Full closed loop open‐source algorithm performance comparison in pigs with diabetes

Clinical and Translational Medicine

Emily C. Gale¹  Lyndsay M. Stapleton²  Caitlin L. Maikawa²  Gillie A. Roth²  Celine S. Liong²  Abigail K. Grosskopf³  Doreen Chan⁴  Sam W. Baker⁵  Joseph P. Garner⁵  Santiago Correa⁶  Joseph L. Mann⁶  Anton A. A. Smith⁶  Catherine M. Meis⁶  Anthony C. Yu⁶  Rayhan A. Lal⁷  Eric A. Appel⁸  Bruce A. Buckingham⁸  David M. Maahs⁸  Dana Lewis⁹ 

[1] Department of Biochemistry Stanford University Stanford California USA;Department of Bioengineering Stanford University Stanford California USA;Department of Chemical Engineering Stanford University Stanford California USA;Department of Chemistry Stanford University Stanford California USA;Department of Comparative Medicine Stanford University Stanford California USA;Department of Materials Science & Engineering Stanford University Stanford California USA;Division of Endocrinology Department of Medicine Stanford University Stanford California USA;Division of Endocrinology Department of Pediatrics Stanford University Stanford California USA;OpenAPS Seattle Washington USA;

关键词: automated insulin delivery;    diabetes;    open‐source closed loop;   

DOI  :  10.1002/ctm2.387

来源: DOAJ

【 摘 要 】

Abstract Understanding how automated insulin delivery (AID) algorithm features impact glucose control under full closed loop delivery represents a critical step toward reducing patient burden by eliminating the need for carbohydrate entries at mealtimes. Here, we use a pig model of diabetes to compare AndroidAPS and Loop open‐source AID systems without meal announcements. Overall time‐in‐range (70–180 mg/dl) for AndroidAPS was 58% ± 5%, while time‐in‐range for Loop was 35% ± 5%. The effect of the algorithms on time‐in‐range differed between meals and overnight. During the overnight monitoring period, pigs had an average time‐in‐range of 90% ± 7% when on AndroidAPS compared to 22% ± 8% on Loop. Time‐in‐hypoglycemia also differed significantly during the lunch meal, whereby pigs running AndroidAPS spent an average of 1.4% (+0.4/−0.8)% in hypoglycemia compared to 10% (+3/−6)% for those using Loop. As algorithm design for closed loop systems continues to develop, the strategies employed in the OpenAPS algorithm (known as oref1) as implemented in AndroidAPS for unannounced meals may result in a better overall control for full closed loop systems.

【 授权许可】

Unknown