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Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Habibović, Pamela / Haueisen, Jens / Jahnen-Dechent, Wilhelm / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Lenarz, Thomas / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen /

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Volume 62, Issue 2


Volume 57 (2012)

Model-based glycaemic control: methodology and initial results from neonatal intensive care

Jennifer L. Dickson
  • Corresponding author
  • Department of Mechanical Engineering, College of University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ J. Geoffrey Chase / Adrienne Lynn / Geoffrey M. Shaw
  • Department of Intensive Care, Christchurch School of Medicine and Health Sciences, New Zealand
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-11-03 | DOI: https://doi.org/10.1515/bmt-2016-0051


Very/extremely premature infants often experience glycaemic dysregulation, resulting in abnormally elevated (hyperglycaemia) or low (hypoglycaemia) blood glucose (BG) concentrations, due to prematurity, stress, and illness. STAR-GRYPHON is a computerised protocol that utilises a model-based insulin sensitivity parameter to directly tailor therapy for individual patients and their changing conditions, unlike other common insulin protocols in this cohort. From January 2013 to January 2015, 13 patients totalling 16 hyperglycaemic control episodes received insulin under STAR-GRYPHON. A significant improvement in control was achieved in comparison to a retrospective cohort, with a 26% absolute improvement in BG within the targeted range and no hypoglycaemia. This improvement was obtained predominantly due to the reduction of hyperglycaemia (%BG>10.0 mmol/l: 5.6 vs. 17.7%, p<0.001), and lowering of the median per-patient BG [6.9 (6.1–7.9) vs. 7.8 (6.6–9.1) mmol/l, p<0.001, Mann-Witney U test]. While cohort-wide control results show good control overall, there is high intra-patient variability in BG behaviour, resulting in overly conservative treatments for some patients. Patient insulin sensitivity differs between and within patients over time, with some patients having stable insulin sensitivity, while others change rapidly. These results demonstrate the trade-off between safety and performance in a highly variable and fragile cohort.

Keywords: glycaemic control; insulin sensitivity; model-based control; physiological modelling; premature infant; stochastic forecasting


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About the article

Received: 2016-02-29

Accepted: 2016-09-29

Published Online: 2016-11-03

Published in Print: 2017-04-01

Citation Information: Biomedical Engineering / Biomedizinische Technik, Volume 62, Issue 2, Pages 225–233, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2016-0051.

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