Clinical Characterization of Data-Driven Diabetes Clusters of Pediatric Type 2 Diabetes.

ABSTRACT:

Background

Pediatric Type 2 diabetes (T2D) is highly heterogeneous. Previous reports on adult-onset diabetes demonstrated the existence of diabetes clusters. Therefore, we set out to identify unique diabetes subgroups with distinct characteristics among youth with T2D using commonly available demographic, clinical, and biochemical data.

Methods

We performed data-driven cluster analysis (K-prototypes clustering) to characterize diabetes subtypes in pediatrics using a dataset with 722 children and adolescents with autoantibody-negative T2D. The six variables included in our analysis were sex, race/ethnicity, age, BMI Z-score and hemoglobin A1c at the time of diagnosis, and non-HDL cholesterol within first year of diagnosis.

Results

We identified five distinct clu

SUBMITTER: Abbasi M 

PROVIDER: S-EPMC11062019 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature