Median Absolute Relative Difference Research Articles

Assessing the Performance of a Noninvasive Glucose Monitor in People with Type 2 Diabetes with Different Demographic Profiles

Background Noninvasive glucose-monitoring devices represent an exciting frontier in diabetes research. GlucoTrack® is a noninvasive device that indirectly measures glucose fluctuation in the earlobe tissue. However, GlucoTrack measurements may be susceptible to effects of quasi-stable factors that may be affected by demographic profiles. The current study, thus, examined device performances in people with type 2 diabetes with different demographic profiles, focusing on age, gender, body mass, and whether the earlobe is pierced. Materials and Methods Clinical trials were conducted on 172 type 2 adult diabetic subjects. Device performance was clinically evaluated using the Clarke error grid (CEG) analysis and statistically assessed using absolute relative difference (ARD). Results CEG analysis revealed that 97.6% of glucose readings were within the clinically acceptable CEG A + B zones. Mean and median ARD were 22.3% and 18.8%, respectively. Likelihood ratio and parametric bootstrap tests revealed that there were no significant differences in ARD values across age, gender, body mass, and whether the earlobe was pierced, indicating that the accuracy of GlucoTrack remains consistent across the tested demographic profiles. Conclusions Our results suggest that GlucoTrack performance does not depend on demographic profiles of its users and it is thus suitable for various people with type 2 diabetes.

First application of a transcutaneous optical single-port glucose monitoring device in patients with type 1 diabetes mellitus

The combination of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion can be used to improve the treatment of patients with diabetes. The aim of this study was to advance an existing preclinical single-port system for clinical application by integrating the sensors of a phosphorescence based CGM system into a standard insulin infusion set. The extracorporeal optical phase fluorimeter was miniaturised and is now comparable with commercial CGM systems regarding size, weight and wear comfort. Sensor chemistry was adapted to improve the adhesion of the sensor elements on the insulin infusion set. In-vitro tests showed a linear correlation of R2=0.998 between sensor values and reference glucose values in the range of 0-300mg/dl. Electrical and cytotoxicity tests showed no negative impact on human health. Two single-port devices were tested in each of 12 patients with type 1 diabetes mellitus in a clinical set-up for 12h. Without additional data processing, the overall median absolute relative difference (median ARD) was 22.5%. For some of the used devices the median ARD was even well below 10%. The present results show that individual glucose sensors performance of the single-port system is comparable with commercial CGM systems but further improvements are needed. The new system offers a high extent of safety and usability by combining insulin infusion and continuous glucose measurement in a single-port system which could become a central element in an artificial pancreas for an improved treatment of patients with type 1 diabetes mellitus.

Does body mass index outperform body weight as a surrogate parameter in the calculation of size-specific dose estimates in adult body CT?

To assess the value of body mass index (BMI) in comparison with body weight as a surrogate parameter for the calculation of size-specific dose estimates (SSDEs) in thoracoabdominal CT. 401 CT examinations in 235 patients (196 chest, 205 abdomen; 95 females, 140 males; age 62.5 ± 15.0 years) were analysed in regard to weight, height and BMI (kg m(-2)). Effective diameter (Deff, cm) was assessed on axial CT images. The correlation between BMI, weight and Deff was calculated. SSDEs were calculated based on Deff, weight and BMI and lookup tables were developed. Overall height, weight, BMI and Deff were 172.5 ± 9.9 cm, 79.5 ± 19.1 kg, 26.6 ± 5.6 kg m(-2) and 30.1 ± 4.3 cm, respectively. There was a significant correlation between Deff and BMI as well as weight (r = 0.85 and r = 0.84; p < 0.05, respectively). Correlation was significantly better for BMI in abdominal CT (r = 0.89 vs r = 0.84; p < 0.05), whereas it was better for weight in chest CT (r = 0.87 vs r = 0.81; p < 0.05). Surrogated SSDEs did not differ significantly from the reference standard with a median absolute relative difference of 4.2% per patient (interquartile range 25-75: 3.1-7.89, range 0-25.3%). BMI and weight exhibit a significant correlation with Deff in adult patients and can be used as surrogates in the calculation of SSDEs. Using the herein-developed lookup charts, SSDEs can be calculated based on patients' weight and BMI. In abdominal CT, BMI has a superior correlation with effective diameter compared with weight, whereas weight is superior in chest CT. Patients' BMI and weight can be used as surrogates in the calculation of SSDEs.

