scholarly journals Relationship Between Blood Glucose Variability in Ambulatory Glucose Profile and Standardized Continuous Glucose Monitoring Metrics; A Pilot Study

2020 ◽  
Author(s):  
Akemi 09034837312 ◽  
Yosuke Okada ◽  
Keiichi Torimoto ◽  
Yoshiya Tanaka
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Control Group ◽  
Diabetic Patients ◽  
Cutoff Value ◽  
Glucose Profile ◽  
Blood Glucose Variability ◽  
The Relationship

Abstract Background: Treatment indexes using continuous glucose monitoring (CGM) have become standardized internationally, and the use of ambulatory glucose profile (AGP) is currently recommended. However, the relationship between AGP indexes and standardized CGM metrics has not been investigated. Using flash glucose monitoring (FGM), this retrospective study served to evaluate the association of the inter-quartile range (IQR) of AGP with standardized CGM metrics.Methods: The study subjects were 30 patients with type 2 diabetes mellitus (T2DM) and 23 non-diabetic patients (control group). We evaluated average IQR (AIQR) and standardized CGM metrics. The primary endpoint was the relationship between AIQR and Time in range (TIR) in a 24-hour period.Results: In the T2DM group, the AIQR was notably high and correlated negatively with TIR, and positively with Time above range, average glucose level, SD, CV, and MODD. For the T2DM group, the AIQR was notably lower in patients who achieved TIR>70%, compared to those who did not. The AIQR cutoff value, as determined by ROC analysis, was 28.3 mg/dL for those who achieved TIR>70%. No association was detected between the presence of hypoglycemia and AIQR.Conclusions: Our study is the first to provide the AIQR cutoff value for achieving the TIR target value. The range of blood glucose variability in AGP was associated with indexes of intra- and interday variations and hyperglycemia. Our results provide new perspectives in the yet-to-be established methods for evaluation of AGP in practical clinical settings.

scholarly journals Relationship between bloodinterstitial glucose variability in ambulatory glucose profile and standardized continuous glucose monitoring metrics; A pilot study

2020 ◽  
Author(s):  
Akemi Tokutsu ◽  
Yosuke Okada ◽  
Keiichi Torimoto ◽  
Yoshiya Tanaka
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Control Group ◽  
Diabetic Patients ◽  
Cutoff Value ◽  
Glucose Profile ◽  
Daily Difference ◽  
Interstitial Glucose ◽  
The Relationship

Abstract Background Treatment indexes using continuous glucose monitoring (CGM) have become standardized internationally, and the use of ambulatory glucose profile (AGP) is currently recommended. However, the relationship between AGP indexes and standardized CGM metrics has not been investigated. Using flash glucose monitoring (FGM), this retrospective study served to evaluate the association of the inter-quartile range (IQR) of AGP with standardized CGM metrics. Methods The study subjects were 30 patients with type 2 diabetes mellitus (T2DM) and 23 non-diabetic patients (control group). We evaluated average IQR (AIQR) and standardized CGM metrics. The primary endpoint was the relationship between AIQR and Time in range (TIR) in a 24-hour period. Results In the T2DM group, the AIQR was notably high and correlated negatively with TIR, and positively with Time above range, average interstitial glucose level, standard deviation of interstitial glucose , coefficient of variation of interstitial glucose , and mean of daily difference in blood glucose (MODD) . For the T2DM group, the AIQR was notably lower in patients who achieved TIR>70%, compared to those who did not. The AIQR cutoff value, as determined by ROC analysis, was 28.3 mg/dL for those who achieved TIR>70%. No association was detected between the presence of hypoglycemia and AIQR. Conclusions Our study is the first to provide the AIQR cutoff value for achieving the TIR target value. The range of interstitial glucose variability in AGP was associated with indexes of intra- and interday variations and hyperglycemia. Our results provide new perspectives in the yet-to-be established methods for evaluation of AGP in practical clinical settings.

