F. Chee

Closed-loop glucose control in critically ill patients using continuous glucose monitoring system (CGMS) in real time

A study was conducted to determine if continuous subcutaneous glucose monitoring (from MiniMed CGMS) could be used in real-time to control blood sugar level (BSL) in patients with critical illness. A closed-loop control system was constructed to use CGMS in a real-time manner, coupled with a proportional integral (PI) control algorithm based on a sliding scale approach, for automatic intravenous infusion of insulin to patients. A total of five subjects with high BSL (>10 mmol/L) participated in formal studies of the closed-loop control system. Subjects were recruited from critically ill patients in the intensive care unit (ICU) after informed consent was obtained. Error grid analysis showed that 64.6% of the BSL readings as determined in real time using CGMS sensor, when compared to conventional BSL measurements on blood drawn from an arterial line, was clinically accurate (i.e., <20% deviation from glucometer value). In the five patients who underwent closed-loop control, the controller managed to control only one patients glycaemia without any manual intervention. Manual intervention was required due to the real-time sensor reading deviating more than 20% from the glucometer value, and also as a safety mechanism. Test on equality of mean and variance for BSL attained prior to, during, and post trial showed that the controllers performance was comparable to manual control. We conclude that the automatic sliding scale approach of closed-loop BSL control is feasible in patients in intensive care. More work is needed in the refinement of the algorithm and the improvement of real-time sensor accuracy.

Simulation study on automatic blood glucose control

Good glycemic control in diabetic patients requires frequent measurements of blood sugar level (BBL) and regular doses of insulin. These doses would most conveniently be administered automatically via a closed-loop system. A closed-loop system is based on a control algorithm which prescribes appropriate insulin doses for the measured BSL. Previously, the development of a control algorithm was based on clinical experience and observation, and later on mathematical modelling. Mathematical modelling, has advantages, in that preliminary testing of any proposed control algorithm can be performed before in vivo testing. The authors have simulated a sliding scale control algorithm using the Minimal model and have achieved BSL maintenance in the range of 6-10 mmol/L (provided the noise in BSL readings was within 20% of reference BSL values). When the noise was greater than 20%, BSL maintenance became more difficult, with a more marked swing in BSL levels. We conclude that mathematical modelling of glucose-insulin interaction is a useful tool in testing the functionality of control algorithms prior to in vivo testing.