Accuracy of a Simplified Glucose Measurement Device--The HemoCue Glucose 201RT.

Easily available, accurate glucose recordings are important when screening for and managing people with diabetes. The photometric HemoCue(®) (Ängelholm, Sweden) Glucose 201+ system, which delivers lab-comparable glucose recordings, has the drawback that its microcuvettes must be delivered and stored at 4-8°C. A newly developed system, HemoCue Glucose 201RT, has microcuvettes that can be stored at room temperature. Participants (n=444; 18-80 years old) in the EUROASPIRE IV survey, all with coronary artery disease, some with known diabetes, were investigated. Plasma glucose recordings, fasting in all participants and postprandial in the majority, were simultaneously recorded with both pieces of equipment. Congruence was expressed as median absolute difference and median absolute relative difference between the two sets of equipment and also compared according to the International Organization for Standardization (ISO) 15197:2013 criteria. Clinical accuracy was calculated with Clarke error grid analysis and cross-tabulated while considering different glucose categories (normal, impaired glucose tolerance, and diabetes). The median absolute difference between the two devices was +0.1 mmol/L, and the median absolute relative difference was +5.4%. This also corresponded with the ISO criteria. In the Clarke error grid, 99.8% ended up in Zones A and B, and 90% of the glucose values in the cross-table allocated the participant to the same glucose category. The HemoCue Glucose 201RT system is accurate, with small nonsystematic deviations, when compared with the commonly used HemoCue Glucose 201+. It is predicted that the HemoCue Glucose 201RT, which is more user friendly, will be a preferred alternative to the HemoCue Glucose 201+.

Effect of Continuous Glucose Monitoring Accuracy on Clinicians' Retrospective Decision Making in Diabetes: A Pilot Study.

The use of continuous glucose monitoring (CGM) in clinical decision making in diabetes could be limited by the inaccuracy of CGM data when compared to plasma glucose measurements. The aim of the present study is to investigate the impact of CGM numerical accuracy on the precision of diabetes treatment adjustments. CGM profiles with maximum 5-day duration from 12 patients with type 1 diabetes treated with a basal-bolus insulin regimen were processed by 2 CGM algorithms, with the accuracy of algorithm 2 being higher than the accuracy of algorithm 1, using the median absolute relative difference (MARD) as the measure of accuracy. During 2 separate and similar occasions over a 1-month interval, 3 clinicians reviewed the processed CGM profiles, and adjusted the dose level of basal and prandial insulin. The precision of the dosage adjustments were defined in terms of the interclinician agreement and the intraclinician reproducibility of the decisions. The Cohen's kappa coefficient was used to assess the precision of the decisions. The study was based on retrospective and blind CGM data. For the interclinician agreement, in the first occasion, the kappa of algorithm 1 was .32, and that of algorithm 2 was .36. For the interclinician agreement, in the second occasion, the kappas of algorithms 1 and 2 were .17 and .22, respectively. For the intraclinician reproducibility of the decisions, the kappas of algorithm 1 were .35, .22, and .80 and the kappas of algorithm 2 were .44, .52, and .32, for the 3 clinicians, respectively. For the interclinician agreement, the relative kappa change from algorithm 1 to algorithm 2 was 86.06%, and for the intraclinician reproducibility, the relative kappa change from algorithm 1 to algorithm 2 was 53.99%. Results indicated that the accuracy of CGM algorithms might potentially affect the precision of the CGM-based insulin adjustments for type 1 diabetes patients. However, a larger study with several clinical centers, with higher number of clinicians and patients is required to validate the impact of CGM accuracy on decisions precision.

