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Understanding parents' perspectives of repeated blinded continuous glucose monitoring in children with early-stage type 1 diabetes and an affected first-degree relative

To explore the lived experiences of parents of children at risk of type 1 diabetes undergoing repeated blinded continuous glucose monitoring. Since 2021, children with persistent islet autoimmunity in the Environmental Determinants of Islet Autoimmunity study have been invited to participate in a sub-study involving blinded Dexcom G6 CGM.

Co-designing a new clinical pathway to support families with children identified as having early-stage type 1 diabetes in Western Australia

Children with early-stage (pre-symptomatic) type 1 diabetes are currently identified primarily via research-based screening programmes in Australia. Once identified, families live with the knowledge that their child has an increased chance of developing symptomatic, lifelong, insulin-requiring type 1 diabetes but have no specific clinical pathway available to them in Western Australia for accessing tailored support or education. This project aimed to co-design a new clinical pathway to address this unmet need.

Body mass index, prebiotic supplementation during pregnancy and gestational diabetes mellitus risk: an effect modification analysis from a randomised controlled trial

Prebiotic dietary supplementation has been shown to improve glucose homeostasis in type 2 diabetes patients. The aim of this analysis was to determine whether pre-pregnancy body mass index (BMI) modifies the effect of prebiotic supplementation from mid-pregnancy on reducing the risk of gestational diabetes mellitus

Distinct Enterovirus Antigen Landscape in Children With Islet Autoimmunity

Enteroviruses (EVs) have long been implicated in the development of islet autoimmunity (IA) and type 1 diabetes. However, given the ubiquity of EV infections in children, disease susceptibility is likely driven by host-specific immune responses rather than viral exposure alone.

Psychosocial aspects of early detection in type 1 diabetes: Language matters, decision making and support needs

The potential implementation of early type 1 diabetes (T1D) detection pathways, encompassing autoantibody screening and longitudinal monitoring, raises important psychosocial considerations for ethical, person-centred care. This review summarises evidence on the psychosocial impact of early T1D detection, identifying key evidence gaps and recommendations for integrating psychosocial support. 

Medication Use in Type 1 Diabetes and the Association with Socioeconomic Disadvantage: Analysis of a National Linked Dataset

To explore trends in the receipt of commonly prescribed medications (beyond insulin) in people with type 1 diabetes in Australia, including polypharmacy, and to investigate socioeconomic disparities across these trends.

A microRNA-based dynamic risk score for type 1 diabetes

Identifying individuals at high risk of type 1 diabetes (T1D) is crucial as disease-delaying medications are available. Here we report a microRNA (miRNA)-based dynamic (responsive to the environment) risk score developed using multicenter, multiethnic and multicountry ('multicontext') cohorts for T1D risk stratification. Discovery (wet and dry lab) analysis identified 50 miRNAs associated with functional β cell loss, which is a hallmark of T1D. 

Differences in Achieving Stringent Glycemic Targets Among Youth with Type 1 Diabetes: A SWEET Registry Study

This study aimed to investigate the associations between glycemic outcomes and a range of clinical and demographic factors, including treatment modality, sex, age, diabetes duration, and body mass index, in youth with type 1 diabetes in an international registry.

Glycemic and Psychosocial Outcomes of Advanced Hybrid Closed-Loop Therapy in Youth With High HbA1c: A Randomized Clinical Trial

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.

Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes — A large multi-centre study in Australia and New Zealand

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 %.