Clustered Phenotypes of Hypertensive Heart Disease With Strain Measurements Reveals Distinct Characteristics, Clinical Course, and Prognosis

Background: Hypertensive heart disease (HHD) encompasses diverse clinical profiles, comorbidities, and cardiac remodeling, but current classifications insufficiently capture this heterogeneity or guide risk stratification. Methods: We studied 1,607 patients with hypertension from the STRATS-HHD registry who underwent echocardiography at baseline and after 6-18 months of antihypertensive therapy. Twenty clinical, laboratory, and echocardiographic variables-including left atrial reservoir strain (LASr) and left ventricular global longitudinal strain (LV-GLS)-underwent principal component analysis and K-means clustering (K=4). Clusters were derived in a derivation cohort (n=1,204) and validated in an independent cohort (n=403). Longitudinal remodeling was assessed with baseline-adjusted models, and outcomes (CV death, heart failure hospitalization [HHF], coronary events, stroke, composite CV death/HHF, and major adverse cardiovascular events [MACE]) with multivariable Cox regression. Results: Four clusters emerged: (1) AF-predominant, with advanced remodeling and highest event risk; (2) elderly, with metabolic-renal comorbidities but preserved function; (3) middle-aged, with prevalent coronary disease and relatively preserved function; and (4) younger, with severe hypertension, marked strain impairment, and greatest remodeling regression with therapy. Prognosis varied across clusters: cluster 1 had the highest risk of CV death, HHF, stroke, and MACE; cluster 3 had elevated coronary risk; and cluster 4 showed the most favorable outcomes. Medication-remodeling associations differed, with renin-angiotensin system blockade linked to LV mass regression in cluster 4. Conclusions: Machine learning-based clustering incorporating LA and LV strain identified four distinct HHD phenotypes with divergent remodeling, therapeutic responses, and outcomes. Data-driven phenotyping may improve risk stratification and guide tailored management in hypertension.