Diabetes technology and the human factor.

The impressive progress achieved in recent years in diabetes technologies has made diabetes technological devices such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) a significant part of diabetes treatment. Many studies conducted in recent years emphasized the advantages of using these technologies. The concept of the “human factor” in diabetes technologies as discussed in this chapter has several different aspects. First, it can refer to the way patients are satisfied with the use of the device and whether it is perceived convenient or inconvenient. For example, is the device perceived as “user friendly” (easy to learn and to operate, comfortable, does not cause many hassles). Second, there is the issue of effectiveness of the technology as it relates to their day-to-day diabetes management. For example, there is an improvement in glycemic control when one diabetes treatment regimen is compared to another (i.e., CSII vs. multiple daily injections (MDI)). Those two fundamental aspects may have different meanings for different groups. For example, different age groups (toddlers, children, adolescents, young adults, adults, and older people) can see different advantages and disadvantages in technological devices. The feasibility and utility of technological devices also need to fit the environments in which they will be used, such as school, the work place, and/or home. Specific subgroups such as diabetic youth with eating disorders can have unique interactions with diabetes technologies. In addition, diabetes technologies can be used as a measurement device, providing more rich and accurate data about patients' self-care that can contribute to our understanding of concepts such as adherence and satisfaction, and they can provide measurement tools to assess how glycemic control can effect cognition and intelligence. The present chapter will review articles published in the last year that have studied some of these issues.

Accuracy of a real-time continuous glucose monitoring system in children with septic shock: A pilot study.

Aims:The aim of this prospective, observational study was to determine the accuracy of a real-time continuous glucose monitoring system (CGMS) in children with septic shock.Subjects and Methods:Children aged 30 days to 18 years admitted to the Pediatric Intensive Care Unit with septic shock were included. A real-time CGMS sensor was used to obtain interstitial glucose readings. CGMS readings were compared statistically with simultaneous laboratory blood glucose (BG).Results:Nineteen children were included, and 235 pairs of BG-CGMS readings were obtained. BG and CGMS had a correlation coefficient of 0.61 (P < 0.001) and a median relative absolute difference of 17.29%. On Clarke's error grid analysis, 222 (94.5%) readings were in the clinically acceptable zones (A and B). When BG was < 70, 70–180, and > 180 mg/dL, 44%, 100%, and 76.9% readings were in zones A and B, respectively (P < 0.001). The accuracy of CGMS was not affected by the presence of edema, acidosis, vasopressors, steroids, or renal replacement therapy. On receiver operating characteristics curve analysis, a CGMS reading <97 mg/dL predicted hypoglycemia (sensitivity 85.2%, specificity 75%, area under the curve [AUC] =0.85). A reading > 141 mg/dL predicted hyperglycemia (sensitivity 84.6%, specificity 89.6%, AUC = 0.87).Conclusion:CGMS provides a fairly, accurate estimate of BG in children with septic shock. It is unaffected by a variety of clinical variables. The accuracy over extremes of blood sugar may be a concern. We recommend larger studies to evaluate its use for the early detection of hypoglycemia and hyperglycemia.

