4.2 Article

Decision support for optimized blood glucose control and nutrition in a neurotrauma intensive care unit: preliminary results of clinical advice and prediction accuracy of the Glucosafe system

Journal

JOURNAL OF CLINICAL MONITORING AND COMPUTING
Volume 26, Issue 4, Pages 319-328

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10877-012-9364-y

Keywords

Hyperglycemia; Blood glucose; Decision support; Nutrition; Insulin therapy; Critical care; Prediction error

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Assessment of glycemic control with model-based decision support (Glucosafe) in neurotrauma intensive care patients in an ongoing randomized controlled trial with a blood glucose (BG) target of 5-8 mmol/L. Assessment of BG prediction accuracy of the model and assessment of the effect that two potential model extensions would have on prediction accuracy in this trial. In the intervention group insulin infusion rates and nutrition are varied based on Glucosafe's decision support. In the control group, the caloric target is 25-30 kcal/kg per day and insulin is regulated according to department rules. BG concentrations, insulin infusion rates, and feed rates are compared from the data of 12 consecutive patients. BG measurements are predicted retrospectively and the mean relative prediction error is calculated using (1) the current model from the trial, (2) the current model modified by using a BG-dependent variable endogenous insulin appearance rate, (3) the current model modified by a patient-specific carbohydrate absorption factor. BG control was improved by Glucosafe. 76 % of BG measurements in Glucosafe patients were in the 5-8 mmol/L band (Controls: 51 %). BG means (log-normal) +/- A SD were 7.0 +/- A 1.19 mmol/L in Glucosafe patients compared to 8.0 +/- A 1.24 mmol/L in controls (P = 0.05). Mean caloric intake was 93.5 +/- A 15 % of resting energy expenditure in Glucosafe patients (Controls: 129 +/- A 29 %). The BG-dependent variable insulin appearance rate had no measurable effect on prediction accuracy. The patient-specific carbohydrate absorption factor improved prediction accuracy significantly (P = 0.001). Glucosafe advice reduces hyperglycemia in neurotrauma intensive care patients. Further parameterization can improve model prediction accuracy.

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