Horm Metab Res 2009; 41(2): 137-141
DOI: 10.1055/s-0028-1128143
Original

© Georg Thieme Verlag KG Stuttgart · New York

Relationships between Glucose Variability and Conventional Measures of Glycemic Control in Continuously Monitored Patients with Type 2 Diabetes

K.-D. Kohnert 1 , L. Vogt 2 , P. Augstein 1 , P. Heinke 1 , E. Zander 3 , K. Peterson 1 , E.-J. Freyse 1 , E. Salzsieder 1
  • 1Institute of Diabetes “Gerhardt Katsch” Karlsburg, Karlsburg, Germany
  • 2Diabetes Service Center Karlsburg, Karlsburg, Germany
  • 3Clinics for Diabetes and Metabolic Diseases, Karlsburg, Germany
Further Information

Publication History

received 29.10.2008

accepted 19.12.2008

Publication Date:
12 February 2009 (online)

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Abstract

Given the importance of glucose variability in the development of diabetic complications, the present study used continuous glucose monitoring (CGM) to determine various indices of glucose variability and to investigate their relationships with conventional measures of chronic sustained hyperglycemia. We examined 53 women and 61 men, aged 36–79 years afflicted with type 2 diabetes for 1–24 years. The following indices of glycemic variability were computed from CGM data sets: mean amplitude of glycemic excursions (MAGE), CGM glucose range, interquartile range (IQR), SD-score, and average daily risk range (ADRR). CGM measurements and self-monitored blood glucose (SMBG) records were used to calculate mean CGM sensor glucose and mean SMBG, respectively. In simple correlation analysis, the indices of glucose variability showed weak correlations with HbA1c: MAGE (r=0.27, p<0.01), CGM glucose range (r=0.21, p<0.05), IQR (r=0.31, p<0.01), SD-score (r=0.34, p<0.001), and ADRR (r=0.24, p<0.05). These indices were found to differ at identical HbA1c among several patients, as reflected by diurnal excursions of different frequency and magnitude. With the exception of ADRR, stronger correlations were found between mean SMBG and the other variability indices (r=0.51–0.63, p<0.01 for all). CGM provides various indices of glycemic variability not captured by conventional measures of glycemic control. Detection of the location and the magnitude of glucose fluctuations by CGM should aid in optimal treatment of glycemic disorders in type 2 diabetes.