Model predictive glycaemic regulation in critical illness using insulin and nutrition input: a pilot study.

Stress-induced hyperglycaemia is prevalent in intensive care, impairing the immune response. Nutritional support regimes with high glucose content further exacerbate the problem. Tight glucose control has been shown to reduce mortality by up to 43% if levels are kept below 6.1 mmol/L. This research develops a control algorithm with insulin and nutritional inputs for targeted glucose control in the critically ill. Ethics approval for this research was granted by the Canterbury Ethics Committee. Proof-of-concept clinical pilot trials were conducted on intubated, insulin-dependent Christchurch ICU patients (n=7) on constant nutritional support. A target 10-15% reduction in glucose level per hour for a desired glucose level of 4-6 mmol/L was set. 43% and 91% of glucose targets were achieved within +/-5 and +/-20%, respectively. The mean error was 8.9% (0.5 mmol/L), with an absolute range [0, 2.9] mmol/L. End glucose levels were 40% lower compared to initial values. All large target errors are attributable to sudden changes in patient physiology at low glucose values, rather than systemic deficiencies. Target errors are consistent with and explainable by published sensor error distributions. The results show that intensive model-based glucose management with nutrition control reduced absolute glucose levels progressively while reducing the severity of glycaemic fluctuation even with significant inter-patient variability and time-varying physiological condition. Trials spanning longer periods of time are in development to verify the short-term pilot studies performed and to test the adaptability of the controller. Clinically, these results indicate potential in clinical use to reduce ICU mortality as well as reduce risk of severe complications.