Navigator Continuous Glucose Monitoring System Research Articles

Analysis of Continuous Glucose Monitoring Data to Assess Outpatient Closed-Loop Studies: Considerations for Different Sensors

Dear Editor: Closed-loop systems have been assessed in many inpatient studies under standardized and controlled conditions but are rarely evaluated in outpatient settings. In most outpatient settings, frequent reference glucose measurements to assess the performance of closed-loop systems are impractical, and continuous glucose monitoring (CGM) could be used alternatively to estimate study outcomes. However, the ability of CGM to provide unbiased outcomes might be hindered by its suboptimal accuracy, and certain mathematical transformations of CGM data might be needed before calculating the end points. Hovorka et al.1 proposed a stochastic modification for CGM readings to provide an unbiased assessment for outpatient closed-loop studies. The authors based their analysis on data from the Navigator® CGM system (Abbott Diabetes Care, Alameda, CA). Their work was an important first step tackling the methodological issues in assessing outpatient studies but is limited by the usage of only one CGM system. We assessed whether their findings generalize to the Medtronic Sof-Sensor® glucose sensor (Medtronic Diabetes, Northridge, CA). We performed secondary analysis on data from two randomized trials (one published2 and one still being conducted) comparing conventional pump therapy with dual-hormone closed-loop delivery driven by the Sof-Sensor. We analyzed data from 23 subjects and included only nighttime data (10 p.m.–7 a.m.) to allow comparison with the work of Hovorka et al.1 Similar to Hovorka et al.,1 the unmodified CGM resulted in overestimation of the time spent in target range with closed-loop therapy (P=0.005) but not with the conventional pump therapy (P=0.22) (Table 1). This is due to, as discussed by Hovorka et al.,1 using the sensor both for driving the algorithm and for calculating the end points. In addition, our unmodified CGM resulted in significant underestimation (P=0.001) of the time spent in hyperglycemia during closed-loop therapy, reflecting that this specific sensor under-reads in the hyperglycemia range.2,3 Table 1. Comparison Between Outcome Measures of Closed-Loop Delivery and Conventional Pump Therapy Calculated Using Reference Glucose and Unmodified, Stochastic, and Corrected Continuous Glucose Monitoring We assessed whether the stochastic CGM would eliminate bias, similar to what was reported with the Navigator CGM system.1 The overestimation of time spent in target range and the underestimation of time spent in hyperglycemia were unfortunately still present (Table 1). Moreover, the stochastic CGM resulted in an additional bias in time spent in the hypoglycemia range (overestimation values, Table 1). Our studies indicate that the Sof-Sensor under-reads in the hyperglycemic range but not in the nonhyperglycemic ranges,2 comparable to observations by others.3 Reflecting these unique characteristics, we proposed a modified CGM that maps the target range from 4.0–8.0 mmol/L in the reference glucose domain to 4.0–7.0 mmol/L in the CGM domain. We adopted this 1 mmol/L difference from analysis of CGM–YSI pairs.2 This corrected CGM would alter the estimation of times spent in target range and hyperglycemia but not hypoglycemia. This corrected CGM resulted in unbiased estimates for all the three end points (Table 1). We also compared the paired difference (closed-loop–conventional pump therapy) when measured using plasma glucose data with that when measured using the unmodified CGM data, stochastic CGM data, and the corrected CGM data (Table 1). It is interesting that all CGM methods resulted in similar conclusions compared with the plasma glucose data (P>0.05). This suggests that if the paired difference is considered, then no transformation for CGM data is necessary, and raw data may provide unbiased estimates. CGM can be used as an outcome measure in closed-loop trials,4 but methodological hurdles remain to be tackled. Hovorka et al.1 proposed a stochastic CGM transformation that led to unbiased estimates with the Navigator system but not, in our data, with the Medtronic Sof-Sensor. Based on the unique characteristics of the Sof-Sensor, we proposed an alternative CGM transformation that led to unbiased estimates. Caution needs to be taken when applying these methods, and considerations for different CGM systems need to be taken.

