Evaluating the Accuracy and Large Inaccuracy of Two Continuous Glucose Monitoring Systems

Abstract

Objective: This study evaluated the accuracy and large inaccuracy of the Freestyle Ò Navigator (FSN) (Abbott Diabetes Care, Alameda, CA) and Dexcom Ò SEVEN Ò PLUS (DSP) (Dexcom, Inc., San Diego, CA) continuous glucose monitoring (CGM) systems during closed-loop studies. Research Design and Methods: Paired CGM and plasma glucose values (7,182 data pairs) were collected, every 15-60 min, from 32 adults (36.2 -9.3 years) and 20 adolescents (15.3 -1.5 years) with type 1 diabetes who participated in closed-loop studies. Levels 1, 2, and 3 of large sensor error with increasing severity were defined according to absolute relative deviation greater than or equal to -40%, -50%, and -60% at a reference glucose level of ‡ 6 mmol/L or absolute deviation greater than or equal to -2.4 mmol/L, -3.0 mmol/L, and -3.6 mmol/L at a reference glucose level of < 6 mmol/L. Results: Median absolute relative deviation was 9.9% for FSN and 12.6% for DSP. Proportions of data points in Zones A and B of Clarke error grid analysis were similar (96.4% for FSN vs. 97.8% for DSP). Large sensor over-reading, which increases risk of insulin over-delivery and hypoglycemia, occurred two-to threefold more frequently with DSP than FSN (once every 2.5, 4.6, and 10.7 days of FSN use vs. 1.2, 2.0, and 3.7 days of DSP use for Level 1-3 errors, respectively). At Levels 2 and 3, large sensor errors lasting 1 h or longer were absent with FSN but persisted with DSP. Conclusions: FSN and DSP differ substantially in the frequency and duration of large inaccuracy despite only modest differences in conventional measures of numerical and clinical accuracy. Further evaluations are required to confirm that FSN is more suitable for integration into closed-loop delivery systems.

Dexcom G4AP: An Advanced Continuous Glucose Monitor for the Artificial Pancreas

“…These errors are particularly difficult to recover from if they persist for a long time (e.g. greater than 60 min 19 ). Large errors in magnitude and duration may result in large increases or decreases in insulin delivery, the effects of which may last for several hours.…”

“…Results for Navigator and SEVEN PLUS are estimated from the published results of Leelarathna and coauthors. 19 using the G4AP and 58 min using the G4 PLATINUM. The single sensor signal responsible for this severe error can be seen in Figure 8, which shows that the poor performance of both G4 algorithms was caused by an inaccurate finger stick calibration (8:00 am).…”

Performance Comparison of CGM Systems

“…same time using a reference system (see, eg, Bailey et al, 3 Damiano et al, 4 Freckmann et al, 5 Garg et al, 6 Kovatchev et al, 7 Kropff et al, 8 Leelarathna et al, 9 Luijf et al, 10 Luijf et al, 11 Weinstein et al, 12 and Zschornack et al 13 )…”

Future of Automated Insulin Delivery Systems

“…Indeed, this was a problem with previous CGM generations. 22 For most devices, the distribution of sensor errors yields a curvilinear relationship between MARD and percentage large sensor deviations (>20% error), which defines a sweet spot of MARD <10% and large deviations <12% (Fig. 1).…”