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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Diabetes Care. Author manuscript; available in PMC 2007 April 1.
Published in final edited form as:
PMCID: PMC1764630

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

The Diabetes Research in Children Network (DirecNet) Study Group



To evaluate the accuracy and precision of the FreeStyle Navigator™ Continuous Glucose Monitoring System (“Navigator”) in children with type 1 diabetes (T1D).

Research Design and Methods

In 30 children with T1D (mean age 11.2 ± 4.1 years), 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% for 8,639 outpatient pairs. Median RAD between 2 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 ≤20%.


The Navigator’s accuracy does not yet approach the accuracy of current generation home glucose meters but is sufficient to believe that the device has the potential to be an important adjunct to treatment of youth with T1D.


Direct reading, near continuous, minimally invasive glucose sensors hold great promise for improving the care of patients with diabetes and other abnormalities of glucose metabolism. These sensors can provide both a measure of the current glucose concentration as well as glucose trends, with alarms for high and low thresholds and predicted hypo- and hyperglycemia. With the recent demonstration that good glycemic control reduces mortality and morbidity in acutely ill non-diabetes patients,(1, 2) glucose sensors could have an even more expanded role outside the realm of diabetes.

A major issue in evaluating utility of a real-time continuous glucose monitor (RT-CGM) is its accuracy across a wide range of glucose levels. Previously we reported on the accuracy of GlucoWatch G2 Biographer™ (“GlucoWatch”, Cygnus, Inc., Redwood City, CA)(3) and the Continuous Glucose Monitoring System (“CGMS”, Medtronic Minimed, Inc., Northridge, CA)(4) in children with type 1 diabetes (T1D). The purpose of this paper is to report on the accuracy of FreeStyle Navigator™ Continuous Glucose Monitoring System (“Navigator”) in children.


The study was conducted by the Diabetes Research in Children Network (DirecNet) at five clinical centers. A Data and Safety Monitoring Board and the Institutional Review Boards at each center approved the study protocol, consent form and assent form. A parent or guardian and each subject 7 years and older gave written consent and assent, respectively. Eligible subjects were between 3 and 18 years old with a clinical diagnosis of T1D of ≥1 year duration. Subjects initially used a Navigator that was blinded so that glucose values could not be seen for approximately one week at home. During this time, glucose levels were checked with the built-in FreeStyle Blood Glucose Meter (“FreeStyle meter”) at least four times per day, including the three meter measurements during the first 24 hours that were used for calibration of the Navigator.

Each subject was then hospitalized for 24 hours in a clinical research center (CRC) where a second Navigator sensor was inserted. Venous blood samples for laboratory serum glucose concentration determinations were taken every 30 minutes during the hospitalization. Additional samples were taken every 20 minutes during a session in which subjects >7 years of age exercised on a treadmill for four 15-minute sessions of moderate intensity interspersed with three 5-minute rest periods (75 minutes total) and every 10 minutes following breakfast (during which time the breakfast insulin dose was delayed) for subjects whose age and weight permitted additional blood samples. Serum glucose concentrations from these samples were measured at the DirecNet Central Biochemistry Laboratory at the University of Minnesota using a hexokinase enzymatic method.(5, 6)

Following the CRC admission, the Navigator was used at home for 13 weeks. Subjects were instructed to use the Navigator continuously. During the first two weeks, subjects were to check the glucose level with the FreeStyle meter whenever the Navigator alarmed; thereafter, meter glucose checks were at the discretion of the subject and parent. Navigator and FreeStyle glucose data were downloaded weekly to the subject’s home computer and emailed to the study coordinating center.

