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This study examines whether the short-term use of a continuous glucose monitor can reduce the fear of hypoglycaemia in individuals with type 1 diabetes...
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.
Diabetes is the name for a number of different metabolic disorders in which the body's healthy levels of blood sugar (glucose) can't be maintained.Diabetes can have a significant impact on quality of life should complications develop. Diabetes can affect the individual's entire body.
To investigate the change in prevalence of impaired awareness of hypoglycemia (IAH) and severe hypoglycemia (SH) across three cohorts (2002, 2015, and 2024) in youth with type 1 diabetes.
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.
Individuals living with type 1 diabetes (T1D) are at an increased risk of experiencing psychological distress; however, there remains a scarcity of scalable and widely accessible support services, particularly for adolescents and young adults. To address this gap, digital mental health interventions are becoming an increasingly important area of innovation in diabetes care.
The rates of obesity and type 1 diabetes (T1D) in children and adolescents are increasing in many settings worldwide, but data on weight gain in this group are limited in New Zealand. We examined temporal body mass index (BMI) changes and associated factors in young people with T1D in a mixed urban-rural region.
Digital interventions have emerged as promising tools to support mental well-being in diabetes. This review aimed to evaluate the effectiveness of digital health interventions in improving mental health outcomes among adults with diabetes, as well as assess the methodological quality of relevant studies and provide a commentary on research gaps and future directions.
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.