Evaluation of Factors Affecting CGMS Calibration Bruce Buckingham, 1 Craig Kollman, 2 Roy W Beck, 2 Andrea Kalajian, 2 Rosanna Fiallo-Scharer, 3 Michael J Tansey, 4 Larry A Fox, 5 Darrell M Wilson, 1 Stuart A Weinzimer, 6 Katrina J Ruedy, 2 and William V Tamborlane 6 for the DirecNet Study Group 1. Stanford, CA; 2. Tampa, FL; 3. Denver, CO.; 4. Iowa City, IA; 5. Jacksonville, FL; 6. New Haven, CT;

Abstract Abstract_title: Evaluation of Factors Affecting CGMS Calibration Abstract: Objective: To explore the optimal number and timing of calibration values entered into the Continuous Glucose Monitoring System ("CGMS"; Medtronic MiniMed, Northridge, CA). Research Design and Methods: Fifty subjects with T1DM (aged 10-18y) were hospitalized in a clinical research center for ~24h on two different days. CGMS and One-Touch® Ultra® Meter ("Ultra"; Lifescan, Milpitas, CA) data were obtained. The CGMS was retrospectively recalibrated using the Ultra data varying the number and timing of calibration values. Resulting CGMS values were compared against laboratory reference values. Results: There was a modest improvement in accuracy with increasing number of calibrations. The median relative absolute deviation (RAD) was 14%, 15%, 13% and 13% when using 3, 4, 5 and 7 calibration values, respectively (p<0.001). Corresponding percentages of CGMS-reference pairs meeting the ISO criteria were 66%, 67%, 71% and 72%, respectively (p<0.001). Nighttime accuracy improved when daytime calibrations (pre-lunch and pre-dinner) were removed leaving only two calibrations at 9p.m. and 6a.m. (median difference: -2 vs. -9mg/dL, p<0.001; median RAD: 12% vs. 15%, p<0.001; ISO: 73% vs. 67%, p=0.003). Accuracy was significantly better on visits where the average absolute rate of glucose change at the times of calibration was lower. On visits with average absolute rates <0.5, 0.5- <1.0, 1.0-<1.5 and ≥1.5mg/dL/min, median RAD values were 11% vs. 15% vs. 18% vs. 19% (p=0.01) and ISO percentages were 76% vs. 68% vs. 58% vs. 59% (p=0.02), respectively. Conclusions: Although accuracy is slightly improved with more calibrations, the timing of the calibrations appears more important. Modifying the algorithm to put less weight on daytime calibrations for nighttime values and calibrating during times of relative glucose stability may have greater impacts on accuracy.

Introduction The Medtronic Minimed continuous glucose monitoring system (CGMS) uses a retrospective calibration based upon 3-4 glucose meter test results/day. Our studies were designed to answer the following questions: 1. Will more than 3 or 4 calibration values improve sensor accuracy? 2. Will the addition of postprandial to preprandial calibration values improve accuracy by providing a broader glucose range? 3. Does the rate of change of glucose values at the time of calibration affect sensor accuracy? 4. How does the use of daytime calibrations affect nighttime readings?

Methods Fifty subjects with type 1 diabetes (average age was 14.8 ± 1.7 years) were hospitalized in a clinical research center on two different days. During one visit, they exercised on a treadmill. A CGMS Gold sensor was calibrated using a One-Touch® Ultra® Meter. Intravenous blood samples for reference serum glucose values were obtained every 20 minutes during the exercise session, and hourly overnight from 10 p.m. to 6 a.m., and measured in a central laboratory (University of Minnesota). Glucose measurements with the Ultra meter were also obtained before lunch and dinner and on the hour starting at 2 p.m. A computer program provided by Medtronic MiniMed was used to recalibrate the CGMS using 3, 4, 5 or 7 Ultra values:

Table 1. Schedule of Recalibrations

Statistics Standard measurements: Difference: CGMS minus laboratory reference Relative absolute difference (RAD: absolute value of the difference divided by the reference; expressed as a percentage) ISO criteria (CGMS within ±15 mg/dL for reference ≤75 mg/dL and within ±20% for reference >75 mg/dL) Analyses were limited to sensors functioning for at least 15 hours and visits where both Ultra and CGMS measurements were available at all 7 calibration time points listed in Table 1. This resulted in 12 of the 100 visits being excluded from analysis. The bootstrap resampling technique was used to account for correlated data from the same subject.

Analyses of false positives for hypoglycemia: based on events rather than discrete points. Episode: At least 2 CGMS values ≤70 mg/dL with no intermediate values >80 mg/dL. Distinct episodes had to be separated by at least 30 min. True positive: at least one reference value ≤70 mg/dL during episode. False positive: reference value >10 mg/dL higher than the concurrent CGMS value. Non-evaluable: If neither of these conditions were met. Rate of change during calibration: was calculated using CGMS values 10 minutes apart (5 minutes prior to and following the time of each calibration). Absolute rate of change was averaged over 4 calibration times (pre-lunch, pre- dinner, 9 p.m., 6 a.m.) for each visit. For analyses of rate of change during calibration, accuracy measures were adjusted for the rate of change during the reference measurement by giving equal weight to each category (<0.5, 0.5-<1.0, 1.0-<1.5 and ≥1.5 mg/dL/min).

Results Original Calibrations: Median number of calibrations = 5. Median RAD = 15% overall, and 18% when reference values ≤70 mg/dL, ISO criteria met = 64%. Table 2: Effect of # of Calibrations on CGMS accuracy Additional calibration values made a modest improvement in accuracy (p<0.001) This trend appeared more pronounced during hypoglycemia Increasing the number of calibrations did not correct the tendency for the CGMS to read low overnight

Table 3: Effect of rate of change during calibration of blood glucose on sensor calibration and accuracy The CGMS was more accurate when the rate of change was lower (p=0.001) Table 4: False positive alarm rates With additional calibrations, there was a trend towards lower overnight false positive rates (p=0.08), and there was trend for lower false alarm rates when the rate of change was slower (p=0.19).

Timing of Calibrations Additional re-calibration schemes were run to explore how the timing of the calibrations might affect accuracy. The 4-calibration scheme (pre-lunch, pre-dinner, 9 p.m., 6 a.m.) was used as a baseline for comparison. Removing the two daytime (pre-lunch and pre-dinner) calibrations actually improved nighttime accuracy (median difference: –2 vs. –9 mg/dL, p<0.001; median RAD: 12% vs. 15%, p=0.001; ISO: 73% vs. 67%, p= Changing the 3 daytime calibration values from pre-prandial to postprandial (i.e., calibrating at 2 p.m., 7 p.m., 10 p.m. and 6 a.m.) did not affect accuracy. The median RAD: 14% vs. 15%, p=0.50; ISO percentage: 68% vs. 67%, p=0.62

Conclusions Our results showed a slight improvement in sensor accuracy when additional calibration values are added with the median RAD improving from 14-15% with 3 or 4 calibrations each day, to 13% with 5 or 7 calibrations each day. Additional calibration values also tended to improve sensor performance during exercise Our results confirm that sensor accuracy is decreased when blood glucose levels are changing rapidly during calibrations Accuracy was not affected by using calibration values obtained either pre- prandially or about 2 hours post-prandially A separate calibration algorithm for overnight readings might improve accuracy at night - The median bias during the day was +4 mg/dL, and overnight the bias was –9 mg/dL - When we limited calibration values to those only obtained overnight, this bias was resolved (–2 mg/dL)