Literature DB >> 12401718

Prevention of hypoglycemia using risk assessment with a continuous glucose monitoring system.

Carine Choleau1, Petr Dokladal, Jean-Claude Klein, W Kenneth Ward, George S Wilson, Gérard Reach.   

Abstract

Due to the lag between sugar intake and the beginning of recovery from hypoglycemia, it is necessary to intervene in an anticipatory way if one wants to prevent, not only detect, hypoglycemia. This article presents the principle of a hypoglycemia prevention system based on risk assessment. The risk situation can be defined as the moment when the system estimates that the glucose concentration is expected to reach a hypoglycemia threshold in less than a given time (e.g., 20 min). Since there are well-known discrepancies between blood and interstitial glucose concentrations, the aim of this experimental study performed in nondiabetic rats was first to validate this strategy, and second to determine whether it can work when the glucose concentration is estimated by a glucose sensor in subcutaneous tissue rather than in blood. We used a model of controlled decrease in blood glucose concentration. A glucose infusion, the profile of which mimicked the appearance of glucose from an intragastric load, was administered either when hypoglycemia was detected or on the basis of risk recognition. Despite the lag between the beginning of the load and that of the increase in blood glucose concentration, which was in all experiments 15-20 min, hypoglycemia was fully prevented without overshoot hyperglycemia in the groups of rats in which the glucose load was started when the hypoglycemia risk was detected, on the basis of either blood or interstitial glucose concentration. This was, of course, not the case when the same glucose load was infused at the detection of the hypoglycemia threshold.

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Year:  2002        PMID: 12401718     DOI: 10.2337/diabetes.51.11.3263

Source DB:  PubMed          Journal:  Diabetes        ISSN: 0012-1797            Impact factor:   9.461


  10 in total

1.  Hypoglycemia prevention via pump attenuation and red-yellow-green "traffic" lights using continuous glucose monitoring and insulin pump data.

Authors:  Colleen S Hughes; Stephen D Patek; Marc D Breton; Boris P Kovatchev
Journal:  J Diabetes Sci Technol       Date:  2010-09-01

2.  Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms.

Authors:  B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

3.  Response to nocturnal alarms using a real-time glucose sensor.

Authors:  Bruce Buckingham; Jen Block; Jonathan Burdick; Andrea Kalajian; Craig Kollman; Michael Choy; Darrell M Wilson; Peter Chase
Journal:  Diabetes Technol Ther       Date:  2005-06       Impact factor: 6.118

4.  Recent advances in continuous glucose monitoring: biocompatibility of glucose sensors for implantation in subcutis.

Authors:  Peter H Kvist; Henrik E Jensen
Journal:  J Diabetes Sci Technol       Date:  2007-09

5.  Historical data enhances safety supervision system performance in T1DM insulin therapy risk management.

Authors:  Colleen Hughes-Karvetski; Stephen D Patek; Marc D Breton; Boris P Kovatchev
Journal:  Comput Methods Programs Biomed       Date:  2012-02-17       Impact factor: 5.428

6.  Contribution of an intrinsic lag of continuous glucose monitoring systems to differences in measured and actual glucose concentrations changing at variable rates in vitro.

Authors:  Raymond J Davey; Chee Low; Timothy W Jones; Paul A Fournier
Journal:  J Diabetes Sci Technol       Date:  2010-11-01

7.  Diabetes: Models, Signals, and Control.

Authors:  Claudio Cobelli; Chiara Dalla Man; Giovanni Sparacino; Lalo Magni; Giuseppe De Nicolao; Boris P Kovatchev
Journal:  IEEE Rev Biomed Eng       Date:  2009-01-01

8.  Statistical hypoglycemia prediction.

Authors:  Fraser Cameron; Günter Niemeyer; Karen Gundy-Burlet; Bruce Buckingham
Journal:  J Diabetes Sci Technol       Date:  2008-07

9.  Hypoglycemia detection and prediction using continuous glucose monitoring-a study on hypoglycemic clamp data.

Authors:  Cesar C Palerm; B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2007-09

Review 10.  "Smart" continuous glucose monitoring sensors: on-line signal processing issues.

Authors:  Giovanni Sparacino; Andrea Facchinetti; Claudio Cobelli
Journal:  Sensors (Basel)       Date:  2010-07-12       Impact factor: 3.576

  10 in total

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