Use of microdialysis-based continuous glucose monitoring to drive real-time semi-closed-loop insulin infusion.

Continuous glucose monitoring (CGM) and automated insulin delivery may make diabetes management substantially easier, if the quality of the resulting therapy remains adequate. In this study, a semi-closed-loop control algorithm was used to drive insulin therapy and its quality was compared to that of subject-directed therapy. Twelve subjects stayed at the study site for approximately 70 hours and were provided with the investigational Automated Pancreas System Test Stand (APS-TS), which was used to calculate insulin dosage recommendations automatically. These recommendations were based on microdialysis CGM values and common diabetes therapy parameters. For the first half of their stay, the subjects directed their diabetes therapy themselves, whereas for the second half, the insulin recommendations were delivered by the APS-TS (so-called algorithm-driven therapy). During subject-directed therapy, the mean glucose was 114 mg/dl compared to 125 mg/dl during algorithm-driven therapy. Time in target (90 to 150 mg/dl) was approximately 46% during subject-directed therapy and approximately 58% during algorithm-driven therapy. When subjects directed their therapy, approximately 2 times more hypoglycemia interventions (oral administration of carbohydrates) were required than during algorithm-driven therapy. No hyperglycemia interventions (delivery of addition insulin) were necessary during subject-directed therapy, while during algorithm-driven therapy, 2 hyperglycemia interventions were necessary. The APS-TS was able to adequately control glucose concentrations in the subjects. Time in target was at least comparable or moderately higher during closed-loop control and markedly fewer hypoglycemia interventions were required, thus increasing patient safety.

Feasibility of overnight closed-loop control based on hourly blood glucose measurements.

INTRODUCTION: Safe and effective closed-loop control (artificial pancreas) is the ultimate goal of insulin delivery. In this study, we examined the performance of a closed-loop control algorithm used for the overnight time period to safely achieve a narrow target range of blood glucose (BG) concentrations prior to breakfast. The primary goal was to compare the quality of algorithm control during repeated overnight experiments. MATERIALS AND METHODS: Twenty-three subjects with type 1 diabetes performed 2 overnight experiments on each of three visits at the study site, resulting in 138 overnight experiments. On the first evening, the subject's insulin therapy was applied; on the second, the insulin was delivered by an algorithm based on subcutaneous continuous glucose measurements (including meal control) until midnight. Overnight closed-loop control was applied between midnight and 6 a.m. based on hourly venous BG measurements during the first and second nights. RESULTS: The number of BG values within the target range (90-150 mg/dl) increased from 52.9% (219 out of 414 measurements) during the first nights to 72.2% (299 out of 414 measurements) during the second nights (p < .001, χ²-test). The occurrence of hypoglycemia interventions was reduced from 14 oral glucose interventions, the latest occurring at 2:36 a.m. during the first nights, to 1 intervention occurring at 1:02 a.m. during the second nights (p < .001, χ²-test). CONCLUSIONS: Overnight controller performance improved when optimized initial control was given; this was suggested by the better metabolic control during the second night. Adequate controller run-in time seems to be important for achieving good overnight control. In addition, the findings demonstrate that hourly BG data are sufficient for the closed-loop control algorithm tested to achieve appropriate glycemic control.