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Calculating individualized glycaemic targets using an algorithm based on expert worldwide diabetologists: Implications in real-life clinical practice.

Fernando Álvarez-GuisasolaAna M Cebrián-CuencaXavier CosManuel Ruiz-QuinteroJose M MillarueloAvivit CahnItamar RazDomingo Orozco-Beltrannull null
Published in: Diabetes/metabolism research and reviews (2018)
In a real-life clinical setting, applying individualized targets did not change the overall rate of patients with good glycaemic control yet led to reclassification of 7.1% (29 of 408) of the patients. More studies are needed to validate these results in different populations.
Keyphrases
  • clinical practice
  • type diabetes
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • machine learning
  • prognostic factors
  • deep learning
  • peritoneal dialysis
  • case control