Literature DB >> 19459770

The "glucose pentagon": assessing glycemic control of patients with diabetes mellitus by a model integrating different parameters from glucose profiles.

Andreas Thomas1, Martin Schönauer, Frank Achermann, Oliver Schnell, Markolf Hanefeld, Hans-Jürgen Ziegelasch, John Mastrototaro, Lutz Heinemann.   

Abstract

Measuring the hemoglobin A(1c) (HbA(1c)) is the standard-of-care method to assess long-term glycemic control of patients with diabetes, describing the average glycemic level. However, the HbA(1c) does not reflect acute fluctuations in glucose levels. Variability of glycemia probably has an impact on the development of diabetes-related late complications. A novel model presented in this article combines different summary measures derived from continuously recorded glucose profiles (including parameters describing glycemic variability) and the HbA(1c). The five parameters taking into account are the axes of a "glucose pentagon." Connecting the values of these parameters provided an enclosed area of a given size. For a patient with diabetes, these parameters and the connected area describe how his or her glycemia was during the monitoring period. The area of the glucose pentagon for a patient with diabetes, divided by the standard area of healthy subjects, yields a non-dimensional characteristic value defined as the glycemic risk parameter. It is assume that this risk parameter provides a more meaningful overall description of metabolic control than the HbA(1c) alone. In addition, it might also allow a better assessment of a patient's risk for developing diabetes-related late complications in comparison to the HbA(1c) alone. Of critical importance is, of course, that the clinical relevance of the glucose pentagon is verified in adequate long-term clinical studies.

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Year:  2009        PMID: 19459770     DOI: 10.1089/dia.2008.0119

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


  13 in total

1.  Prediction of the risk to develop diabetes-related late complications by means of the glucose pentagon model: analysis of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring study.

Authors:  Andreas Thomas; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2012-05-01

Review 2.  The challenges of measuring glycemic variability.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2012-05-01

3.  Evaluating Glucose Control With a Novel Composite Continuous Glucose Monitoring Index.

Authors:  Lalantha Leelarathna; Hood Thabit; Malgorzata E Wilinska; Lia Bally; Julia K Mader; Thomas R Pieber; Carsten Benesch; Sabine Arnolds; Terri Johnson; Lutz Heinemann; Norbert Hermanns; Mark L Evans; Roman Hovorka
Journal:  J Diabetes Sci Technol       Date:  2019-03-31

4.  Evaluating quality of glycemic control: graphical displays of hypo- and hyperglycemia, time in target range, and mean glucose.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2014-10-14

5.  Sensitivity of Traditional and Risk-Based Glycemic Variability Measures to the Effect of Glucose-Lowering Treatment in Type 2 Diabetes Mellitus.

Authors:  Boris Kovatchev; Guillermo Umpierrez; Andres DiGenio; Rong Zhou; Silvio E Inzucchi
Journal:  J Diabetes Sci Technol       Date:  2015-06-15

6.  A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas.

Authors:  Irl B Hirsch; Andrew K Balo; Kevin Sayer; Arturo Garcia; Bruce A Buckingham; Thomas A Peyser
Journal:  Diabetes Technol Ther       Date:  2017-06       Impact factor: 6.118

7.  The Comprehensive Glucose Pentagon: A Glucose-Centric Composite Metric for Assessing Glycemic Control in Persons With Diabetes.

Authors:  Robert A Vigersky; John Shin; Boyi Jiang; Thorsten Siegmund; Chantal McMahon; Andreas Thomas
Journal:  J Diabetes Sci Technol       Date:  2017-07-27

8.  A Review of Continuous Glucose Monitoring-Based Composite Metrics for Glycemic Control.

Authors:  Michelle Nguyen; Julia Han; Elias K Spanakis; Boris P Kovatchev; David C Klonoff
Journal:  Diabetes Technol Ther       Date:  2020-03-04       Impact factor: 6.118

9.  Differences in Glycemic Variability Between Normoglycemic and Prediabetic Subjects.

Authors:  Markolf Hanefeld; Stefan Sulk; Matthias Helbig; Andreas Thomas; Carsta Köhler
Journal:  J Diabetes Sci Technol       Date:  2014-03-02

10.  Glucose Variability: Comparison of Different Indices During Continuous Glucose Monitoring in Diabetic Patients.

Authors:  Jean-Pierre Le Floch; Laurence Kessler
Journal:  J Diabetes Sci Technol       Date:  2016-06-28
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