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    Virtual Patients and Clinical Trial Simulations to Improve Safety of Glucose Control in Intensive Care (2012)

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    12640883_PS26_Virtual_trial_E_-_PRINTED.pdf (656.2Kb)
    Type of Content
    Journal Article
    UC Permalink
    http://hdl.handle.net/10092/6920
    
    Publisher
    University of Canterbury. Mechanical Engineering
    ISSN
    2040-2295
    Collections
    • Engineering: Journal Articles [1527]
    Authors
    Fisk, L.
    Le Compte, A.J.
    Shaw, Geoff cc
    Chase, Geoff cc
    show all
    Abstract

    Despite the potential clinical benefits of normalizing blood glucose in critically ill patients, the risk of hypoglycemia is a major barrier to widespread clinical adoption of accurate glycemic control. To compare five glucose control protocols, a validated insulin-glucose system model was employed to perform simulated clinical trials. STAR, SPRINT, UNC, Yale and Glucontrol protocols were assessed over a medical-surgical intensive care unit patient cohort. Results were interpreted separately for patients with low to high sensitivity to insulin, and low to high variability in metabolic state. STAR and SPRINT provided good glucose control with risk of severe hypoglycemia less than 0.05% across all patient groups. UNC also achieved good control for patients with low and medium levels of insulin sensitivity (SI), but risk of severe hypoglycemia was raised for patients with high SI. Glucontrol showed degradation of performance for patients with high metabolic variability.

    Citation
    Fisk, L., Le Compte, A.J., Shaw, G.M., Chase, J.G. (2012) Virtual Patients and Clinical Trial Simulations to Improve Safety of Glucose Control in Intensive Care. Journal of Healthcare Engineering, 3(3), pp. 415-430.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    critical care; glycemic control; virtual trials
    ANZSRC Fields of Research
    40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineering
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive care
    32 - Biomedical and clinical sciences::3205 - Medical biochemistry and metabolomics::320502 - Medical biochemistry - carbohydrates
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinology
    32 - Biomedical and clinical sciences::3201 - Cardiovascular medicine and haematology::320102 - Haematology
    Rights
    https://hdl.handle.net/10092/17651

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    • Development and pilot trial results of stochastic targeted (STAR) glycemic control in a medical ICU 

      Fisk, L.; Le Compte, A.J.; Shaw, Geoff; Penning, S.; Desaive, T.; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2012)
      Accurate glycemic control (AGC) is difficult due to excessive hypoglycemia risk. Stochastic TARgeted (STAR) glycemic control forecasts changes in insulin sensitivity to calculate a range of glycemic outcomes for an insulin ...
    • Validation of a virtual patient and virtual trials method for accurate prediction of TGC protocol performance 

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