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Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes.

A L J CarrD J PerryA L LynamS ChamalaC S FlaxmanS A SharpL A FerratAngus G JonesM L BeeryL M JacobsenC H WasserfallM L Campbell-ThompsonI KusmartsevaA PosgaiD A SchatzM A AtkinsonT M BruskoS J RichardsonB M ShieldsRichard D Oram
Published in: Diabetic medicine : a journal of the British Diabetic Association (2020)
Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19-22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6-8 March 2019.
Keyphrases
  • type diabetes
  • cardiovascular disease
  • glycemic control
  • machine learning
  • deep learning
  • metabolic syndrome
  • kidney transplantation