Statistical Methods

Accuracy analyses were performed separately for inpatient and outpatient Navigator use. For the inpatient analysis, accuracy was evaluated separately for the half-hour measurements and for the exercise and breakfast testing. Laboratory serum glucose values were used as the reference during the inpatient CRC visit and FreeStyle glucose measurements (excluding those used to calibrate the Navigator) were used as the reference during home use. In a prior study, we found that the FreeStyle meter had a high degree of accuracy.(7) Each reference glucose value was paired to the closest Navigator reading within ± 5 minutes. The following were computed for each Navigator-reference pair: difference (Navigator value minus reference value), absolute difference (absolute value of difference, referred to as “AD”), and relative absolute difference (absolute difference divided by reference value, expressed as a percentage, referred to as “RAD”). The difference measure incorporates the direction of the error so that pairs with the sensor reading high cancel out pairs with the sensor reading low. The median difference therefore evaluates whether there is any bias for the sensor to read systematically high or low. The AD and RAD values use the absolute value of the difference between the sensor value and the reference value, ignoring the direction of the error. These measures reflect the magnitude of the error without regard to whether the sensor value was higher or lower than the reference value. Each pair was also evaluated to determine whether the sensor value met the International Organisation for Standardisation (ISO) criteria for home glucose meters (for reference glucose value ≤75 mg/dL, meter value within ±15 mg/dL and for reference glucose value >75 mg/dL, meter value within ±20%, hereafter referred to as the “ISO criteria”).(8) Summary statistics (e.g., median and percentages) were calculated by pooling all paired values. Median values were reported instead of means because of the skewed distribution. The bootstrap technique (resampling subjects with replacement)(9) was used to account for the within subject correlation in the statistical comparisons and calculation of confidence intervals.

Since point-to-point measures of accuracy do not capture the temporal dimension of near-continuous data, we supplemented these with “event-based” analyses. The glucose excursion during the exercise session (drop from baseline to nadir) for the laboratory reference values and the Navigator were compared. The Navigator nadir glucose was defined as the lowest glucose value from baseline until 30 minutes following the laboratory nadir (to allow for a possible lag). The rate of change was defined from baseline until the nadir. An analogous analysis was not performed for the post-breakfast period because many subjects still had not reached their peak glucose when reference sampling was stopped 1 hour after breakfast.


The average age of the 30 subjects was 11.2 ± 4.1 years (range 4 to 17 years); 40% were female; 93% were Caucasian, 3% Hispanic and 3% Asian. The mean duration of diabetes was 5.8 ± 3.0 years and the mean HbA1c was 7.1 ± 0.6%.

Inpatient Accuracy Assessment

During the CRC admission, there were 1,811 half-hour laboratory glucose measurements paired with glucose measurements from 58 Navigator sensors (not including the exercise session or the post-breakfast assessment). The median number of paired values per subject was 66 (interquartile range 53 to 69) ranging from 25 to 79. As shown in Table 1, there was no tendency for the Navigator to read systematically higher or lower than the reference glucose (median difference = −2 mg/dL; 95% confidence interval −7 to +5; p=0.34). Overall, the median AD was 17 mg/dL (interquartile range 8 to 31; 90th percentile 53 mg/dL) and the median RAD was 12% (interquartile range 6% to 21%; 90th percentile 33%), with 74% of sensor values meeting ISO home glucose meter criteria. When the reference glucose was ≤70 mg/dL, the median absolute difference was 14 mg/dL (interquartile range 8 to 22; 90th percentile 44 mg/dL). When the reference glucose was 71 to 180 mg/dL, the median RAD was 13% (interquartile range 6% to 22%; 90th percentile 36%). When the reference glucose was >180 mg/dL, the median RAD was 10% (interquartile range 5% to 18%; 90th percentile 25%). As would be expected, the AD was greater at higher glucose levels and the RAD was greater at lower glucose levels. Accuracy measures improved slightly when incorporating a 10-minute sensor lag (p<0.001; Table 1). Among the 53 sensors with at least 10 navigator-reference pairs, 19 (36%) had a median RAD ≤10%, 23 (43%) a median RAD of 10.1% to 15%, 6 (11%) a median RAD of 15.1% to 20%, and 5 (9%) a median RAD of >20%.

Table 1
Navigator Point Accuracy According to Various Factors*

Prior to starting exercise, the median Navigator glucose concentration was 161 mg/dL (interquartile range 118 to 220) and median reference glucose concentration was 172 mg/dL (interquartile range 122 to 239). As shown in Figure 1A, the Navigator accurately measured the magnitude of glucose falls during exercise. The median fall in reference glucose was 91 mg/dL (interquartile range 51 to 129) and the median absolute difference in this fall between the Navigator and reference was 16 mg/dL (interquartile range 8 to 29). Although the drop in glucose was generally well tracked by the Navigator, the sensor glucose values lagged behind the reference values causing the Navigator to underestimate the rate of change, particularly in subjects with a rapid fall in glucose during exercise (Figure 1B). The median time to the nadir was 100 minutes for the Navigator and 78 minutes for the reference (Table 2). The reference glucose fell to ≤70 mg/dL during exercise for 4 subjects (lab values 56, 60, 68 and 70 mg/dL) with corresponding sensor glucose nadirs of 70, 146, 71 and 62 mg/dL, respectively. The sensor with the glucose nadir of 146 mg/dL tracked the drop in the glucose level during exercise, but it provided erroneously high glucose readings throughout. Point to point accuracy showed a median (25th, 75th percentiles) RAD of 17% (9%, 27%) during exercise (Table 1), which improved to 11% (7%, 22%) when a 10-minute lag was assumed.