An assessment of the performance of the Monitor for AeRosols and GAses in ambient air (MARGA): a semi-continuous method for soluble compounds

Abstract. Ambient air monitoring as part of the US Environmental Protection Agency's (US EPA's) Clean Air Status and Trends Network (CASTNet) currently uses filter packs to measure weekly integrated concentrations. The US EPA is interested in supplementing CASTNet with semi-continuous monitoring systems at select sites to characterize atmospheric chemistry and deposition of nitrogen and sulfur compounds at higher time resolution than the filter pack. The Monitor for AeRosols and GAses in ambient air (MARGA) measures water-soluble gases and aerosols at an hourly temporal resolution. The performance of the MARGA was assessed under the US EPA Environmental Technology Verification (ETV) program. The assessment was conducted in Research Triangle Park, North Carolina, from 8 September to 8 October 2010 and focused on gaseous SO2, HNO3, and NH3 and aerosol SO42-, NO3-, and NH4+. Precision of the MARGA was evaluated by calculating the median absolute relative percent difference (MARPD) between paired hourly results from duplicate MARGA units (MUs), with a performance goal of ≤ 25%. The accuracy of the MARGA was evaluated by calculating the MARPD for each MU relative to the average of the duplicate denuder/filter pack concentrations, with a performance goal of ≤ 40%. Accuracy was also evaluated by using linear regression, where MU concentrations were plotted against the average of the duplicate denuder/filter pack concentrations. From this, a linear least squares line of best fit was applied. The goal was for the slope of the line of best fit to be between 0.8 and 1.2. The MARGA performed well in comparison to the denuder/filter pack for SO2, SO42−, and NH4+, with all three compounds passing the accuracy and precision goals by a significant margin. The performance of the MARGA in measuring NO3- could not be evaluated due to the different sampling efficiency of coarse NO3- by the MUs and the filter pack. Estimates of "fine" NO3- were calculated for the MUs and the filter pack. Using this and results from a previous study, it is concluded that if the MUs and the filter pack were sampling the same particle size, the MUs would have good agreement in terms of precision and accuracy. The MARGA performed moderately well in measuring HNO3 and NH3, though neither met the linear regression slope goals. However, recommendations for improving the measurement of HNO3 and NH3 are discussed. It is concluded that SO42-, SO2, NO3-, HNO3, NH4+, and NH3 concentrations can be measured with acceptable accuracy and precision when the MARGA is operated in conjunction with the recommendations outlined in the manuscript.

Accuracy and acceptability of the 6-day Enlite continuous subcutaneous glucose sensor.

This study evaluated the performance and acceptability of the Enlite(®) glucose sensor (Medtronic MiniMed, Inc., Northridge, CA). Ninety adults with type 1 or type 2 diabetes wore two Enlite sensors on the abdomen and/or buttock for 6 days and calibrated them at different frequencies. On Days 1, 3, and 6, accuracy was evaluated by comparison of sensor glucose values with frequently sampled plasma glucose values collected over a 12-h period. Accuracy was assessed at different reference glucose concentrations and during times when absolute glucose concentration rates of change were <1, 1-2, and >2 mg/dL/min. The sensor's ability to detect hypoglycemia or hyperglycemia was evaluated with simulated alerts. Subject satisfaction was evaluated with a 7-point Likert-type questionnaire, with a score of 7 indicating strong agreement. With abdomen sensors under actual-use calibration (mean, 2.8 ± 0.9 times/day), the overall mean (median) absolute relative difference (ARD) values between sensor and reference values were 13.6% (10.1%); the corresponding buttock sensor ARD values were 15.5% (10.5%). With abdomen sensors under minimal calibration (mean, 1.2 ± 0.9 times/day), the mean (median) ARD values were 14.7% (10.8%). Mean ARD values of abdomen sensors at rates of change of <1, 1-2, and >2 mg/dL/min were 13.6%, 12.9%, and 16.3%, respectively. With abdomen sensors, 79.5% and 94.1% of hypoglycemic and hyperglycemic events, respectively, were correctly detected; 81.9% and 94.9% of hypoglycemic and hyperglycemic alerts, respectively, were confirmed. The failure rates for abdomen and buttock sensors were 19.7% and 13.9%, respectively. Mean responses to survey questions for all subjects related to comfort and ease of use were favorable. The Enlite sensor provided accurate data at different glucose concentrations and rates of change. Subjects found the sensor comfortable and easy to use.