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

This study is aimed at comparing the performance of three continuous glucose monitoring (CGM) systems following the Clinical and Laboratory Standards Institute's POCT05-A guideline, which provides recommendations for performance evaluation of CGM systems. A total of 12 subjects with type 1 diabetes were enrolled in this study. Each subject wore six CGM systems in parallel, two sensors of each CGM system [FreeStyle Navigator™ (Navigator), MiniMed Guardian® REAL-Time with Enlite sensor (Guardian), DexCom™ Seven® Plus 3rd generation (Seven Plus)]. Each sensor was used for the lifetime specified by the manufacturer. To follow POCT05-A recommendations, glucose excursions were induced on two separate occasions, and venous and capillary blood glucose (BG) concentrations were obtained every 15 min for five consecutive hours. Capillary BG concentrations were measured at least once per hour during the day and once at night. Parameters investigated were CGM-to-BG differences [mean absolute relative difference (MARD)] and sensor-to-sensor differences [precision absolute relative difference (PARD)]. Compared with capillary BG reference readings, the Navigator showed the lowest MARD, with 12.1% overall and 24.6% in the hypoglycemic range; for the Guardian and the Seven Plus, MARD was 16.2%/34.9% and 16.3%/32.7%, respectively. PARD also was lowest for the Navigator (9.6%/9.8%), followed by the Seven Plus (16.7%/25.5%) and the Guardian (18.1%/20.2%). During induced glucose excursions, MARD between CGM and BG was, again, lowest for the Navigator (14.3%), followed by the Seven Plus (15.8%) and the Guardian (19.2%). In this study, two sensors of each of the three CGM systems were compared in a setting following POCT05-A recommendations. The Navigator CGM system achieved more accurate results than the Guardian or the Seven Plus with respect to MARD and PARD. Performance in the hypoglycemic range was markedly worse for all CGM systems when compared with BG results.

FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart Algorithm, a 1-Hour Warm-up Time

The first-generation FreeStyle Navigator® Continuous Glucose Monitoring System (FreeStyle Navigator CGM) requires a 10 h warm-up period to avoid inaccurate glucose readings caused by sensor insertion trauma and wound-healing processes. The performance of a second-generation FreeStyle Navigator CGM that begins reporting glucose 1 h after sensor insertion is described. Second-generation FreeStyle Navigator CGM performance was evaluated in an in-clinic study using the YSI Model 2300 STATPlus Glucose Analyzer as reference with 47 subjects with type 1 diabetes. The reference readings were taken at 15 min intervals, and the study was designed to emphasize the first 10 h of use. The second-generation FreeStyle Navigator CGM exhibited continuous glucose error grid analysis ratings of 93.7% "clinically accurate," 3.6% "benign errors," and 2.8% "clinical errors" and a mean and median absolute relative difference of 14.5% and 10.7%, respectively. The second-generation algorithm detected signal instability in the first 10 h of use and suspended the reporting of 14.1% of first day continuous glucose readings. The clinical accuracy of the second-generation FreeStyle Navigator CGM was similar for the first 10 h versus subsequent hours, with 92.6% and 94.2% "clinically accurate" readings, respectively. The warm-up period for the second-generation FreeStyle Navigator CGM was reduced from 10 to 1 h, with minimal interruption of glucose reporting and without sacrificing clinical performance.

Comparison of the Clinical Information Provided by the FreeStyle Navigator Continuous Interstitial Glucose Monitor Versus Traditional Blood Glucose Readings

