Background: People with type 1 diabetes occasionally forget to announce meals to their insulin pump, which degrades glycemic control. We have developed a meal detection algorithm for the artificial pancreas (AP) that detects unannounced meals and delivers boluses.

Methods: We conducted a randomized crossover trial in adolescents aged 12-18 years with type 1 diabetes. We compared (i) CSII, (ii) AP, and (iii) AP with a meal detection algorithm (AP+MDA) in controlling post-prandial glucose levels after a meal without a bolus. Participants underwent three 9-hour interventions which included breakfast with a CHO-matched bolus and lunch without a bolus. The primary outcome was the iAUC of the glucose excursions from the start of lunch to 4 hours post-lunch.

Results: 11 participants (mean age 14.9±1.3, HbA1c 8.3±0.6%) were included. Compared to CSII, AP+MDA decreased iAUC from the start of lunch to 4 hours post-lunch from 24±9.5 h.mmol/L to 15±8 h.mmol/L (p=0.03). The AP+MDA reduced time > 10 mmol/L after the missed bolus by -21.6% (IQR: [-39.4- -3.8]) compared to CSII (p=0.02). The mean meal detection time was 41.8±16 minutes after meal consumption.

Conclusions: The AP+MDA successfully decreased iAUC after an unannounced meal in adolescents with type 1 diabetes. Longer and larger studies are needed to evaluate the efficacy of this meal detection algorithm in real-world settings.


E. Palisaitis: None. A. El Fathi: None. A. Haidar: Consultant; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Eli Lilly and Company. J.E. von Oettingen: None. L. Legault: Advisory Panel; Self; Dexcom, Inc., Lilly Diabetes. Research Support; Self; AstraZeneca K.K., Merck & Co., Inc., Sanofi-Aventis. Other Relationship; Self; Lilly Diabetes.

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