Assessment of the Aerosol Products From the SeaWiFS and MODIS Ocean-Color Missions

The aerosol products derived from the ocean-color missions Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate-Resolution Spectroradiometer (MODIS) Aqua and Terra are compared with field measurements from globally distributed Aerosol Robotic Network (AERONET) sites. Validation statistics are found consistent for the three missions. The median absolute relative difference between SeaWiFS and AERONET aerosol optical thickness τa is approximately 20% at all bands while it is slightly higher for both MODIS products (between 20% and 28%). This is associated with a larger relative bias (median of relative differences between satellite and AERONET τa) on the order of +15% for these missions. With respect to previous processing versions, a noticeable improvement is seen in the representation of the spectral dependence of τa. The bias found for the Angstrom exponent varies from -0.08 to +0.13 for the three missions.

Performance Comparison of the Medtronic Sof-Sensor and Enlite Glucose Sensors in Inpatient Studies of Individuals with Type 1 Diabetes

Knowledge of the accuracy of continuous glucose monitoring (CGM) devices is important for its use as a management tool for individuals with diabetes and for its use to assess outcomes in clinical studies. Using data from several inpatient studies, we compared the accuracy of two sensors, the Medtronic Enlite™ using MiniMed Paradigm(®) Veo™ calibration and the Sof-Sensor(®) glucose sensor using Guardian(®) REAL-Time CGM calibration (all from Medtronic Diabetes, Northridge, CA). Nocturnal data were analyzed from eight inpatient studies in which both CGM and reference glucose measurements were available. The analyses included 1,666 CGM-reference paired glucose values for the Enlite in 54 participants over 69 nights and 3,627 paired values for the Sof-Sensor in 66 participants over 91 nights. The Enlite sensor tended to report glucose levels lower than the reference over the entire range of glucose values, whereas the Sof-Sensor values tended to be higher than reference values in the hypoglycemic range and lower than reference values in the hyperglycemic range. The overall median sensor-reference difference was -15 mg/dL for the Enlite and -1 mg/dL for the Sof-Sensor (P<0.001). The median relative absolute difference was 15% for the Enlite versus 12% for the Sof-Sensor (P=0.06); 66% of Enlite values and 73% of Sof-Sensor values met International Organization for Standardization criteria. We found that the Enlite tended to be biased low over the entire glucose range, whereas the Sof-Sensor showed the more typical sensor pattern of being biased high in the hypoglycemic range and biased low in the hyperglycemic range.

Accuracy of continuous glucose monitoring during exercise in type 1 diabetes pregnancy.

Performance of continuous glucose monitors (CGMs) may be lower when glucose levels are changing rapidly, such as occurs during physical activity. Our aim was to evaluate accuracy of a current-generation CGM during moderate-intensity exercise in type 1 diabetes (T1D) pregnancy. As part of a study of 24-h closed-loop insulin delivery in 12 women with T1D (disease duration, 17.6 years; glycosylated hemoglobin, 6.4%) during pregnancy (gestation, 21 weeks), we evaluated the Freestyle Navigator(®) sensor (Abbott Diabetes Care, Alameda, CA) during afternoon (15:00-18:00 h) and morning (09:30-12:30 h) exercise (55 min of brisk walking on a treadmill followed by a 2-h recovery), compared with sedentary conditions (18:00-09:00 h). Plasma (reference) glucose, measured at regular 15-30-min intervals with the YSI Ltd. (Fleet, United Kingdom) model YSI 2300 analyzer, was used to assess CGM performance. Sensor accuracy, as indicated by the larger relative absolute difference (RAD) between paired sensor and reference glucose values, was lower during exercise compared with rest (median RAD, 11.8% vs. 18.4%; P<0.001). These differences remained significant when correcting for plasma glucose relative rate of change (P<0.001). Analysis by glucose range showed lower accuracy during hypoglycemia for both sedentary (median RAD, 24.4%) and exercise (median RAD, 32.1%) conditions. Using Clarke error grid analysis, 96% of CGM values were clinically safe under resting conditions compared with only 87% during exercise. Compared with sedentary conditions, accuracy of the Freestyle Navigator CGM was lower during moderate-intensity exercise in pregnant women with T1D. This difference was particularly marked in hypoglycemia and could not be solely explained by the glucose rate of change associated with physical activity.

