Literature DB >> 17331614

Chronic hyperglycemia but not glucose variability determines HbA1c levels in well-controlled patients with type 2 diabetes.

Klaus-Dieter Kohnert1, Petra Augstein, Peter Heinke, Eckhard Zander, Karolina Peterson, Ernst-Joachim Freyse, Eckhard Salzsieder.   

Abstract

To determine the relationships between HbA1c, characteristics of hyperglycemia and glycemic variability in well-controlled type 2 diabetes (HbA1c<7.0%), we studied 63 primary-care patients (36 men and 27 women), aged 34-75 years, with type 2 diabetes for 2-32 years using a continuous glucose monitoring system (CGMS) and standardized meal test (MMT). Duration of hyperglycemia (>8.0 mmol/l), standard deviation score (S.D.-score) and mean amplitude of glycemic excursions (MAGE) were analyzed from CGMS data and postprandial glucose during MMT (PPG(MMT)). Patients were hyperglycemic for 5.7h/day (median), experienced 4.1 hyperglycemic episodes/day, and 78% exceeded PPG levels of 8.0 mmol/l. HbA1c, though associated with the extent of hyperglycemia (r=0.40, p<0.001), failed to correlate with S.D.-score and MAGE. Multiple regression analysis demonstrated that HbA1c was predicted only by fasting glucose (R(2)=0.24, p<0.001) but neither by PPG(MMT), duration of hyperglycemia, S.D.-score nor MAGE. CGMS and meal test provide the tools for complete characterization of glycemia in type 2 diabetes. In well-controlled type 2 diabetes, HbA1c correlates with chronic hyperglycemia but not with glucose variability. Our data suggest that chronic sustained hyperglycemia and glucose fluctuations are two independent components of dysglycemia in diabetes.

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Year:  2007        PMID: 17331614     DOI: 10.1016/j.diabres.2007.01.021

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  22 in total

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Authors:  Klaus-Dieter Kohnert; Peter Heinke; Lutz Vogt; Eckhard Salzsieder
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Review 2.  Arguments for and against the role of glucose variability in the development of diabetes complications.

Authors:  Eric S Kilpatrick
Journal:  J Diabetes Sci Technol       Date:  2009-07-01

Review 3.  The role of self-monitoring of blood glucose in glucagon-like peptide-1-based treatment approaches: a European expert recommendation.

Authors:  Oliver Schnell; Hasan Alawi; Tadej Battelino; Antonio Ceriello; Peter Diem; Anne-Marie Felton; Wladyslaw Grzeszczak; Kari Harno; Peter Kempler; Ilhan Satman; Bruno Vergès
Journal:  J Diabetes Sci Technol       Date:  2012-05-01

4.  The Karlsburg Diabetes Management System: translation from research to eHealth application.

Authors:  Eckhard Salzsieder; Petra Augstein
Journal:  J Diabetes Sci Technol       Date:  2011-01-01

5.  The Relationship Between CGM-Derived Metrics, A1C, and Risk of Hypoglycemia in Older Adults With Type 1 Diabetes.

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Journal:  Diabetes Care       Date:  2020-05-27       Impact factor: 19.112

Review 6.  The role of self-monitoring of blood glucose in patients treated with SGLT-2 inhibitors: a European expert recommendation.

Authors:  Oliver Schnell; Hasan Alawi; Tadej Battelino; Antonio Ceriello; Peter Diem; Anne-Marie Felton; Kari Harno; Ilhan Satman; Bruno Vergès
Journal:  J Diabetes Sci Technol       Date:  2014-05-18

Review 7.  Self-monitoring of blood glucose in type 2 diabetes: recent studies.

Authors:  Oliver Schnell; Hasan Alawi; Tadej Battelino; Antonio Ceriello; Peter Diem; Anne-Marie Felton; Wladyslaw Grzeszczak; Kari Harno; Peter Kempler; Ilhan Satman; Bruno Vergès
Journal:  J Diabetes Sci Technol       Date:  2013-03-01

Review 8.  The impact of glycemic variability on diabetic peripheral neuropathy.

Authors:  Heung Yong Jin; Kyung Ae Lee; Tae Sun Park
Journal:  Endocrine       Date:  2016-07-06       Impact factor: 3.633

9.  Feasibility and acceptability of continuous glucose monitoring and accelerometer technology in exercising individuals with type 2 diabetes.

Authors:  Nancy A Allen; Cynthia S Jacelon; Stuart R Chipkin
Journal:  J Clin Nurs       Date:  2009-02       Impact factor: 3.036

10.  New indices for predicting glycaemic variability.

Authors:  Akifumi Ogawa; Akinori Hayashi; Eriko Kishihara; Sonomi Yoshino; Akihiro Takeuchi; Masayoshi Shichiri
Journal:  PLoS One       Date:  2012-09-27       Impact factor: 3.240

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