Settings Associated with Optimal Glycemic Outcomes with the Omnipod® 5 Automated Insulin Delivery System: Evidence from Real-World Users with Type 1 Diabetes
Alexandra Sawyer, Emma G. Wilmot, Duy Do, Kellee M. Miller, Trang T. Ly, Gregory P. ForlenzaObjective:
Identifying programmable device settings and user behaviors associated with achieving glycemic targets is critical for informing clinical practice and improving outcomes with automated insulin delivery (AID) systems. This real-world analysis aimed to identify predictors of achieving optimal glycemic outcomes for people with type 1 diabetes (T1D) using the Omnipod ® 5 AID System.
Methods:
This retrospective analysis included real-world data from Omnipod 5 users aged ≥ 2 years with T1D in the United States and Europe who had sufficient continuous glucose monitor data (≥30 days with ≥1 reading; ≥75% of days with ≥220 readings) available in Insulet’s device and person-reported datasets between January 1 and March 31, 2025. Logistic regression was used to identify programmable settings and user behaviors associated with achieving >70% time in range (TIR; 70–180 mg/dL [3.9–10.0 mmol/L]). Optimal thresholds for the top modifiable predictors were determined using Youden’s J statistic, and their impact on glycemic outcomes was explored.
Results:
Data from 176,405 users were analyzed. Predictors of achieving >70% TIR included the following: a higher number of user-initiated boluses/day, greater time in Automated Mode, use of lower glucose targets, and a more aggressive correction factor (CF) and insulin-to-carbohydrate (I:C) ratio (all
Conclusions:
These results provide actionable guidance for clinicians to optimize outcomes for people with T1D using the Omnipod 5 System.