Development and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive care

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dc.contributor.authorDickson, J.L.
dc.contributor.authorLe Compte, A.J.
dc.contributor.authorFloyd, R.P.
dc.contributor.authorChase, Geoff
dc.contributor.authorLynn, A.
dc.contributor.authorShaw, Geoff
dc.date.accessioned2016-01-19T23:50:00Z
dc.date.available2016-01-19T23:50:00Z
dc.date.issued2013en
dc.description.abstractHyperglycaemia is a common complication of prematurity and stress in neonatal intensive care units (NICUs). It has been linked to worsened outcomes and mortality. There is currently no universally accepted best practice glycaemic control method, with many protocols lacking patient specificity or relying heavily on ad hoc clinical judgment from clinical staff who may be caring or overseeing care for several patients at once. The result is persistent hypoglycaemia and poor control. This research presents the virtual trial design and optimisation of a stochastic targeted (STAR) approach to improve performance and reduce hypoglycaemia. Clinically validated virtual trials based on NICU patient data (N = 61 patients, 7006 hours) are used to develop and optimise a STAR protocol that improves on current STAR-NICU performance and reduce hypoglycaemia. Five approaches are used to maximize the stochastic range of BG outcomes within 4.0-8.0mmol/L, and are designed based on an overall cohort risk to provide clinically specified risk (5%) of BG above or below a clinically specified level. The best protocol placed the 5th percentile BG outcome for an intervention on 4.0mmol/L band. The optimised protocol increased %BG in the 4.0-8.0mmol/L band by 3.5% and the incidence of BG<2.6mmol/L by 1 patient (50%). Significant intra- and inter- patient variability limited possible performance gains so that they are unlikely to be clinically substantial, indicating a need for a further increase patient-specific or sub-cohort specific approaches to manage variability.en
dc.identifier.citationDickson, J.L., Le Compte, A.J., Floyd, R.P., Chase, J.G., Lynn, A., Shaw, G.M. (2013) Development and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive care. Biomedical Signal Processing and Control, 8(2), pp. 215-221.en
dc.identifier.doihttps://doi.org/10.1016/j.bspc.2012.08.002
dc.identifier.issn1746-8094
dc.identifier.urihttp://hdl.handle.net/10092/11677
dc.language.isoen
dc.publisherUniversity of Canterbury. Chemical and Process Engineeringen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectInsulin sensitivityen
dc.subjectcontrol algorithmsen
dc.subjectphysiological modelsen
dc.subjectsimulationen
dc.subjectintensive careen
dc.subject.anzsrcFields of Research::40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineeringen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive careen
dc.titleDevelopment and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive careen
dc.typeJournal Article
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