The purpose of the analysis was to compare the clinical utility of data from traditional self-monitoring of blood glucose (SMBG) to that of continuous glucose monitoring (CGM). A clinical study of the clinical accuracy of the FreeStyle Navigator CGM System (Abbott Diabetes Care, Alameda, CA), which includes SMBG capabilities, was conducted by comparison to the YSI blood glucose analyzer (YSI Inc., Yellow Springs, OH) using 58 subjects with type 1 diabetes. The Continuous Glucose-Error Grid Analysis (CG-EGA) was used as the analytical tool. Using CG-EGA, the "clinically accurate," "benign errors," and "clinical errors" were 86.8%, 8.7%, and 4.5% for SMBG and 92.7%, 3.7%, and 3.6% for CGM, respectively. If blood glucose is viewed as a process in time, SMBG would provide accurate information about this process 86.8% of the time, whereas CGM would provide accurate information about this process 92.7% of the time (P < 0.0001). In the hypoglycemic range, however, SMBG is more accurate as the "clinically accurate," "benign errors," and "clinical errors" were 83.5%, 6.4%, and 10.1% for SMBG and 57.1%, 8.4%, and 34.5% (P < 0.0001) for CGM, respectively. While SMBG produces more accurate instantaneous glucose values than CGM, control of blood glucose involves a system in flux, and CGM provides more detailed insight into the dynamics of that system. In the normal and elevated glucose ranges, the additional information about the direction and rate of glucose change provided by the FreeStyle Navigator CGM System increases the ability to make correct clinical decisions when compared to episodic SMBG tests.

Electrochemistry in Diabetes Management

Diabetes devastates lives and burdens society. Hypoglycemic (low glucose) episodes cause blackouts, and severe ones are life-threatening. Periods of hyperglycemia (high glucose) cause circulatory disease, stroke, amputations, blindness, kidney failure and nerve degeneration. In this Account, we describe the founding of TheraSense, now a major part of Abbott Diabetes Care, and the development of two products that have improved the lives of people with diabetes. The first, a virtually painless microcoulometer (300 nL volume), the FreeStyle blood glucose monitoring system, was approved by the FDA and became available in 2000. In 2009, this system was used in more than one billion blood assays. The second, the enzyme-wiring based, subcutaneously-implanted FreeStyle Navigator continuous glucose monitoring system, was approved by the FDA and became available in the United States in 2008. The strips of the FreeStyle blood glucose monitoring system comprise a printed parallel plate coulometer, with a 50 microm gap between two facing printed electrodes, a carbon electrode and a Ag/AgCl electrode. The volume of blood between the facing plates is accurately controlled. The glucose is electrooxidized through catalysis by a glucose dehydrogenase (GDH) and an Os(2+/3+) redox mediator, which is reduced by the glucose-reduced enzyme and is electrooxidized on the carbon electrode. Initially the system used pyrroloquinoline quinone (PQQ)-dependent GDH but now uses flavin adenine dinucleotide (FAD)-dependent GDH. Because the facing electrodes are separated by such a small distance, shuttling of electrons by the redox couple could interfere with the coulometric assay. However, the Os(2+/3+) redox mediator is selected to have a substantially negative formal potential, between 0.0 and -0.2 V, versus that of the facing Ag/AgCl electrode. This makes the flow of a shuttling current between the two electrodes virtually impossible because the oxidized Os(3+) complex cannot be appreciably reduced at the more positively poised Ag/AgCl electrode. The FreeStyle Navigator continuous glucose monitoring system uses a subcutaneously implanted miniature plastic sensor connected to a transmitter to measure glycemia amperometrically and sends the information to a PDA-like device every minute. The sensor consists of a narrow (0.6 mm wide) plastic substrate on which carbon-working, Ag/AgCl reference, and carbon counter electrodes are printed in a stacked geometry. The active wired enzyme sensing layer covers only about 0.1 mm(2) of the working electrode and is overlaid by a flux-limiting membrane. It resides at about 5 mm depth in the subcutaneous adipose tissue and monitors glucose concentrations over the range 20-500 mg/dL. Its core component, a miniature, disposable, amperometric glucose sensor, has an electrooxidation catalyst made from a crosslinked adduct of glucose oxidase (GOx) and a GOx wiring redox hydrogel containing a polymer-bound Os(2+/3+) complex. Because of the selectivity of the catalyst for glucose, very little current flows in the absence of glucose. That feature, either alone or in combination with other features of the sensor, facilitates the one-point calibration of the system. The sensor is implanted subcutaneously and replaced by the patient after 5 days use with minimal pain. The wearer does not feel its presence under the skin.

