Reduced hypoglycemia and increased time in target using closed-loop insulin delivery during nights with or without antecedent afternoon exercise in type 1 diabetes.

OBJECTIVE: Afternoon exercise increases the risk of nocturnal hypoglycemia (NH) in subjects with type 1 diabetes. We hypothesized that automated feedback-controlled closed-loop (CL) insulin delivery would be superior to open-loop (OL) control in preventing NH and maintaining a higher proportion of blood glucose levels within the target blood glucose range on nights with and without antecedent afternoon exercise. RESEARCH DESIGN AND METHODS: Subjects completed two 48-h inpatient study periods in random order: usual OL control and CL control using a proportional-integrative-derivative plus insulin feedback algorithm. Each admission included a sedentary day and an exercise day, with a standardized protocol of 60 min of brisk treadmill walking to 65-70% maximum heart rate at 3:00 p.m. RESULTS: Among 12 subjects (age 12-26 years, A1C 7.4±0.6%), antecedent exercise increased the frequency of NH (reference blood glucose<60 mg/dL) during OL control from six to eight events. In contrast, there was only one NH event each on nights with and without antecedent exercise during CL control (P=0.04 vs. OL nights). Overnight, the percentage of glucose values in target range was increased with CL control (P<0.0001). Insulin delivery was lower between 10:00 p.m. and 2:00 a.m. on nights after exercise on CL versus OL, P=0.008. CONCLUSIONS: CL insulin delivery provides an effective means to reduce the risk of NH while increasing the percentage of time spent in target range, regardless of activity level in the mid-afternoon. These data suggest that CL control could be of benefit to patients with type 1 diabetes even if it is limited to the overnight period.

Modeling insulin action for development of a closed-loop artificial pancreas.

Three models of glucose homeostasis are compared in terms of their steady-state dose-response characteristics, how they characterize glucose distribution kinetics, and how they characterize the dynamics of insulin action. The three models [minimal model, AIDA (Automated Insulin Dosage Advisor), and a model by Sorensen] are used to discuss a wider variety of questions related to metabolic modeling. Simulations are performed comparing each model's response to an intravenous glucose tolerance test, with and without incremental insulin responses, to existing data in individuals with type 1 diabetes mellitus. Predicted changes in blood glucose following a subcutaneous bolus of insulin or an incremental increase in basal insulin delivery are simulated. From these results, the models are evaluated as potential candidates for simulating changes in treatment and developing a closed-loop insulin delivery algorithm. While no consensus model is proposed, relevant issues needing to be addressed are highlighted.