Literature DB >> 20388051

Hospital glucose control: safe and reliable glycemic control using enhanced model predictive control algorithm in medical intensive care unit patients.

Karin Amrein1, Martin Ellmerer, Roman Hovorka, Norman Kachel, Dieter Parcz, Stefan Korsatko, Karlheinz Smolle, Sabine Perl, Gerlies Bock, Werner Doll, Gerd Köhler, Thomas R Pieber, Johannes Plank.   

Abstract

BACKGROUND: The aim of this study was to investigate the performance of the enhanced Model Predictive Control (eMPC) algorithm for glycemic control in medical critically ill patients for the whole length of intensive care unit (ICU) stay.
METHODS: The trial was designed as a single-center, open, noncontrolled clinical investigation in a nine-bed medical ICU in a tertiary teaching hospital. In 20 patients, blood glucose (BG) was controlled with a laptop-based bedside version of the eMPC. Efficacy was assessed by percentage of time within the target range (4.4-6.1 mM; primary end point), mean BG, and BG sampling interval. Safety was assessed by the number of severe hypoglycemic episodes (<2.2 mM).
RESULTS: Twenty patients (69 +/- 11 years old; body mass index, 27.4 +/- 4.5 kg/m(2); APACHE II, 25.5 +/- 5.2) were included for a period of 7.3 days (median; interquartile range, 4.4-10.2 days) in the study. Time within target range was 58.12 +/- 10.05% (mean +/- SD). For all patients with at least 7 days in the ICU, there was no statistically significant difference between the daily mean percentage of times in target range in respect of the averages. Mean arterial BG was 5.8 +/- 0.5 mM, insulin requirement was 101.3 +/- 50.7 IU/day, and mean carbohydrate intake (enteral and parenteral nutrition) was 176.4 +/- 61.9 g/day. Three hypoglycemic episodes occurred in three subjects, corresponding to a rate of 0.02 per treatment day.
CONCLUSIONS: In our single-center, noncontrolled study the eMPC algorithm was a safe and reliable method to control BG in critically medical ICU patients for the whole length of ICU stay.

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Year:  2010        PMID: 20388051     DOI: 10.1089/dia.2009.0147

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  8 in total

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2.  In silico evaluation of an artificial pancreas combining exogenous ultrafast-acting technosphere insulin with zone model predictive control.

Authors:  Justin J Lee; Eyal Dassau; Howard Zisser; Rebecca A Harvey; Lois Jovanovič; Francis J Doyle
Journal:  J Diabetes Sci Technol       Date:  2013-01-01

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.  The intraoperative glycemic response to intravenous insulin during noncardiac surgery: a subanalysis of the DeLiT randomized trial.

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5.  A controlled study of the effectiveness of an adaptive closed-loop algorithm to minimize corticosteroid-induced stress hyperglycemia in type 1 diabetes.

Authors:  Joseph El Youssef; Jessica R Castle; Deborah L Branigan; Ryan G Massoud; Matthew E Breen; Peter G Jacobs; B Wayne Bequette; W Kenneth Ward
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6.  Comparison of Space Glucose Control and Routine Glucose Management Protocol for Glycemic Control in Critically Ill Patients: A Prospective, Randomized Clinical Study.

Authors:  Biao Xu; Wei Jiang; Chun-Yao Wang; Li Weng; Xiao-Yun Hu; Jin-Min Peng; Bin Du
Journal:  Chin Med J (Engl)       Date:  2017-09-05       Impact factor: 2.628

7.  Glucose control in intensive care: usability, efficacy and safety of Space GlucoseControl in two medical European intensive care units.

Authors:  Karin Amrein; Norman Kachel; Heike Fries; Roman Hovorka; Thomas R Pieber; Johannes Plank; Urs Wenger; Barbara Lienhardt; Marco Maggiorini
Journal:  BMC Endocr Disord       Date:  2014-07-29       Impact factor: 2.763

Review 8.  Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas.

Authors:  J Geoffrey Chase; Thomas Desaive; Julien Bohe; Miriam Cnop; Christophe De Block; Jan Gunst; Roman Hovorka; Pierre Kalfon; James Krinsley; Eric Renard; Jean-Charles Preiser
Journal:  Crit Care       Date:  2018-08-02       Impact factor: 9.097

  8 in total

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