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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. 

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

Experiences and Attitudes of Parents Reducing Carbohydrate Intake in the Management of Their Child’s Type 1 Diabetes: A Qualitative Study

Reducing carbohydrate (CHO) intake is being used as an approach to manage type 1 diabetes (T1D) in children. This study aimed to investigate the experiences and attitudes of parents of children with T1D who are reducing CHO intake to help manage blood glucose levels.

Physical activity management for youth with type 1 diabetes: Supporting active and inactive children

Regular physical activity and exercise are important for youth and essential components of a healthy lifestyle. For youth with type 1 diabetes, regular physical activity can promote cardiovascular fitness, bone health, insulin sensitivity, and glucose management. However, the number of youth with type 1 diabetes who regularly meet minimum physical activity guidelines is low, and many encounter barriers to regular physical activity.

CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review

The National Institute for Clinical Excellence updated guidance for continuous glucose monitoring (CGM) in 2022, recommending that CGM be available to all people living with type 1 diabetes. Manufacturers can trade in the UK with Conformité Européenne (CE) marking without an initial national assessment. The regulatory process for CGM CE marking, in contrast to the Food and Drug Administration (FDA) and Australian Therapeutic Goods Administration (TGA) process, is described.

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes

Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates.

Web-Based Self-Compassion Training to Improve the Well-Being of Youth With Chronic Medical Conditions: Randomized Controlled Trial

Up to one-third of young people live with chronic physical conditions (eg, diabetes, asthma, and autoimmune disease) that frequently involve recurrent pain, fatigue, activity limitations, stigma, and isolation.

Experiences of Caregivers and At-Risk Children Enrolled in a Prospective Pregnancy-Birth Cohort Study into the Causes of Type 1 Diabetes: The ENDIA Study

We sought research experiences of caregivers and their children were enrolled in the Environmental Determinants of Islet Autoimmunity (ENDIA) study.

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 %.