A Comparative Effectiveness Analysis of Three Continuous Glucose Monitors

Abstract

The effectiveness and safety of continuous glucose monitors (CGMs) is dependent on their accuracy and reliability. The objective of this study was to compare 3 CGMs in adult and pediatric subjects with type 1 diabetes under closed-loop blood-glucose (BG) control. Twenty-four subjects (12 adults) with type 1 diabetes each participated in one 48-hour closed-loop BG control experiment. Venous plasma glucose (PG) measurements obtained every 15 minutes (4657 values) were paired in time with corresponding CGM glucose (CGMG) measurements obtained from 3 CGMs (FreeStyle Navigator, Abbott Diabetes Care; G4 Platinum, Dexcom; Enlite, Medtronic) worn simultaneously by each subject. The Navigator and G4 Platinum (G4) had the best overall accuracy, with an aggregate mean absolute relative difference (MARD) of all paired points of 12.3 ± 12.1% and 10.8 ± 9.9%, respectively. Both had lower MARDs of all paired points than Enlite (17.9 ± 15.8%, P < .005). Very large errors (MARD > 50%) were less common with the G4 (0.5%) than with the Enlite (4.3%, P = .0001) while the number of very large errors with the Navigator (1.4%) was intermediate between the G4 and Enlite (P = .1 and P = .06, respectively). The average MARD for experiments in adolescent subjects were lower than in adult subjects for the Navigator and G4, while there was no difference for Enlite. All 3 devices had similar reliability. A comprehensive head-to-head-to-head comparison of 3 CGMs revealed marked differences in both accuracy and precision. The Navigator and G4 were found to outperform the Enlite in these areas.

Performance Evaluation of Three Continuous Glucose Monitoring Systems: Comparison of Six Sensors Per Subject in Parallel

“…The MARD and PARD results obtained from complete experiments are in agreement with previous reports about the three CGM systems, [2][3][4][5][6][7][8][9][10]12,[16][17][18][19] with the Navigator achieving better performance than the other two systems. Results obtained from core phase evaluation, i.e., during days 2 to 5 when all sensors were used in parallel minus ~24 h runin time, differ only slightly from results for complete experiments, thus the influence from run-in time and different duration of sensor usage was, in this study, less important than expected.…”

“…This result is in agreement with other studies incorporating EGA analysis. 3,8,9,12,13,[16][17][18][19]21,22 Only 70% to 80% of paired readings were found to be within the system accuracy limits of ISO 15197:2003. 20 According to ISO 15197, 95% of device readings must be within ±15 mg/dl or ±20% of the paired reference readings below or above 75 mg/dl.…”

“…In 2008, the Clinical and Laboratory Standards Institute published POCT05-A, which provides recommendations for study design and parameters of interest in the performance evaluation of CGM systems. 1 Multiple studies investigating CGM systems were published over the years; [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] only one claimed to use procedures recommended in POCT05-A. 13 A comparison of these studies, however, is difficult due to variations in subject groups 11 and study design, including use of different devices for calibration of CGM systems and for reference measurements, either overall or for different study phases.…”

Toward Biofunctional Microneedles for Stimulus Responsive Drug Delivery

“…While implantable sensors have been developed for continuous glucose monitoring, they suffer from limitations in precision and accuracy. 87 Improved sensing capabilities are on the horizon, with influences from lab-on-chip technology, potentially building on miniaturized enzymatic amperometric sensors as described by Senapati et al, where the charge of the captured target molecules is used to block ionic current through an ion-selective membrane 88 . Further advances in decreasing the required sample analysis volume are needed and reducing the size and cost of the sensors.…”

Adding exercise or subtracting sitting time for glycaemic control: where do we stand?

“…However, it should also be made clear that, while CGM offers many clinical and research advantages, it is an imperfect surrogate for venous blood glucose. Signal stability, physiological differences in interstitial glucose homeostasis, physiological/device lag-times and individual differences are all factors that require consideration when interpreting CGM data [20,21]. Further, since CGM only measures glucose levels, it does not provide any estimation of insulin sensitivity or beta cell function--key information to fully understanding glycaemic responses.…”