Autoantibody Profiling for Accurate Differentiation of Type 1 and Type 2 Diabetes Mellitus in Omani Patients: A Retrospective Study.

ABSTRACT: Background/Objectives: Differentiating Type 1 from Type 2 diabetes mellitus (T1DM vs. T2DM) remains clinically challenging, especially in early-onset cases with overlapping features. This study assessed the diagnostic utility of diabetes-related autoantibodies in an Omani cohort and evaluated their predictive performance using machine learning. Methods: Clinical and laboratory data from 448 patients (aged ≥ 2 years) in Al Batinah North, Oman, were retrospectively analyzed. We assessed autoantibody positivity (anti-GAD, anti-islet, anti-TPO, anti-tissue), age, sex, and HbA1c. Receiver operating characteristic (ROC) curves and a neural network model were used to evaluate diagnostic accuracy. Results: Anti-GAD and anti-islet antibodies were significantly more prevalent in

SUBMITTER: Al-Okla S 

PROVIDER: S-EPMC12468106 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature