1864-P: What Makes the Difference? Predicting Glycemic Trajectory following AID Initiation in Youth with Type 1 Diabetes

Introduction and Objective: Automated insulin delivery (AID) systems improve glycemia but show high variability in individual outcomes. The aim was to identify predictors of glycemic patterns in youth after AID initiation. Methods: We used group-based trajectory modeling to characterize groups based on 18 months of glycemic data using CGM-determined % time in range (TIR) in youth ages 6-18 with T1D. Multivariable multinomial logistic regression estimated associations between clinical and sociodemographic predictors and trajectories. Results: Four TIR trajectories emerged among 713 AID users (Figure 1). All groups showed improvement, but only a small subset (Group 4) achieved and sustained TIR >70%. Compared to Group 4, Group 1 (lowest TIR) was older, had longer T1D duration, greater socioeconomic disadvantage (Area Deprivation Index), bolused less, and entered fewer carbohydrates at baseline. After adjusting for covariates including age, sex, T1D duration, and prior treatment, participants with fewer self-initiated boluses [OR 0.39 (95% CI: 0.28, 0.53)] and fewer appointments [OR 0.36 (0.16, 0.79)] had higher odds of Group 1 than Group 4. Higher insulin doses/kg [OR 1.53 (1.25, 1.88)] and greater parent inter-visit communication [OR 1.13 (0.99, 1.29)] were associated with increased odds of Group 1 membership. Conclusion: Distinct glycemic trajectories following AID initiation exist. Access to care and modifiable factors are strongly associated with trajectory group.