scholarly journals Establishment of normal reference ranges for glycemic variability in Chinese subjects using continuous glucose monitoring

2011 ◽  
Vol 17 (1) ◽  
pp. CR9-CR13 ◽  
Author(s):  
Jian Zhou ◽  
Hong Li ◽  
Xingwu Ran ◽  
Wenying Yang ◽  
Qiang Li ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Reference Ranges ◽  
Normal Reference ◽  
Chinese Subjects

Reference values of glycemic variability indicators based on data from professional continuous glucose monitoring

2020 ◽  
Vol 21 (4) ◽  
pp. 41-46
Author(s):  
A. S. Sudnitsyna ◽  
◽  
L. A. Suplotova ◽  
N. V. Romanova ◽  
K. A. Sidorenko ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Carbohydrate Metabolism ◽  
Continuous Glucose Monitoring ◽  
Reference Values ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Reference Ranges ◽  
Sensor Glucose ◽  
The Subject

Glycemia variability (GV) is an important factor in assessing the quality of glycemic control, as it contributes to the development of micro- and macrovascular complications of diabetes. Currently, there are mathematical methods for assessing GV, obtained using data from professional continuous glucose monitoring (PCGM). PCGM is one of the most modern, innovative technologies that allow assessing the quality of glycemic control and GV in patients with diabetes. The widespread clinical use of PCGM and the interpretation of the data obtained are limited by the lack of generally accepted reference values, as well as by the cost of technology. Reference ranges are needed to interpret the PCGM data in order to improve the quality of glycemic control in patients with carbohydrate metabolic disorders. Aim. Determine the reference ranges for glycemic variability indicators based on the data of professional continuous glucose monitoring to assess the quality of glycemic control. Materials and methods. We studied a population of people without carbohydrate metabolism disorders. A portable Medtronic iPro2 system (USA) was used for PCGM. A sensor was introduced into the subcutaneous fat of the subject, with the help of which 288 glucose measurements were made per day. Calibration was carried out by the subject himself 4 times a day using an individual glucometer. GV parameters were calculated using the Care Link iPro2 Medtronic and EasyGV version 9.0 programs in order to work out the reference ranges. The duration of the study inclusion period was 2 months. The observation period of the participants was 6 days. Results. As a result of the study, the following reference ranges were obtained: the median sensor glucose was 5.0 [4.8; 5.4] mmol/l, TIR – 98.0% [95.0; 99.0], TAR – 0.0% [0.0; 0.0], TBR – 1.5% [1.0; 5.0], GMI – 5.4% [5.3; 5.6], CV – 13.6% [11.6; 15.1], SD – 0.7 mmol/l [0.6; 0.9], MAGE – 1.5 mmol/l [1.2; 1.7], MAG – 0.7 mmol/l/hour [0.6; 0.9], M-Value – 3.7 mmol/l [1.8; 4.4], J-index – 10.4 [9.4; 13.1], CONGA – 4.6 mmol/l [4.5; 5.0], HBGI – 0.7 [0.6; 0.9], LBGI – 2.9 [1.5; 3.2], ADRR – 1.1 [1.0; 2.3]. When conducting a comparative analysis of indicators of glycemic variability, it was found that there were no statistically significant differences depending on age, gender and BMI. Only TBR had statistically significant gender differences (p = 0.007). When carrying out the correlation analysis, only GMI, sensor glucose, M-value, J-index, CONGA, LBGI indicators were statistically significantly correlated with all indicators of the time spent in the ranges. Conclusion. In the course of the study, reference ranges for GV indicators were determined – TIR, TAR, TBR, GMI, CV, sensor glucose, SD, MAGE, MAG, M-Value, J-index, CONGA, HBGI, LBGI, ADRR in the russian population. The obtained values will help physicians in the interpretation of the PNMG data, the wider use of the method in clinical practice, and the expansion of diagnostic capabilities for disorders of carbohydrate metabolism.

863-P: In Patients without Diabetes, Glycemic Variability Derived from Continuous Glucose Monitoring (CGM) Data Relates to Hyperglycemia More Than Insulin Resistance

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 863-P
Author(s):  
YUAN ZHANG ◽  
EVAN A. OLAWSKY ◽  
ALISON C. ALVEAR ◽  
LYNN E. EBERLY ◽  
LISA S. CHOW
Keyword(s):  
Insulin Resistance ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability

Glycemic Variability and Insulin Needs in Patients with Type 1 Diabetes Mellitus Supplemented with Vitamin D: A Pilot Study Using Continuous Glucose Monitoring System

2018 ◽  
Vol 14 (4) ◽  
pp. 395-403 ◽  
Author(s):  
Karem Mileo Felício ◽  
Ana Carolina Contente Braga de Souza ◽  
Joao Felicio Abrahao Neto ◽  
Franciane Trindade Cunha de Melo ◽  
Carolina Tavares Carvalho ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Vitamin D ◽  
Type 1 Diabetes ◽  
Pilot Study ◽  
Type 1 Diabetes Mellitus ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability

scholarly journals Enlarged glycemic variability in sulfonylurea-treated well-controlled type 2 diabetics identified using continuous glucose monitoring

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fumi Uemura ◽  
Yosuke Okada ◽  
Keiichi Torimoto ◽  
Yoshiya Tanaka
Keyword(s):  
Glucose Level ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
High Dose ◽  
Type 2 Diabetics ◽  
Time In Range ◽  
The Difference ◽  
Glycated Hemoglobin Level

AbstractTime in range (TIR) is an index of glycemic control obtained from continuous glucose monitoring (CGM). The aim was to compare the glycemic variability of treatment with sulfonylureas (SUs) in type 2 diabetes mellitus (T2DM) with well-controlled glucose level (TIR > 70%). The study subjects were 123 patients selected T2DM who underwent CGM more than 24 h on admission without changing treatment. The primary endpoint was the difference in glycemic variability, while the secondary endpoint was the difference in time below range < 54 mg/dL; TBR < 54, between the SU (n = 63) and non-SU (n = 60) groups. The standard deviation, percentage coefficient of variation (%CV), and maximum glucose level were higher in the SU group than in the non-SU group, and TBR < 54 was longer in the high-dose SU patients. SU treatment was identified as a significant factor that affected %CV (β: 2.678, p = 0.034). High-dose SU use contributed to prolonged TBR < 54 (β: 0.487, p = 0.028). Our study identified enlarged glycemic variability in sulfonylurea-treated well-controlled T2DM patients and high-dose SU use was associated with TBR < 54. The results highlight the need for careful adjustment of the SU dose, irrespective of glycated hemoglobin level or TIR value.

Resistance to Data Loss of Glycemic Variability Measurements in Long-Term Continuous Glucose Monitoring

2018 ◽  
Vol 20 (12) ◽  
pp. 833-842 ◽  
Author(s):  
Przemysław Kucharski ◽  
Konrad Pagacz ◽  
Agnieszka Szadkowska ◽  
Wojciech Młynarski ◽  
Andrzej Romanowski ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Data Loss
Sign in / Sign up

Export Citation Format

Share Document