Nonlinear Model Predictive Glycemic Control of Critically Ill Patients Using Online Identification of Insulin Sensitivity

In critically ill patients suffering from hyperglycemia, it has been recently shown that mortality and morbidity can be reduced by keeping blood glucose within the range of 80-110 mg/dL. However, maintaining glycemia within such range is difficult due to the time variability in insulin sensitivity in critically ill patients. In this paper, we propose a novel glycometabolism model of critically ill patients with an insulin sensitivity parameter and develop a nonlinear model predictive glycemic control system with online identification of insulin sensitivity at one-hour intervals. Simulation results show that our system keeps 70% of BG measurements within the range of 80-110 mg/dL without any severe hypoglycemic incidents, which indicates the effectiveness and safety of our system.