Daily improvement of blood glucose profile by continuous glucose monitoring (CGM)

2019 ◽  
Vol 6 (2) ◽  
pp. 24-26 ◽  
Author(s):  
Hiroshi Bando ◽  
Yoshikane Kato ◽  
Setsuko Kanazawa ◽  
Mayumi Tanaka ◽  
Etsuko Sueki ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Insulin Injection ◽  
Glucose Variability ◽  
Diabetic Control ◽  
Future Research ◽  
Glucose Profile ◽  
Insulin Glargin ◽  
Blood Glucose Profile

Background: The problem of glucose variability has been in focus for type 1 diabetes mellitus (T1DM) on insulin treatment. Daily profile of blood glucose was studied on Continuous Glucose Monitoring (CGM) using Free Style Libre. Case presentation and results: Patient is 54 year-old T1DM female, with HbA1c 7.8%. The blood glucose variability was measured by Free Style Libre. Insulin therapy included multiple daily insulin injection (MDI) of Insulin Glargin and Aspart. The result revealed unstable blood glucose profile in day 1 and 2. After that, the level and fluctuation of blood glucose gradually decreased from day 3 to 14. Average blood glucose in a day was 174mg/dL, 159mg/dL, 138mg/dL, 125mg/dL and 110mg/dL, in day 2, 4, 7, 9, 11, respectively. There was a discrepancy of HbA1c between 7.8% by laboratory measurement and 6.3% presumed value by Free Style Libre. Discussion and Conclusion: Free Style Libre showed satisfactory results as CGM. There was lower HbA1c value by presumed calculation, which would be possibly due to every 15minutes measurement and difficulty in checking abrupt glucose surges. CGM application would probably bring diabetic subjects behavioral change of life style, leading to better diabetic control. These results would become reference data in CGM study for future research.

scholarly journals Characterizing Blood Glucose Variability Using New Metrics with Continuous Glucose Monitoring Data

2011 ◽  
Vol 5 (4) ◽  
pp. 871-878 ◽  
Author(s):  
Cynthia R. Marling ◽  
Jay H. Shubrook ◽  
Stanley J. Vernier ◽  
Matthew T. Wiley ◽  
Frank L. Schwartz
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Monitoring Data ◽  
Blood Glucose Variability

scholarly journals Assessment of Hyperglycemia, Hypoglycemia and Inter-Day Glucose Variability Using Continuous Glucose Monitoring among Diabetic Patients on Chronic Hemodialysis

2021 ◽  
Vol 10 (18) ◽  
pp. 4116
Author(s):  
Maria Divani ◽  
Panagiotis I. Georgianos ◽  
Triantafyllos Didangelos ◽  
Vassilios Liakopoulos ◽  
Kali Makedou ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glycated Albumin ◽  
Glucose Monitoring ◽  
Area Under The Curve ◽  
Glucose Variability ◽  
Hemodialysis Patients ◽  
Chronic Hemodialysis ◽  
Diabetic Patients ◽  
Lower Efficiency ◽  
Target Glucose

Continuous glucose monitoring (CGM) facilitates the assessment of short-term glucose variability and identification of acute excursions of hyper- and hypo-glycemia. Among 37 diabetic hemodialysis patients who underwent 7-day CGM with the iPRO2 device (Medtronic Diabetes, Northridge, CA, USA), we explored the accuracy of glycated albumin (GA) and hemoglobin A1c (HbA1c) in assessing glycemic control, using CGM-derived metrics as the reference standard. In receiver operating characteristic (ROC) analysis, the area under the curve (AUC) in diagnosing a time in the target glucose range of 70–180 mg/dL (TIR70–180) in <50% of readings was higher for GA (AUC: 0.878; 95% confidence interval (CI): 0.728–0.962) as compared to HbA1c (AUC: 0.682; 95% CI: 0.508–0.825) (p < 0.01). The accuracy of GA (AUC: 0.939; 95% CI: 0.808–0.991) in detecting a time above the target glucose range > 250 mg/dL (TAR>250) in >10% of readings did not differ from that of HbA1c (AUC: 0.854; 95% CI: 0.699–0.948) (p = 0.16). GA (AUC: 0.712; 95% CI: 0.539–0.848) and HbA1c (AUC: 0.740; 95% CI: 0.570–0.870) had a similarly lower efficiency in detecting a time below target glucose range < 70 mg/dL (TBR<70) in >1% of readings (p = 0.71). Although the mean glucose levels were similar, the coefficient of variation of glucose recordings (39.2 ± 17.3% vs. 32.0 ± 7.8%, p < 0.001) and TBR<70 (median (range): 5.6% (0, 25.8) vs. 2.8% (0, 17.9)) were higher during the dialysis-on than during the dialysis-off day. In conclusion, the present study shows that among diabetic hemodialysis patients, GA had higher accuracy than HbA1c in detecting a 7-day CGM-derived TIR70–180 < 50%. However, both biomarkers provided an imprecise reflection of acute excursions of hypoglycemia and inter-day glucose variability.

