Continuous glucose monitoring has an increasing role in pre-symptomatic type 1 diabetes: advantages, limitations, and comparisons with laboratory-based testing.

Type 1 diabetes (T1D) is well-recognised as a continuum heralded by the development of islet autoantibodies, progression to islet autoimmunity causing beta cell destruction, culminating in insulin deficiency and clinical disease. Abnormalities of glucose homeostasis are known to exist well before the onset of typical symptoms. Laboratory-based tests such as the oral glucose tolerance test (OGTT) and glycated haemoglobin (HbA1c) have been used to stage T1D and assess the risk of progression to clinical T1D. Continuous glucose monitoring (CGM) can detect early glycaemic abnormalities and can therefore be used to monitor for metabolic deterioration in pre-symptomatic, islet autoantibody positive, at-risk individuals. Early identification of these children can not only reduce the risk of presentation with diabetic ketoacidosis (DKA), but also determine eligibility for prevention trials, which aim to prevent or delay progression to clinical T1D. Here, we describe the current state with regard to the use of the OGTT, HbA1c, fructosamine and glycated albumin in pre-symptomatic T1D. Using illustrative cases, we present our clinical experience with the use of CGM, and advocate for an increased role of this diabetes technology, for monitoring metabolic deterioration and disease progression in children with pre-symptomatic T1D.

Improved Glycemic Outcomes With Diabetes Technology Use Independent of Socioeconomic Status in Youth With Type 1 Diabetes.

OBJECTIVE: Technology use in type 1 diabetes (T1D) is impacted by socioeconomic status (SES). This analysis explored relationships between SES, glycemic outcomes, and technology use. RESEARCH DESIGN AND METHODS: A cross-sectional analysis of HbA1c data from 2,822 Australian youth with T1D was undertaken. Residential postcodes were used to assign SES based on the Index of Relative Socio-Economic Disadvantage (IRSD). Linear regression models were used to evaluate associations among IRSD quintile, HbA1c, and management regimen. RESULTS: Insulin pump therapy, continuous glucose monitoring, and their concurrent use were associated with lower mean HbA1c across all IRSD quintiles (P < 0.001). There was no interaction between technology use and IRSD quintile on HbA1c (P = 0.624), reflecting a similar association of lower HbA1c with technology use across all IRSD quintiles. CONCLUSIONS: Technology use was associated with lower HbA1c across all socioeconomic backgrounds. Socioeconomic disadvantage does not preclude glycemic benefits of diabetes technologies, highlighting the need to remove barriers to technology access.

Socioeconomic status and diabetes technology use in youth with type 1 diabetes: a comparison of two funding models.

Background: Technology use, including continuous glucose monitoring (CGM) and insulin pump therapy, is associated with improved outcomes in youth with type 1 diabetes (T1D). In 2017 CGM was universally funded for youth with T1D in Australia. In contrast, pump access is primarily accessed through private health insurance, self-funding or philanthropy. The study aim was to investigate the use of diabetes technology across different socioeconomic groups in Australian youth with T1D, in the setting of two contrasting funding models. Methods: A cross-sectional evaluation of 4957 youth with T1D aged <18 years in the national registry was performed to determine technology use. The Index of Relative Socio-Economic Disadvantage (IRSD) derived from Australian census data is an area-based measure of socioeconomic status (SES). Lower quintiles represent greater disadvantage. IRSD based on most recent postcode of residence was used as a marker of SES. A multivariable generalised linear model adjusting for age, diabetes duration, sex, remoteness classification, and location within Australia was used to determine the association between SES and device use. Results: CGM use was lower in IRSD quintile 1 in comparison to quintiles 2 to 5 (p<0.001) where uptake across the quintiles was similar. A higher percentage of pump use was observed in the least disadvantaged IRSD quintiles. Compared to the most disadvantaged quintile 1, pump use progressively increased by 16% (95% CI: 4% to 31%) in quintile 2, 19% (6% to 33%) in quintile 3, 35% (21% to 50%) in quintile 4 and 51% (36% to 67%) in the least disadvantaged quintile 5. Conclusion: In this large national dataset, use of diabetes technologies was found to differ across socioeconomic groups. For nationally subsidised CGM, use was similar across socioeconomic groups with the exception of the most disadvantaged quintile, an important finding requiring further investigation into barriers to CGM use within a nationally subsidised model. User pays funding models for pump therapy result in lower use with socioeconomic disadvantage, highlighting inequities in this funding approach. For the full benefits of diabetes technology to be realised, equitable access to pump therapy needs to be a health policy priority.