The Expanding Use of Continuous Glucose Monitoring in Type 2 Diabetes

A probabilistic computation framework to estimate the dawn phenomenon in type 2 diabetes using continuous glucose monitoring

In type 2 diabetes (T2D), the dawn phenomenon is an overnight glucose rise recognized to contribute to overall glycemia and is a potential target for therapeutic intervention. Existing CGM-based approaches do not account for sensor error, which can mask the true extent of the dawn phenomenon. To address this challenge, we developed a probabilistic framework that incorporates sensor error to assign a probability to the occurrence of dawn phenomenon. In contrast, the current approaches label glucose fluctuations as dawn phenomena as a binary yes/no. We compared the proposed probabilistic model with a standard binary model on CGM data from 173 participants (71% female, 87% Hispanic/Latino, 54 ± 12 years, with either a diagnosis of T2D for six months or with an elevated risk of T2D) stratified by HbA1c levels into normal but at risk for T2D, with pre-T2D, or with non-insulin-treated T2D. The probabilistic model revealed a higher dawn phenomenon frequency in T2D [49% (95% CI 37-63%)] compared to pre-T2D [36% (95% CI 31-48%), p = 0.01] and at-risk participants [34% (95% CI 27-39%), p < 0.0001]. While these trends were also found using the binary approach, the probabilistic model identified significantly greater dawn phenomenon frequency than the traditional binary model across all three HbA1c sub-groups (p < 0.0001), indicating its potential to detect the dawn phenomenon earlier across diabetes risk categories.

Roadmap to Achieving Continuous Glucose Monitoring Equity: Insights From the T1D Exchange Quality Improvement Collaborative

This article describes successful interventions from the T1D Exchange Quality Improvement Collaborative (T1DX-QI) to reduce inequities in access to and use of continuous glucose monitoring (CGM). The author proposes a roadmap with recommendations for different stakeholders to achieve CGM equity using insights from the T1DX-QI experience.

Mobile Health Intervention in Patients With Type 2 Diabetes: A Randomized Clinical Trial

Importance

Clinical pharmacists and health coaches using mobile health (mHealth) tools, such as telehealth and text messaging, may improve blood glucose levels in African American and Latinx populations with type 2 diabetes.

Objective

To determine whether clinical pharmacists and health coaches using mHealth tools can improve hemoglobin A1c (HbA1c) levels.

Design, Setting, and Participants

This randomized clinical trial included 221 African American or Latinx patients with type 2 diabetes and elevated HbA1c (≥8%) from an academic medical center in Chicago. Adult patients aged 21 to 75 years were enrolled and randomized from March 23, 2017, through January 8, 2020. Patients randomized to the intervention group received mHealth diabetes support for 1 year followed by monitored usual diabetes care during a second year (follow-up duration, 24 months). Those randomized to the waiting list control group received usual diabetes care for 1 year followed by the mHealth diabetes intervention during a second year.

Interventions

The mHealth diabetes intervention included remote support (eg, review of glucose levels and medication intensification) from clinical pharmacists via a video telehealth platform. Health coach activities (eg, addressing barriers to medication use and assisting pharmacists in medication reconciliation and telehealth) occurred in person at participant homes and via phone calls and text messaging. Usual diabetes care comprised routine health care from patients' primary care physicians, including medication reconciliation and adjustment.

Main Outcomes and Measures

Outcomes included HbA1c (primary outcome), blood pressure, cholesterol, body mass index, health-related quality of life, diabetes distress, diabetes self-efficacy, depressive symptoms, social support, medication-taking behavior, and diabetes self-care measured every 6 months.

Results

Among the 221 participants (mean [SD] age, 55.2 [9.5] years; 154 women [69.7%], 148 African American adults [67.0%], and 73 Latinx adults [33.0%]), the baseline mean (SD) HbA1c level was 9.23% (1.53%). Over the initial 12 months, HbA1c improved by a mean of -0.79 percentage points in the intervention group compared with -0.24 percentage points in the waiting list control group (treatment effect, -0.62; 95% CI, -1.04 to -0.19; P = .005). Over the subsequent 12 months, a significant change in HbA1c was observed in the waiting list control group after they received the same intervention (mean change, -0.57 percentage points; P = .002), while the intervention group maintained benefit (mean change, 0.17 percentage points; P = .35). No between-group differences were found in adjusted models for secondary outcomes.

