Benchtop to bedside to worldwide: Implementing model-based glycemic control in intensive care

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dc.contributor.authorLeCompte, A.J.
dc.contributor.authorShaw, Geoff
dc.contributor.authorChase, Geoff
dc.date.accessioned2013-01-14T23:21:02Z
dc.date.available2013-01-14T23:21:02Z
dc.date.issued2012en
dc.description6-pagesen
dc.description.abstractHyperglycaemia is a common physiological response in critically ill patients, and reflects the perturbed metabolic state associated with severe illness. Regulating blood glucose (BG) levels to pre-ICU concentrations may provide patients with a greater chance of survival and reduced complications. However, despite the potential benefits there is still no universally adopted method for regulating BG levels in the ICU, and several large trials have failed to provide a consistent level of BG regulation across multiple centers. Models of the glucose regulatory system together with specialized controllers can assist clinical staff in therapy decisions by optimizing insulin and nutrition dosing. These systems can be readily implemented using existing or commodity equipment. This article presents experiences in implementing such model-based BG control in eight studies across four clinical units in three countries and highlights challenges faced when translating control systems from design and simulation environments to daily bedside clinical usage. Several practical issues need to be addressed for successful clinical implementation. Patient response to glucose and insulin inputs needs to be characterized, and it has been observed that level of insulin response varies significantly between patients and within patients over time. Clinically desired target ranges for BG control often vary by clinic and by year, and thus control schemes are required to adapt. Finally, the design of the system interface plays an important role in merging with local clinical practices and achieving nursing support for the system. Considerable variation exists, not only in the types of patients and observed responses to treatment, but also in the provision of clinical treatment. Thus a balance is required between flexibility and complexity to reduce training time and costs, improve transparency and promote independent clinical uptake.en
dc.identifier.citationLeCompte, A.J., Shaw, G.M., Chase, J.G. (2012) Benchtop to bedside to worldwide: Implementing model-based glycemic control in intensive care. Budapest, Hungary: 8th IFAC Symposium on Biological and Medical Systems (BMS12), 29-31 Aug 2012.en
dc.identifier.urihttp://hdl.handle.net/10092/7338
dc.language.isoen
dc.publisherUniversity of Canterbury. Mechanical Engineeringen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectbiomedical computingen
dc.subjectclinical trialen
dc.subjectforecastingen
dc.subjectstochastic approximationen
dc.subjectglycemic controlen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinologyen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive careen
dc.titleBenchtop to bedside to worldwide: Implementing model-based glycemic control in intensive careen
dc.typeConference Contributions - Other
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