Introduction: A healthy young woman, age 26 without prior cardiac complications, experienced an out-of-hospital cardiac arrest caused by ventricular fibrillation (VF), which coincided with a fever. Comprehensive diagnostics including echo, CMR, exercise testing, and genetic sequencing, did not identify any potential cause. This led to the diagnosis of idiopathic VF and installment of an implantable cardioverter defibrillator, which six months later appropriately intervened another VF episode under conditions comparable to the first event.
View Article and Find Full Text PDFBackground: founder variants cause hypertrophic cardiomyopathy leading to heart failure and malignant ventricular arrhythmias. Exercise is typically regarded as a risk factor for disease expression although evidence is conflicting. Stratifying by type of exercise may discriminate low- from high-risk activities in these patients.
View Article and Find Full Text PDFPurpose Of Review: This review aims to explore the emerging potential of artificial intelligence (AI) in refining risk prediction, clinical diagnosis, and treatment stratification for cardiomyopathies, with a specific emphasis on arrhythmogenic cardiomyopathy (ACM).
Recent Findings: Recent developments highlight the capacity of AI to construct sophisticated models that accurately distinguish affected from non-affected cardiomyopathy patients. These AI-driven approaches not only offer precision in risk prediction and diagnostics but also enable early identification of individuals at high risk of developing cardiomyopathy, even before symptoms occur.
J Cardiovasc Electrophysiol
December 2024
Arrhythmogenic cardiomyopathy (ACM) is a genetically heterogeneous inherited cardiomyopathy with an estimated prevalence of 1:5000-10 000 that predisposes patients to life-threatening ventricular arrhythmias (VA) and sudden cardiac death (SCD). ACM diagnostic criteria and risk prediction models, particularly for arrhythmogenic right ventricular cardiomyopathy (ARVC), the most common form of ACM, are typically genotype-agnostic, but numerous studies have established clinically meaningful genotype-phenotype associations. Early signs of ACM onset differ by genotype indicating the need for genotype-specific diagnostic criteria and family screening paradigms.
View Article and Find Full Text PDFJ Am Heart Assoc
August 2024
J Cardiovasc Magn Reson
January 2025
Background: While late gadolinium enhancement (LGE) is proposed as a diagnostic criterion for arrhythmogenic right ventricular cardiomyopathy (ARVC), the potential of LGE to distinguish ARVC from differentials remains unknown. We aimed to assess the diagnostic value of LGE for ARVC diagnosis.
Methods: We included 132 subjects (60% male, 47 ± 11 years) who had undergone cardiac magnetic resonance imaging with LGE assessment for ARVC or ARVC differentials.
Background: Phospholamban (PLN) p.(Arg14del) variant carriers are at risk for development of malignant ventricular arrhythmia (MVA). Accurate risk stratification allows timely implantation of intracardiac defibrillators and is currently performed with a multimodality prediction model.
View Article and Find Full Text PDFBackground And Aims: Implantable cardioverter-defibrillators (ICDs) are critical for preventing sudden cardiac death (SCD) in arrhythmogenic right ventricular cardiomyopathy (ARVC). This study aims to identify cross-continental differences in utilization of primary prevention ICDs and survival free from sustained ventricular arrhythmia (VA) in ARVC.
Methods: This was a retrospective analysis of ARVC patients without prior VA enrolled in clinical registries from 11 countries throughout Europe and North America.
Background: The arrhythmogenic cardiomyopathy (ACM) phenotype, with life-threatening ventricular arrhythmias and heart failure, varies according to genetic aetiology. We aimed to characterise the phenotype associated with the variant c.1211dup (p.
View Article and Find Full Text PDFAims: A risk calculator for individualized prediction of first-time sustained ventricular arrhythmia (VA) in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients has recently been developed and validated (www.ARVCrisk.com).
View Article and Find Full Text PDFBackground: Clinical guidelines recommend regular screening for arrhythmogenic right ventricular cardiomyopathy (ARVC) to monitor at-risk relatives, resulting in a significant burden on clinical resources. Prioritizing relatives on their probability of developing definite ARVC may provide more efficient patient care.
Objectives: The aim of this study was to determine the predictors and probability of ARVC development over time among at-risk relatives.
Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease.
View Article and Find Full Text PDFArrhythmogenic cardiomyopathy (ACM) is a progressive inheritable disease which is characterized by a gradual fibro-(fatty) replacement of the myocardium. Visualization of diffuse and patchy fibrosis patterns is challenging using clinically applied cardiac imaging modalities (e.g.
View Article and Find Full Text PDF