912-P: Two Novel Pharmacokinetic Parameters Assess Dietary Glucose Concentration Changes in a Diabetic Patient Using Freestyle Libre Continuous Glucose Monitoring (CGM)

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 912-P
Author(s):  
JOHN S. MELISH
Keyword(s):  
Diabetic Patient ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring ◽  
Pharmacokinetic Parameters ◽  
Freestyle Libre ◽  
Concentration Changes

68-LB: Acute Diabetes Events and All-Cause Hospitalizations among Continuous Glucose Monitoring Device Recipients with Type 1 and Type 2 Diabetes: A Comparison of FreeStyle Libre and Dexcom

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 68-LB
Author(s):  
IRL B. HIRSCH ◽  
GREGORY J. ROBERTS ◽  
JENNIFER JOSEPH ◽  
YELENA NABUTOVSKY ◽  
NAUNIHAL VIRDI ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Monitoring Device ◽  
Freestyle Libre ◽  
Acute Diabetes

scholarly journals Relationship of Glucose Variability and Daily Lifestyle by Continuous Glucose Monitoring (CGM)

2020 ◽  
Vol 3 (3) ◽  
pp. 206-212
Author(s):  
Yamashita H ◽  
Kato Y ◽  
Bando H ◽  
Kanazawa S ◽  
Tanaka M ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Future Research ◽  
Low Carbohydrate Diet ◽  
Freestyle Libre ◽  
Low Carbohydrate ◽  
Working Day ◽  
Multiple Daily Insulin Injections ◽  
Relationship Of

Authors and collaborators have continued diabetic practice and research on low carbohydrate diet (LCD), continuous glucose monitoring (CGM), and so on. The case is a 64-year-old male with type 2 diabetes mellitus (T2DM) treated with multiple daily insulin injections (MDI). When his HbA1c was 8.2% before, he changed to take tofu instead of rice and bread. HbA1c decreased to 7.1% and 4kg of weight reduction in 2 months. Tofu is a traditional Japanese food made from soybeans, which is a suitable LCD with Protein:Fat:Carbohydrate (PFC) ratio=40:45:15 in this case. His HbA1c is recently unstable, then glucose variability was investigated by CGM using FreeStyle Libre. The glucose pattern was different due to his lifestyle, including working day, off day, playing golf, respectively. The average glucose was 143-167 mg/dL and the estimated HbA1c was 7.1%, whereas HbA1c in outclinic was 8.1%, respectively. This report will hopefully become reference data for future research.

scholarly journals Comparative Accuracy Analysis of a Real-time and an Intermittent-Scanning Continuous Glucose Monitoring System

2019 ◽  
pp. 193229681989502
Author(s):  
Manuela Link ◽  
Ulrike Kamecke ◽  
Delia Waldenmaier ◽  
Stefan Pleus ◽  
Arturo Garcia ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Comparison Method ◽  
Freestyle Libre ◽  
Glucose Meter ◽  
Error Grid ◽  
Blood Glucose Meter

Background: Currently, two different types of continuous glucose monitoring (CGM) systems are available: real time (rt) CGM systems that continuously provide glucose values and intermittent-scanning (is) CGM systems. This study compared accuracy of an rtCGM and an isCGM system when worn in parallel. Methods: Dexcom G5 Mobile (DG5) and FreeStyle Libre (FL) were worn in parallel by 27 subjects for 14 days including two clinic sessions with induced glucose excursions. The percentage of CGM values within ±20% or ±20 mg/dL of the laboratory comparison method results (YSI 2300 STAT Plus, YSI Inc., Yellow Springs, OH, United States; glucose oxidase based) or blood glucose meter values and mean absolute relative difference (MARD) were calculated. Consensus error grid and continuous glucose error grid analyses were performed to assess clinical accuracy. Results: Both systems displayed clinically accurate readings. Compared to laboratory comparison method results during clinic sessions, DG5 had 91.5% of values within ±20%/20 mg/dL and a MARD of 9.5%; FL had 82.5% of scanned values within ±20%/20 mg/dL and an MARD of 13.6%. Both systems showed a lower level of performance during the home phase and when using the blood glucose meter as reference. Conclusion: The two systems tested in this study represent two different principles of CGM. DG5 generally provided higher accordance with laboratory comparison method results than FL.

