scholarly journals Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study

2021 ◽  
Author(s):  
Daniel A Hochfellner ◽  
Amra Simic ◽  
Marlene T Taucher ◽  
Lea S Sailer ◽  
Julia Kopanz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
State Of The Art ◽  
Accuracy Assessment ◽  
Relative Difference ◽  
Medical Waste ◽  
Self Monitoring ◽  
Sensor Performance ◽  
Laboratory Reference ◽  
Error Grid

Aim of this study was to evaluate the accuracy and usability of a novel continuous glucose moni-toring (CGM) system designed for needle-free insertion and reduced environmental impact. We assessed sensor performance of two GlucoMen® Day CGM systems worn simultaneously in eight participants with type 1 diabetes. Self-monitoring of blood glucose (SMBG) was performed reg-ularly over 14 days at home. Participants underwent two standardized 5-hour meal challenges with frequent plasma glucose (PG) measurements using a laboratory reference instrument at the research center. When comparing CGM to PG the overall mean absolute relative difference (MARD) was 9.7 [2.6-14.6]%. The overall MARD of CGM vs SMBG was 13.1 [3.5-18.6]%. In the consensus error grid (CEG) analysis, 98% of both CGM/PG and CGM/SMBG pairs were in the clinically acceptable zones A and B. The analysis confirms that GlucoMen® Day CGM meets the clinical requirements for state-of-the-art CGM. The needle-free insertion technology is well toler-ated by users and reduces medical waste compared to conventional CGM systems.

scholarly journals Differences Between Flash Glucose Monitor and Fingerprick Measurements

Biosensors ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 93 ◽  
Author(s):  
Odd Staal ◽  
Heidi Hansen ◽  
Sverre Christiansen ◽  
Anders Fougner ◽  
Sven Carlsen ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Bias Correction ◽  
Relative Difference ◽  
Self Monitoring ◽  
Freestyle Libre ◽  
Poor Individual ◽  
The Individual

Freestyle Libre (FL) is a factory calibrated Flash Glucose Monitor (FGM). We investigated Mean Absolute Relative Difference (MARD) between Self Monitoring of Blood Glucose (SMBG) and FL measurements in the first day of sensor wear in 39 subjects with Type 1 diabetes. The overall MARD was 12.3%, while the individual MARDs ranged from 4% to 25%. Five participants had a MARD ≥ 20%. We estimated bias and lag between the FL and SMBG measurements. The estimated biases range from −1.8 mmol / L to 1.4 mmol / L , and lags range from 2 min to 24 min . Bias is identified as a main cause of poor individual MARDs. The biases seem to persist in days 2–7 of sensor usage. All cases of MARD ≥ 20% in the first day are eliminated by bias correction, and overall MARD is reduced from 12.3% to 9.2%, indicating that adding support for voluntary user-supplied bias correction in the FL could improve its performance.

Model estimates of the results of diabetes patients using modern glucometers with tri-color technology for displaying test results

2019 ◽  
pp. 81-89
Author(s):  
Larisa Dmitrievna Popovich ◽  
Svetlana Valentinovna Svetlichnaya ◽  
Aleksandr Alekseevich Moiseev
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Economic Benefits ◽  
Test Results ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Impact

Diabetes – a disease in which the effect of the treatment substantially depends on the patient. Known a study showed that the use of glucometers with the technology of three-color display of test results facilitates self-monitoring of blood sugar and leads to a decrease in glycated hemoglobin (HbAlc). Purpose of the study: to modeling the impact of using of a glucometer with a color-coded display on the clinical outcomes of diabetes mellitus and calculating, the potential economic benefits of reducing the hospitalization rate of patients with diabetes. Material and methods. Based on data from two studies (O. Schnell et al. and M. Baxter et al.) simulation of the reduction in the number of complications with the use of a glucometer with a color indication. In a study by O. Schnell et al. a decrease of HbA1c by 0.69 percent is shown when using the considered type of glucometers, which was the basis of the model. Results. In the model, the use of a glucometer with a color-coded display for type 1 diabetes led to a decrease in the total number of complications by 9.2 thousand over 5 years per a cohort of 40 thousand patients with different initial levels of HbA1c. In a cohort of 40 thousand patients with type 2 diabetes, the simulated number of prevented complications was 1.7 thousand over 5 years. When extrapolating these data to all patients with diabetes included in the federal register of diabetes mellitus (FRD), the number of prevented complications was 55.4 thousand cases for type 1 diabetes and 67.1 thousand cases for type 2 diabetes. The possible economic effect from the use of the device by all patients with a diagnosis of diabetes, which are included in the FRD, estimated at 1.5 billion rubles for a cohort of patients with type 1 diabetes and 5.3 billion rubles for patients with type 2 diabetes. Conclusion. Improving the effectiveness of self-monitoring, which is the result of the use of glucometers with color indicators, can potentially significantly reduce the incidence of complications in diabetes and thereby provide significant economic benefits to society.

