Literature DB >> 18661120

Intensive insulin therapy: enhanced Model Predictive Control algorithm versus standard care.

Jeremy J Cordingley1, Dirk Vlasselaers, Natalie C Dormand, Pieter J Wouters, Stephen D Squire, Ludovic J Chassin, Malgorzata E Wilinska, Clifford J Morgan, Roman Hovorka, Greet Van den Berghe.   

Abstract

OBJECTIVE: To investigate the effectiveness of an enhanced software Model Predictive Control (eMPC) algorithm for intravenous insulin infusion, targeted at tight glucose control in critically ill patients, over 72 h, in two intensive care units with different management protocols.
DESIGN: Comparison with standard care in a two center open randomized clinical trial.
SETTING: Two adult intensive care units in University Hospitals. PATIENTS AND PARTICIPANTS: Thirty-four critically ill patients with hyperglycaemia (glucose >120 mg/dL) or already receiving insulin infusion.
INTERVENTIONS: Patients were randomized, within each ICU, to intravenous insulin infusion advised by eMPC algorithm or the ICU's standard insulin infusion administration regimen. MEASUREMENTS AND
RESULTS: Arterial glucose concentration was measured at study entry and when advised by eMPC or measured as part of standard care. Time-weighted average glucose concentrations in patients receiving eMPC advised insulin infusions were similar [104 mg/dL (5.8 mmol/L)] in both ICUs. eMPC advised glucose measurement interval was significantly different between ICUs (1.1 vs. 1.8 h, P < 0.01). The standard care insulin algorithms resulted in significantly different time-weighted average glucose concentrations between ICUs [128 vs. 99 mg/dL (7.1 vs. 5.5 mmol/L), P < 0.01].
CONCLUSIONS: In this feasibility study the eMPC algorithm provided similar, effective and safe tight glucose control over 72 h in critically ill patients in two different ICUs. Further development is required to reduce glucose sampling interval while maintaining a low risk of hypoglycaemia.

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Year:  2008        PMID: 18661120     DOI: 10.1007/s00134-008-1236-z

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


  17 in total

1.  Intensive insulin therapy in critically ill patients.

Authors:  G van den Berghe; P Wouters; F Weekers; C Verwaest; F Bruyninckx; M Schetz; D Vlasselaers; P Ferdinande; P Lauwers; R Bouillon
Journal:  N Engl J Med       Date:  2001-11-08       Impact factor: 91.245

2.  Model predictive glycaemic regulation in critical illness using insulin and nutrition input: a pilot study.

Authors:  X W Wong; J G Chase; G M Shaw; C E Hann; T Lotz; J Lin; I Singh-Levett; L J Hollingsworth; O S W Wong; S Andreassen
Journal:  Med Eng Phys       Date:  2005-12-15       Impact factor: 2.242

3.  Glucommander: a computer-directed intravenous insulin system shown to be safe, simple, and effective in 120,618 h of operation.

Authors:  Paul C Davidson; R Dennis Steed; Bruce W Bode
Journal:  Diabetes Care       Date:  2005-10       Impact factor: 19.112

4.  Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients.

Authors:  Johannes Plank; Jan Blaha; Jeremy Cordingley; Malgorzata E Wilinska; Ludovic J Chassin; Cliff Morgan; Stephen Squire; Martin Haluzik; Jaromir Kremen; Stepan Svacina; Wolfgang Toller; Andreas Plasnik; Martin Ellmerer; Roman Hovorka; Thomas R Pieber
Journal:  Diabetes Care       Date:  2006-02       Impact factor: 19.112

5.  Implementation of a tight glycaemic control protocol using a web-based insulin dose calculator.

Authors:  A N Thomas; A E Marchant; M C Ogden; S Collin
Journal:  Anaesthesia       Date:  2005-11       Impact factor: 6.955

6.  Closing the loop: the adicol experience.

Authors:  Roman Hovorka; Ludovic J Chassin; Malgorzata E Wilinska; Valentina Canonico; Joyce Akwe Akwi; Marco Orsini Federici; Massimo Massi-Benedetti; Ivo Hutzli; Claudio Zaugg; Heiner Kaufmann; Marcel Both; Thomas Vering; Helga C Schaller; Lukas Schaupp; Manfred Bodenlenz; Thomas R Pieber
Journal:  Diabetes Technol Ther       Date:  2004-06       Impact factor: 6.118

7.  Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting.

Authors:  Anthony P Furnary; Guangqiang Gao; Gary L Grunkemeier; YingXing Wu; Kathryn J Zerr; Stephen O Bookin; H Storm Floten; Albert Starr
Journal:  J Thorac Cardiovasc Surg       Date:  2003-05       Impact factor: 5.209

Review 8.  Insulin therapy and in-hospital mortality in critically ill patients: systematic review and meta-analysis of randomized controlled trials.

Authors:  Anastassios G Pittas; Richard D Siegel; Joseph Lau
Journal:  JPEN J Parenter Enteral Nutr       Date:  2006 Mar-Apr       Impact factor: 4.016

9.  Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.

Authors:  James Stephen Krinsley
Journal:  Mayo Clin Proc       Date:  2004-08       Impact factor: 7.616

10.  How to compare adequacy of algorithms to control blood glucose in the intensive care unit?

Authors:  Greet Van den Berghe
Journal:  Crit Care       Date:  2004-03-23       Impact factor: 9.097

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  25 in total

1.  Organ dysfunction is associated with hyperglycemia in critically ill children.

Authors:  Ursula G Kyle; Jorge A Coss Bu; Curtis E Kennedy; Larry S Jefferson
Journal:  Intensive Care Med       Date:  2009-10-31       Impact factor: 17.440

2.  Feasibility of overnight closed-loop control based on hourly blood glucose measurements.

Authors:  Caroline Patte; Stefan Pleus; Paul Galley; Stefan Weinert; Cornelia Haug; Guido Freckmann
Journal:  J Diabetes Sci Technol       Date:  2012-07-01

Review 3.  The future is now: software-guided intensive insulin therapy in the critically ill.

Authors:  Rishi Rattan; Stanley A Nasraway
Journal:  J Diabetes Sci Technol       Date:  2013-03-01

4.  Use of microdialysis-based continuous glucose monitoring to drive real-time semi-closed-loop insulin infusion.

Authors:  Guido Freckmann; Nina Jendrike; Stefan Pleus; Harvey Buck; Steven Bousamra; Paul Galley; Ajay Thukral; Robin Wagner; Stefan Weinert; Cornelia Haug
Journal:  J Diabetes Sci Technol       Date:  2014-09-09

Review 5.  Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges.

Authors:  Robert S Parker; Gilles Clermont
Journal:  J R Soc Interface       Date:  2010-02-10       Impact factor: 4.118

6.  Blood glucose control in the intensive care unit: discrepancy between belief and practice.

Authors:  Dirk Vlasselaers
Journal:  Crit Care       Date:  2010-05-05       Impact factor: 9.097

Review 7.  Year in review in Intensive Care Medicine 2009: I. Pneumonia and infections, sepsis, outcome, acute renal failure and acid base, nutrition and glycaemic control.

Authors:  Massimo Antonelli; Elie Azoulay; Marc Bonten; Jean Chastre; Giuseppe Citerio; Giorgio Conti; Daniel De Backer; François Lemaire; Herwig Gerlach; Goran Hedenstierna; Michael Joannidis; Duncan Macrae; Jordi Mancebo; Salvatore M Maggiore; Alexandre Mebazaa; Jean-Charles Preiser; Jerôme Pugin; Jan Wernerman; Haibo Zhang
Journal:  Intensive Care Med       Date:  2010-01-08       Impact factor: 17.440

8.  Computerization of the Yale insulin infusion protocol and potential insights into causes of hypoglycemia with intravenous insulin.

Authors:  Michael R Marvin; Silvio E Inzucchi; Brian J Besterman
Journal:  Diabetes Technol Ther       Date:  2013-01-04       Impact factor: 6.118

9.  Intensive Care Unit Insulin Delivery Algorithms: Why So Many? How to Choose?

Authors:  Garry M Steil; Dorothee Deiss; Judy Shih; Bruce Buckingham; Stuart Weinzimer; Michael S D Agus
Journal:  J Diabetes Sci Technol       Date:  2009-01

Review 10.  Health technology assessment review: Computerized glucose regulation in the intensive care unit--how to create artificial control.

Authors:  Miriam Hoekstra; Mathijs Vogelzang; Evgeny Verbitskiy; Maarten W N Nijsten
Journal:  Crit Care       Date:  2009-10-16       Impact factor: 9.097

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