Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients*

Berghe, Greet Van den; Wouters, Pieter; Kesteloot, Katrien; Hilleman, Daniel E.

doi:10.1097/01.ccm.0000201408.15502.24

Cited by 184 publications

(103 citation statements)

References 14 publications

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“…They were matched by equally impressive reductions in cost per patient treated [37,38], and in reduced clinical incidence of sepsis, polyneuropathy and organ failure [36,39].…”

Section: Hyperglycemia Hypoglycemia Tgc and Patient Mortality Outcomementioning

confidence: 99%

Tight glycemic control in critical care – The leading role of insulin sensitivity and patient variability: A review and model-based analysis

Chase

Compte

Suhaimi

et al. 2011

Computer Methods and Programs in Biomedicine

123

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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 (S I ). Variation in S I 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/ S I ) 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.

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“…They were matched by equally impressive reductions in cost per patient treated [37,38], and in reduced clinical incidence of sepsis, polyneuropathy and organ failure [36,39].…”

Section: Hyperglycemia Hypoglycemia Tgc and Patient Mortality Outcomementioning

confidence: 99%

Tight glycemic control in critical care – The leading role of insulin sensitivity and patient variability: A review and model-based analysis

Chase

Compte

Suhaimi

et al. 2011

Computer Methods and Programs in Biomedicine

123

View full text Add to dashboard Cite

show abstract

“…Bandwidth can be matched to a specific TGC interval [8][9][10][11][12][13][14][15][16][17][18] (Fig. 5), here 80-110 mg/dl [16][17][18].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of point-of-care glucose testing accuracy using locally-smoothed median absolute difference curves

Kost

Tran

Abad

et al. 2008

Clinica Chimica Acta

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“…Tight glycaemic control (TGC) can reduce these adverse outcomes [2], [3], as well as reducing economic costs [4]. Hence, TGC using model-based methods has become an active research field [5].…”

Section: Introductionmentioning

confidence: 99%

Optimal Tight Glycaemic Control Supported by Differential Geometric Methods

et al. 2011

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Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients*

Abstract: Intensive insulin therapy, which reduces morbidity and mortality rates of mechanically ventilated patients admitted to a surgical intensive care unit, is associated with substantial cost savings compared with conventional insulin therapy.

Cited by 184 publications

References 14 publications

Tight glycemic control in critical care – The leading role of insulin sensitivity and patient variability: A review and model-based analysis

Tight glycemic control in critical care – The leading role of insulin sensitivity and patient variability: A review and model-based analysis

Evaluation of point-of-care glucose testing accuracy using locally-smoothed median absolute difference curves

Optimal Tight Glycaemic Control Supported by Differential Geometric Methods

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