Mavacamten in hypertrophic obstructive cardiomyopathy: Prospects for AI integration and mitigating healthcare disparities

Abstract

Hypertrophic obstructive cardiomyopathy (HOCM) is an autosomal dominant condition that still remains significantly under-diagnosed worldwide. Early detection through clinical evaluation, imaging, and familial history is crucial to prevent severe complications such as heart failure and sudden cardiac death. While cuddsnt management strategies primarily offer symptomatic relief through pharmacotherapy or invasive procedures, their effectiveness and accessibility are limited, revealing substantial gaps in care. The emergence of Mavacamten, a recently FDA-approved drug, could potentially revolutionize HOCM management as it addresses the underlying pathophysiology by inhibiting cardiac myosin ATPase, showing promise in reducing obstruction and improving cardiac function.

Our review aims to assess mavacamten's efficacy, emphasizing the pivotal role of genetic testing in identifying at-risk individuals and guiding precise diagnoses for personalized treatments. Additionally, we aim to highlight disparities in access to advanced diagnostics and therapies, particularly affecting underserved populations globally and within communities, as well as explore the potential of artificial intelligence (AI) in enhancing early detection and monitoring treatment responses in HOCM. This review thus offers valuable insights to inform future research directions and clinical practices aimed at optimizing outcomes for individuals with HOCM.