Sang-Man Jin1, Tae-Hun Kim1, Ji Cheol Bae1, Kyu Yeon Hur1, Myung-Shik Lee1, Moon-Kyu Lee1, Jae Hyeon Kim2. 1. Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710, Republic of Korea. 2. Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710, Republic of Korea. Electronic address: jaehyeon@skku.edu.
Abstract
AIM: Factors associated with absolute and relative measures of glycemic variability have not been determined by continuous glucose monitoring (CGM) and concurrent measurement of fasting C-peptide levels. METHODS: We analyzed CGM data for subjects with type 1 diabetes (T1D; n=81) and type 2 diabetes (T2D; insulin-treated, n=168; not insulin-treated, n=231) who underwent CGM between October 2009 and September 2011 at Samsung Medical Center. Correlations between clinical factors and both standard deviation (SD) and coefficient of variance (CV) in CGM were analyzed by multiple regression. RESULTS: Regardless of the type of diabetes and insulin therapy, higher CV, but not SD, was significantly associated with a minimum glucose level of <70 mg/dL (3.9 mmol/l) in CGM (p<0.001). In T1D, fasting C-peptide levels inversely correlated with SD while BMI inversely correlated with CV, and duration of diabetes, and HDL levels positively correlated with CV. Use of pre-mixed insulin increased both SD and CV. In insulin-treated T2D, fasting C-peptide levels inversely correlated with both SD and CV while HbA1c correlated with SD, and duration of diabetes positively correlated with CV. In T2D without insulin therapy, age, BMI, HbA1c, HDL, triglyceride levels and use of sulfonylurea positively correlated with SD while HDL levels and use of sulfonylurea positively correlated with CV, and LDL levels inversely correlated with CV. CONCLUSIONS: Relative glycemic variability (CV) was determined by factors different from those that affect absolute glycemic variability (SD). Some of these factors were indicators of higher insulin sensitivity and residual insulin secretion.
AIM: Factors associated with absolute and relative measures of glycemic variability have not been determined by continuous glucose monitoring (CGM) and concurrent measurement of fasting C-peptide levels. METHODS: We analyzed CGM data for subjects with type 1 diabetes (T1D; n=81) and type 2 diabetes (T2D; insulin-treated, n=168; not insulin-treated, n=231) who underwent CGM between October 2009 and September 2011 at Samsung Medical Center. Correlations between clinical factors and both standard deviation (SD) and coefficient of variance (CV) in CGM were analyzed by multiple regression. RESULTS: Regardless of the type of diabetes and insulin therapy, higher CV, but not SD, was significantly associated with a minimum glucose level of <70 mg/dL (3.9 mmol/l) in CGM (p<0.001). In T1D, fasting C-peptide levels inversely correlated with SD while BMI inversely correlated with CV, and duration of diabetes, and HDL levels positively correlated with CV. Use of pre-mixed insulin increased both SD and CV. In insulin-treated T2D, fasting C-peptide levels inversely correlated with both SD and CV while HbA1c correlated with SD, and duration of diabetes positively correlated with CV. In T2D without insulin therapy, age, BMI, HbA1c, HDL, triglyceride levels and use of sulfonylurea positively correlated with SD while HDL levels and use of sulfonylurea positively correlated with CV, and LDL levels inversely correlated with CV. CONCLUSIONS: Relative glycemic variability (CV) was determined by factors different from those that affect absolute glycemic variability (SD). Some of these factors were indicators of higher insulin sensitivity and residual insulin secretion.
Authors: Thomas A Peyser; Andrew K Balo; Bruce A Buckingham; Irl B Hirsch; Arturo Garcia Journal: Diabetes Technol Ther Date: 2017-12-11 Impact factor: 6.118
Authors: Ana M Gómez; Oscar M Muñoz; Alejandro Marin; Maria Camila Fonseca; Martin Rondon; María Alejandra Robledo Gómez; Andrei Sanko; Dilcia Lujan; Maira García-Jaramillo; Fabian Mauricio León Vargas Journal: J Diabetes Sci Technol Date: 2018-02-16