Validation of SeaWiFS and MODIS Aqua/Terra aerosol products in coastal regions of European marginal seas

The aerosol products associated with the ocean colour missions SeaWiFS and MODIS (both Aqua and Terra) are assessed with AERONET field measurements collected in four European marginal seas for which fairly large uncertainties in ocean colour in-water products have been documented: the northern Adriatic, the Baltic, Black and North Seas. On average, more than 500 match-ups are found for each basin and satellite mission, showing an overall consistency of validation statistics across the three missions. The median absolute relative difference between satellite and field values of aerosol optical thickness τa at 443nm varies from 12% to 15% for the three missions at the northern Adriatic and Black Sea sites, and from 13% to 26% for the Baltic and North Sea sites. It is in the interval 16–31% for the near-infrared band. The spectral shape of τa is well reproduced with a median bias of the Ångström exponent varying between -15% and +14%, which represents a clear improvement with respect to previous versions of the atmospheric correction scheme. These results show that the uncertainty associated with τa in the considered coastal waters of the European marginal seas is comparable to global validation statistics.

Periodic Extraction of Interstitial Fluid from the Site of Subcutaneous Insulin Infusion for the Measurement of Glucose: A Novel Single-Port Technique for the Treatment of Type 1 Diabetes Patients

Treatment of type 1 diabetes patients could be simplified if the site of subcutaneous insulin infusion could also be used for the measurement of glucose. This study aimed to assess the agreement between blood glucose concentrations and glucose levels in the interstitial fluid (ISF) that is extracted from the insulin infusion site during periodic short-term interruptions of continuous subcutaneous insulin infusion (CSII). A perforated cannula (24 gauge) was inserted into subcutaneous adipose tissue of C-peptide-negative type 1 diabetes subjects (n=13) and used alternately to infuse rapid-acting insulin (100 U/mL) and to extract ISF glucose during a fasting period and after ingestion of a standard oral glucose load (75 g). Although periodically interrupted for extracting glucose (every hour for approximately 10 min), insulin infusion with the cannula was adequate to achieve euglycemia during fasting and to restore euglycemia after glucose ingestion. Furthermore, the ISF-derived estimates of plasma glucose levels agreed well with plasma glucose concentrations. Correlation coefficient and median absolute relative difference values were found to be 0.95 and 8.0%, respectively. Error grid analysis showed 99.0% of all ISF glucose values within clinically acceptable Zones A and B (83.5% Zone A, 15.5% Zone B). Results show that ISF glucose concentrations measured at the insulin infusion site during periodic short-term interruptions of CSII closely reflect blood glucose levels, thus suggesting that glucose monitoring and insulin delivery may be performed alternately at the same tissue site. A single-port device of this type could be used to simplify and improve glucose management in diabetes.

The Accuracy and Efficacy of Real-Time Continuous Glucose Monitoring Sensor in Chinese Diabetes Patients: A Multicenter Study

