Hypertrophic cardiomyopathy (HCM) is a condition characterized by left ventricular hypertrophy, with physiopathological remodeling that predisposes patients to atrial fibrillation (AF). The electrocardiogram is a basic diagnostic tool for evaluating heart electrical activity. Key electrocardiographic features that correlate with AF onset are P-wave duration, P-wave dispersion, and electromechanical delay in left atrium (LA). Clinical markers, including age, body mass index, New York Heart Association functional class, and heart failure symptoms, are also strong predictors of AF in HCM. Risk scores have been created using multiple variables to better predict AF development. Increasing knowledge of genetic subsets in HCM and cardiovascular pathology in general has provided novel insight in this context. Structural and mechanical LA remodeling, including fibrosis, altered LA function, and changes in atrial size, further contribute to AF risk prediction. Cardiovascular magnetic resonance (CMR) and echocardiographic measures provide accurate information about atrial structure and function. Machine learning models are increasingly being utilized to refine risk prediction, incorporating a wide range of variables. This review highlights the multifaceted approach required to understand and predict AF development in HCM. Such an approach is imperative to enhance prognostic accuracy and improve the quality of life of these patients. Further research is necessary to refine patient outcomes and develop customized management strategies for HCM-associated AF.

Hypertrophic cardiomyopathy (HCM) is a cardiac disorder characterized by unexplained left ventricular hypertrophy and a clinical presentation that is heterogeneous, ranging from asymptomatic cases to sudden cardiac death (SCD). The condition’s complex pathophysiology encompasses myocyte disarray, fibrosis, and impaired cellular metabolism. Advancements in non-invasive cardiac imaging, notably echocardiography and cardiac magnetic resonance (CMR), have led to substantial progress in the domains of early diagnosis, phenotypic characterization, and risk stratification. Echocardiography is the preferred diagnostic modality, as it provides a comprehensive evaluation of ventricular hypertrophy patterns, left ventricular outflow tract (LVOT) obstruction, mitral valve abnormalities, left atrial size, and diastolic function. Novel techniques, such as speckle-tracking strain imaging, have emerged as means to detect subclinical myocardial dysfunction and to provide significant prognostic information. Cine-CMR sequences, tissue characterization with late gadolinium enhancement, and quantitative techniques such as strain imaging have been shown to enhance diagnostic precision and prognostic evaluation. The integration of multimodality imaging has been demonstrated to enhance the management of patients with HCM, both in the short term and in the long term, by facilitating individualized monitoring. This review summarizes the role of cardiac imaging in the comprehensive evaluation of HCM, emphasizing the impact of these methods on diagnosis, risk assessment, and personalized patient care, particularly in challenging clinical settings, such as cases of athlete’s heart and pathological ventricular hypertrophy.

Background: Several drugs are emerging as potential therapeutic resources in the context of chronic heart failure (CHF), although their impact on daily clinical practice remains unknown. The objective of this study was to investigate the theoretical eligibility for vericiguat and omecamtiv mecarbil (OM) in a real-world outpatient setting. Methods: A cross-sectional observational study was conducted, enrolling all patients with CHF who had at least one visit between January 2023 and January 2024 in a dedicated outpatient clinic of a tertiary referral center. Theoretical eligibility for vericiguat and OM in our population was assessed by adopting the criteria of the respective phase III clinical trials (VICTORIA trial for vericiguat and GALACTIC-HF trial for OM). Results: In 350 patients with CHF, the rate of individuals eligible was 2% for vericiguat and 4% for OM. A value for left ventricular ejection fraction (LVEF) over the clinical trials’ cutoffs was observed in 41% of cases for vericiguat and 69% for OM. The absence of a recent heart failure (HF) worsening was found in 78% of cases for vericiguat and 72% for OM. Conclusions: Only a small proportion of CHF patients would be eligible for vericiguat and OM in a real-world outpatient setting. The absence of a recent HF worsening and an LVEF over the established trials’ cutoffs are the main causes of non-eligibility. Further studies are required to assess the efficacy of these drugs in a wider population in order to increase the candidates for these beneficial treatments.