Alarm Characterization for a Continuous Glucose Monitor That Replaces Traditional Blood Glucose Monitoring

Continuous glucose monitoring (CGM) devices available in the United States are approved for use as adjuncts to self-monitoring of blood glucose (SMBG); all CGM alarms require SMBG confirmation before treatment. In this report, an analysis method is proposed to determine the CGM threshold alarm accuracy required to eliminate SMBG confirmation. The proposed method builds on the Clinical and Laboratory Standards Institute (CLSI) guideline for evaluating CGM threshold alarms using data from an in-clinic study of subjects with type 1 diabetes. The CLSI method proposes a maximum time limit of +/-30 minutes for the detection of hypo- and hyperglycemic events but does not include limits for glucose measurement accuracy. The International Standards Organization (ISO) standard for SMBG glucose measurement accuracy (ISO 15197) is +/-15 mg/dl for glucose <75 mg/dl and +/-20% for glucose > or = 75 mg/dl. This standard was combined with the CLSI method to more completely characterize the accuracy of CGM alarms. Incorporating the ISO 15197 accuracy margins, FreeStyle Navigator CGM system alarms detected 70 mg/dl hypoglycemia within 30 minutes at a rate of 70.3%, with a false alarm rate of 11.4%. The device detected high glucose in the range of 140-300 mg/dl within 30 minutes at an average rate of 99.2%, with a false alarm rate of 2.1%. Self-monitoring of blood glucose confirmation is necessary for detecting and treating hypoglycemia with the FreeStyle Navigator CGM system, but at high glucose levels, SMBG confirmation adds little incremental value to CGM alarms.

Detection of Hypoglycemia with Continuous Interstitial and Traditional Blood Glucose Monitoring Using the FreeStyle Navigator Continuous Glucose Monitoring System

The objective of the analysis was to compare detection of hypoglycemic episodes (glucose <70 mg/dL lasting >15 min) with the FreeStyle Navigator Continuous Glucose Monitoring System (FSN-CGM) (Abbott Diabetes Care, Alameda, CA) alarms to detection with traditional finger stick testing at an average frequency of eight tests per day. The performance of FSN-CGM alarms was evaluated in a clinic setting using 58 subjects with type 1 diabetes mellitus (T1DM) monitoring interstitial glucose concentration over a 5-day period compared to reference YSI measurements (instrument manufactured by YSI, Yellow Springs, OH) at 15-min intervals. Finger stick glucose testing was evaluated in the home environment with 91 subjects with TIDM monitoring with the blood glucose meter integrated into the FreeStyle Navigator (FSN-BG) over a 20-day period. The reference was FSN-CGM with results masked from the subjects. Blood glucose values <=85 mg/dL were considered the optimal treatment level to avoid or reverse hypoglycemia. With a threshold alarm setting of 85 mg/dL, 90.6% of hypoglycemic episodes were detected within +/- 30 min by FSN-CGM in the clinic study. When the alarm was activated, YSI glucose was <= 85 mg/dL 77.2% of the time. In the home environment, the average FSN-BG testing frequency was 7.9 tests per day. Hypoglycemia was verified within +/- 30 min by FSN-BG measurements <= 85 mg/dL at a rate of 27.5%. Even with a high rate of FSN-BG testing, hypoglycemia detected by FSN-CGM was verified by patients with T1DM very infrequently. A high rate of hypoglycemia detection with a moderate rate of unnecessary alarms can be attained using FSN-CGM.

Early Patient and Clinician Experiences with Continuous Glucose Monitoring

Fifteen years after publication of landmark studies that clearly demonstrated the benefits of intensive diabetes management, patients continue to fall short of glycemic goals. The risk of hypoglycemia remains a major barrier to optimal glycemic control. Continuous glucose monitoring (CGM) can assist in overcoming some of the limitations of self-monitoring of blood glucose by providing the ability to track glucose levels 24 hours a day, observe glucose trends and patterns, and receive alarms or alerts for actual and impending hypo- and hyperglycemia. In the brief time it has been available, studies have already demonstrated an association between the use of CGM and less time spent in hypo- and hyperglycemia, reduced glycemic variability, and reduced hemoglobin A1c levels. Because little information exists in the literature regarding teaching and learning experiences to assist clinicians beginning to incorporate CGM into their practices, the training and user experience from a 12-week study of patients using the FreeStyle Navigator CGM system was evaluated. Through responses to questionnaires, clinicians indicated the ability to train easily on the CGM system, and both patients and clinicians felt that they were able to make more informed decisions on therapy adjustments based on information from the receiver and the data management reports. It is important for clinicians and patients to understand the scope and limitations of this new technology to prevent unrealistic expectations. It is imperative to provide adequate training and education to effectively manage and use the large amount of data made available by CGM.

FreeStyle Navigator Continuous Glucose Monitoring System Use in Children With Type 1 Diabetes Using Glargine-Based Multiple Daily Dose Regimens

In a previous pilot study of the FreeStyle Navigator Continuous Glucose Monitoring System, hereafter referred to as “Navigator,” in 30 children and adolescents with type 1 diabetes using insulin pumps, we found that Navigator use averaged >130 h per week over 13 weeks and mean A1C level dropped from 7.1 ± 0.6 to 6.8 ± 0.7% ( P = 0.02) (1). The current study evaluated whether the Navigator was similarly tolerated over 13 weeks in 27 children aged 4–17 years with type 1 diabetes using glargine-based, multiple daily injection(MDI) insulin regimens. Subjects averaged >100 h/week of Navigator use. Mean A1C level fell from 7.9 ± 1.0% at baseline to 7.3 ± 0.9% at 13 weeks ( P = 0.004). High satisfaction with the Navigator was reported on the Continuous Glucose Monitor Satisfaction Scale. These encouraging pilot study results support the inclusion of MDI users in longer-term randomized clinical trials of continuous glucose monitors. Institutional review boards at each of the Diabetes Research in Children Network (DirecNet) centers approved the study protocol and consent/assent forms. Research methods were virtually identical to those employed in our previous Navigator (Abbott Diabetes Care; Alameda, CA) study (1) except that all subjects were treated with glargine-based MDI treatment. Other eligibility requirements were as follows: subjects must 1 ) be aged 3–17 years, 2 ) have type 1 diabetes for a duration ≥1 year, 3 ) have access to a home computer equipped with E-mail, and 4 ) have a parent/older subject who comprehended English. Subjects were excluded for asthma, cystic fibrosis, psychiatric disorder, and use of glucocorticoids. Subjects were selected for participation from the existing patient population at each center. There was a 1-week run-in period during which Navigator use was blinded to collect baseline glucose data, followed by unblinded home use for 3 months. To blind subjects to the results …

Numerical simulation of the effect of rate of change of glucose on measurement error of continuous glucose monitors.

A 5-day in-patient study designed to assess the accuracy of the FreeStyle Navigator Continuous Glucose Monitoring System revealed that the level of accuracy of the continuous sensor measurements was dependent on the rate of glucose change. When the absolute rate of change was less than 1 mg*dl(-1)*min(-1) (75% of the time), the median absolute relative difference (ARD) was 8.5%, with 85% of all points falling within the A zone of the Clarke error grid. When the absolute rate of change was greater than 2 mg*dl(-1)*min(-1) (8% of the time), the median ARD was 17.5%, with 59% of all points falling within the Clarke A zone. Numerical simulations were performed to investigate effects of the rate of change of glucose on sensor measurement error. This approach enabled physiologically relevant distributions of glucose values to be reordered to explore the effect of different glucose rate-of-change distributions on apparent sensor accuracy. The physiological lag between blood and interstitial fluid glucose levels is sufficient to account for the observed difference in sensor accuracy between periods of stable glucose and periods of rapidly changing glucose. The role of physiological lag on the apparent decrease in sensor accuracy at high glucose rates of change has implications for clinical study design, regulatory review of continuous glucose sensors, and development of performance standards for this new technology. This work demonstrates the difficulty in comparing accuracy measures between different clinical studies and highlights the need for studies to include both relevant glucose distributions and relevant glucose rate-of-change distributions.

