This study aims to classify adult-onset diabetes patients into distinct data-driven clusters, such as severe insulin-deficient, severe insulin-resistant, mild obesity-related, and mild age-related diabetes, based on clinical and biochemical characteristics. Using a cross-sectional design, data will be collected from individuals attending outpatient diabetes clinics at tertiary care hospitals in Pakistan. The study will analyze the distribution of metabolic and demographic characteristics within each cluster and assess subgroup-specific risks for diabetic complications. Additionally, the relationship between clustering variables and the risk of complications will be evaluated to enhance the understanding of diabetes heterogeneity and its impact on patient outcomes.
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Classify patients into data-driven clusters (e.g., severe insulin-deficient, severe insulin-resistant, mild obesity-related and mild age-related diabetes).
Timeframe: At the time of clinic visit during enrollment