The Arrhythmic Burden of Cardiac Amyloidosis: A Comprehensive Review

Cardiac amyloidosis (CA) represents a growing etiology of heart failure (HF) and arrhythmogenesis, driven by the intramyocardial deposition of aberrantly folded proteins, notably immunoglobulin light chains (AL) and transthyretin (ATTR). This infiltrative process compromises myocardial compliance and disrupts the cardiac conduction system, leading to a diverse spectrum of dysrhythmias. The escalating prevalence of CA, particularly within geriatric demographics and individuals with plasma cell dyscrasias, underscores the imperative for refined diagnostic and therapeutic paradigms. The considerable arrhythmic burden in CA significantly contributes to patient morbidity, thromboembolic events, and sudden cardiac death, thus providing the impetus for this comprehensive review. Despite advancements in cardiac imaging and biomarker analysis, detailed electrophysiological characterization and arrhythmia-specific management strategies in CA remain incompletely elucidated. This review aims to provide a comprehensive overview of current evidence related to the arrhythmic features of CA. In addition, it characterizes the electrophysiological consequences of amyloid infiltration, distinguishes arrhythmic profiles between AL and ATTR subtypes, and evaluates diagnostic methods and treatment options to optimize clinical management decision-making. Atrial fibrillation is a prevalent arrhythmia, particularly in wild-type ATTR amyloidosis. In contrast, AL amyloidosis, characterized by direct myocyte cytotoxicity and accelerated disease progression, frequently manifests with ventricular arrhythmias and conduction disturbances. Ultimately, arrhythmias in CA are multifactorial, necessitating a subtype-specific approach to diagnosis and treatment. Risk stratification, integrating electrocardiographic, imaging, biomarker, and genetic data, is crucial for guiding patient management. Future directions involve personalized treatment frameworks leveraging multiomics integration, remote rhythm monitoring, and artificial intelligence-driven predictive modeling to advance precision electrophysiology in systemic amyloidosis.