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Authors
Le Compte, Aaron; Chase, J. Geoffrey; Lynn, Adrienne; Hann, Christopher E; Shaw, Geoffrey M; Lin, Jessica

Identifier
10.3182/20090812-3-DK-2006.00004

Index Terms
Critical care and decision support systems; Endocrine and metabolic systems; Pharmacokinetics and drug delivery,

Abstract
Premature neonates often experience hyperglycaemia, which has been linked to increased mortality and worsened outcomes. Insulin therapy can assist in controlling blood glucose levels. However a reliable, robust control protocol is required to avoid hypoglycaemia and to meet nutrition goals. This study presents an adaptive, model-based predictive controller designed to incorporate the unique metabolic state and control parameters of the neonate. Controller performance was tested in virtual trials on a 25 patient retrospective cohort and 24-hour pilot clinical trials. The effects of measurement frequency and BG sensor error were also evaluated. Time in the 4 – 7 mmol/L BG band was increased by 110%-145% compared to retrospective control for that cohort, with fewer hypoglycaemic measurements. Controllers were robust to BG sensor errors.

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