Clinical Utility of the Novel Classification of Type 2 Diabetes (T2D) among Ghanaian Patients Diagnosed with T2D: Evidence from a Multicenter Hospital-based Study in Accra, Ghana

Abstract Aim/Introduction: Classifying diabetes based on unique characteristics and complications aids in personalized care. Furthermore, it predicts better patients who need intensive treatment. This study aimed to test the clinical utility of Ahlqvist et al . technique of the novel classification of type 2 diabetes (T2D) among resident Ghanaian diabetes patients. Clinical characteristics and different treatments in each subgroup were compared. Materials and Methods: This cross-sectional study consecutively recruited 353 patients with T2D, 18 years and older, from diabetes clinics in four hospitals across the Greater Accra Region of Ghana between March and June 2023. The K-means was used to cluster and analyze the data using five parameters: age at diagnosis, body mass index, glycosylated hemoglobin, homeostatic model assessment 2, to estimate beta-cell function (HOMA2-β), and insulin resistance (HOMA2-IR). Blood pressure (BP), waist circumference (WC), and lipid profile were included to enhance the clinical utility after the cluster analysis. Results: Four distinct clusters were replicated with varying characteristics: severe insulin-resistant diabetes (SIRD), mild age-related diabetes (MARD), severe insulin-deficient diabetes (SIDD), and mild obesity-related diabetes. The MARD group was the predominant cluster (37%). Medication usage, total cholesterol, systolic BP, and mean WC were significantly different among the clusters (all P value < 0.001). Comparing the two severe forms of T2D (SIRD and SIDD) in this study, participants were more insulin-deficient than insulin-resistant. Conclusions: Four distinct clusters were identified in the Ghanaian population. The risk of diabetic complications, medication treatment, and patient characteristics varied significantly across each cluster.