Figure 1
Navigator vs. Laboratory Measured Drops in Glucose (A) and Rates of Change (B) during Exercise
Table 2
Navigator Excursion Accuracy during Exercise Session (N=19)*

Outpatient Accuracy Assessment

At home, subjects averaged 137 ± 30 hours of Navigator use per week. Excluding calibration values, there were 8,639 paired sensor-FreeStyle meter values from 607 Navigator sensors. As shown in Table 1, the outpatient accuracy results were similar to the inpatient results.

Among the 347 sensors with at least 10 navigator-reference paired values, 68 (20%) had a median RAD ≤10%, 115 (33%) a median RAD of 10.1% to 15%, 99 (29%) a median RAD of 15.1% to 20%, and 65 (19%) a median RAD of >20%.

Factors Affecting Accuracy

Accuracy was fairly consistent over five days of use in both the inpatient and outpatient settings. Accuracy did not substantially vary according to insertion site (location data only available in inpatient setting) or gender (Table 1). After adjustment for glucose level, accuracy was significantly better at night for both inpatient (RAD: p<0.001; ISO: p=0.002) and outpatient settings (p<0.001 RAD and ISO). Accuracy was also significantly better for children 14–18 years of age during home use (RAD: p=0.005; ISO: p=0.01), but was not impacted by age during the inpatient visit (RAD: p=0.28; ISO: p=0.16).


During the CRC admission, subjects simultaneously used two Navigator sensors resulting in 1,971 Navigator-Navigator pairs. The median (25th, 75th percentiles) RAD between two simultaneous (within ±5 min) Navigator measurements was 13% (interquartile range 6% to 21%), 15% for values ≤70 mg/dL (average of the two Navigator values), 13% for values 71 to 180 mg/dL, and 13% for values >180 mg/dL.


We found that the overall relative absolute difference between Navigator measurements of interstitial glucose concentrations and reference serum glucose levels was similar during inpatient and outpatient assessments with median values of 12% and 14%, respectively. The AD was greater at higher glucose levels and the RAD was greater at lower glucose levels.

In previous studies, we evaluated the accuracy of the GlucoWatch and CGMS during inpatient use. The median RAD with the GlucoWatch was 16% and 60% of values meeting ISO criteria.(3) With the CGMS, the median RAD was 19% with the original sensor and 11% with a newer modified sensor; 53% and 72% of values, respectively, met ISO criteria.(4) It is particularly noteworthy that the Navigator, which gives values in real time, was as accurate as the CGMS which calculates values retrospectively. All other things being equal, retrospective analysis of sensor data generally enhances accuracy, since there are a larger number of meter values to use for calibration than with rolling, real-time calibration algorithms. Studies of other real-time sensors in adults reported a median RAD of 17% during outpatient use for the Guardian® RT Continuous Glucose Monitoring System (Medtronic Minimed, Northridge, CA) (10) and 16% (inpatient and outpatient data pooled) (11) to 20% (inpatient and outpatient data pooled) (12) for the DexCom™ STS™ Continuous Glucose Monitoring System (DexCom, Inc., San Diego, CA).

The Navigator system tracked the drop in blood glucose induced by exercise well, especially with respect to the magnitude of fall in glucose concentration. However, sensor glucose levels lagged behind the blood glucose levels, causing the device to underestimate the true rate of fall in glucose during exercise in some subjects. Navigator readings were as accurate on the fifth day of use as they were on the first day. Exploratory analyses within subgroups controlling for the reference glucose concentration found that the Navigator was more accurate at night than during the day. In past studies we and others observed that the CGMS, in contrast, was less accurate during the night than during the day, leading to overestimation of the frequency of nocturnal hypoglycemia.(4, 13, 14) This might be due to the potential for biofouling to occur when there is decreased movement, or to changes in the subcutaneous circulation or oxygen availability overnight. The Navigator does not appear to have the same susceptibility to low glucose readings overnight, which could be due to differences in the sensor chemistry (the Navigator is less oxygen dependent) or to difference in the biocompatibility or diffusion characteristics of the membranes coating the sensor. During the day, a large number of glucose values were obtained when there were rapid rates of change of the blood glucose which makes point-to-point comparisons less accurate because of the physiologic lag between interstitial and blood glucose levels. At night there was a much slower rate of change of blood glucose levels which allowed the interstitial glucose levels to be equilibrated with blood glucose levels at the time the point-to-point comparisons were determined.