Accuracy of a 14-Day Factory-Calibrated Continuous Glucose Monitoring System With Advanced Algorithm in Pediatric and Adult Population With Diabetes

2020 ◽  
pp. 193229682095875
Author(s):  
Shridhara Alva ◽  
Timothy Bailey ◽  
Ronald Brazg ◽  
Erwin S. Budiman ◽  
Kristin Castorino ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Dynamic Range ◽  
Pediatric Population ◽  
Adult Population ◽  
Venous Blood ◽  
Time Lag ◽  
Glucose Monitoring ◽  
The United States ◽  
Relative Difference ◽  
Freestyle Libre

Background: In this study, we evaluated the analytical performance of the second-generation factory-calibrated FreeStyle Libre Flash Glucose Monitoring (FreeStyle Libre 2) System compared to plasma venous blood glucose reference, Yellow Springs Instrument 2300 (YSI). Methods: The study enrolled participants aged four and above with type 1 or type 2 diabetes at seven sites in the United States. Adult participants (18+ years) participated in three in-clinic sessions and pediatric participants (4-17 years) participated in up to two in-clinic sessions stratified to provide data for days 1, 2, 3, 7, 8, 9, 12, 13, or 14 of sensor wear. Participants aged 11+ underwent supervised glycemic manipulation during in-clinic sessions to achieve glucose levels across the measurement range of the System. Performance evaluation included accuracy measures such as the proportion of continuous glucose monitoring (CGM) values that were within ±20% or ±20 mg/dL of reference glucose values, and bias measures such as the mean absolute relative difference (MARD) between CGM and reference values. Results: Data from the 144 adults and 129 pediatric participants were analyzed. Percent of sensor results within ±20%/20 mg/dL of YSI reference were 93.2% and 92.1%, and MARD was 9.2% and 9.7% for the adults and pediatric participants, respectively. The System performed well in the hypoglycemic range, with 94.3% of the results for the adult population and 96.1% of the data for pediatric population being within 15 mg/dL of the YSI reference. The time lag was 2.4 ± 4.6 minutes for adults and 2.1 ± 5.0 minutes for pediatrics. Conclusions: The System demonstrated improved analytical accuracy performance across the dynamic range during the 14-day sensor wear period as compared to the previous-generation device. NCT#: NCT03607448 and NCT03820050

scholarly journals Time in Specific Glucose Ranges, Glucose Management Indicator, and Glycemic Variability: Impact of Continuous Glucose Monitoring (CGM) System Model and Sensor on CGM Metrics

2020 ◽  
pp. 193229682093182
Author(s):  
Stefan Pleus ◽  
Ulrike Kamecke ◽  
Delia Waldenmaier ◽  
Manuela Link ◽  
Eva Zschornack ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
International Consensus ◽  
Freestyle Libre ◽  
Pairwise Differences ◽  
Assess Quality ◽  
Glucose Management ◽  
Post Hoc ◽  
The Impact

Background: International consensus recommends a set of continuous glucose monitoring (CGM) metrics to assess quality of diabetes therapy. The impact of individual CGM sensors on these metrics has not been thoroughly studied yet. This post hoc analysis aimed at comparing time in specific glucose ranges, coefficient of variation (CV) of glucose concentrations, and glucose management indicator (GMI) between different CGM systems and different sensors of the same system. Method: A total of 20 subjects each wore two Dexcom G5 (G5) sensors and two FreeStyle Libre (FL) sensors for 14 days in parallel. Times in ranges, GMI, and CV were calculated for each 14-day sensor experiment, with up to four sensor experiments per subject. Pairwise differences between different sensors of the same CGM system as well as between sensors of different CGM system were calculated for these metrics. Results: Pairwise differences between sensors of the same model showed larger differences and larger variability for FL than for G5, with some subjects showing considerable differences between the two sensors. When pairwise differences between sensors of different CGM models were calculated, substantial differences were found in some subjects (75th percentiles of differences of time spent <70 mg/dL: 5.0%, time spent >180 mg/dL: 9.2%, and GMI: 0.42%). Conclusion: Relevant differences in CGM metrics between different models of CGM systems, and between different sensors of the same model, worn by the same study subjects were found. Such differences should be taken into consideration when these metrics are used in the treatment of diabetes.

scholarly journals Flash glucose monitoring in gestational diabetes mellitus: possibilities for assessing glycemic variability

2021 ◽  
pp. 414-419
Author(s):  
F. O. Ushanova ◽  
T. Yu. Demidova ◽  
M. Ya. Izmaylova
Keyword(s):  
Glycemic Control ◽  
Pregnant Women ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Blood Glucose Monitoring ◽  
Freestyle Libre ◽  
Glycemic Profile ◽  
Glycemic Monitoring

