Aetiological clustering of newly diagnosed type 2 diabetes using machine learning: a retrospective cross-sectional study in Dubai, UAE.

ABSTRACT:

Objectives

Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to validate these clusters in newly diagnosed T2D patients without any complications and determine whether severe and mild phenotypes are detectable early in the disease course.

Design

Retrospective, cross-sectional, non-interventional study.

Setting

Primary healthcare centres in Dubai, UAE.

Participants

A total of 451 adults, including both Emiratis and expatriates, diagnosed with T2D in the last 5 years and without T2D-related complications at the time of visit, were enrolled. Patients with complications, incomplete clin

SUBMITTER: Dsouza SM 

PROVIDER: S-EPMC12658501 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature