Literature DB >> 16443872

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.

Johannes Plank1, 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.   

Abstract

OBJECTIVE: To evaluate a fully automated algorithm for the establishment of tight glycemic control in critically ill patients and to compare the results with different routine glucose management protocols of three intensive care units (ICUs) across Europe (Graz, Prague, and London). RESEARCH DESIGN AND METHODS: Sixty patients undergoing cardiac surgery (age 67 +/- 9 years, BMI 27.7 +/- 4.9 kg/m2, 17 women) with postsurgery blood glucose levels >120 mg/dl (6.7 mmol/l) were investigated in three different ICUs (20 per center). Patients were randomized to either blood glucose management (target range 80-110 mg/dl [4.4-6.1 mmol/l]) by the fully automated model predictive control (MPC) algorithm (n = 30, 10 per center) or implemented routine glucose management protocols (n = 30, 10 per center). In all patients, arterial glucose was measured hourly to describe the glucose profile until the end of the ICU stay but for a maximum period of 48 h.
RESULTS: Compared with routine protocols, MPC treatment resulted in a significantly higher percentage of time within the target glycemic range (% median [min-max]: 52 [17-92] vs. 19 [0-71]) over 0-24 h (P < 0.01). Improved glycemic control with MPC treatment was confirmed in patients remaining in the ICU for 48 h (0-24 h: 50 [17-71] vs. 21 [4-67], P < 0.05, and 24-48 h: 65 [38-96] vs. 25 [8-79], P < 0.05, for MPC [n = 16] vs. routine protocol [n = 13], respectively). Two hypoglycemic events (<54 mg/dl [3.0 mmol/l]) were observed with routine protocol treatment. No hypoglycemic event occurred with MPC.
CONCLUSIONS: The data suggest that the MPC algorithm is safe and effective in controlling glycemia in critically ill postsurgery patients.

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Year:  2006        PMID: 16443872     DOI: 10.2337/diacare.29.02.06.dc05-1689

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  55 in total

1.  Postprandial glycemic excursions with the use of a closed-loop platform in subjects with type 1 diabetes: a pilot study.

Authors:  Arianne C van Bon; Jeroen Hermanides; Robin Koops; Joost B L Hoekstra; J Hans DeVries
Journal:  J Diabetes Sci Technol       Date:  2010-07-01

Review 2.  Toward closing the loop: an update on insulin pumps and continuous glucose monitoring systems.

Authors:  Tandy Aye; Jen Block; Bruce Buckingham
Journal:  Endocrinol Metab Clin North Am       Date:  2010-09       Impact factor: 4.741

3.  Computer-based insulin infusion protocol improves glycemia control over manual protocol.

Authors:  Jeffrey B Boord; Mona Sharifi; Robert A Greevy; Marie R Griffin; Vivian K Lee; Ty A Webb; Michael E May; Lemuel R Waitman; Addison K May; Randolph A Miller
Journal:  J Am Med Inform Assoc       Date:  2007-02-28       Impact factor: 4.497

Review 4.  Essential elements of the native glucoregulatory system, which, if appreciated, may help improve the function of glucose controllers in the intensive care unit setting.

Authors:  Leon DeJournett
Journal:  J Diabetes Sci Technol       Date:  2010-01-01

5.  Parenteral glucose and glucose control in the critically ill: a kinetic appraisal.

Authors:  Roman Hovorka; Jeremy Cordingley
Journal:  J Diabetes Sci Technol       Date:  2007-05

6.  A stepwise approach toward closed-loop blood glucose control for intensive care unit patients: results from a feasibility study in type 1 diabetic subjects using vascular microdialysis with infrared spectrometry and a model predictive control algorithm.

Authors:  Franz Feichtner; Julia K Mader; Roland Schaller; Lukas Schaupp; Martin Ellmerer; Stefan Korsatko; Venkata R Kondepati; H Michael Heise; Malgorzata E Wilinska; Roman Hovorka; Thomas R Pieber
Journal:  J Diabetes Sci Technol       Date:  2011-07-01

7.  Evaluation of implementation of a fully automated algorithm (enhanced model predictive control) in an interacting infusion pump system for establishment of tight glycemic control in medical intensive care unit patients.

Authors:  Roman Kulnik; Johannes Plank; Christoph Pachler; Malgorzata E Wilinska; Andrea Groselj-Strele; Doris Röthlein; Matthias Wufka; Norman Kachel; Karl Heinz Smolle; Sabine Perl; Thomas Rudolf Pieber; Roman Hovorka; Martin Ellmerer
Journal:  J Diabetes Sci Technol       Date:  2008-11

8.  Tight glycemic control in the hospital.

Authors:  Martin Ellmerer; Christoph Pachler; Johannes Plank
Journal:  J Diabetes Sci Technol       Date:  2008-07

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

Authors:  Jeremy J Cordingley; 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
Journal:  Intensive Care Med       Date:  2008-07-26       Impact factor: 17.440

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

Authors:  Gerald J Kost; Nam K Tran; Victor J Abad; Richard F Louie
Journal:  Clin Chim Acta       Date:  2007-12-03       Impact factor: 3.786

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