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The purpose of this study was to determine whether the accuracy of CGMs also improves if multiple calibrations are performed in vitro.
The aim was to compare maternal and neonatal outcomes of Australian and foreign women with and without gestational diabetes mellitus.
The objective of this study was to examine rates of severe hypoglycemia (SH) in a large population-based cohort of children with type 1 diabetes and...
In light of the obesity epidemic, we aimed to characterize novel childhood adiposity trajectories from birth to age 14 years and to determine their relation...
Automated insulin delivery (AID) improves glycemia in people with type 1 diabetes (T1D). However, concern remains about early worsening of diabetic retinopathy (EWDR) following rapid and large glycemic improvements. This study evaluated diabetic retinopathy (DR) outcomes in adolescents and young adults with T1D (aged 10-30 years) following AID initiation.
Type 1 Diabetes (T1D) is a 'family illness'; diagnoses and management can be perceived as invasive or traumatic. Caregivers bear the brunt of the diagnostic shock, influencing their child's experience. Children and adolescents may grapple with the psychological effects of past/ongoing medical trauma. Additionally, adolescents may struggle with their mental health as they navigate tensions between caregiver involvement and their developmental need for autonomy.
Despite the various traumatic events that a young person living with type 1 diabetes (T1D) may experience, little is known about the burden and manifestation of traumatic stress in this population. Though mental health outcomes have been explored generally, medical trauma-sensitive approaches to understanding these experiences remain limited. We utilised a qualitative descriptive approach to explore the impact of T1D on young people’s mental health through the paediatric medical traumatic stress model.
Peroxisome proliferator-activated receptor γ (PPARγ) is a prominent ligand-inducible transcription factor involved in adipocyte differentiation, glucose homeostasis, insulin sensitivity, inflammation, and cell proliferation, making it a therapeutic target for diabetes, metabolic syndrome, autoimmune diseases, and cancer.
Understanding the distribution and variation in NMR-based inflammatory markers is crucial to the evaluation of their clinical utility in disease prognosis and diagnosis. We applied high-resolution 1H NMR spectroscopy of blood plasma and serum to measure the acute phase reactive glycoprotein signals and the subregions of the lipoprotein-based Supramolecular Phospholipid Composite signals in a large multicohort population study.
To map and systematise existing research on the use of artificial intelligence (AI) in mental health-based diabetes care contexts, identify trends and potential gaps in the literature, examine methodological limitations and highlight future research directions.