Conclusions and Relevance

In this randomized clinical trial, HbA1c levels improved among African American and Latinx adults with type 2 diabetes. These findings suggest that a clinical pharmacist and health coach-delivered mobile health intervention can improve blood glucose levels in African American and Latinx populations and may help reduce racial and ethnic disparities.

Trial Registration

ClinicalTrials.gov Identifier: NCT02990299.

The Evolution of Diabetes Technology - Options Towards Personalized Care

Advances in diabetes technology, especially in the last few decades, have transformed our ability to deliver care to persons with diabetes (PWD). Developments in glucose monitoring, especially continuous glucose monitoring systems (CGM), have revolutionized diabetes care and empowered our patients to manage their disease. CGM has also played an integral role in advancing automated insulin delivery systems. Currently available and upcoming advanced hybrid-closed loop systems aim to decrease patient involvement and are approaching the functionality of a fully automated artificial pancreas. Other advances, such as smart insulin pens and daily patch pumps, offer more options for patients and require less complicated and costly technology. Evidence to support the role of diabetes technology is growing, and PWD and clinicians must choose the right type of technology with a personalized strategy to manage diabetes effectively. Here, we review currently available diabetes technologies, summarize their individual features and highlight key patient factors to consider when creating a personalized treatment plan. We also address current challenges and barriers to the adoption of diabetes technologies.

G6 continuous glucose monitoring system feature use and its associations with glycaemia in Europe

AIMS

Current continuous glucose monitoring (CGM) devices provide features that alert individuals with diabetes about their current and impending adverse glycaemic events. The use of these features has been associated with glycaemic improvements. However, how these features are utilised under real-world conditions has not been well studied. We queried a large database to quantify utilisation of the Dexcom G6 system features and how utilisation impacted glycaemic outcomes within a cohort of European users.

METHODS

This 6-month retrospective, observational, large database analysis utilised anonymised data from a sample of 47,784 Europe-based G6 users. Primary outcome measures were associations between utilisation and customisation of High/Low threshold alerts, 'urgent low soon' (ULS) alert, and established CGM metrics.

RESULTS

Users in the Germany, Austria, Switzerland region (n = 20,257), the Nordic countries (n = 10,314), United Kingdom (n = 9006), Italy (n = 4747), France (n = 2130) and Spain (1330) were included. All alert features were utilised by >75% of the cohort across all regions/countries and age groups. Enabling the Low alert and ULS alert was associated with lower percentage of time below range compared to disabling the Low alert (p < 0.001). Enabling the High alert was associated with higher percentage of time in range (%TIR) and lower percentage of time above range (%TAR) %TAR compared to disabling the High alert (p < 0.001). Paediatric patients and older adults tended to set a higher threshold for High/Low alerts, while younger adults tended to use lower threshold values for High/Low alerts.

CONCLUSIONS

Individuals who utilised the Dexcom G6 features showed better glycaemic control, particularly among those who utilised more sensitive High alert and Low alert settings, than users who did not utilise the system features.

Continuous glucose monitors and virtual care in high-risk, racial and ethnic minority populations: Toward promoting health equity

Continuous glucose monitors (CGMs) have become an important tool to aid self-management of blood glucose for many patients with diabetes in the U.S., and the benefits of CGM use are well-documented. However, disparities in CGM use exist, with lower use in certain marginalized racial and ethnic groups. CGM may be an important and underutilized tool to help reduce inequities. Evidence supporting the use of CGMs as a part of virtual care is discussed, with an emphasis on designing virtual diabetes care programs to promote health equity. Recommendations for clinical practice and research are presented. In clinical practice, CGM should be an option for all people with diabetes who qualify based on clinical practice guidelines, regardless of race, ethnicity, or other individual characteristics. Future research should characterize the use of, benefit from, and preferences for CGM among individuals from racial and ethnic groups to guide interventions at the health system, clinic, provider, and patient levels to promote equitable, evidence-based, and guideline-directed CGM use in marginalized racial and ethnic groups with diabetes.