Article

Data-driven cardiometabolic phenogroups reveal distinct subclinical cardiac and proteomic profiles

2026-06-24

Abstract excerpt

<h4>Abstracts</h4> <h4>Background</h4> Cardiometabolic disease is heterogeneous and incompletely resolved by conventional classification. We aimed to use expanded variables to identify data-driven phenogroups and characterise their echocardiographic and proteomic features. <h4>Methods</h4> Latent class analysis was applied to a discovery cohort (RESET; n=1,034) using fourteen cardiometabolic variables. A decisi...

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Literature Corpus work: 738c212b-eb88-5215-9c27-f3c52947f4df
DOI: 10.64898/2026.06.15.26355645

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