Continuous Glucose Monitoring During a 100-km Race: A Case Study in an Elite Ultramarathon Runner

2015 ◽  
Vol 10 (1) ◽  
pp. 124-127 ◽  
Author(s):  
Yasuo Sengoku ◽  
Kazuteru Nakamura ◽  
Hitomi Ogata ◽  
Yoshiharu Nabekura ◽  
Shoichiro Nagasaka ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Energy Intake ◽  
Glucose Level ◽  
Continuous Glucose Monitoring ◽  
Glucose Sensor ◽  
Glucose Monitoring ◽  
Carbohydrate Intake ◽  
Current Case ◽  
Glucose Profile

The current case study intended to measure blood glucose fluctuation in 2 marathon runners during a 100-km race using a continuous glucose-monitoring system (CGMS) and investigate the relationship between glucose profile and change in running speed. Two experienced ultramarathon runners participated in this study. A CGMS glucose sensor was inserted into the subcutaneous abdominal tissue at 35 h before the 100-km race, and the glucose profile was monitored continuously until the end of the race. Race pace and energy intake during the race were recorded. Participants finished the race in 6h:51min:17s (runner A) and 8h:56min:04s (runner B), and the race-pace decrement ratios were 17.6% for runner A and 27.2% for runner B. The average relative intensity throughout the 100-km race was 89.9% ± 5.8% lactate threshold (LT) in runner A and 78.4% ± 8.6% LT in runner B. The total amount of carbohydrate intake during the race was 249 g and 366 g in runners A and B, respectively. Despite lower carbohydrate intake, runner A maintained a normal glucose level throughout the race, while runner B rapidly decreased blood glucose and became hypoglycemic after the 80-km point. These results suggest that elite ultramarathon runners may have the ability to prevent a large decrement in blood glucose level regardless of the amount of energy intake during the race to maintain higher relative running intensity.

scholarly journals Continuous Glucose Monitoring System Versus Self-Monitoring Blood Glucose in Type 1 Diabetes Mellitus Children: A Randomised Controlled Trial (RoSEC)

2021 ◽  
Vol 27 (2) ◽  
pp. 51-68
Author(s):  
Muhd Alwi Muhd Helmi ◽  
Norsa'adah Bachok ◽  
Suhaimi Hussain
Keyword(s):  
Diabetes Mellitus ◽  
Blood Glucose ◽  
Glycaemic Control ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Controlled Trial ◽  
Glucose Monitoring ◽  
Control Group ◽  
Self Monitoring ◽  
The Mean

Objectives: The primary and secondary objectives were to compare the glycaemic control and frequency of hypoglycaemia between continuous glucose monitoring system (CGMS) and self-monitoring blood glucose (SMBG). Methods: A single centre, randomised, parallel-group controlled trial was conducted involving twenty-two type one Diabetes Mellitus (T1DM) patients with the mean age of 13.8 years assigned to either intervention or control group. All respondents wore the CGMS device at the beginning of the study. Intervention group (n=11) had their insulin adjusted based on the CGMS data, while the control group (n=11) was based on SMBG. Monthly average blood sugar level (BSL) and monthly mean hypoglycemic events per week (HE/wk) were measured at baseline, first month, second month, and third month. HbA1c levels were measured at baseline and in the third month. Results: The baseline characteristics were similar. The data were analysed using repeated measure analysis of variance (ANOVA). The mean difference of HbA1c within the group was not statistically significant with p=0.322. There were significant differences in the monthly mean HE/wk within and between groups, p=0.004, and p=0.037. Conclusion: In conclusion, CGMS is equivalent to SMBG in optimising glycaemic control but is more effective in detecting hypoglycaemia in children.  

Sign in / Sign up

Export Citation Format

Share Document