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

Highlight

  • 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.

Study Background

Comments

No comments yet. Why don’t you start the discussion?

Leave a Reply