Neonatal Glycemic Control - Model Validation and In Silico Virtual Patient Trials

Simple item page
dc.contributor.authorLe Compte, A.J.
dc.contributor.authorLynn, A.
dc.contributor.authorChase, Geoff
dc.contributor.authorShaw, Geoff
dc.contributor.authorRussel, G.
dc.contributor.authorBlakemore, A.
dc.contributor.authorLee, D.S.
dc.contributor.authorWong, X.W.
dc.date.accessioned2009-05-13T21:54:37Z
dc.date.available2009-05-13T21:54:37Z
dc.date.issued2009en
dc.description.abstractIntroduction: Premature, low-birth-weight infants in the neonatal intensive care unit (NICU) can lose blood glucose homeostasis due to immaturity of endogenous regulatory systems and the stress of their condition. Typical treatment relies on glucose restriction before insulin administration due to fear of hypoglycaemia. A model of the fundamental glucose regulatory dynamics could enable optimised treatment approaches. Methods: An adult critical care metabolic system model is adapted to the unique physiological case of the neonate. Integral-based methods identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles for virtual patient trials. Retrospective clinical for N=25 cases contained 1079 glucose measurements over 3589 total patient hours plus all insulin and nutritional infusion data. Birth weights were all less than 1.5 kg and gestational age was 23-28.6 weeks. The model is validated for predictions of 1-4 hours forward. Virtual patients are used to develop model-based glycaemic control protocols. Results: The identified model had a median absolute percentage error of 2.50% [IQR: 1.0%-5.3%]. Median absolute prediction errors at 1, 2 and 4-hour intervals were 5.8% [IQR: 2.6%-11.2%], 9.9% [IQR: 4.5%-19.3%] and 14.5% [IQR: 6.3%-27.2%] respectively. Virtual trial results targeting a 72-125 mg/dL range yield a median blood glucose level of 104 mg/dL [IQR: 90-117]. Average insulin usage is 0.069 U/kg/hr. These results are compared to clinical values of 144 mg/dL [IQR: 113-178] mg/dL and 0.034U/kg/hr. Average dextrose delivery was 8.9 mg/kg/min. Hypoglycemic events were minimised in virtual trials. Conclusions: The model accurately captures and predicts the fundamental dynamic behaviours of the neonatal metabolism well enough for effective potential clinical use in glycaemic control. Model-based control can offer improved control with greater nutrition delivery to provide potentially better long-term outcomes.en
dc.identifier.citationLe Compte, A.J., Lynn, A., Chase, J.G., Shaw, G.M., Russel, G., Blakemore, A., Lee, D.S., Wong, X.W. (2008) Neonatal Glycemic Control - Model Validation and In Silico Virtual Patient Trials. Bethesda, MD, USA: 8th Annual Diabetes Technology Meeting, 13-15 Nov 2008.en
dc.identifier.urihttp://hdl.handle.net/10092/2446
dc.language.isoen
dc.publisherUniversity of Canterbury. Mathematics and Statisticsen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subject.marsdenFields of Research::290000 Engineering and Technology::290500 Mechanical and Industrial Engineering::290501 Mechanical engineeringen
dc.subject.marsdenFields of Research::290000 Engineering and Technology::291500 Biomedical Engineering::291504 Biomechanical engineeringen
dc.titleNeonatal Glycemic Control - Model Validation and In Silico Virtual Patient Trialsen
dc.typeConference Contributions - Other
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
12612096_NICU_DTS_2008v2 - POSTER.pdf
Size:
279.9 KB
Format:
Adobe Portable Document Format
Download
Collections
Engineering: Conference Contributions