Introduction. Blood glucose monitoring is critical in maintaining glycemic control in women with GDM and in reducing adverse maternal and fetal outcomes. One of the tools that can help achieve optimal glycemic control during pregnancy is continuous glucose monitoring, which empowers clinicians to assess the characteristics of daily glycemic variability.The aim. Compare biweekly glycemic profiles and glycemic variability in pregnant women with GDM and in healthy pregnant women using the FreeStyle Libre flash glycemic monitoring system.Materials and methods. Analysis of the glycemic profile of 49 pregnant women aged 33.2 ± 6.1 years. The average gestational age of the women included in the study was 12.6 ± 6.4 weeks. Pregnant women were divided into 2 groups: 37 pregnant women with GDM and 12 healthy pregnant women. Each group underwent two-week glucose profile monitoring using the FreeStyle Libre continuous monitoring system. Statistical analysis was carried out using Microsoft Office Excel 2016, STATISTICA 10 programs (developed by StatSoft.Inc), EasyGV, version 9.Results. The average glycemic level in the groups was 4.724 ± 0.37 mmol/L vs 4.24 ± 0.34 mmol/L, respectively (p˂0.001). Comparative analysis of GV parameters in groups of pregnant women with and without GDM: SD – 0.908 vs 0.7213 (p˂0.05); LI – 1.5 vs 0.8 (p˂0.05); HBGI – 0.503 vs 0.42 (p˂0.05); J-index – 10.343 vs 7.9870 (p˂0.001); MOOD – 0.956 vs 0.7992 (p˂0.05); MAGE  – 2.326  vs 1.8042  (p˂0.05); ADDR  – 2.216  vs 0.4210  (p˂0.05); MAG  – 4.612  vs 2.6163  (p˂0.001), respectively. The CONGA index did not show a statistically significant difference in both groups: 3.95 vs 3.7 (p = 0.5).Conclusions. Flash-glycemic monitoring can be used to obtain more detailed information about the glycemic profile, especially when it is difficult to assess the degree of GDM compensation. Continuous glucose monitoring can facilitate the optimization of glycemic control and provide a basis for treatment decisions. 

scholarly journals Hemodialysis-Related Glycemic Disarray Proven by Continuous Glucose Monitoring: Glycemic Markers and Hypoglycemia

2021 ◽  
Author(s):  
Akinori Hayashi ◽  
Naoya Shimizu ◽  
Agena Suzuki ◽  
Kenta Matoba ◽  
Akari Momozono ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glycated Albumin ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Sensor Glucose ◽  
Time In Range ◽  
Deviation Coefficient ◽  
Glycemic Markers ◽  
Design And Methods

<b>OBJECTIVE</b> <p>There is a high risk of asymptomatic hypoglycemia associated with hemodialysis (HD) using glucose-free dialysate; therefore, the inclusion of glucose in the dialysate is believed to prevent intradialytic hypoglycemia. However, the exact glycemic fluctuation profiles and frequency of asymptomatic hypoglycemia using dialysates containing >100 mg/dL glucose have not been determined.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>We evaluated the glycemic profiles of 98 type 2 diabetes patients undergoing HD (68 men, HbA1c 6.4±1.2%, glycated albumin 20.8±6.8%) with a dialysate containing 100, 125, or 150 mg/dL glucose using continuous glucose monitoring.</p> <p><b>RESULTS</b></p> <p>Sensor glucose level (SGL) showed a sustained decrease during HD, irrespective of the dialysate glucose concentration, and reached a nadir that was lower than the dialysate glucose concentration in 49 participants (50%). Twenty-one participants (21%) presented with HD-related hypoglycemia, defined by an SGL <70 mg/dL during HD and/or between the end of HD and their next meal. All these hypoglycemic episodes were asymptomatic. Measures of glycemic variability calculated using the SGL data (standard deviation, coefficient of variation, and range of SGL) were higher and time below range (<70 mg/dL) was lower in participants who experienced HD-related hypoglycemia than in those who did not, whereas time in range between 70 and 180 mg/dL, time above range (>180 mg/dL), HbA1c and GA of the two groups were similar.</p> <p><b>CONCLUSIONS</b></p> <p>Despite the use of dialysate containing 100–150 mg/dL glucose, diabetic HD patients experienced HD-related hypoglycemia unawareness frequently. SGL may fall well below the dialysate glucose concentration toward the end of HD.<br> </p>

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