Streamlining Identification of Ketosis-Prone Diabetes in Youth Using PEPPER: Advancing Atypical Diabetes Discovery

Introduction of PEPPER, a novel Python-based EMR search program designed to identify youth with ketosis-prone diabetes (KPD).
PEPPER demonstrated 100% accuracy and significantly reduced chart review time compared to manual methods.
Successfully identified 110 youths with type 2 diabetes and diabetic ketoacidosis (DKA) within six months of diagnosis, 21 of whom met criteria for atypical A-β+ KPD.
This innovative tool promises improved discovery and classification of atypical diabetes phenotypes, potentially enhancing patient care and research efficiency.

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