The purpose of this multicenter study was to investigate the accuracy of a real-time continuous glucose monitoring sensor in Chinese diabetes patients. In total, 48 patients with type 1 or 2 diabetes from three centers in China were included in the study. The MiniMed Paradigm(®) 722 insulin pump (Medtronic, Northridge, CA) was used to monitor the real-time continuous changes of blood glucose levels for three successive days. Venous blood of the subjects was randomly collected every 15 min for seven consecutive hours on the day when the subjects were wearing the sensor. Reference values were provided by the YSI(®) 2300 STAT PLUS™ glucose and lactate analyzer (YSI Life Sciences, Yellow Springs, OH). In total, 1,317 paired YSI-sensor values were collected from the 48 patients. Of the sensor readings, 88.3% (95% confidence interval, 0.84-0.92) were within±20% of the YSI values, and 95.7% were within±30% of the YSI values. Clarke and consensus error grid analyses showed that the ratios of the YSI-sensor values in Zone A to the values in Zone B were 99.1% and 99.9%, respectively. Continuous error grid analysis showed that the ratios of the YSI-sensor values in the region of accurate reading, benign errors, and erroneous reading were 96.4%, 1.8%, and 1.8%, respectively. The mean absolute relative difference (ARD) for all subjects was 10.4%, and the median ARD was 7.8%. Bland-Altman analysis detected a mean blood glucose level of 3.84 mg/dL. Trend analysis revealed that 86.1% of the difference of the rates of change between the YSI values and the sensor readings occurred within the range of 1 mg/dL/min. The Paradigm insulin pump has high accuracy in both monitoring the real-time continuous changes and predicting the trend of changes in blood glucose level. However, actual clinical manifestations should be taken into account for diagnosis of hypoglycemia.

Real-Time Continuous Glucose Monitoring in an Intensive Care Unit: Better Accuracy in Patients with Septic Shock

This study assessed the accuracy of real-time continuous glucose monitoring system (RTCGMS) devices in an intensive care unit (ICU) to determine whether the septic status of the patient has any influence on the accuracy of the RTCGMS. In total, 41 patients on insulin therapy were included. Patients were monitored for 72 h using RTCGMS. Arterial blood glucose (ABG) samples were obtained following the protocol established in the ICU. The results were evaluated using paired values (excluding those used for calibration) with the performance assessed using numerical accuracy. Nonparametric tests were used to determine statistically significant differences in accuracy. In total, 956 ABG/RTCGMS pairs were analyzed. The overall median relative absolute difference (RAD) was 13.5%, and the International Organization for Standardization (ISO) criteria were 68.1%. The median RADs reported for patients with septic shock, with sepsis, and without sepsis were 11.2%, 14.3%, and 16.3%, respectively (P<0.05). Measurements meeting the ISO criteria were 74.5%, 65.6%, and 63.7% for patients with septic shock, with sepsis, and without sepsis, respectively (P<0.05). The results showed that the septic status of patients influenced the accuracy of the RTCGMS in the ICU. Accuracy was significantly better in patients with septic shock in comparison with the other patient cohorts.

Optimal Sampling Intervals to Assess Long-Term Glycemic Control Using Continuous Glucose Monitoring

The optimal duration and frequency of short-term continuous glucose monitoring (CGM) to reflect long-term glycemia have not been determined. The Juvenile Diabetes Research Foundation CGM randomized trials provided a large dataset of longitudinal CGM data for this type of analysis. The analysis included 185 subjects who had 334 3-month intervals of CGM data meeting specific criteria. For various glucose indices, correlations (r²) were computed for the entire 3-month interval versus selected sampling periods ranging from 3 to 15 days. Other computed agreement measures included median relative absolute difference, values within ± 10% and ± 20% of full value, and median absolute difference. As would be expected, the more days of glucose data that were sampled, the higher the correlation with the full 3 months of data. For 3 days of sampling, the r² value ranged from 0.32 to 0.47, evaluating mean glucose, percentage of values 71-180 mg/dL, percentage of values > 180 mg/dL, percentage of values ≤ 70 mg/dL, and coefficient of variation; in contrast, for 15 days of sampling, the r² values ranged from 0.66 to 0.75. The results were similar when the analysis intervals were stratified by age group (8-14, 15-24, and ≥ 25 years), by baseline hemoglobin A1c level (< 7.0% and ≥ 7.0%), and by CGM device type. Our data suggest that a 12-15-day period of monitoring every 3 months may be needed to optimally assess overall glucose control. Shorter periods of sampling can be useful, but the correlation with 3-month measures of glycemic control is lower.

