Comparison of clustering and phenotyping approaches for subclassification of type 2 diabetes and its association with remission in Indian population.

ABSTRACT: Identification of novel subgroups of type 2 diabetes (T2D) has helped improve its management. Most classification techniques focus on clustering or subphenotyping but not on both. This study aimed to compare both these methods and examine the rate of T2D remission in these subgroups in the Indian population. K-means clustering (using age at onset, HbA1C, BMI, HOMA2 IR and HOMA2%B) and subphenotyping (using homeostatic model assessment (HOMA) estimates) analysis was done on the baseline data of 281 patients with recently diagnosed T2D who participated in a 1-year online diabetes management program. Cluster analysis revealed three distinct clusters: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), and mild obesity-related diabetes (MOD) while subphenotyping

SUBMITTER: Tripathi P 

PROVIDER: S-EPMC11366003 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature