scholarly journals Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

2019 ◽  
Vol 14 (1) ◽  
pp. 135-150 ◽  
Author(s):  
Lutz Heinemann ◽  
Michael Schoemaker ◽  
Günther Schmelzeisen-Redecker ◽  
Rolf Hinzmann ◽  
Adham Kassab ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Continuous Glucose Monitoring ◽  
Medical Devices ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
High Quality ◽  
Quality Performance ◽  
Performance Of Systems ◽  
Patients With Diabetes ◽  
The Mean

High-quality performance of medical devices for glucose monitoring is important for a safe and efficient usage of this diagnostic option by patients with diabetes. The mean absolute relative difference (MARD) parameter is used most often to characterize the measurement performance of systems for continuous glucose monitoring (CGM). Calculation of this parameter is relatively easy and comparison of the MARD numbers between different CGM systems appears to be straightforward on the first glance. However, a closer look reveals that a number of complex aspects make interpretation of the MARD numbers provided by the manufacturer for their CGM systems difficult. In this review, these aspects are discussed and considerations are made for a systematic and appropriate evaluation of the MARD in clinical trials. The MARD should not be used as the sole parameter to characterize CGM systems, especially when it comes to nonadjunctive usage of such systems.

scholarly journals Accuracy of Dexcom G6 Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients with Diabetes

2021 ◽  
Author(s):  
Georgia M. Davis ◽  
Elias K. Spanakis ◽  
Alexandra L. Migdal ◽  
Lakshmi G. Singh ◽  
Bonnie Albury ◽  
...  
Keyword(s):  
Critically Ill ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Hospitalized Patients ◽  
Matched Pair ◽  
Patients With Diabetes ◽  
Clarke Error Grid ◽  
Error Grid

<b>Background: </b>Advances in continuous glucose monitoring (CGM) have transformed ambulatory diabetes management. Until recently, inpatient use of CGM has remained investigational with limited data on its accuracy in the hospital setting. <p><b>Methods: </b>To analyze the accuracy of Dexcom G6 CGM,<b> </b>we compared retrospective matched-pair CGM and capillary point-of-care (POC) glucose data from three inpatient CGM studies (two interventional and one observational) in general medicine and surgery patients with diabetes treated with insulin. Analysis of accuracy metrics included mean absolute relative difference (MARD), median absolute relative difference (ARD), and proportion of CGM values within ±15, 20 and 30% or ±15, 20 and 30 mg/dL of POC reference values for blood glucose >100 mg/dL or ≤100 mg/dL, respectively (?/15, /20, 0/30). Clinical reliability was assessed using Clarke error grid analyses.</p> <p><b>Results: </b>A total of 218 patients were included (96% with type 2 diabetes) with a mean age of 60.6 ± 12 years. The overall MARD (n=4,067 matched glucose pairs) was 12.8% and median ARD was 10.1% [IQR 4.6, 17.6]. The proportion of readings meeting ?/15, /20 and 0/30 criteria were 68.7, 81.7, and 93.8%. Clarke error grid analysis showed 98.7% of all values in zones A+B. MARD and median ARD were higher in hypoglycemia (<70mg/dL) and severe anemia (hemoglobin <7g/dL).</p> <p><b>Conclusion: </b>Our results indicate that CGM technology is a reliable tool for hospital use and may help improve glucose monitoring in non-critically ill hospitalized patients with diabetes. </p>

scholarly journals Self-measurement of Blood Glucose and Continuous Glucose Monitoring – Is There Only One Future?

2018 ◽  
Vol 14 (2) ◽  
pp. 24 ◽  
Author(s):  
Lutz Heinemann ◽  
Andreas Stuhr
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Subcutaneous Tissue ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Management Options ◽  
Measurement Quality ◽  
Glucose Levels ◽  
Wide Range ◽  
Patients With Diabetes

Monitoring glycaemic control in patients with diabetes has evolved dramatically over the past decades. The introduction of easy-to-use systems for self-monitoring of blood glucose (SMBG) utilising capillary blood samples has resulted in the availability of a wide range of systems, providing different measurement quality. Systems for continuous glucose monitoring (CGM) – used mainly in patients with type 1 diabetes (T1D) – were made possible by the development of glucose sensors that measure glucose levels in the interstitial fluid (ISF) in the subcutaneous tissue of the skin. CGM readings might not correspond exactly to SMBG measurement results taken at the same time, especially during rapid changes in either blood glucose or ISF glucose levels. The mean absolute relative difference is the most popular method used for characterising the measurement performance of CGM systems. Unlike the International Organization for Standardization 15197:2013 criteria for SMBG systems, no accuracy standards for CGM systems exist. Measurement quality of CGM systems can vary based on several factors, limiting their safety and effective use in managing diabetes. Patients have to be trained adequately to make safe and efficient use of CGM systems (like with SMBG systems). Also, systems for CGM must be evaluated in terms of patient safety and the ability to provide accurate measurements regardless of the fluctuation of glucose levels. As new technological advancements in glucose monitoring are essential for improved management options of diabetes, such as automated insulin dosing systems, there is a need for a critical view of all such developments. It is likely that both, SMBG and CGM systems, will play important future roles in the treatment of diabetes.

scholarly journals Continuous Glucose Monitoring for the Detection of Hypoglycemia in Patients With Diabetes of the Exocrine Pancreas

2020 ◽  
pp. 193229682097474
Author(s):  
Channabasappa Shivaprasad ◽  
Kolla Gautham ◽  
Kejal Shah ◽  
Soumya Gupta ◽  
Preethika Palani ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Exocrine Pancreas ◽  
Glucose Monitoring ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Mean ◽  
Mean Time

Background: Detailed evaluations of hypoglycemia and associated indices based on continuous glucose monitoring (CGM) are limited in patients with diabetes of the exocrine pancreas. Our study sought to evaluate the frequency and pattern of hypoglycemic events and to investigate hypoglycemia-specific indices in this population. Methods: This was a cross-sectional study comprising 83 participants with diabetes of the exocrine pancreas. CGM and self-monitoring of blood glucose (SMBG) were performed on all participants for a minimum period of 72 hours. The frequency and pattern of hypoglycemic events, as well as hypoglycemia-related indices, were evaluated. Results: Hypoglycemia was detected in 90.4% of patients using CGM and 38.5% of patients using SMBG. Nocturnal hypoglycemic events were more frequent (1.9 episodes/patient) and prolonged (142 minutes) compared with day-time events (1.1 episodes/patient; 82.8 minutes, P < 0.05). The mean low blood glucose index was 2.1, and glycemic risk assessment diabetes equation hypoglycemia was 9.1%. The mean time spent below (TSB) <70 mg/dL was 9.2%, and TSB <54 mg/dL was 3.7%. The mean area under curve (AUC) <70 mg/dL was 1.7 ± 2.5 mg/dL/hour and AUC <54 mg/dL was 0.6 ± 1.3 mg/dL/hour. All of the CGM-derived hypoglycemic indices were significantly more deranged at night compared with during the day ( P < 0.05). Conclusion: Patients with diabetes of the exocrine pancreas have a high frequency of hypoglycemic episodes that are predominantly nocturnal. CGM is superior to SMBG in the detection of nocturnal and asymptomatic hypoglycemic episodes. CGM-derived hypoglycemic indices are beneficial in estimating the risk of hypoglycemia.

scholarly journals A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 479
Author(s):  
Elena Muñoz Fabra ◽  
José-Luis Díez ◽  
Jorge Bondia ◽  
Alejandro José Laguna Sanz
Keyword(s):  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Extensive Literature ◽  
Integrated Sensor ◽  
Monitoring Accuracy ◽  
The Mean

Continuous Glucose Monitoring (CGM) has been a springboard of new diabetes management technologies such as integrated sensor-pump systems, the artificial pancreas, and more recently, smart pens. It also allows patients to make better informed decisions compared to a few measurements per day from a glucometer. However, CGM accuracy is reportedly affected during exercise periods, which can impact the effectiveness of CGM-based treatments. In this review, several studies that used CGM during exercise periods are scrutinized. An extensive literature review of clinical trials including exercise and CGM in type 1 diabetes was conducted. The gathered data were critically analysed, especially the Mean Absolute Relative Difference (MARD), as the main metric of glucose accuracy. Most papers did not provide accuracy metrics that differentiated between exercise and rest (non-exercise) periods, which hindered comparative data analysis. Nevertheless, the statistic results confirmed that CGM during exercise periods is less accurate.