The Navigator’s accuracy does not yet approach the accuracy of current generation home glucose meters but is sufficient to believe that the device has the potential to be an important adjunct to treatment of youth with T1D. Clinical trials are needed, however, to truly demonstrate the clinical utility of the Navigator as well as other glucose sensors.


Appreciation is expressed for the work performed by the CRC Nurses at the five clinical centers. This research was supported by the following NIH/NICHD Grants: HD041919-01; HD041915-01; HD041890; HD041918-01; HD041908-01; and HD041906-01. Clinical Centers also received funding through the following GCRC Grant Numbers M01 RR00069; RR00059; RR 06022 and RR00070-41. Abbott Diabetes Care, Alameda, CA, provided the FreeStyle Navigator™ Continuous Glucose Monitoring Systems and the FreeStyle Blood Glucose Meter test strips.


Writing Committee

Lead authors: Darrell M. Wilson, MD; Roy W. Beck, MD, PhD; William V. Tamborlane, MD; Mariya J. Dontchev, MPH. Craig Kollman, PhD. Additional writing committee members (alphabetical): Peter Chase, MD; Larry A. Fox, MD; Katrina J. Ruedy, MSPH; Eva Tsalikian, MD; Stuart A. Weinzimer, MD

The DirecNet Study Group

Clinical Centers: (Listed in alphabetical order with clinical center name, city, and state. Personnel are listed as (PI) for Principal Investigator, (I) for co-Investigator and (C) for Coordinators.) (1) Barbara Davis Center for Childhood Diabetes, University of Colorado, Denver, CO: H. Peter Chase, MD (PI); Rosanna Fiallo-Scharer, MD (I); Laurel Messer, RN (C); Barbara Tallant, RN, MA (C); (2) Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA: Eva Tsalikian, MD (PI); Michael J. Tansey, MD (I); Linda F. Larson, RN (C); Julie Coffey, MSN (C); Joanne Cabbage (C); (3) Nemours Children’s Clinic, Jacksonville, FL: Tim Wysocki, PhD, ABPP (PI); Nelly Mauras, MD (I); Larry A. Fox, MD (I); Keisha Bird, MSN (C); Kim Englert, RN (C); (4) Division of Pediatric Endocrinology and Diabetes, Stanford University, Stanford, CA: Bruce A. Buckingham, MD (PI); Darrell M. Wilson, MD (I); Jennifer M. Block, RN, CDE (C); Paula Clinton, RD, CDE (C); Kimberly Caswell, APRN; (5) Department of Pediatrics, Yale University School of Medicine, New Haven, CT: Stuart A. Weinzimer, MD (PI); William V. Tamborlane, MD (I); Elizabeth A. Doyle, MSN (C); Heather Mokotoff, MSN (C); Amy Steffen (C); Coordinating Center: Jaeb Center for Health Research, Tampa, FL: Roy W. Beck, MD, PhD; Katrina J. Ruedy, MSPH; Craig Kollman, PhD; Dongyuan Xing, MPH; Mariya Dontchev, MPH; Cynthia R. Stockdale; Judy Jackson; University of Minnesota Central Laboratory: Michael W. Steffes, MD, PhD; Jean M. Bucksa, CLS; Maren L. Nowicki, CLS; Carol A. Van Hale, CLS; Vicky Makky, CLS; National Institutes of Health: Gilman D. Grave, MD; Mary Horlick, PhD; Karen Teff, PhD; Karen K. Winer, MD; Data and Safety Monitoring Board: Dorothy M. Becker, MBBCh; Patricia Cleary, MS; Christopher M. Ryan, PhD; Neil H. White, MD, CDE; Perrin C. White, MD


Publisher's Disclaimer: This is an author-created, uncopyedited electronic version of an article accepted for publication in Diabetes Care ( The American Diabetes Association (ADA), publisher of Diabetes Care, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version is available online at


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