Left atrial size trajectories and outcome over a 35-year follow-up in patients with hypertrophic cardiomyopathy.

Background: In Hypertrophic cardiomyopathy (HCM) increasing evidence suggests left atrial (LA) remodelling plays a critical role in disease progression. Traditional static LA size measurements, while established as risk markers, do not reflect the dynamic nature of LA changes over time.

Objectives: This study aimed to define long-term LA remodelling trajectories in HCM and assess their prognostic value for predicting atrial fibrillation (AF), sudden cardiac death (SCD), and heart failure (HF) death.

Unveiling the complexity of nonobstructive hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a genetic heart disorder defined by the presence of a maximal wall thickness of at least 15 mm with two main forms: obstructive (oHCM) and nonobstructive (nHCM). While oHCM is characterized by left ventricular (LV) outflow tract obstruction (LVOTO), nHCM lacks this feature and shows significant variability in its hemodynamic and anatomical traits. In nHCM, LV hypertrophy (LVH) presents diverse morphologies, including apical hypertrophy and reverse septal curvature, the latter potentially causing mid-ventricular obstruction and near-complete LV emptying.

Long-term follow-up study on obstructive hypertrophic cardiomyopathy patients treated with disopyramide: evidences of a notable trend in symptom control within a real-world clinical setting.

Background: In obstructive hypertrophic cardiomyopathy (HOCM), disopyramide is used in patients who remain symptomatic despite -blockers or verapamil. However, effectiveness of disopyramide therapy has not been clearly established due to inconsistent definition of responders and the insufficient length of follow-ups reported in literature. To address these shortcomings, we have conducted a retrospective analysis from detailed databases with long follow-up, from two HCM Referral Centers.

Artificial intelligence-driven electrocardiography: Innovations in hypertrophic cardiomyopathy management.

Hypertrophic Cardiomyopathy (HCM) presents a complex diagnostic and prognostic challenge due to its heterogeneous phenotype and clinical course. Artificial Intelligence (AI) and Machine Learning (ML) techniques hold promise in transforming the role of Electrocardiography (ECG) in HCM diagnosis, prognosis, and management. AI, including Deep Learning (DL), enables computers to learn patterns from data, allowing for the development of models capable of analyzing ECG signals.

Echocardiographic Strain Abnormalities Precede Left Ventricular Hypertrophy Development in Hypertrophic Cardiomyopathy Mutation Carriers.

Hypertrophic cardiomyopathy (HCM) is a genetic disease characterized by unexplained left ventricular hypertrophy (LVH), diastolic dysfunction, and increased sudden-death risk. Early detection of the phenotypic expression of the disease in genetic carriers without LVH (Gen+/Phen-) is crucial for emerging therapies. This clinical study aims to identify echocardiographic predictors of phenotypic development in Gen+/Phen-.