scholarly journals Accuracy of Dexcom G6 Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients with Diabetes

2021 ◽  
Author(s):  
Georgia M. Davis ◽  
Elias K. Spanakis ◽  
Alexandra L. Migdal ◽  
Lakshmi G. Singh ◽  
Bonnie Albury ◽  
...  
Keyword(s):  
Critically Ill ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Hospitalized Patients ◽  
Matched Pair ◽  
Patients With Diabetes ◽  
Clarke Error Grid ◽  
Error Grid

<b>Background: </b>Advances in continuous glucose monitoring (CGM) have transformed ambulatory diabetes management. Until recently, inpatient use of CGM has remained investigational with limited data on its accuracy in the hospital setting. <p><b>Methods: </b>To analyze the accuracy of Dexcom G6 CGM,<b> </b>we compared retrospective matched-pair CGM and capillary point-of-care (POC) glucose data from three inpatient CGM studies (two interventional and one observational) in general medicine and surgery patients with diabetes treated with insulin. Analysis of accuracy metrics included mean absolute relative difference (MARD), median absolute relative difference (ARD), and proportion of CGM values within ±15, 20 and 30% or ±15, 20 and 30 mg/dL of POC reference values for blood glucose >100 mg/dL or ≤100 mg/dL, respectively (?/15, /20, 0/30). Clinical reliability was assessed using Clarke error grid analyses.</p> <p><b>Results: </b>A total of 218 patients were included (96% with type 2 diabetes) with a mean age of 60.6 ± 12 years. The overall MARD (n=4,067 matched glucose pairs) was 12.8% and median ARD was 10.1% [IQR 4.6, 17.6]. The proportion of readings meeting ?/15, /20 and 0/30 criteria were 68.7, 81.7, and 93.8%. Clarke error grid analysis showed 98.7% of all values in zones A+B. MARD and median ARD were higher in hypoglycemia (<70mg/dL) and severe anemia (hemoglobin <7g/dL).</p> <p><b>Conclusion: </b>Our results indicate that CGM technology is a reliable tool for hospital use and may help improve glucose monitoring in non-critically ill hospitalized patients with diabetes. </p>

scholarly journals Simple Post-Processing of Continuous Glucose Monitoring Measurements Improves Endpoints in Clinical Trials

2019 ◽  
Vol 14 (6) ◽  
pp. 1074-1078 ◽  
Author(s):  
Morten Hasselstrøm Jensen ◽  
Claus Dethlefsen ◽  
Ole Hejlesen ◽  
Peter Vestergaard
Keyword(s):  
Clinical Trials ◽  
Clinical Research ◽  
Continuous Glucose Monitoring ◽  
State Of The Art ◽  
Glucose Monitoring ◽  
Postprandial Glucose ◽  
Relative Difference ◽  
Time Shift ◽  
Post Processing ◽  
Processing Procedure

Background: Continuous glucose monitoring (CGM) is a powerful tool to be considered both in clinical practice and clinical trials. However, CGM has been criticized for being inaccurate for many reasons including a physiological delay. This study sought to investigate the current delay issue and propose a simple post-processing procedure. Method: More than a million hours of the Dexcom G4 CGM from 472 subjects investigated in a state-of-the-art clinical trial were analyzed by time shifting the CGM measurements and comparing them to plasma glucose (PG) measurements. The resultant CGM measurements were then assessed in relation to real-world clinical research endpoints. Results: A CGM time shift of −9 minutes was optimal and reduced mean absolute relative difference (MARD) statistically significantly with 1.0% point. The MARD reduction resulted in better clinical research endpoints of hypoglycemia and postprandial glucose increments. Conclusions: The delay in CGM is still an issue. The delay in this study was identified to be 9 minutes compared to PG. With a simple post-processing approach of time shifting the CGM measurements with −9 minutes, it was possible to obtain a statistically significantly lower MARD and subsequently obtain clinical research endpoints of improved validity.