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.

Noninvasive Glucose Monitoring: Increasing Accuracy by Combination of Multi-Technology and Multi-Sensors

The main concern in noninvasive (NI) glucose monitoring methods is to achieve high accuracy results despite the fact that no direct blood or interstitial fluid glucose measurement is performed. An alternative approach to increase the accuracy of NI glucose measurement was previously suggested through a combination of three NI methods: ultrasonic, electromagnetic, and thermal. This paper provides further explanation about the nature of the implemented technologies, and multi-sensors are presented, as well as a detailed elaboration on the novel algorithm for data analysis. Clinical trials were performed on two different days. During the first day, calibration and six subsequent measurements were performed. During the second day, a "full day" session of about 10 hours took place. During the trial, type 1 and 2 diabetes patients were calibrated and evaluated with GlucoTrack glucose monitor against HemoCue (Glucose 201+). A total of 91 subjects were tested during the trial period. Clarke error grid (CEG) analysis shows 96% of the readings (on both days 1 and 2) fall in the clinically accepted A and B zones, of which 60% are within zone A. The absolute relative differences (ARDs) yield mean and median values of 22.4% and 15.9%, respectively. The CEG for day 2 of the trial shows 96% of the points in zones A and B, with 57% of the values in zone A. Mean and median ARD values for the readings on day 2 are 23.4% and 16.5%, respectively. The intervals between day 1 (calibration and measurements) and day 2 (measurements only) were 1-22 days, with a median of 6 days. The presented methodology shows that increased accuracy was indeed achieved by combining multi-technology and multi-sensors. The approach of integration contributes to increasing the signal-to-noise ratio (glucose to other contributors). A combination of several technologies allows compensation of a possible aberration in one modality by the others, while multi-sensor implementation enables corrections for interference contributions. Furthermore, clinical trials indicate the ability of using the device for a wide range of demography, showing clearly that the calibration is valid for long term.

Assessment of different techniques for subcutaneous glucose monitoring in Type 1 diabetic patients during ‘real‐life’ glucose excursions

To compare the accuracy of two marketed subcutaneous glucose monitoring devices (Guardian RT, GRT; GlucoDay S, GDS) and standard microdialysis (CMA60; MD) in Type 1 diabetic patients. Seven male Type diabetic patients were investigated over a period of 26 h simulating real-life meal glucose excursions. Catheters of the three systems were inserted into subcutaneous adipose tissue of the abdominal region. For MD, interstitial fluid was sampled at 30- to 60-min intervals for offline glucose determination. Reference samples were taken at 15- to 60-min intervals. All three systems were prospectively calibrated to reference. Median differences, median absolute relative differences (MARD), median absolute differences (MAD), Bland-Altman plot and Clark Error Grid were used to determine accuracy. Bland-Altman analysis indicated a mean glucose difference (2 standard deviations) between reference and interstitial glucose of -10.5 (41.8) % for GRT, 20.2 (55.9) % for GDS and 6.5 (35.2) % for MD, respectively. Overall MAD (interquartile range) was 1.07 (0.39; 2.04) mmol/l for GRT, 1.59 (0.54; 3.08) mmol/l for GDS and 0.76 (0.26; 1.58) mmol/l for MD. Overall MARD was 15.0 (5.6; 23.4) % (GRT), 19.7 (6.1; 37.6) % (GDS) and 8.7 (4.1; 18.3) % (MD), respectively. Total sensor failure occurred in two subjects using GRT and one subject using GDS. The three investigated technologies had comparable performance. Whereas GRT underestimated actual blood glucose, GDS and MD overestimated blood glucose. Considerable deviations during daily life meal glucose excursions from reference glucose were observed for all three investigated technologies. Present technologies may require further improvement until individual data can lead to direct and automated generation of therapeutic advice in diabetes management.