Clinical characterization of data-driven diabetes clusters of pediatric type 2 diabetes

Pediatric type 2 diabetes (T2D) is highly heterogeneous, similar to adult-onset diabetes. We performed data-driven cluster analysis to identify five distinct clusters of pediatric T2D based on commonly available clinical and biochemical data at the time of diagnosis. Thes clusters exhibit unique characteristics and associations with risk factors, conditions, and treatment regimens. Our findings suggest the potential need for personalized early treatment strategies. Furthermore, we observed intriguing insights into the use of metformin for pediatric patients in specific clusters, raising questions about its suitability as a first-line treatment.