Medscape April 25, 2024
LONDON — A machine learning model designed to predict inpatient hypoglycemic events using only capillary blood glucose (CBG) showed excellent performance, according to results of an artificial intelligence study.
In a separate analysis, researchers used the model to assess the relative importance of different glycemic features in predicting inpatient hypoglycemia, concluding that extreme and variable CBG measurements had the greatest prognostic value.
Chris Sainsbury, MD, consultant in diabetes and endocrinology at Gartnavel General Hospital in Glasgow, Scotland, presented the results at this year’s Diabetes UK Professional Conference (DUKPC) 2024, alongside his hospital colleagues Greg Jones, MD, diabetes consultant, and Deborah Morrison, MD, a general practitioner with diabetes specialist training.
Today's Sponsors
Today's Sponsor