Skip Navigation
Skip to contents

Endocrinol Metab : Endocrinology and Metabolism

clarivate
OPEN ACCESS
SEARCH
Search

Author index

Page Path
HOME > BROWSE ARTICLES > Author index
Search
Sang-Ouk Chin  (Chin SO) 1 Article
Obesity and Metabolism
Factors Associated with Glycemic Variability in Patients with Type 2 Diabetes: Focus on Oral Hypoglycemic Agents and Cardiovascular Risk Factors
Soyeon Yoo, Sang-Ouk Chin, Sang-Ah Lee, Gwanpyo Koh
Endocrinol Metab. 2015;30(3):352-360.   Published online August 4, 2015
DOI: https://doi.org/10.3803/EnM.2015.30.3.352
  • 4,567 View
  • 51 Download
  • 10 Web of Science
  • 10 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

The role of glycemic variability (GV) in development of cardiovascular diseases remains controversial, and factors that determine glucose fluctuation in patients with diabetes are unknown. We investigated relationships between GV indices, kinds of oral hypoglycemic agents (OHAs), and cardiovascular risk factors in patients with type 2 diabetes mellitus (T2DM).

Methods

We analyzed 209 patients with T2DM. The GV index (standard deviation [SD] and mean absolute glucose change [MAG]) were calculated from 7-point self-monitoring of blood glucose profiles. The patients were classified into four groups according to whether they take OHAs known as GV-lowering (A) and GV-increasing (B): 1 (A only), 2 (neither), 3 (both A and B), and 4 (B only). The 10-year risk for atherosclerotic cardiovascular disease (ASCVD) was calculated using the Pooled Cohort Equations.

Results

GV indices were significantly higher in patients taking sulfonylureas (SUs), but lower in those taking dipeptidyl peptidase-4 inhibitors. In hierarchical regression analysis, the use of SUs remained independent correlates of the SD (β=0.209, P=0.009) and MAG (β=0.214, P=0.011). In four OHA groups, GV indices increased progressively from group 1 to group 4. However, these did not differ according to quartiles of 10-year ASCVD risk.

Conclusion

GV indices correlated significantly with the use of OHAs, particularly SU, and differed significantly according to combination of OHAs. However, cardiovascular risk factors and 10-year ASCVD risk were not related to GV indices. These findings suggest that GV is largely determined by properties of OHAs and not to cardiovascular complications in patients with T2DM.

Citations

Citations to this article as recorded by  
  • Comparative Effectiveness of Oral Hypoglycemic Agents for Glycemic Control and Glycemic Variability in Patients with Type 2 Diabetes Mellitus: Using Flash Glucose Monitoring
    Poongothai Venkatachalapathy, Karthik Kumar Dos Alagarswamy Mohandoss, Murali Munisamy, Mohan Sellappan
    Current Diabetes Reviews.2025;[Epub]     CrossRef
  • Prognostic value of longitudinal HbA1c variability in predicting the development of diabetic sensorimotor polyneuropathy among patients with type 2 diabetes mellitus: A prospective cohort observational study
    Yun‐Ru Lai, Wen‐Chan Chiu, Chih‐Cheng Huang, Ben‐Chung Cheng, I‐Hsun Yu, Chia‐Te Kung, Ting Yin Lin, Hui Ching Chiang, Chun‐En Aurea Kuo, Cheng‐Hsien Lu
    Journal of Diabetes Investigation.2024; 15(3): 326.     CrossRef
  • Influence of dipeptidyl peptidase-4 inhibitors on glycemic variability in patients with type 2 diabetes: A meta-analysis of randomized controlled trials
    Shangyu Chai, Ruya Zhang, Ye Zhang, Richard David Carr, Yiman Zheng, Swapnil Rajpathak, Miao Yu
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Glycemic Variability in Subjects with Diabetes and Hypogonadism during Testosterone Replacement Treatment: A Pilot Study
    Giuseppe Defeudis, Ernesto Maddaloni, Giovanni Rossini, Alfonso Maria Di Tommaso, Rossella Mazzilli, Paolo Di Palma, Paolo Pozzilli, Nicola Napoli
    Journal of Clinical Medicine.2022; 11(18): 5333.     CrossRef
  • New Insights into the Role of Visit-to-Visit Glycemic Variability and Blood Pressure Variability in Cardiovascular Disease Risk
    Jin J. Zhou, Daniel S. Nuyujukian, Peter D. Reaven
    Current Cardiology Reports.2021;[Epub]     CrossRef
  • Prevalence of glycemic variability and factors associated with the glycemic arrays among end-stage kidney disease patients on chronic hemodialysis
    Abdul Hanif Khan Yusof Khan, Nor Fadhlina Zakaria, Muhammad Adil Zainal Abidin, Nor Azmi Kamaruddin
    Medicine.2021; 100(30): e26729.     CrossRef
  • Dipeptidyl-Peptidase-IV Inhibitors, Imigliptin and Alogliptin, Improve Beta-Cell Function in Type 2 Diabetes
    Xu Liu, Yang Liu, Hongzhong Liu, Haiyan Li, Jianhong Yang, Pei Hu, Xinhua Xiao, Dongyang Liu
    Frontiers in Endocrinology.2021;[Epub]     CrossRef
  • HbA 1C variability and hypoglycemia hospitalization in adults with type 1 and type 2 diabetes: A nested case-control study
    Victor W. Zhong, Juhaeri Juhaeri, Stephen R. Cole, Christina M. Shay, Penny Gordon-Larsen, Evangelos Kontopantelis, Elizabeth J. Mayer-Davis
    Journal of Diabetes and its Complications.2018; 32(2): 203.     CrossRef
  • Glucose fluctuation and the resultant endothelial injury are correlated with pancreatic β cell dysfunction in patients with coronary artery disease
    Makoto Murata, Hitoshi Adachi, Shigeru Oshima, Masahiko Kurabayashi
    Diabetes Research and Clinical Practice.2017; 131: 107.     CrossRef
  • Efficacy of lifestyle interventions in patients with type 2 diabetes: A systematic review and meta-analysis
    Xiao-Li Huang, Jian-Hua Pan, Dan Chen, Jing Chen, Fang Chen, Tao-Tao Hu
    European Journal of Internal Medicine.2016; 27: 37.     CrossRef
Close layer

Endocrinol Metab : Endocrinology and Metabolism
TOP