Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability

A review and model-based analysis

J. Geoffrey Chase, Aaron J. Le Compte, Fatanah Suhaimi, Geoffrey M. Shaw, Adrienne Lynn, Jessica Lin, Christopher G. Pretty, Normy Norfiza Abdul Razak, Jacquelyn D. Parente, Christopher E. Hann, Jean Charles Preiser, Thomas Desaive

Research output: Contribution to journalArticle

70 Citations (Scopus)

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 75,000h 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.

Original languageEnglish
Pages (from-to)156-171
Number of pages16
JournalComputer Methods and Programs in Biomedicine
Volume102
Issue number2
DOIs
Publication statusPublished - 01 May 2011

Fingerprint

Insulin
Critical Care
Insulin Resistance
Mortality
Hypoglycemia
Cohort Studies
Carbohydrates
Clinical Trials
Costs and Cost Analysis
Research

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Health Informatics

Cite this

Chase, J. Geoffrey ; Le Compte, Aaron J. ; Suhaimi, Fatanah ; Shaw, Geoffrey M. ; Lynn, Adrienne ; Lin, Jessica ; Pretty, Christopher G. ; Abdul Razak, Normy Norfiza ; Parente, Jacquelyn D. ; Hann, Christopher E. ; Preiser, Jean Charles ; Desaive, Thomas. / Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability : A review and model-based analysis. In: Computer Methods and Programs in Biomedicine. 2011 ; Vol. 102, No. 2. pp. 156-171.
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Chase, JG, Le Compte, AJ, Suhaimi, F, Shaw, GM, Lynn, A, Lin, J, Pretty, CG, Abdul Razak, NN, Parente, JD, Hann, CE, Preiser, JC & 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, vol. 102, no. 2, pp. 156-171. https://doi.org/10.1016/j.cmpb.2010.11.006

Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability : A review and model-based analysis. / Chase, J. Geoffrey; Le Compte, Aaron J.; Suhaimi, Fatanah; Shaw, Geoffrey M.; Lynn, Adrienne; Lin, Jessica; Pretty, Christopher G.; Abdul Razak, Normy Norfiza; Parente, Jacquelyn D.; Hann, Christopher E.; Preiser, Jean Charles; Desaive, Thomas.

In: Computer Methods and Programs in Biomedicine, Vol. 102, No. 2, 01.05.2011, p. 156-171.

Research output: Contribution to journalArticle

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