Algorithm-Driven Initiation and Adaptation of Hybrid Closed-Loop in Young Children with Type 1 Diabetes: A Pilot Study

Abstract

Introduction: Glucose regulation in young children is complicated by higher glycemic variability, unpredictable behaviors, and low insulin needs. While the benefits of automated insulin delivery (AID) for this population are established, how to initiate and adjust pump settings still represents a challenging task for health care providers. In this study, we investigate the safety and efficacy of using algorithm-driven initiation and adjustments of AID parameters in children aged 2-6 years. Methods: Participants used AID at home for 8 weeks. Initial settings and periodic adjustments of therapy profiles (basal rates, insulin-to-carbohydrate ratios, insulin-correction factors, and sleep schedules) were provided through a cloud-based investigational software. Investigators reviewed therapy recommendations and could adjust if necessary. Primary safety endpoints included the percentage of time <54 mg/dL and >250 mg/dL, tested for noninferiority with respect to baseline. Primary efficacy endpoints (tested in a hierarchical manner) were the percentage of time in 70-180 mg/dL, mean glucose, the percentage of time >250 mg/dL, <70 mg/dL, and <54 mg/dL. Results: Thirty-two participants (age range: 2.0-5.9 years) were recruited for the study; 29 had sufficient data for the analysis. Investigators overrode 15% of software recommendations. The percentage of time <54 mg/dL and >250 mg/dL was noninferior in the 8-week follow-up with respect to baseline (P < 0.001). Statistically significant improvements were observed in the percentage of time in 70-180 mg/dL (P = 0.005), >250 mg/dL (P = 0.003), and mean glucose (P = 0.02). No difference was observed in the percentage of time <70 mg/dL (P = 0.34). Furthermore, no difference was observed with respect to a similar study cohort (same age range, n = 86) with expert pediatric endocrinologists modifying pump settings. Conclusions: Findings from this pilot study suggest that the use of AID with algorithm-driven initiation and adjustment of pump parameters is safe and effective in young children with type 1 diabetes. Further study of the algorithm in a larger cohort is indicated. Clinical Trials Registration number: NCT06017089.

Keywords: artificial intelligence; automated insulin delivery; decision support; digital twins; pediatrics; type 1 diabetes.