Literature DB >> 21210080

The metrics of glycaemic control in critical care.

Iain M J Mackenzie1, Tony Whitehouse, Peter G Nightingale.   

Abstract

INTRODUCTION: Trials of tight glucose control have compared measures of central tendency, such as average blood glucose, and yielded conflicting results. Other metrics, such as standard deviation, reflect different properties of glucose control and are also associated with changes in outcome. It is possible, therefore, that the conflicting results from interventional studies arise from effects on glycaemic control that have not been reported.
METHODS: Using glucose measurements from patients admitted to four adult intensive care units in one UK hospital, we sought to identify metrics of glycaemic control, examine the relationship between them and identify the metrics that are both independently and most strongly associated with outcome.
RESULTS: We examined nine previously described metrics and identified a further four. Cluster analysis classified these metrics into two families, namely, those reflecting measures of central tendency and those reflecting measures of dispersion. A measure of minimum glucose was also identified but related to neither family. Plots of the quintiles of these metrics against hospital mortality revealed population-specific relationships. Areas under receiver-operating characteristic curves could not identify an optimum metric of central tendency or dispersion. Using odds ratios, we were able to show that the effect of these metrics is independent of one another.
CONCLUSION: Our results suggest that glycaemic control is associated with outcome on the basis of three independent metrics, reflecting measures of central tendency, measures of dispersion and a measure of minimum glucose.

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Year:  2011        PMID: 21210080     DOI: 10.1007/s00134-010-2103-2

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN: 0342-4642            Impact factor:   17.440


  45 in total

1.  Mean glucose level is not an independent risk factor for mortality in mixed ICU patients.

Authors:  Jack J M Ligtenberg; Sofie Meijering; Ymkje Stienstra; Iwan C C van der Horst; Mathijs Vogelzang; Maarten W N Nijsten; Jaap E Tulleken; Jan G Zijlstra
Journal:  Intensive Care Med       Date:  2006-02-14       Impact factor: 17.440

2.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

3.  Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.

Authors:  James Stephen Krinsley
Journal:  Mayo Clin Proc       Date:  2003-12       Impact factor: 7.616

4.  Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients.

Authors:  Christoph Pachler; Johannes Plank; Heinz Weinhandl; Ludovic J Chassin; Malgorzata E Wilinska; Roman Kulnik; Peter Kaufmann; Karl-Heinz Smolle; Ernst Pilger; Thomas R Pieber; Martin Ellmerer; Roman Hovorka
Journal:  Intensive Care Med       Date:  2008-02-23       Impact factor: 17.440

5.  Introduction of intensive glycaemic control into a neurosurgical intensive care unit: a retrospective cohort study.

Authors:  Marc D Wittenberg; David J Gattas; Angela Ryan; Richard Totaro
Journal:  Crit Care Resusc       Date:  2008-09       Impact factor: 2.159

6.  Intensive versus conventional insulin therapy: a randomized controlled trial in medical and surgical critically ill patients.

Authors:  Yaseen M Arabi; Ousama C Dabbagh; Hani M Tamim; Abdullah A Al-Shimemeri; Ziad A Memish; Samir H Haddad; Sofia J Syed; Hema R Giridhar; Asgar H Rishu; Mouhamad O Al-Daker; Salim H Kahoul; Riette J Britts; Maram H Sakkijha
Journal:  Crit Care Med       Date:  2008-12       Impact factor: 7.598

7.  Assessment of the severity of hypoglycemia and glycemic lability in type 1 diabetic subjects undergoing islet transplantation.

Authors:  Edmond A Ryan; Tami Shandro; Kristy Green; Breay W Paty; Peter A Senior; David Bigam; A M James Shapiro; Marie-Christine Vantyghem
Journal:  Diabetes       Date:  2004-04       Impact factor: 9.461

8.  Glucose variability is associated with intensive care unit mortality.

Authors:  Jeroen Hermanides; Titia M Vriesendorp; Robert J Bosman; Durk F Zandstra; Joost B Hoekstra; J Hans Devries
Journal:  Crit Care Med       Date:  2010-03       Impact factor: 7.598

9.  The impact of early hypoglycemia and blood glucose variability on outcome in critical illness.

Authors:  Sean M Bagshaw; Rinaldo Bellomo; Michael J Jacka; Moritoki Egi; Graeme K Hart; Carol George
Journal:  Crit Care       Date:  2009-06-17       Impact factor: 9.097

10.  The impact of the severity of sepsis on the risk of hypoglycaemia and glycaemic variability.

Authors:  Reiner M Waeschle; Onnen Moerer; Reinhard Hilgers; Peter Herrmann; Peter Neumann; Michael Quintel
Journal:  Crit Care       Date:  2008-10-21       Impact factor: 9.097

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  31 in total

1.  Random errors in insulin infusion concentrations.

Authors:  Richard Pierson; Ari Ercole; Barbara Bewley; Iain Mackenzie
Journal:  Intensive Care Med       Date:  2012-04-18       Impact factor: 17.440

2.  Assessing inpatient glycemic control: what are the next steps?

Authors:  Curtiss B Cook; Kay E Wellik; Gail L Kongable; Jianfen Shu
Journal:  J Diabetes Sci Technol       Date:  2012-03-01

3.  Understanding glycemic control in the critically ill: three domains are better than one.

Authors:  James S Krinsley
Journal:  Intensive Care Med       Date:  2011-01-06       Impact factor: 17.440

4.  Comparative Simulation Study of Glucose Control Methods Designed for Use in the Intensive Care Unit Setting via a Novel Controller Scoring Metric.

Authors:  Jeremy DeJournett; Leon DeJournett
Journal:  J Diabetes Sci Technol       Date:  2017-06-22

5.  Multiplicative surrogate standard deviation: a group metric for the glycemic variability of individual hospitalized patients.

Authors:  Susan S Braithwaite; Guillermo E Umpierrez; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

6.  Dynamic properties of glucose complexity during the course of critical illness: a pilot study.

Authors:  Emmanuel Godat; Jean-Charles Preiser; Jean-Christophe Aude; Pierre Kalfon
Journal:  J Clin Monit Comput       Date:  2019-03-19       Impact factor: 2.502

7.  The Development of a Continuous Intravascular Glucose Monitoring Sensor.

Authors:  Barry C Crane; Nicholas P Barwell; Palepu Gopal; Mannam Gopichand; Timothy Higgs; Tony D James; Christopher M Jones; Alasdair Mackenzie; Krishna Prasad Mulavisala; William Paterson
Journal:  J Diabetes Sci Technol       Date:  2015-06-01

8.  Blood glucose level and outcome after cardiac arrest: insights from a large registry in the hypothermia era.

Authors:  Fabrice Daviaud; Florence Dumas; Nadège Demars; Guillaume Geri; Adrien Bouglé; Tristan Morichau-Beauchant; Yên-Lan Nguyen; Wulfran Bougouin; Frédéric Pène; Julien Charpentier; Alain Cariou
Journal:  Intensive Care Med       Date:  2014-03-25       Impact factor: 17.440

Review 9.  Reporting on Glucose Control Metrics in the Intensive Care Unit.

Authors:  Tironi Rafael Machado; Preiser Jean-Charles
Journal:  Eur Endocrinol       Date:  2015-08-19

Review 10.  Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence.

Authors:  Susan S Braithwaite
Journal:  Curr Diab Rep       Date:  2013-02       Impact factor: 4.810

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