scholarly journals Variation of Mean Absolute Relative Differences of Continuous Glucose Monitoring Systems Throughout the Day

2021 ◽  
pp. 193229682199237
Author(s):  
Stefan Pleus ◽  
Andreas Stuhr ◽  
Manuela Link ◽  
Cornelia Haug ◽  
Guido Freckmann
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Number Of Factors ◽  
Marked Variability ◽  
Therapeutic Decisions ◽  
Complete Study ◽  
The Mean ◽  
Relative Differences

Background: There is an increasing use of continuous glucose monitoring (CGM) by people with diabetes. Measurement performance is often characterized by the mean absolute relative difference (MARD). However, MARD is influenced by a number of factors and little is known about whether MARD is stable throughout the day. Material and Methods: A total of 24 participants with type 1 diabetes were enrolled in the study. The study was performed for seven in-patient days. Participants wore two CGM systems in parallel and performed additional frequent blood glucose (BG) measurements. On two days, glucose excursions were induced. MARD was calculated between pairs of CGM and BG values, with BG values serving as reference values. ARD values calculated from CGM-BG pairs were grouped by hour of the day. Results were analyzed separately for glucose excursion days and for regular days. Results: Total MARDs for the complete study duration were 12.5% ± 3.6% and 13.2% ± 2.4% ( n = 24). Throughout the day marked variability of MARD was observed (8.0% ± 1.3%-16.3% ± 2.9% (G5); 9.1% ± 1.4%-16.3% ± 5.3% (FL), up to n = 157 each). Low(est) MARD values were observed before breakfast and dinner, when subjects were in or near a fasting state. Especially after breakfast and lunch, MARD values were higher than average. Conclusions: Analytical performance of the two CGM systems, assessed by MARD, was found to vary markedly throughout the day. Activities of daily life likely triggered these variations. An increasing number of CGM users base therapeutic decisions on CGM values, and they should be aware of these variations of performance throughout the day.

scholarly journals In silico imaging clinical trials: cheaper, faster, better, safer, and more scalable

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Aldo Badano
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Medical Devices ◽  
In Silico ◽  
Lessons Learned ◽  
Patient Access ◽  
High Quality ◽  
Virtual Imaging ◽  
Regulatory Evaluation

AbstractImaging clinical trials can be burdensome and often delay patient access to novel, high-quality medical devices. Tools for in silico imaging trials have significantly improved in sophistication and availability. Here, I describe some of the principal advantages of in silico imaging trials and enumerate five lessons learned during the design and execution of the first all-in silico virtual imaging clinical trial for regulatory evaluation (the VICTRE study).

The Accuracy of Continuous Glucose Monitoring in the Medical Intensive Care Unit

2021 ◽  
pp. 193229682110275
Author(s):  
Wannita Tingsarat ◽  
Patinut Buranasupkajorn ◽  
Weerapan Khovidhunkit ◽  
Patchaya Boonchaya-anant ◽  
Nitchakarn Laichuthai
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Continuous Glucose Monitoring ◽  
Medical Intensive Care Unit ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Risk Zone ◽  
Medical Intensive Care ◽  
Vasopressor Use ◽  
Error Grid

Objective: To assess the accuracy of continuous glucose monitoring (CGM) in medical intensive care unit (MICU) patients. Methods: A Medtronic Enlite® sensor accuracy was assessed versus capillary blood glucose (CBG) and plasma glucose (PG) using the mean absolute relative difference (MARD), surveillance error grid (SEG) analysis and modified Bland-Altman plots. Results: Using CBG as a reference, MARD was 6.6%. Overall, 99.7% of the CGM readings were within the “no risk” zone. No significant differences in accuracy were seen within vasopressor subgroups. Using PG as the reference, MARD was 8.8%. The surveillance error grid analysis showed 95.2% of glucose readings were within the “no risk” zone. There were no device-related adverse events. Conclusion: The CGM sensor showed acceptable accuracy in MICU patients, regardless of vasopressor use.

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