Insulin pump with adaptive therapy settings improved time in range in type 1 diabetes
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Adults with type 1 diabetes who used an automated insulin delivery system with settings changed by the system instead of a provider had improvements in time in range and HbA1c at 13 weeks, according to a speaker.
In a proof-of-concept trial, a small group of adults with type 1 diabetes used the t:slim X2 insulin pump (Tandem Diabetes Care) with adaptive therapy settings enabled for 13 weeks. The cohort had an increase in time of range of nearly 24% during the trial and reported no occurrences of hypoglycemia or diabetic ketoacidosis that were related to the device.
“Our study suggests that computerized optimization of an automated insulin delivery system is feasible and improves HbA1c,” Viral Shah, MD, associate professor of medicine and pediatrics in the adult clinic of the Barbara Davis Center for Diabetes at the University of Colorado Anschutz Medical Campus, told Healio. “This is a game changer, as it may improve automated insulin delivery utilization and adoption by patients and primary care providers.”
Researchers enrolled 33 adults with type 1 diabetes who were using multiple daily injection insulins and had an HbA1c between 7.5% and 11% to participate in a prospective, single-arm trial (mean age, 36.1 years; mean HbA1c, 8.5%). The study began with a 2-week run-in period where participants used a continuous glucose monitor. At the end of the run-in period, the cohort began using the t:slim X2 insulin pump with Control-IQ technology and adaptive therapy settings enabled. The system used an algorithm to set the initial basal rate, carbohydrate ratio and correction factor at device initiation. Adjustments were made automatically by the system at 3 days and 7 days and then weekly until the end of the trial at 13 weeks. Efficacy was measured through changes in CGM metrics and HbA1c from the run-in period to the last 30 days of the trial. Cases of severe hypoglycemia and DKA were collected to determine safety.
“The primary care physicians, who are seeing the majority of patients with type 1 diabetes, can’t keep up with these [system] changes,” Shah said during a presentation. “When we see the patients initially, we call the patients back and titrate [insulin] until we reach the goal. But that’s a tough task at the primary care level. That’s why we did this study, to have computerized-based optimization of automated insulin delivery.”
Of the 33 enrolled participants, 29 completed the trial. The cohort had an increase in time in range between 70 mg/dL and 180 mg/dL from 45.7% during the 14-day run-in period to 69.1% with automated insulin delivery (P < .001). The improvement in time in range began immediately with an increase of 18.8% observed in the first week with automated insulin delivery.
Time above range of greater than 180 mg/dL decreased from 51.9% in the run-in period to 29.5% in the last 30 days of the trial (P < .001). Time below range of less than 70 mg/dL declined from 1.8% in the run-in period to 1% at the end of the trial (P = .03). The cohort had a reduction in HbA1c from 7.9% during the run-in period to 6.9% with automated insulin delivery (P < .001). By the end of the study, 55% of the cohort achieved an HbA1c of less than 7%.
One participant had two hypoglycemic events during the trial that were not linked to the automated system. There were no DKA events reported.
“With three automated insulin delivery systems in the U.S. and many more waiting to enter the market, it can be overwhelming for primary care physicians to update themselves on these systems as each system works very differently,” Shah told Healio. “Therefore, we need to automate automated insulin delivery adjustments so that it can take away the burden from providers.”
Shah said more studies are needed involving the other automated insulin delivery systems and to further improve automation of insulin delivery initiation and optimization.
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Shah V, et al. OP 014. Presented at: International Conference on Advanced Technologies & Treatments for Diabetes; Feb. 22-25, 2023; Berlin (hybrid meeting).
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