Comparisons of Fifth-, Sixth-, and Seventh-Generation Continuous Glucose Monitoring Systems.

BACKGROUND: Between-system differences for continuous glucose monitoring (CGM) devices have important clinical consequences. PURPOSE: Here we review attributes of Dexcom's fifth-, sixth-, and seventh-generation (G5, G6, and G7) CGM systems. METHODS: Accuracy metrics were derived from preapproval trials of the three systems and compared after propensity score adjustments were used to balance baseline demographic characteristics. Metrics included mean absolute relative differences (MARD) between CGM and YSI values and the proportion of CGM values within 20% or 20 mg/dL of the YSI values ("%20/20"). Ease-of-use was evaluated by formal task analysis. CONCLUSIONS: Adjusted MARD and %20/20 agreement rates were 9.0%/93.1% (abdomen-placed G5), 9.9%/92.3% (abdomen-placed G6), 9.1%/93.2% (abdomen-placed G7), and 8.2%/95.3% (arm-placed G7). Task analysis favored G7 over earlier systems. Favorable clinical outcomes such as hemoglobin A1c reduction and hypoglycemia avoidance seen with G5 and G6 are anticipated with G7 use.

Accuracy and Safety of Dexcom G7 Continuous Glucose Monitoring in Adults with Diabetes.

Background: We evaluated the accuracy and safety of a seventh generation (G7) Dexcom continuous glucose monitor (CGM) during 10.5 days of use in adults with diabetes. Methods: Adults with either type 1 or type 2 diabetes (on intensive insulin therapy or not) participated at 12 investigational sites in the United States. In-clinic visits were conducted on days 1 or 2, 4 or 7, and on the second half of day 10 or the first half of day 11 for frequent comparisons with comparator blood glucose measurements obtained with the YSI 2300 Stat Plus glucose analyzer. Participants wore sensors concurrently on the upper arm and abdomen. Accuracy evaluation included the proportion of CGM values within 15% of comparator glucose levels >100 mg/dL or within 15 mg/dL of comparator levels ≤100 mg/dL (%15/15), along with the %20/20 and %30/30 agreement rates. The mean absolute relative difference (MARD) between temporally matched CGM and comparator values was also calculated. Results: Data from 316 participants (619 sensors, 77,774 matched pairs) were analyzed. For arm- and abdomen-placed sensors, overall MARDs were 8.2% and 9.1%, respectively. Overall %15/15, %20/20, and %30/30 agreement rates were 89.6%, 95.3%, and 98.8% for arm-placed sensors and were 85.5%, 93.2%, and 98.1% for abdomen-placed sensors. Across days of wear, glucose concentration ranges, and rates of change, %20/20 agreement rates varied by no more than 9% from the overall %20/20. No serious adverse events were reported. Conclusions: The G7 CGM provides accurate glucose readings with single-digit MARD with arm or abdomen placement in adults with diabetes. Clinicaltrials.gov: NCT04794478.

Performance of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System in Pediatric Participants With Type 1 Diabetes.

BACKGROUND: The perceived value and consistent use of continuous glucose monitoring (CGM) systems depends in part on their accuracy. We assessed the performance of a sixth-generation CGM system (Dexcom G6) in children and adolescents. METHODS: Forty-nine participants (6-17 years of age, mean ± SD of 13.5 ± 3.3 years), all with type 1 diabetes, enrolled and data were available from 37. Each participant wore 1 sensor for up to 10 days and was asked to undergo an in-clinic visit lasting 6-12 hours for frequent blood glucose (BG) sample testing on one of the sensor wear days. Estimated glucose values (EGVs) from the G6 system were compared with venous BG values measured with a laboratory reference instrument (YSI). RESULTS: The overall mean absolute relative difference (MARD) for 1387 EGV-YSI pairs was 7.7%, and the overall percentage of EGVs within 20% or 20 mg/dL of the YSI reference value (for YSI > or ⩽100 mg/dL, respectively, the "%20/20") was 96.2%. The %20/20 was 92.1% on Day 1 and 91.0% on Day 10 of sensor wear. For EGVs <70 mg/dL, 92.6% of the YSI values were within 20 mg/dL and for EGVs >250 mg/dL, 100% of the YSI values were within 20%. Differences between EGVs and YSI values in over 99.9% of the pairs posed no or only slight clinical risk as evaluated by surveillance error grid analysis. CONCLUSIONS: The accuracy of the G6 CGM system in pediatrics may encourage consistent use of the system and contribute to improved glycemic outcomes in this population.

Resistance to Acetaminophen Interference in a Novel Continuous Glucose Monitoring System.

Acetaminophen (APAP) can cause erroneously high readings in real-time continuous glucose monitoring (rtCGM) systems. APAP-associated bias in an investigational rtCGM system (G6) was evaluated by taking the difference in glucose measurements between rtCGM and YSI from 1 hour before to 6 hours after a 1-g oral APAP dose in 66 subjects with type 1 or type 2 diabetes. The interference effect was defined as the average post-dose (30-90 minutes) bias minus the average baseline bias for each subject. The clinically meaningful interference effect was defined as 10 mg/dL. The G6 system's overall mean (±SD) interference effect was 3.1 ± 4.8 mg/dL (one-sided upper 95% CI = 4.1 mg/dL), significantly lower than 10 mg/dL. The G6 system's resistance to APAP interference should provide reassurance to those using the drug.

Glycemic Variability Percentage: A Novel Method for Assessing Glycemic Variability from Continuous Glucose Monitor Data.

