Blood Glucose Control of Critically Ill Patients with Time-varying Insulin Sensitivity Using Nonlinear Model Predictive Control

Abstract

In critically ill patients suffering from hyperglycemia it has been recently shown that mortality and morbidity can be reduced by keeping glycemia within 80-110 mg/dL (4.4-6.1 mmol/L). However, maintaining blood glucose (BG) levels within such range is difficult because of the time variability in insulin sensitivity through the patient recovery. In this study, we introduce a nonlinear model predictive control algorithm using a time-invariant model of glucose-insulin metabolism for the eventual development of a control system that regulates BG levels of critically ill patients. Simulation results using virtual patients with time-varying insulin sensitivity show that BG levels can be kept 58.3% within the 80-110 mg/dL range with only 1.4% of BG levels decreasing below 80 mg/dL (4.4 mmol/L), which demonstrates the safety of the present control algorithm.