Open Access Journal of Diabetes & Metabolism J o u r n a l o f D i a b e t e s & M e t a b o l i s m ISSN: 2155-6156 Tong et al., J Diabetes Metab 2016, 7:2 http://dx.doi.org/10.4172/2155-6156.1000652 Volume 7 • Issue 2 • 1000652 J Diabetes Metab ISSN: 2155-6156 JDM, an open access journal Research Article Abstract Objective: The aim of this study was to evaluate Glycemic Variability (GV) among older adults with type 2 diabetes in a tertiary center (Putrajaya Hospital) using the Continuous Glucose Monitoring System (CGMS) and to compare the GV between patients with optimal versus suboptimal glycemic control. Research designs and methods: A total of 138 patients (69 with HbA1c<7% (53 mmol/mol) and another 69 with HbA1c ≥ 7% (53 mmol/mol) with type 2 diabetes age 65 and above were included in this study. All subjects underwent baseline clinical evaluation followed by monitoring using CGMS for six days. Data from CGMS was extracted to calculate GV using the Easy GV software available at www.easygv.co.uk. Results: The patients with HbA1c ≥ 7% (53 mmol/l) had signifcantly longer duration of diabetes, higher use of insulin, more micro-vascular complications, higher systolic blood pressure, higher fasting blood glucose, total cholesterol and triglyceride levels. The Mean Amplitude Glycemic Excursions (MAGE), Continuous Overlapping Net Glycemic Action (CONGA, Standard Deviation (SD), M-value, Average Daily Risk Ratio (ADDR), Lability Index (LI) , High Blood Glucose Index (HBGI), Mean of Daily Difference (MODD), Glycemic Risk Assessment in Diabetes Equation (GRADE) and Mean Absolute Glucose (MAG) were signifcantly higher in the group with HbA1c ≥ 7% (53 mmol/mol). The Low Blood Glucose Index (LBGI) [2.14(IQR 3.4) versus 2.11(2.6)] which represents risks of hypoglycemia was the only parameter which was not signifcantly different between both groups. Conclusions: We present the glycemic variability parameters for older adults with type 2 diabetes. Among this population, the risk of hypoglycemia is similar between those with optimal HbA1c versus their counterparts. This underscores the importance of looking out for hypoglycemia in every older individual with type 2 diabetes. Glycemic Variability among Older Adults with Type 2 Diabetes Chin Voon Tong*, Nurain Mohd Noor, Masni Mohamad, Shalena Nesaratnam and Zanariah Hussein Endocrine Unit, Department of Medicine, Putrajaya Hospital, Malaysia *Corresponding author: Chin Voon Tong, Endocrine Unit, Department of Medicine, Putrajaya Hospital, Pusat Pentadbiran Kerajaan Persekutuan Presinct 7, 62250 Putrajaya, Malaysia, Tel: +60126026702; Fax: +0388889169; E-mail: tchinvoon@yahoo.com Received February 16, 2016; Accepted February 26, 2016; Published February 29, 2016 Citation: Tong CV, Noor NM, Mohamad M, Nesaratnam S, Hussein Z (2016) Glycemic Variability among Older Adults with Type 2 Diabetes. J Diabetes Metab 7: 652. doi:10.4172/2155-6156.1000652 Copyright: © 2016 Tong CV, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Keywords: Type 2 diabetes; Glycemic variability; Older adults; Hypoglycemia; Continuous glucose monitoring system (CGMS); HbA1c; Microvascular complications; Macrovascular complications Introduction Diabetes in the older adults (defned as those aged 65 years and above) is an emerging epidemic associated with higher mortality, reduced functional status and increased risk of institutionalization [1]. In the local setting, the latest National Health and Morbidity Survey (NHMS 2015) reported that 17.5% of Malaysian adults aged 18 and above have diabetes. In the older population, above the age of 65, the prevalence was between 37 – 39% [2]. Terefore a special focus on care of older persons with diabetes is pertinent to reduce the multitude of diabetic related complications and to improve the quality of life among the patients. Both sustained hyperglycemia and acute glucose fuctuations contribute to the dysglycemia in diabetes and lead to diabetes complications through two main mechanisms; excessive protein glycation and oxidative stress [3]. Landmark studies have confrmed that post prandial hyperglycemia is an independent risk factor for macrovascular complications [4]. However, glycemic variability (GV) that includes both upward and downward acute glucose changes has been found to cause deleterious efects on endothelial function and oxidative stress which lead to development and progression of cardiovascular complications in diabetes as well. It was found that in type 2 diabetes, the urinary excretion of 8-iso-PGF2α, which is a reliable marker of the activation of oxidative stress was highly, positively correlated with GV [5]. HbA1c which refects average blood glucose over 2-3 months, is the commonest tool used to refect glycemic control. However it cannot be used to assess postprandial hyperglycemia and fasting hyperglycemia separately and is unable to refect short term glycemic changes or variability. Various other factors such as renal function, anemia and certain hemoglobinopathies also afect the validity of HbA1c results. Even patients who have HbA1c levels below 7% (53 mmol/mol) have been found to have GV and postprandial hyperglycemia [6]. Because of the limitations of HbA1c, other tools are required to measure GV. However GV is a complex phenomenon with intra and inter-day components as well as minor and major fuctuations; thus several approaches have been developed to quantify it. By using data from the continuous glucose monitoring system (CGMS), various objective parameters can be assessed. Tis include the standard deviation (SD), M-Value, Mean Amplitude of Glucose Excursion (MAGE), average daily risk ratio (ADRR), Lability Index (LI), Low Blood Glucose Index (LBGI), High Blood Glucose Index (HBGI) continuous overlapping net glycemic action (CONGA), mean of daily diferences (MODD), Glycemic Risk Assessment in Diabetes Equation (GRADE) and Mean absolute Glucose (MAG). The GV among older adults with type 2 diabetes in a multiracial population like ours is not known. The aim of this study was to