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    Tight Glycemic Control in Intensive Care: From engineering to clinical practice change

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    Author
    Chase, J.G.
    Le Compte, A.J.
    Evans, A.
    Ward, L.
    Steel, J.
    Tan, C-S.
    Pretty, C.G.
    Penning, S.
    Desaive, T.
    Shaw, G.M.
    Date
    2011
    Permanent Link
    http://hdl.handle.net/10092/6449

    Tight glycemic control (TGC) is prevalent in critical care. Providing safe, effective TGC has proven very difficult to achieve with clinically derived protocols. The prob-lem is exacerbated by extreme patient variability and the need to minimize clinical effort and burden. These ingredients make an ideal scenario for model-based methods to provide opti-mised solutions. This paper presents the development, clinical-ly validated virtual trials optimisation, and initial clinical implementation of a stochastic targeted (STAR) TGC method and framework. It is compared to a prior successful, model-derived, less flexible and dynamic TGC protocol (SPRINT). The use of stochastic models to safely forecast a range of glu-cose outcomes over 1-3 hours ensures better performance, more dynamic use of the range of insulin and nutrition inputs and thus better glycemic performance and safety from hypog-lycemia, the latter of which was reduced by 3.0x times. Hence, the paper presents an overall engineering approach to TGC from engineering models to clinical implementation and ongo-ing clinical practice change

    Subjects
    ICU
     
    TGC
     
    glycemic control
     
    control systems
     
    modelling
     
    hypoglycemia
     
    clinical trials
     
    Field of Research::09 - Engineering::0903 - Biomedical Engineering
    Collections
    • Engineering: Conference Contributions [1920]
    Rights
    https://canterbury.libguides.com/rights/ir

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