Unknown

Dataset Information

Etiologies underlying subtypes of long-standing type 2 diabetes.


ABSTRACT:

Background

Attempts to subtype, type 2 diabetes (T2D) have mostly focused on newly diagnosed European patients. In this study, our aim was to subtype T2D in a non-white Emirati ethnic population with long-standing disease, using unsupervised soft clustering, based on etiological determinants.

Methods

The Auto Cluster model in the IBM SPSS Modeler was used to cluster data from 348 Emirati patients with long-standing T2D. Five predictor variables (fasting blood glucose (FBG), fasting serum insulin (FSI), body mass index (BMI), hemoglobin A1c (HbA1c) and age at diagnosis) were used to determine the appropriate number of clusters and their clinical characteristics. Multinomial logistic regression was used to validate clustering results.

Results

Five clusters were identifi

SUBMITTER: Bayoumi R 

PROVIDER: S-EPMC11132508 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature