Background: Accuracy and feature sets of continuous glucose monitoring (CGM) systems may influence device utilization and outcomes. We compared clinical trial accuracy and real-world utilization and effectiveness of two different CGM systems. Materials and Methods: Separately conducted accuracy studies of a fifth-generation and a sixth-generation CGM system involved 50 and 159 adults, respectively. For between-system performance comparisons, propensity score methods were utilized to balance cohort characteristics. Real-world outcomes were assessed in 10,000 anonymized patients who had switched from the fifth-generation to the sixth-generation system and had used connected mobile devices to upload data from both systems, allowing pairwise comparisons of device utilization and glucose concentration distributions. Results: Propensity score-adjusted mean absolute relative differences for the fifth-and sixth-generation systems were 9.0% and 9.9%, and the percentages of values within-20%/20 mg/dL were 93.1% and 92.5%, respectively. The sixth-generation system, but not the fifth-generation system, met accuracy criteria for interoperable CGM systems. Both systems had high real-world utilization rates (93.8% and 95.3% in the fifth-and sixthgeneration systems, respectively). Use of the sixth-generation system was associated with fewer glucose values <55 mg/dL (<3.1 mmol/L) (0.7% vs. 1.1%, P < 0.001) and more values 70-180 mg/dL (3.9-10.0 mmol/L) (57.3% vs. 56.0%, P < 0.001) than the fifth-generation system. Conclusions: CGM performance outcomes can be compared through the propensity score analysis of clinical trial data and pairwise comparisons of real-world data. The systems compared here had nearly equivalent accuracy and utilization rates. Longer term biochemical and psychosocial benefits observed with the fifthgeneration system are also expected with the sixth-generation system.

Background: Programmable and fixed auditory and/or vibratory threshold alerts are essential features of realtime continuous glucose monitoring (rtCGM) systems that provide users time to intervene before the onset of clinical hypoglycemia or hyperglycemia. A sixth-generation rtCGM system from Dexcom, Inc. (G6) includes a new alert that is triggered when an algorithm predicts that an estimated glucose value £55 mg/dL will occur within 20 min, allowing users more time to act to avoid hypoglycemia. We examined whether this predictive low glucose alert provided added benefit to traditional low threshold alerts. Methods: We analyzed glucose values from an anonymized sample of 1424 patients who transitioned to G6 from the preceding fifth-generation system (G5) with no predictive alert. Users with the low threshold alert setting of 70 or 80 mg/dL were evaluated separately. Receiver users, those who disabled the predictive low glucose alert, or those with <30 days of data immediately before or after the transition to G6 were excluded. Results: Percent time <54, £55, <70, and >250 mg/dL fell significantly after the transition to G6, independent of low threshold alert setting. Time in range improved for G6 users with a low threshold alert setting of 70 mg/dL. Conclusions: Advance warning provided by predictive low glucose alerts may further reduce hypoglycemia among rtCGM-experienced users.

Aims To identify clinically useful associations between HbA1c levels and various continuous glucose monitoring‐derived metrics. Methods We retrospectively analysed end‐of‐study HbA1c levels and >2 weeks of continuous glucose monitoring data collected from 530 adults with Type 1 diabetes or insulin‐requiring Type 2 diabetes during four randomized trials. Each trial lasted ≥24 weeks and provided central laboratory end‐of‐study HbA1c levels and continuous glucose monitoring data from the preceding 3 months. Participants were assigned to groups based on either HbA1c levels or continuous glucose monitoring‐derived glucose values. Results HbA1c was strongly correlated with mean glucose value (r=0.80), time spent with glucose values in the 3.9–10.0 mmol/l range (time in range; r=–0.75) and percentage of glucose values >13.9 mmol/l (r=0.72), but was weakly correlated with the percentage of glucose values <3.9 mmol/l (r=–0.39) or <3.0 mmol/l (r=–0.21). The median percentage of glucose values <3.0 mmol/l was <1.2% (<20 min/day) for all HbA1c‐based groups, but the median percentage of values >13.9 mmol/l varied from 2.5% (0.6 h/day) to 27.8% (6.7 h/day) in the lowest and highest HbA1c groups, respectively. More than 90% of participants with either <2% of glucose values >13.9 mmol/l, mean glucose <7.8 mmol/l, or time in range >80% had HbA1c levels ≤53 mmol/mol (≤7.0%). For participants with HbA1c ≥64 mmol/mol (≥8.0%), the median time in range was 44%, with 90% of participants having a time in range of <59%. Conclusions The associations shown in the present study suggest that continuous glucose monitoring‐derived metrics may help guide diabetes therapy intensification efforts in an HbA1c‐independent manner.

Do-it-yourself automated insulin delivery systems for people living with type 1 diabetes use commercially available continuous glucose sensors and insulin pumps linked by unregulated open source software. Uptake of these systems is increasing, with growing evidence suggesting that positive glucose outcomes may be feasible. Increasing interest from people living with, or affected by, type 1 diabetes presents challenges to healthcare professionals, device manufacturers and regulators as the legal, governance and risk frameworks for such devices are not defined. We discuss the data, education, policy, technology and medicolegal obstacles to wider implementation of DIY systems and outline the next steps required for a co-ordinated approach to reducing variation in access to a technology that has potential to enable glucose self-management closer to target.

Background Those caring for children and adolescents with diabetes often use glucose concentration and trending information in management decisions. Some continuous glucose monitoring (CGM) systems offer real-time sharing and monitoring capabilities through mobile apps carried by the person with diabetes and the caregiver(s), respectively. Few large studies have explored real-world associations between sharing and following, CGM utilization, and glycemic outcomes. Methods We performed a retrospective evaluation of device usage and glycemic control in 15,000 youth ranging in age from 2 to 18 years by analyzing anonymized data that had been uploaded with a mobile app that provides optional sharing. The presence or absence of a real-time monitor (a “Follower”) was established on 15 June 2018. Each day with ≥ 1 uploaded glucose values was counted as a day of device usage. Between-group glucose comparisons were made with two-sided Welch’s t tests. Results Overall, 94.8% of the population used the sharing feature and had at least one Follower. The mean numbers of Followers for patients aged 2–5, 6–12, and 13–18 years were 2.8, 2.8, and 2.4, respectively. In all three age categories, the presence of at least one Follower was associated with lower mean glucose values, more glucose values in the 70- to 180-mg/dL range, correspondingly fewer glucose values representing hypoglycemia and hyperglycemia, and significantly more device utilization. Conclusion Real-time sharing and following of CGM data are associated with improved device utilization and glycemic parameters. The observed association suggests either more timely interventions or higher levels of engagement among the caregivers or the youth with diabetes. Funding Dexcom, Inc.