MULTI-CENTER RANDOMIZED CROSS-OVER ITALIAN PEDIATRIC SUMMER CAMP: AP VS SAP IN 5–9 YEAR OLD CHILDREN in 9th International Conference on Advanced Technologies & Treatment of Diabetes (ATTD) Barcellona 2016

Background and Aims: The Artificial Pancreas (AP) system based on the Modular Model Predictive Control algorithm (MMPC) running on the wearable platform Diabetes Assistant (DiAs, University of Virginia) has been successfully used for 2 months in adults patients reducing time-in-hypo (CGM <70 mg/dL) and increasing timein- target (70-180 mg/dL) with respect to Sensor Augmented Pump therapy (SAP). Here we report the first outpatient AP trial in 5–8 year old children, using MMPC on DiAs in the PedArPan (PEDiatric ARtificial PANcreas) project. Methods: Thirty children with type 1 diabetes, 5–8 years old, and their parents were recruited in 5 Italian pediatric centers and completed a randomized cross-over trial in a summer camp. Glucose control achieved in 3 days of AP use was compared against 3 days of parents-managed SAP. Results:Overnight (00:00–07:30) The AP significantly reduced time-in-hypo with respect to SAP, 0.00%[0.00–2.22] vs 2.19%[0–12.3], p-value = 0.002, without significant worsening of time-in-target, 55.97%(22.53) vs 59.69% (21.24), p-value = 0.422, nor of time-in-tight-target (80–140 mg/dl), 31.27% (20.23) vs 33.02%(19.80), p-value = 0.668. Overall (00:00–24:00) A statistically significant 3-fold reduction of time-in-hypo, 1.93%[1.17–4.54] vs 6.67%[2.26–11.54], p-value <0.001, was recorded with the AP at the expenses of a statistically significant deterioration of time-in-target, 56.79%(13.47) vs 63.09%(10.98), p-value = 0.015. Parents initiated manual interventions (via correction boluses or temporary basal rate settings) occurred 0[0-0] times with the AP vs 3.5[1–7] times in SAP. Closed-loop functioned for 96.97%[93.47-98.43] of the time. Conclusions: This study shows feasibility and safety of a wearable MMPC in young children. Next steps will include overnight testing at-home and re-tuning of the algorithm to improve efficacy during daytime