A randomized controlled trial of transition from insulin pump to multiple daily injections using insulin degludec

Disparities in Diabetes Technology Uptake in Youth and Young Adults With Type 1 Diabetes: A Global Perspective

Globally, nearly 9 million people are living with type 1 diabetes (T1D). Although the incidence of T1D is not affected by socioeconomic status, the development of complications and limited access to modern therapy is overrepresented in vulnerable populations. Diabetes technology, specifically continuous glucose monitoring and automated insulin delivery systems, are considered the gold standard for management of T1D, yet access to these technologies varies widely across countries and regions, and varies widely even within high-income countries. This review focuses on disparities in diabetes technology use among adolescents and young adults with T1D, barriers to access and use, and summarizes common themes emerging across countries and regions. We conducted a survey among medical technology manufacturers and physicians in various countries across diverse geographical regions and performed extensive literature searches. Across all countries and regions, economic barriers stand out as the largest and most common barriers, either preventing market penetrance of technology into a country or limiting its access to the individual with diabetes due to high out of pocket costs. Other common barriers include structural or accessibility barriers, such as stringent eligibility requirements by insurance providers, regardless of whether the insurance was private or government-based, and provider/individual level barriers. Based on the evidence presented, we suggest the need for a joint effort involving governments, private health insurers, technology manufacturers, and healthcare providers to address the global disparities of diabetic technology utilization and ensure equitable access for all individuals living with T1D worldwide.

Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis

Aim

Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA.

Methods

Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used.

Results

Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID.

Conclusion

Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.

Correlation in Dose-Response to Rapid- and Long-Acting Insulin for People with Type 1 Diabetes

In diabetes, it can become necessary to switch between pump- and pen-based insulin treatment. This switch involves a translation between rapid- and long-acting insulin analogues. In standard-of-care translation algorithms, a unit-to-unit conversion is applied. However, this simplification may not fit all individuals. In this paper, we investigate the correlation between dose-response to rapid- and long-acting insulin in the same individual, and compare the correlation across individuals. As a measure of dose-response, we estimate the insulin sensitivity in clinical data from 25 subjects with type 1 diabetes. For parameter estimation, we use maximum likelihood with a continuous-discrete extended Kalman filter and Bergman's minimal model. The results show a weak correlation between insulin sensitivity to rapid- and long-acting insulin across individuals. On this sparse data set, the analysis suggests that the standardized unit-to-unit translation between insulin analogues may not benefit all subjects.