title: Nonlinear model predictive glycemic control of critically ill patients using online identification of insulin sensitivity.
abstract: 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.
authors.lastname: Sha Wu
authors.forename: Eiko
authors.initials: E
authors.lastname: Furutani
mesh_terms: D001786:Blood Glucose; D016638:Critical Illness; D006801:Humans; D006943:Hyperglycemia; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D007328:Insulin / Q000627:therapeutic use; D007333:Insulin Resistance; D008962:Models, Theoretical; D017711:Nonlinear Dynamics
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin