Glycemic Control for Critically Ill Patients with Online Identification of Insulin Sensitivity

Abstract

Hyperglycemia is common in critically ill patients and leads to various severe complications and even death. Keeping blood glucose within the range of 80-110 mg/dL (4.4-6.1 mmol/L) has been shown to reduce mortality and morbidity in intensive care units (ICU). Many studies on BG control systems for ICU patients have been reported. However, it is not easy to maintain blood glucose within the desired range because of the time variability of insulin sensitivity in critically ill patients. In this study, to improve the prediction accuracy of blood glucose level in patients, we modi ed a glycometabolism model developed in our previous study, by identifying parameter values from clinical ICU data. Then, we modi ed insulin sensitivity online identi cation algorithm to avoid a sudden change in insulin sensitivity during online identi cation that updates insulin sensitivity value at intervals of 30 min. Finally, since hypoglycemia prevention as important, we designed a glycemic control system using nonlinear model predictive control based on the modi ed model and the online identi cation algorithm of insulin sensitivity. The new glycemic control system achieved 71% of blood glucose measurements within the range of 80-110 mg/dL and 1.5% of measurements below 80 mg/dL, which indicated effectiveness and safety.

Glycemic Control for Critically Ill Patients Using Zone Model Predictive Control

“…Simulation result on ICU virtual patient no. 3 by the glycemic control systems using zone MPC and nonlinear MPC [17]. The top panel: BG levels regulated by zone MPC (red line) and nonlinear MPC (blue line), the desired BG range of 80–110 mg/dl (dotted line).…”

“…In our previous study [17], we developed a glycemic control system using nonlinear MPC with online identification of insulin sensitivity, which showed effectiveness on maintaining BG within the desirable range. However, there was no improvement in preventing hypoglycemia from the existing systems.…”

“…2) with the online identification of insulin sensitivity given in Ref. [17]. To predict BG level in ICU patients the model described by Eqs.…”

“…Due to limitation of paper‐based insulin infusion protocols, such as lack of considering inter‐individual differences between patients, computer‐based protocols have been widely studied [5–17]. The Glucosafe system [5] for tight glucose control in critical care is a model‐based decision support system based on the prediction of BG trajectory using the Glucosafe model [18].…”

“…Due to limitation of paper-based insulin infusion protocols, such as lack of considering inter-individual differences between a Correspondence to: Sha Wu, E-mail: wu.sha.56e@st.kyoto-u.ac.jp *Department of Electrical Engineering, Kyoto University, Kyoto Daigakukatsura, Nishikyo-ku, Kyoto 615-8510, Japan **Department of Anesthesiology, Kagawa University, Takamatsu, Japan ***Department of Electrical Materials and Engineering, University of Hyogo, Kobe, Japan [Correction added on 09 January 2021, after first online publication: Order of authors has been amended.] patients, computer-based protocols have been widely studied [5][6][7][8][9][10][11][12][13][14][15][16][17]. The Glucosafe system [5] for tight glucose control in critical care is a model-based decision support system based on the prediction of BG trajectory using the Glucosafe model [18].…”