Numerical Simulation of the Effect of Rate of Change of Glucose on Measurement Error of Continuous Glucose Monitors

Background

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.

Method

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.

Results

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.

Conclusions

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.     

Accuracy of flash glucose monitoring in insulin‐treated patients with type 2 diabetes

The present study evaluated the accuracy of interstitial glucose measurements by flash glucose monitoring (FGM) and continuous glucose monitoring (CGM). Five diabetes patients simultaneously underwent FGM (FreeStyle Libre Pro) and CGM (iPro?2), and their glucose levels were compared with venous blood and capillary blood glucose levels. The range of daily venous blood glucose levels (30 measurements) was 70–245 mg/dL, with a median of 138 mg/dL. There were good correlations of glucose levels measured by FGM (r² = 0.90, mean absolute relative difference 8.2 ± 5.6%), CGM (r² = 0.86, mean absolute relative difference 9.2 ± 9.1%) and capillary blood (r² = 0.87, mean absolute relative difference 7.2 ± 7.2%) with venous blood glucose levels. The accuracy of FGM measurements was also shown against CGM, with 99.9% of the FGM values (1,279 measurements) being within the Parkes error grid zones A and B. The results suggest that the accuracy of FGM is similar to that of CGM, and that FGM is a useful tool for determining daily glucose profile.     

The Accuracy of a New Real-Time Continuous Glucose Monitoring Algorithm: An Analysis

In this issue of Journal of Diabetes Science and Technology, Keenan and colleagues used archival data from the STAR 1 clinical trial (Medtronic Diabetes) to support the claim that the new Veo™ calibration algorithm improves the accuracy of continuous glucose monitoring, particularly in the critical hypoglycemic range. Extensive data analyses are presented to support this claim; the results are convincing, and the estimated improvement in hypoglycemic detection from 55% for the standard calibration to 82% for the Veo is particularly impressive. We can therefore conclude that the Veo algorithm has the potential to improve the accuracy of hypoglycemia alarms and ultimately contribute to closed-loop control. However, the presented results should be interpreted cautiously because they are based on retrospective analysis and are heavily dependent on the distribution of blood glucose levels observed in a particular data set.     

Establishing a Continuous Glucose Monitoring Program

Real-time continuous glucose monitoring (RT-CGM) devices provide detailed information on glucose patterns and trends, and alarms that alert the patient to both hyper- and hypoglycemia. This technology can dramatically improve the day-to-day management of patients with diabetes and promises to be a major advance in diabetes care. The safe and effective use of RT-CGM in diabetes management rests on an understanding of several physiological as well as technological issues. This article outlines the key issues that should be addressed in the training curriculum for patients starting on RT-CGM: (1) physiologic lag between interstitial and blood glucose levels and the implications for device calibration, and interpretation and use of data in diabetes management; (2) practical considerations with the use of sensor alarms and caveats in the setting of alarm thresholds; and (3) potential risk for hypoglycemia related to excessive postprandial bolusing by RT-CGM users, and the practical implications for patient training.     

Clinical Overview of Continuous Glucose Monitoring

Continuous glucose monitoring (CGM) is now available from several companies in the United States for purchase or research studies. This article provides an overview of these devices and reviews the use of sensors for managing diabetes in “real time,” as well as the use of retrospective analysis of CGM results.     

An Analysis of the SEVEN? System: Have We Reached the Summit of Needle-Type Sensor Accuracy?

In this issue of Journal of Diabetes Science and Technology, Zisser and colleagues show improved sensor accuracy with the newest generation of needle-type sensors as compared to first generation sensors. Can we expect further improvement? It is unknown what the future holds, but there certainly seems much to be gained from improved calibration procedures. In addition, sensor operating times are increasing and it is hoped that this will translate into improved sensor use and thereby into improved glycemic control.     

