bridging these gaps could help guiding future research and guideline development towards improving patient outcomes.

Despite advances in cardiovascular care and improved outcomes, fragmented healthcare systems, nonequitable access to health care, and nonuniform and unbiased collection and access to healthcare data have exacerbated disparities in healthcare provision and further delayed the technological-enabled implementation of precision medicine. Precision medicine relies on a foundation of accurate and valid omics and phenomics that can be harnessed at scale from electronic health records. Big data approaches in noncardiovascular healthcare domains have helped improve efficiency and expedite the development of novel therapeutics; therefore, applying such an approach to cardiovascular precision medicine is an opportunity to further advance the field. Several endeavors, including the American Heart Association Precision Medicine platform and public-private partnerships (such as BigData@Heart in Europe), as well as cloud-based platforms, such as Terra used for the National Institutes of Health All of Us, are attempting to temporally and ontologically harmonize data. This state-of-the-art review summarizes best practices used in cardiovascular genomic and precision medicine and provides recommendations for systems’ requirements that could enhance and accelerate the integration of these platforms.

Abstract Dilated cardiomyopathy (DCM) is a clinical diagnosis characterized by the presence of left ventricular dilatation and systolic dysfunction unexplained by abnormal loading conditions or coronary artery disease. However, a broad range of phenotypic manifestations, encompassing isolated scar, DCM with preserved ejection fraction, and overt DCM, should be regarded as a diagnostic classification representing a broad spectrum of underlying aetiologies, including both inherited and acquired heart muscle disorders. A multimodal non-invasive imaging approach is essential for accurate morpho-functional assessment of cardiac chambers and is key to establish the cardiac phenotype and to rule out an underlying ischaemic aetiology. Furthermore, advanced imaging techniques enable deep cardiovascular phenotyping and non-invasive tissue characterization. The aim of this review is to propose a systematic approach to the diagnosis of DCM, emphasizing the importance of genetics and clinical findings for a precise and practical clinical approach. Also, we strive to qualify the role of cardiac imaging in the diagnosis of DCM, particularly on the relevance of novel techniques and clinical utility of actionable parameters to improve current diagnostic schemes and risk stratification algorithms. We further elaborate on the role of cardiac imaging to deliver optimal guidance to aetiology-based therapeutic approaches, verification of treatment response and disease progression monitoring.