Literature DB >> 19885178

Parameters affecting postprandial blood glucose: effects of blood glucose measurement errors.

Theodor Koschinsky1, Sascha Heckermann, Lutz Heinemann.   

Abstract

BACKGROUND: The Diabetes Error Test Model (DETM) has been developed to characterize the clinical relevance of the large and varying margins of error of parameters affecting postprandial blood glucose (BG) levels, which increase the risk for hypo- or hyperglycemia.
METHODS: The DETM is based on a treatment concept aimed at normoglycemia after meals. The model includes as parameters (a) preprandial BG measurement by patient self-monitoring (SMBG), (b) patient estimate of carbohydrate amounts (CARB-P) in food, (c) effect of CARB-P on maximum BG increase, (d) effect of insulin on maximum BG decrease, and (e) insulin dosage. Covering the relevant range of preprandial BG (30-330 mg/dl), the DETM simulates the maximum effect of these parameters and their margins of error on postprandial BG values.
RESULTS: According to the DETM, a SMBG error of +20% results in normoglycemia (BG range: 60-160 mg/dl) as the postprandial outcome if preprandial BG values are in the range of 30-130 or 260-330 mg/dl, but can unexpectedly result in hypoglycemia if preprandial BG values are between 131 and 259 mg/dl. If the SMBG error of +20% is combined, e.g., with an error of CARB-P estimate in the food of +20%, hypoglycemia as the postprandial outcome is worsened. If one combines the effects of errors of more than two parameters, even with errors that are so small that they have no clinically relevant dysglycemic effect on postprandial BG per se (e.g., +/-6%), this can result in postprandial hypo- or hyperglycemic values.
CONCLUSION: The DETM simulates the effects of errors of parameters affecting postprandial BG within the clinically relevant BG range. The DETM offers the opportunity to evaluate the clinical relevance of these errors and their contribution to the increased risk of meal-related excessive glucose excursions during intensified insulin therapy.

Entities:  

Keywords:  SMBG; glucose excursions; insulin therapy; prandial insulin therapy

Year:  2008        PMID: 19885178      PMCID: PMC2769704          DOI: 10.1177/193229680800200109

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  22 in total

1.  Run-to-run control of meal-related insulin dosing.

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2.  Standards of medical care in diabetes--2007.

Authors: 
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3.  Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals.

Authors:  Guido Freckmann; Sven Hagenlocher; Annette Baumstark; Nina Jendrike; Ralph C Gillen; Katja Rössner; Cornelia Haug
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4.  Evaluating clinical accuracy of systems for self-monitoring of blood glucose.

Authors:  W L Clarke; D Cox; L A Gonder-Frederick; W Carter; S L Pohl
Journal:  Diabetes Care       Date:  1987 Sep-Oct       Impact factor: 19.112

5.  Run-to-run control of blood glucose concentrations for people with Type 1 diabetes mellitus.

Authors:  Camelia Owens; Howard Zisser; Lois Jovanovic; Bala Srinivasan; Dominique Bonvin; Francis J Doyle
Journal:  IEEE Trans Biomed Eng       Date:  2006-06       Impact factor: 4.538

6.  Randomized trial of computer-assisted insulin delivery in patients with type I diabetes beginning pump therapy.

Authors:  C M Peterson; L Jovanovic; L H Chanoch
Journal:  Am J Med       Date:  1986-07       Impact factor: 4.965

7.  Controlled multicenter study on the effect of computer assistance in intensive insulin therapy of type 1 diabetics.

Authors:  Jürgen Schrezenmeir; Kay Dirting; Peter Papazov
Journal:  Comput Methods Programs Biomed       Date:  2002-08       Impact factor: 5.428

8.  Variability of blood glucose levels in patients with type 1 diabetes mellitus on intensified insulin regimens.

Authors:  E A Moberg; P E Lins; U K Adamson
Journal:  Diabete Metab       Date:  1994 Nov-Dec

9.  The impact of non-model-related variability on blood glucose prediction.

Authors:  Jonas Kildegaard; Jette Randløv; Jens Ulrik Poulsen; Ole K Hejlesen
Journal:  Diabetes Technol Ther       Date:  2007-08       Impact factor: 6.118

10.  Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.

Authors: 
Journal:  Lancet       Date:  1998-09-12       Impact factor: 79.321

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2.  Accuracy in blood glucose measurement: what will a tightening of requirements yield?

Authors:  Lutz Heinemann; Volker Lodwig; Guido Freckmann
Journal:  J Diabetes Sci Technol       Date:  2012-03-01

3.  Statistical approach of assessing the reliability of glucose sensors: the GLYCENSIT procedure.

Authors:  Tom Van Herpe; Kristiaan Pelckmans; Jos De Brabanter; Frizo Janssens; Bart De Moor; Greet Van den Berghe
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Review 4.  Interferences and Limitations in Blood Glucose Self-Testing: An Overview of the Current Knowledge.

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Journal:  J Diabetes Sci Technol       Date:  2016-08-22
  4 in total

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