Data-driven phenomapping for novel classification for cardiovascular outcomes compared with traditional obesity index: Tehran Lipid and Glucose Study.

ABSTRACT:

Objective

This study aimed to propose a data-driven framework for classification of at-risk people for cardiovascular outcomes regarding obesity and metabolic syndrome.

Design

A population-based prospective cohort study with a long-term follow-up.

Setting

Data from the Tehran Lipid and Glucose Study (TLGS) were interrogated.

Participants

12 808 participants of the TLGS cohort, aged ≥20 years who have followed for over 15 years were assessed.

Main outcome measures

Data for 12 808 participants, aged ≥20 years who have followed for over 15 years, collected through TLGS as a prospective, population-based cohort study, were analysed. Feature engineering followed by hierarchical clustering was used to determine meaningful clusters and novel endophenotypes. Cox

SUBMITTER: Zare Borzeshi E 

PROVIDER: S-EPMC10277045 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature