Abstract 24031: Machine Learning Detection of Obstructive Hypertrophic Cardiomyopathy Using a Wearable Biosensor

Introduction: Hypertrophic cardiomyopathy (HCM) is a heart muscle disease characterized by left ventricular (LV) hypertrophy without a systemic etiology and is associated with heart failure, stroke and sudden death. Disease prevalence is estimated at 1:500, but ~84% remain undiagnosed. Patients with obstructive HCM (oHCM) have dynamic obstruction of the LV outflow tract and characteristic abnormalities in arterial bloodflow patterns. Hypothesis: Arterial pulsewaves recorded with a wearable biosensor and analyzed with machine learning algorithms could identify a signature of oHCM when compared to unaffected controls. Methods: We compared baseline arterial pulse wave morphology, obtained by photoplethysmography using an investigational wristworn biosensor (Wavelet Health, Mtn. View, CA), from oHCM patients enrolled in a digital health substudy of PIONEER HCM (NCT02842242) to unaffected controls from a Wavelet Health database. Five minute recordings were obtained at rest, and data sets were divided into trai...