Computer methods and programs in biomedicine · 2025
Cluster-Based Insights into Cardiovascular and Autonomic Responses to Head-Up Tilt in Hypertension.
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Ooi Jia Hui, Goh Choon-Hian, Argha Ahmadreza, Tan Maw Pin, Beh Hooi Chin, Sari Nor Ashikin Md, Lovell Nigel H, Lim Einly
Аннотация
BACKGROUND: Cardiovascular dysfunction including vascular and cardiac remodeling, and autonomic dysfunction, can emerge before the clinical diagnosis for hypertension, often involving subtle impairments in autonomic regulation and hemodynamic adaptation. This study applied a data-driven clustering approach to uncover latent cardiovascular response phenotypes from autonomic and hemodynamic adaptations during a 70° head-up tilt (HUT) test in hypertensive and normotensive participants. This study aimed to reveal hidden autonomic-structural mechanisms and to provide new physiological insight into early cardiovascular regulation.
METHODS: Continuous hemodynamic measurements during a 10-min HUT test and baseline echocardiographic assessment were performed. After excluding poor-quality data, 40 hypertensive and 32 normotensive participants were analyzed using K-means, Fuzzy C-means and Hierarchical clustering, with dimensionality reduction via principal component analysis, uniform manifold approximation and projection (UMAP). The UMAP + K-means model showed the best clustering performance and was selected for further analysis.
RESULTS: Three distinct compensatory mechanisms were identified. Cluster 1 exhibited sympathetic-mediated vasoconstriction resembling the normotensive profile. Cluster 2 showed an enhanced chronotropic response with impaired vasoconstriction, the lowest complexity index, and signs of cardiac remodeling. Cluster 3 demonstrated attenuated reflex-mediated adjustments but preserved complexity, accompanied by more advanced cardiac-vascular remodeling. Clusters 2 and 3, predominantly hypertensive participants, reflected differing combinations of autonomic and structural adaptation.
CONCLUSIONS: This physiology-driven approach uncovered hidden cardiovascular phenotypes beyond conventional diagnostic categories. These findings highlight the potential of functional profiling for advancing early understanding of altered cardiovascular regulation and guiding future studies toward targeted strategies for cardiovascular risk reduction and hypertension management.
METHODS: Continuous hemodynamic measurements during a 10-min HUT test and baseline echocardiographic assessment were performed. After excluding poor-quality data, 40 hypertensive and 32 normotensive participants were analyzed using K-means, Fuzzy C-means and Hierarchical clustering, with dimensionality reduction via principal component analysis, uniform manifold approximation and projection (UMAP). The UMAP + K-means model showed the best clustering performance and was selected for further analysis.
RESULTS: Three distinct compensatory mechanisms were identified. Cluster 1 exhibited sympathetic-mediated vasoconstriction resembling the normotensive profile. Cluster 2 showed an enhanced chronotropic response with impaired vasoconstriction, the lowest complexity index, and signs of cardiac remodeling. Cluster 3 demonstrated attenuated reflex-mediated adjustments but preserved complexity, accompanied by more advanced cardiac-vascular remodeling. Clusters 2 and 3, predominantly hypertensive participants, reflected differing combinations of autonomic and structural adaptation.
CONCLUSIONS: This physiology-driven approach uncovered hidden cardiovascular phenotypes beyond conventional diagnostic categories. These findings highlight the potential of functional profiling for advancing early understanding of altered cardiovascular regulation and guiding future studies toward targeted strategies for cardiovascular risk reduction and hypertension management.