O’Neal, David N.

Abstract Background: Flash glucose monitoring (FGM) can improve diabetes management, but no randomised controlled trials (RCTs) of FGM have been undertaken in Indigenous Australian populations. This study aimed to assess the feasibility of performing a RCT of FGM in Indigenous Australians with type 2 diabetes. Methods: In this open-labelled pilot RCT, Indigenous adults with type 2 diabetes were randomised to FGM or standard care for 6 months. Eligible participants were being treated with injectable diabetes medications and had a glycosylated haemoglobin (HbA1c) ≥ 7.0%. The feasibility outcome was the proportion of participants completing the trial. The preliminary effective outcome was the change in HbA1c. Secondary effectiveness outcomes included a change in time spent in target blood glucose; safety (hypoglycaemic episodes); and quality of life (EuroQol 5-Dimension 3-Level (EQ-5D-3L) score). Results: Of 126 screened individuals, 74 were eligible, 40 (31.7%) were randomised and 39 (97.5%) completed the study. Participants’ baseline characteristics were similar between the FGM and usual care groups, except for sex and body mass index. There were no between-group differences for: change in HbA1c; percentage of time spent in target blood glucose, low glucose and high glucose; or EQ-5D-3L scores. No severe hypoglycaemic episodes occurred. Conclusions: This is the first pilot RCT of FGM in Indigenous Australians with type 2 diabetes. The results support a larger RCT, which is currently in progress. Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR12621000021875), retrospectively registered on 14 January 2021.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.