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Advanced hybrid closed-loop (AHCL) therapy with the Medtronic MiniMed™ 780G system improves glycemia; however, the clinical outcomes in younger children remain less established. This pilot study aimed to explore the continuous glucose monitoring (CGM) metrics in very young children on AHCL. Children between 2 and 7 years of age and on insulin pump therapy were recruited.
The evidence about the acceptability and effectiveness of innovative paediatric models of care for Type 1 diabetes is limited. To address this gap, we synthesised literature on implemented models of care, model components, outcomes, and determinants of implementation and sustainability.
The Children's Diabetes Centre's research into Type 1 diabetes, childhood onset Type 2 diabetes and obesity aims to improve the lives of children and adolescents affected by these conditions.
One hundred years after the discovery of insulin, technology advancements are being heralded as the dawn of a new era for managing type 1 diabetes (T1D) in young people.
Read about Professor Tim Jones and Associate Professor Liz Davis, co-directors of the Children's Diabetes Centre.
A new Q&A series focusing on the different research themes within the Children’s Diabetes Centre - technology.
Diabetes research got a huge boost when the WA Children’s Diabetes Research and Education Centre for Research Excellence opened late last year.
To determine the efficacy of advanced hybrid closed-loop therapy in a high-risk cohort of youth on continuous subcutaneous insulin infusion with or without continuous glucose monitoring with suboptimal glycemia.
Less than 20% of Australians with type 1 diabetes (T1D) meet recommended glucose targets. Technology use is associated with better glycaemia, with the most advanced being automated insulin delivery (AID) systems, which are now recommended as gold-standard T1D care. Our Australian AID trial shows a wide spectrum of adults with T1D can achieve recommended targets. Other studies, including lived experience data, are supportive. Insulin pumps are not subsidised for most Australian adults with T1D. We advocate change.
Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.