Utilisation, access and recommendations regarding technologies for people living with type 1 diabetes: consensus statement of the ADS/ADEA/APEG/ADIPS Working Group.

INTRODUCTION: Type 1 diabetes presents significant challenges for optimal management. Despite intensive glycaemic control being the standard of care for several decades, glycaemic targets are infrequently achieved and the burden of complications remains high. Therefore, the advancement of diabetes management technologies has a major role in reducing the clinical and economic impact of the disease on people living with type 1 diabetes and on health care systems. However, a national framework is needed to ensure equitable and sustainable implementation of these technologies as part of holistic care. MAIN RECOMMENDATIONS: This consensus statement considers technologies for insulin delivery, glucose sensing and insulin dose advice that are commercially available in Australia. While international position statements have provided recommendations for technology implementation, the ADS/ADEA/APEG/ADIPS Working Group believes that focus needs to shift from strict trial-based glycaemic criteria towards engagement and individualised management goals that consider the broad spectrum of benefits offered by technologies. CHANGES IN MANAGEMENT AS RESULT OF THIS STATEMENT: This Australian consensus statement from peak national bodies for the management of diabetes across the lifespan outlines a national framework for the optimal implementation of technologies for people with type 1 diabetes. The Working Group highlights issues regarding equity of access to technologies and services, scope of clinical practice, credentialling and accreditation requirements, regulatory issues with "do-it-yourself" technology, national benchmarking, safety reporting, and ongoing patient advocacy.

A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus.

INTRODUCTION: Accurate early risk prediction for gestational diabetes mellitus (GDM) would target intervention and prevention in women at the highest risk. We evaluated novel biomarker predictors to develop a first-trimester risk prediction model in a large multiethnic cohort. METHODS: Maternal clinical, aneuploidy and pre-eclampsia screening markers (PAPP-A, free hCGß, mean arterial pressure, uterine artery pulsatility index) were measured prospectively at 11-13+6 weeks' gestation in 980 women (248 with GDM; 732 controls). Nonfasting glucose, lipids, adiponectin, leptin, lipocalin-2, and plasminogen activator inhibitor-2 were measured on banked serum. The relationship between marker multiples-of-the-median and GDM was examined with multivariate regression. Model predictive performance for early (< 24 weeks' gestation) and overall GDM diagnosis was evaluated by receiver operating characteristic curves. RESULTS: Glucose, triglycerides, leptin, and lipocalin-2 were higher, while adiponectin was lower, in GDM (p < 0.05). Lipocalin-2 performed best in Caucasians, and triglycerides in South Asians with GDM. Family history of diabetes, previous GDM, South/East Asian ethnicity, parity, BMI, PAPP-A, triglycerides, and lipocalin-2 were significant independent GDM predictors (all p < 0.01), achieving an area under the curve of 0.91 (95% confidence interval [CI] 0.89-0.94) overall, and 0.93 (95% CI 0.89-0.96) for early GDM, in a combined multivariate prediction model. CONCLUSIONS: A first-trimester risk prediction model, which incorporates novel maternal lipid markers, accurately identifies women at high risk of GDM, including early GDM.