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 ◽  
...  

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.

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Marcelo Rocha Nasser Hissa ◽  
Priscilla Nogueira Gomes Hissa ◽  
Sérgio Botelho Guimarães ◽  
Miguel Nasser Hissa

Abstract Background Studies highlight the inaccuracy of glycated hemoglobin (HbA1c) for the assessment of glycemic control in dialysis diabetics and suggest the use of continuous glucose monitoring (CGM) as an alternative. Of the CGMs, FreeStyle Libre® is the most used in worldwide, but there is still no consensus on its use in dialysis. Method A 3-week prospective study was performed with 12 patients comparing capillary and interstitial glucose during dialysis. Results Comparing capillary and interstitial measurements, similar values were observed in pre-dialysis in the 1st week (184.1 ± 69.5 mg/dl and 173.1 ± 78.9 mg/dl, respectively, p = 0.303), in patients with body mass index less than 24.9 kg/m2 (214.2 ± 72.2 mg/dl and 201.3 ± 77.0 mg/dl respectively, p = 0.466), in those dialysis fluid loss less than 2 l (185.5 ± 82.6 mg/dl and 183.1 ± 94.0 mg/dl respectively and p = 0.805) and in those with hemoglobin greater than 12 g/dl (152.0 ± 35, 5 mg/dl and 129.5 ± 47.4 mg/dl respectively, p = 0.016). In the correlation of the capillary measurement with the interstitial sensor, it was observed that the proportions in the Clarke Error Grid of zone A, zone B, zone C, zone D and zone E were 62.5%, 27.1%, 0.0%, 10.4% and 0.0% respectively and in the Parkes error grid in zone A, zone B, zone C, zone D and zone E were 80.6%, 9.7%, 9.7% 0.0% and 0.0%, respectively. Conclusion The mean absolute relative difference in dialysis patients is higher than the general population without end-stage renal disease. However, clinical decision-making based on the values measured by the system can be made with a good margin based on the correlation between interstitial and capillary measurements.


2021 ◽  
Author(s):  
Marcelo Rocha Nasser Hissa ◽  
Priscilla Nogueira Gomes Hissa ◽  
Sérgio Botelho Guimarães ◽  
Miguel Nasser Hissa

Abstract Background Studies highlight the inaccuracy of glycated hemoglobin (HbA1c) for the assessment of glycemic control in dialysis diabetics and suggest the use of continuous glucose monitoring (CGM) as an alternative. Of the CGMs, FreeStyle Libre ® is the most used in worldwide, but there is still no consensus on its use in dialysis. Method: A 3-week prospective study was performed with 12 patients comparing capillary and interstitial glucose during dialysis. Results Comparing capillary and interstitial measurements, similar values were observed in pre-dialysis in the first week (184.1 ± 69.5 mg/dl and 173.1 ± 78.9 mg/dl, respectively, p = 0.303), in patients with body mass index less than 24.9 kg/m2 (214.2 ± 72.2 mg/dl and 201.3 ± 77.0 mg/dl respectively, p = 0.466), in those dialysis fluid loss less than 2 liters (185.5 ± 82.6 mg/dl and 183.1 ± 94.0 mg/dl respectively and p = 0.805) and in those with hemoglobin greater than 12g/dl (152.0 ± 35, 5 mg/dl and 129.5 ± 47.4 mg/dl respectively, p = 0.016). In the correlation of the capillary measurement with the interstitial sensor, it was observed that the proportions in the Clarke Error Grid of zone A, zone B, zone C, zone D and zone E were 62.5%, 27.1%, 0.0 %, 10.4% and 0.0% respectively and in the Parkes Error Grid in zone A, zone B, zone C, zone D and zone E were 80.6%, 9.7%, 9.7% 0.0% and 0.0%, respectively. Conclusion The mean absolute relative difference in dialysis patients is higher than the general population without end-stage renal disease. However, clinical decision-making based on the values measured by the system can be made with a good margin based on the correlation between interstitial and capillary measurements.


2021 ◽  
pp. 193229682110275
Author(s):  
Wannita Tingsarat ◽  
Patinut Buranasupkajorn ◽  
Weerapan Khovidhunkit ◽  
Patchaya Boonchaya-anant ◽  
Nitchakarn Laichuthai

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.


2021 ◽  
Author(s):  
Georgia M. Davis ◽  
Elias K. Spanakis ◽  
Alexandra L. Migdal ◽  
Lakshmi G. Singh ◽  
Bonnie Albury ◽  
...  

<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>


Author(s):  
Matt Baker ◽  
Megan E Musselman ◽  
Rachel Rogers ◽  
Richard Hellman

Abstract Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Inpatient diabetes management involves frequent assessment of glucose levels for treatment decisions. Here we describe a program for inpatient real-time continuous glucose monitoring (rtCGM) at a community hospital and the accuracy of rtCGM-based glucose estimates. Methods Adult inpatients with preexisting diabetes managed with intensive insulin therapy and a diagnosis of coronavirus disease 2019 (COVID-19) were monitored via rtCGM for safety. An rtCGM system transmitted glucose concentration and trending information at 5-minute intervals to nearby smartphones, which relayed the data to a centralized monitoring station. Hypoglycemia alerts were triggered by rtCGM values of ≤85 mg/dL, but rtCGM data were otherwise not used in management decisions; insulin dosing adjustments were based on blood glucose values measured via blood sampling. Accuracy was evaluated retrospectively by comparing rtCGM values to contemporaneous point-of-care (POC) blood glucose values. Results A total of 238 pairs of rtCGM and POC data points from 10 patients showed an overall mean absolute relative difference (MARD) of 10.3%. Clarke error grid analysis showed 99.2% of points in the clinically acceptable range, and surveillance error grid analysis showed 89.1% of points in the lowest risk category. It was determined that for 25% of the rtCGM values, discordances in rtCGM and POC values would likely have resulted in different insulin doses. Insulin dose recommendations based on rtCGM values differed by 1 to 3 units from POC-based recommendations. Conclusion rtCGM for inpatient diabetes monitoring is feasible. Evaluation of individual rtCGM-POC paired values suggested that using rtCGM data for management decisions poses minimal risks to patients. Further studies to establish the safety and cost implications of using rtCGM data for inpatient diabetes management decisions are warranted.


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