Tight Glycemic Control in Critical Care - The leading role of insulin sensitivity and patient variability – A review and model-based analysis (2011)
Type of ContentJournal Article
PublisherUniversity of Canterbury. Electrical and Computer Engineering
University of Canterbury. Mathematics and Statistics
University of Canterbury. Mechanical Engineering
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.
CitationChase, 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.
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KeywordsCritical Care; Glycemic Control; Variability; Modeling; Insulin Sensitivity; TGC; ICU; Mortality; SPRINT; Glucontrol; Intensive Insulin Therapy; IIT
ANZSRC Fields of Research32 - 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
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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 ...
Interface design and human factors considerations for model-based tight glycemic control in critical care Ward, L.; Steel., J; LeCompte, A.J.; Evans, A.; Tan, C-S.; Penning, S.; Shaw, Geoff; Desaive, T.; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2012)Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to implement. Model-based methods and computerized protocols offer the opportunity to improve TGC quality and compliance. This research ...
Ward, L.; Steel, J.; LeCompte, A.J.; Evans, A.; Tan, C.S.; Penning, S.; Shaw, Geoff; Desaive, T.; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2012)Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human ...