Lal, Rayhan A

Objective: To evaluate the function and safety of the SteadiSet™ infusion set over a continuous 7-day wear period in adults with type 1 diabetes. Research Design and Methods: Participants used a SteadiSet infusion set with a t:slim X2™ insulin pump with Control-IQ™ technology, and either insulin aspart or insulin lispro, for a target of 7 days for 12 consecutive wear periods. Each set removed before 7 days was adjudicated by an independent committee to assess the cause of early removal and to determine whether criteria for primary or key secondary endpoints were met. Results: There were 260 participants who inserted 3028 infusion sets. For the primary endpoint, the Kaplan–Meier 7-day survival estimate was 95% (95% CI 94% to 96%). For the key secondary endpoint, which expanded the reasons for a failed infusion set, the Kaplan–Meier 7-day survival estimate was 84% (95% CI 82% to 86%). For both endpoints, the P value was <0.001 compared with a prespecified survival rate of 75%. Time-in-range 70–180 mg/dL (TIR) increased through day 3 of set wear and then decreased through day 7, with the average TIR being 70.6% over the entire wear period across all infusion sets, including those that failed. An increase in total daily insulin was observed from day 4 through day 7. Conclusions: The 7-day survival of the SteadiSet infusion set was very high for the primary endpoint and at an acceptable level with respect to early removal for any reason related to the device.

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.