BACKGROUND: High levels of glycemic variability are still observed in most patients with diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor for acute and chronic complications. Despite its clinical importance, there is no consensus on the optimum method for characterizing glycemic variability. METHOD: We developed a simple new metric, the glycemic variability percentage (GVP), to assess glycemic variability by analyzing the length of the continuous glucose monitoring (CGM) temporal trace normalized to the duration under evaluation. The GVP is similar to other recently proposed glycemic variability metrics, the distance traveled, and the mean absolute glucose (MAG) change. We compared results from distance traveled, MAG, GVP, standard deviation (SD), and coefficient of variation (CV) applied to simulated CGM traces accentuating the difference between amplitude and frequency of oscillations. The GVP metric was also applied to data from clinical studies for the Dexcom G4 Platinum CGM in subjects without diabetes, with type 2 diabetes, and with type 1 diabetes (adults, adolescents, and children). RESULTS: In contrast to other metrics, such as CV and SD, the distance traveled, MAG, and GVP all captured both the amplitude and frequency of glucose oscillations. The GVP metric was also able to differentiate between diabetic and nondiabetic subjects and between subjects with diabetes with low, moderate, and high glycemic variability based on interquartile analysis. CONCLUSION: A new metric for the assessment of glycemic variability has been shown to capture glycemic variability due to fluctuations in both the amplitude and frequency of glucose given by CGM data.

Application of Glycemic Variability Percentage: Implications for Continuous Glucose Monitor Utilization and Analysis of Artificial Pancreas Data.

BACKGROUND: The problem of glycemic variability has been widely acknowledged in patients with diabetes with severe insulin deficiency. In a companion article, we proposed a novel metric, the glycemic variability percentage (GVP), for assessing glycemic variability that accounts for both the amplitude and frequency of glycemic fluctuations. METHOD: We applied the new metric, the GVP, to a previously reported case of a subject using an earlier generation continuous glucose monitoring (CGM) device, in which successive periods of use were associated with an apparent decrease in glycemic variability. Results were compared with histogram distributions for the rate of change of glucose as well. The GVP was also applied to data from a published study of a bihormonal artificial pancreas system comparing results from open loop and closed loop in adolescents and in adults. RESULTS: The GVP was able to quantify the changes in glycemic variability during successive periods of CGM use. Application of the GVP to a published study of a bihormonal artificial pancreas found an increase in glycemic variability compared with other accepted metrics which suggested a decrease in glycemic variability. CONCLUSION: The GVP may be a clinically useful tool in characterizing the change in glycemic variability in subjects using CGM devices. Compared with metrics, such as the standard deviation, that focus solely on the amplitude of oscillations, the GVP, which measures both frequency and amplitude, may also be a more useful tool in assessing the true level of glycemic variability in artificial pancreas studies.

A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas.

BACKGROUND: The potential clinical benefits of continuous glucose monitoring (CGM) have been recognized for many years, but CGM is used by a small fraction of patients with diabetes. One obstacle to greater use of the technology is the lack of simplified tools for assessing glycemic control from CGM data without complicated visual displays of data. METHODS: We developed a simple new metric, the personal glycemic state (PGS), to assess glycemic control solely from continuous glucose monitoring data. PGS is a composite index that assesses four domains of glycemic control: mean glucose, glycemic variability, time in range and frequency and severity of hypoglycemia. The metric was applied to data from six clinical studies for the G4 Platinum continuous glucose monitoring system (Dexcom, San Diego, CA). The PGS was also applied to data from a study of artificial pancreas comparing results from open loop and closed loop in adolescents and in adults. RESULTS: The new metric for glycemic control, PGS, was able to characterize the quality of glycemic control in a wide range of study subjects with various mean glucose, minimal, moderate, and excessive glycemic variability and subjects on open loop versus closed loop control. CONCLUSION: A new composite metric for the assessment of glycemic control based on CGM data has been defined for use in assessing glycemic control in clinical practice and research settings. The new metric may help rapidly identify problems in glycemic control and may assist with optimizing diabetes therapy during time-constrained physician office visits.

Stability, Accuracy, and Risk Assessment of a Novel Subcutaneous Glucose Sensor.

BACKGROUND: Users of continuous glucose monitoring (CGM) systems are concerned with the frequency of inserting and calibrating new sensors, with sensor accuracy and reliability throughout the sensor's functional life, and with the risks associated with inaccurate sensor readings. METHODS: A sensor for our next-generation CGM system was tested for accuracy by comparison with self-monitored blood glucose (SMBG) values throughout 10 days of wear. Fifty subjects (49 with type 1 diabetes, 1 with type 2 diabetes, 20 male, mean ± standard deviation [SD] age 32.5 ± 18.7 years) enrolled. Subjects wore one sensor each, calibrated it once per day, and obtained multiple daily SMBG values for comparison. A total of 2739 paired CGM-SMBG values were analyzed to arrive at standard accuracy statistics and plotted on the surveillance error grid (SEG) to estimate the risk of SMBG-CGM discrepancies. RESULTS: The overall mean and median absolute relative difference (ARD) values were 9.6% and 7.2%, respectively. The median ARD values ranged from 8.9% on Day 1 to 6.5% on Day 10. SEG analysis categorized 2727 points (99.6%) as "no" or "slight" risk and 12 points (0.4%) as "moderate" or "great" risk. Thirty-nine (79.6%) of the 49 systems worked through the end of Day 10. Sensors and adhesives were well tolerated, with minimal erythema and induration. CONCLUSIONS: This new CGM system's accuracy throughout its 10-day functional life, the convenience associated with once-daily calibrations, and the high proportion of measurements in the "no risk" zone of the SEG support its nonadjunctive use in diabetes management and closed-loop insulin delivery systems.