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    Tight Glycemic Control in Critical Care - The leading role of insulin sensitivity and patient variability – A review and model-based analysis (2011)

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    12635864_CMPB-D-10-00130 - REVISED final.pdf (614.0Kb)
    Type of Content
    Journal Article
    UC Permalink
    http://hdl.handle.net/10092/6323
    
    Publisher's DOI/URI
    https://doi.org/10.1016/j.cmpb.2010.11.006
    
    Publisher
    University of Canterbury. Electrical and Computer Engineering
    University of Canterbury. Mathematics and Statistics
    University of Canterbury. Mechanical Engineering
    ISSN
    0169-2607
    Collections
    • Engineering: Journal Articles [1527]
    Authors
    Chase, Geoff cc
    Le Compte, A.J.
    Suhaimi, F.
    Shaw, Geoff cc
    Lynn, A.
    Lin, J.
    Pretty, Christopher cc
    Razak, N.N.
    Parente, J.D.
    Hann, C.E.
    Preiser, J-C.
    Desaive, T.
    show all
    Abstract

    Tight glycemic control (TGC) has emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and costs. However, repeating initial successful TGC trials that reduced mortality and other outcomes has proven difficult with more failures than successes. Hence, there has been growing debate over the necessity of TGC, its goals, the risk of severe hypoglycemia, and target cohorts. This paper provides a review of TGC via new analyses of data from several clinical trials, including SPRINT, Glucontrol and a recent NICU study. It thus provides both a review of the problem and major background factors driving it, as well as a novel model-based analysis designed to examine these dynamics from a new perspective. Using these clinical results and analysis, the goal is to develop new insights that shed greater light on the leading factors that make TGC difficult and inconsistent, as well as the requirements they thus impose on the design and implementation of TGC protocols. A model-based analysis of insulin sensitivity using data from three different critical care units comprising over 75,000 hours of clinical data is used to analyse variability in metabolic dynamics using a clinically validated model-based insulin sensitivity metric (SI). Variation in SI provides a new interpretation and explanation for the variable results seen (across cohorts and studies) in applying TGC. In particular, significant intra- and inter- patient variability in insulin resistance (1/ SI) is seen be a major confounder that makes TGC difficult over diverse cohorts, yielding variable results over many published studies and protocols. Further factors that exacerbate this variability in glycemic outcome are found to include measurement frequency and whether a protocol is blind to carbohydrate administration.

    Citation
    Chase, J.G., Le Compte, A.J., Suhaimi, F., Shaw, G.M., Lynn, A., Lin, J., Pretty, C.G., Razak, N.N., Parente, J.D., Hann, C.E., Preiser, J-C., Desaive, T. (2011) Tight Glycemic Control in Critical Care - The leading role of insulin sensitivity and patient variability – A review and model-based analysis. Computer Methods and Programs in Biomedicine, 102(2), pp. 156-171.
    This citation is automatically generated and may be unreliable. Use as a guide only.
    Keywords
    Critical Care; Glycemic Control; Variability; Modeling; Insulin Sensitivity; TGC; ICU; Mortality; SPRINT; Glucontrol; Intensive Insulin Therapy; IIT
    ANZSRC Fields of Research
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive care
    40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineering
    32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinology
    32 - Biomedical and clinical sciences::3201 - Cardiovascular medicine and haematology::320102 - Haematology
    08 - Information and Computing Sciences::0802 - Computation Theory and Mathematics
    Rights
    https://hdl.handle.net/10092/17651

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    • Insulin Sensitivity, Its Variability and Glycemic Outcome: A model-based analysis of the difficulty in achieving tight glycemic control in critical care 

      Chase, Geoff; Le Compte, A.J.; Preiser, J.C.; Pretty, C.G.; Moorhead, K.T.; Penning, S.; Shaw, Geoff; Desaive, T. (University of Canterbury. Mechanical Engineering, 2011)
      Effective tight glycemic control (TGC) can improve outcomes in intensive care unit (ICU) patients, but is difficult to achieve consistently. Glycemic level and variability, particularly early in a patient’s stay, are a ...
    • Physiological Modeling, Tight Glycemic Control and the ICU Clinician: What are models and how can they affect practice? 

      Chase, Geoff; Le Compte, A.J.; Preiser, J.C.; Shaw, Geoff; Penning, S.; Desaive, T. (University of Canterbury. Mechanical Engineering, 2011)
      Critically ill patients are highly variable in their response to care and treatment. This variability and the search for improved outcomes have led to a significant increase in the use of protocolized care to reduce ...
    • Validation of a Model-based Virtual Trials Method for Tight Glycemic Control in Intensive Care 

      Suhaimi, F.M.; Chase, Geoff; LeCompte, A.J.; Preiser, J-C,; Lin, J.; Shaw, Geoff (University of Canterbury. Mechanical Engineering, 2010)
      In-silico virtual trials offer significant advantages in cost, time and safety. However, no such method has been truly validated with clinical data. This study tests 2 matched cohorts from an independent ICU treated with ...
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