scholarly journals The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day

2018 ◽  
Vol 12 (2) ◽  
pp. 273-281 ◽  
Author(s):  
Roberto Visentin ◽  
Enrique Campos-Náñez ◽  
Michele Schiavon ◽  
Dayu Lv ◽  
Martina Vettoretti ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
In Silico ◽  
Artificial Pancreas ◽  
Real Life ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Self Monitoring ◽  
Inhaled Insulin ◽  
Single Meal

Background: A new version of the UVA/Padova Type 1 Diabetes (T1D) Simulator is presented which provides a more realistic testing scenario. The upgrades to the previous simulator, which was accepted by the Food and Drug Administration in 2013, are described. Method: Intraday variability of insulin sensitivity (SI) has been modeled, based on clinical T1D data, accounting for both intra- and intersubject variability of daily SI. Thus, time-varying distributions of both subject’s basal insulin infusion and insulin-to-carbohydrate ratio were calculated and made available to the user. A model of “dawn” phenomenon based on clinical T1D data has been also included. Moreover, the model of subcutaneous insulin delivery has been updated with a recently developed model of commercially available fast-acting insulin analogs. Models of both intradermal and inhaled insulin pharmacokinetics have been included. Finally, new models of error affecting continuous glucose monitoring and self-monitoring of blood glucose devices have been added. Results: One hundred in silico adults, adolescent, and children have been generated according to the above modifications. The new simulator reproduces the intraday glucose variability observed in clinical data, also describing the nocturnal glucose increase, and the simulated insulin profiles reflect real life data. Conclusions: The new modifications introduced in the T1D simulator allow to extend its domain of validity from “single-meal” to “single-day” scenarios, thus enabling a more realistic framework for in silico testing of advanced diabetes technologies including glucose sensors, new insulin molecules and artificial pancreas.

Accuracy of Blood Glucose Meters for Self-Monitoring Affects Glucose Control and Hypoglycemia Rate in Children and Adolescents with Type 1 Diabetes

2015 ◽  
Vol 17 (4) ◽  
pp. 275-282 ◽  
Author(s):  
Claudia Boettcher ◽  
Axel Dost ◽  
Stefan A. Wudy ◽  
Marion Flechtner-Mors ◽  
Martin Borkenstein ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Children And Adolescents ◽  
Glucose Control ◽  
Self Monitoring

scholarly journals Use of Ecological Momentary Assessment to Measure Self-Monitoring of Blood Glucose Adherence in Youth With Type 1 Diabetes

2020 ◽  
Vol 33 (3) ◽  
pp. 280-289 ◽  
Author(s):  
Jennifer L. Warnick ◽  
Sarah C. Westen ◽  
Anastasia Albanese-O’Neill ◽  
Stephanie L. Filipp ◽  
Desmond Schatz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Ecological Momentary Assessment ◽  
Self Monitoring ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals Knowledge and Demand for Information about Islet Transplantation in Patients with Type 1 Diabetes

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Yuko Yamamoto ◽  
Masakazu Nishigaki ◽  
Naoko Kato ◽  
Michio Hayashi ◽  
Teruo Shiba ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Islet Transplantation ◽  
Cross Sectional Study ◽  
Sources Of Information ◽  
Related Factors ◽  
Cross Sectional ◽  
Self Monitoring ◽  
High Level ◽  
Source Of Information

This cross-sectional study based on self-administrated questionnaire was conducted to investigate knowledge, related factors, and sources of information regarding islet transplantation in patients with type 1 diabetes in Japan. Among 137 patients who provided valid responses, 67 (48.9%) knew about islet transplantation. Their main source of information was newspapers or magazines (56.7%) and television or radio (46.3%). However, 85.8% of patients preferred the attending physician as their source of information. Although more than half of the patients were correctly aware of issues related to islet transplantation, the following specific issues for islet transplantation were not understood or considered, and there was little knowledge of them: need for immunosuppressants, lifestyle and dietary adaptations, fewer bodily burdens, and complications. The experience of hypoglycaemia, a high level of academic background, frequent self-monitoring of blood glucose, and the use of continuous subcutaneous insulin infusion were related to higher knowledge about islet transplantation.

scholarly journals Adherence of self-monitoring of blood glucose in persons with type 1 diabetes in Sweden

2017 ◽  
Vol 5 (1) ◽  
pp. e000342 ◽  
Author(s):  
Peter Moström ◽  
Elsa Ahlén ◽  
Henrik Imberg ◽  
Per-Olof Hansson ◽  
Marcus Lind
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Self Monitoring
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