Continuous Glucose Monitoring in Children with Type 1 Diabetes

To examine the feasibility of daily use of a continuous glucose monitor, the FreeStyle Navigator Continuous Glucose Monitoring System ("Navigator"), in children with type 1 diabetes (T1D). After a masked Navigator was used for 4 to 7 days to establish a baseline level of glycemic control, 30 insulin pump users with T1D (average age 11.2 years) were asked to use the Navigator daily for 13 weeks. Subjects averaged 149 h/wk of Navigator use during the first 4 weeks, which decreased slightly to 134 h/wk during weeks 9 to 13 (P = .006). Mean hemoglobin A1c improved from 7.1% at baseline to 6.8% at 13 weeks (P = .02), and the percentage of glucose values between 71 and 180 mg/dL increased from 52% to 60% (P = .01). Subjects and parents reported high satisfaction with the Navigator on the Continuous Glucose Monitor Satisfaction Scale. Two subjects had severe skin reactions related to sensor mount adhesive. This study indicates that incorporating real-time continuous glucose monitoring into the daily treatment of children with T1D is feasible. The results provide a compelling rationale for conducting a randomized trial of daily use of a continuous glucose monitor in children with T1D.

Accuracy of the 5-Day FreeStyle Navigator Continuous Glucose Monitoring System

The purpose of this study was to compare the accuracy of measurements of glucose in interstitial fluid made with the FreeStyle Navigator Continuous Glucose Monitoring System with Yellow Springs Instrument laboratory reference measurements of venous blood glucose. Fifty-eight subjects with type 1 diabetes, aged 18-64 years, were enrolled in a multicenter, prospective, single-arm study. Each subject wore two sensors simultaneously, which were calibrated with capillary fingerstick measurements at 10, 12, 24, and 72 h after insertion. Measurements from the FreeStyle Navigator system were collected at 1-min intervals and compared with venous measurements taken once every 15 min for 50 h over the 5-day period of sensor wear in an in-patient clinical research center. Periods of high rates of change of glucose were induced by insulin and glucose challenges. Comparison of the FreeStyle Navigator measurements with the laboratory reference method (n = 20,362) gave mean and median absolute relative differences (ARDs) of 12.8 and 9.3%, respectively. The percentage in the clinically accurate Clarke error grid A zone was 81.7% and that in the in the benign error B zone was 16.7%. During low rates of change (< +/-1 mg x dl(-1) x min(-1)), the percentage in the A zone was higher (84.9%) and the mean and median ARDs were lower (11.7 and 8.5%, respectively). Measurements with the FreeStyle Navigator system were found to be consistent and accurate compared with venous measurements made using a laboratory reference method over 5 days of sensor wear (82.5% in the A zone on day 1 and 80.9% on day 5).

Modal plots of diurnal glucose during masked and unmasked use of the FreeStyle Navigator Continuous Glucose Monitoring System®

Modal plots of diurnal glucose during masked and unmasked use of the FreeStyle Navigator Continuous Glucose Monitoring System®

The Accuracy of the FreeStyle Navigator Continuous Glucose Monitoring System in Children With Type 1 Diabetes

To evaluate the accuracy and precision of the FreeStyle Navigator continuous glucose monitoring system in children with type 1 diabetes. In 30 children with type 1 diabetes (mean age 11.2 +/- 4.1 years), the Navigator glucose values were compared with reference serum glucose values of blood samples obtained in an inpatient clinical research center and measured in a central laboratory using a hexokinase enzymatic method and in an outpatient setting with a FreeStyle meter. Median absolute difference (AD) and median relative absolute difference (RAD) were computed for sensor-reference and sensor-sensor pairs. The median AD and RAD were 17 mg/dl and 12%, respectively, for 1,811 inpatient sensor-reference pairs and 20 mg/dl and 14%, respectively, for 8,639 outpatient pairs. The median RAD between two simultaneous Navigator measurements (n = 1,971) was 13%. Ninety-one percent of sensors in the inpatient setting and 81% of sensors in the outpatient setting had a median RAD < or = 20%. The Navigator's accuracy does not yet approach the accuracy of current-generation home glucose meters, but it is sufficient to believe that the device has the potential to be an important adjunct to treatment of youth with type 1 diabetes.