Abstract 163: Identification and Characterization of Distinct Clusters of Patients with Type 2 Diabetes Mellitus in Tertiary Care Hospital In North India

Introduction: Type 2 diabetes is a heterogeneous disease and its categorization into different clusters has revealed distinct subgroups from all over the world including India but no such study has been done till date in north India. Aims and Objectives: To identify clusters intype 2 diabetes mellitus by k means clustering and to describe different characteristics of patients in each of the identified clusters. Methods: Optimal number of clusters i.e., the K value was decided by two step clustering and the subtypes of the clusters were obtained by K means clustering using SPSS version 29 software. Variables which were used for clustering were age atdiagnosis, BMI, HbA1c, HOMA islet and HOMA insulin resistance (based on fasting C-peptide levels) along with waist circumference which has important role in type 2 diabetes mellitus physiology in south east Asians. Results: Total number of participants were 520, out of which 47.7% were males and females were 52.3%. The optimal number of clusters i.e., K = 4 was determined based on silhouette width. Using this K value K means clustering was done which resulted in formation of clusters differing in phenotypic characters. Cluster 1 severe insulin deficient diabetes (SIDD), Cluster 2 Mild age-related diabetes (MARD), Cluster 3 severe insulin resistant diabetes (SIRD), Cluster 4 mild obesity related diabetes (MOD). Phenotypically these clusters were same as defined by Ahlqvist et al in Scandinavian population. When compared with these Swedish clusters, MOD cluster was most common in our study population (37.1% vs 21.6%). SIDD cluster was more common than in Swedish study (21.3% vs 17.5%). In Swedish study MARD cluster was most common (39.1%) where as in our study it constituted 24.2% of patients. Conclusion: This study suggests that clusters in type 2 diabetes can be replicated in different ethnicities and highlights importance of including waist circumference in clustering in Asian Indians. Further studies are needed to look at differences in treatment response when treatment targeting the basic pathophysiological mechanism in different clusters is given to the respective clusters.