Randomized controlled trial to assess the impact of continuous glucose monitoring on HbA1c in insulin‐treated diabetes (MITRE Study)

Aims To determine whether continuous glucose information provided through use of either the GlucoWatch G2 Biographer or the MiniMed continuous glucose monitoring system (CGMS) results in improved glycated haemoglobin (HbA_1c) for insulin‐treated adults with diabetes mellitus, relative to an attention control and standard care group. Methods Four hundred and four adults taking at least two daily insulin injections and with two consecutive HbA_1c values ≥ 7.5% were recruited to this randomized controlled trial (RCT). All were trained at baseline to use the same monitor for traditional capillary glucose testing throughout the 18‐month study. The CGMS group were asked to wear the device three times during the first 3 months of the trial and on another three occasions thereafter. The GlucoWatch group wore the device a minimum of four times per month and a maximum of four times per week during the first 3 months and as desired for the remainder of the trial. Trained diabetes research nurses used downloaded data to guide therapy adjustments. Proportional reduction in HbA_1c from baseline to 18 months was the primary outcome measure. Results Neither an intention‐to‐treat nor per‐protocol analysis showed improvement in HbA_1c in the device groups compared with standard care. For the intention‐to‐treat analysis, when the standard care group was compared with each of the other groups, this equated to differences in mean relative HbA_1c reduction (95% confidence interval) from baseline to 18 months of 3.5% (?1.3 to 8.3; GlucoWatch), 0.7% (?4.1 to 5.5; CGMS), and ?0.1% (?4.6 to 4.3; attention control). Conclusions The additional information provided by these devices did not result in improvements in HbA_1c in this population.     

Continuous Glucose Monitoring: Evidence and Consensus Statement for Clinical Use

Continuous glucose monitoring (CGM) is an essential tool for modern diabetes therapy. Randomized controlled studies have provided evidence that hemoglobin A1c (HbA1c) results can be improved in patients with type 1 diabetes with elevated baseline HbA1c when using CGM frequently enough and that the frequency and duration of hypoglycemic events can be reduced in patients with satisfactory baseline HbA1c. The CGM group within the Working Group Diabetes Technology (AGDT) of the German Diabetes Association (DDG) has defined evidence-based indications for the practical use of CGM in this consensus statement related to hypoglycemia (frequent, severe, or nocturnal) or hypoglycemia unawareness, insufficient metabolic control despite use of all possible therapeutic options and patient compliance, pregnancy associated with inadequate blood glucose results, and the need for more than 10 blood glucose measurements per day. Contraindications and defined preconditions for the successful use of CGM should be considered.     

Do Different Frequencies of Self-monitoring of Blood Glucose Influence Control in Type 1 Diabetic Patients?

The effect of altering the frequency of self-monitoring of blood glucose upon blood glucose control was assessed in 25 Type 1 diabetic patients. Patients entered a balanced, crossover study in which they were randomly allocated to three 12-week periods. During each period the frequency at which patients self-monitored their blood glucose was: (1) four-point profiles on 2 days per week; (2) four-point profiles on 1 day per week; (3) two-point profiles on every day of the week. There were no significant differences in mean blood glucose concentration, fructosamine or glycosylated haemoglobin concentrations during the three periods. There was no correlation between the frequency at which patients altered insulin doses and measures of metabolic control. Altering the frequency of blood glucose self-monitoring had a variable and uncertain influence upon the frequency at which patients altered insulin doses. Some patients felt unsafe monitoring blood glucose only four times per week. There was however no patient consensus on the best-liked regimen.     

Acceptability and Utility of the mySentry Remote Glucose Monitoring System

Background

The mySentry system (Medtronic Inc.) is the first to amplify and relay continuous glucose monitoring (CGM) and insulin pump data to a remote site within the house. Its usability and acceptability were evaluated in families having a child with type 1 diabetes.

Methods

Each enrolled family included a child (age 7–17 years) who used a Paradigm REAL-Time Revel sensor-augmented insulin pump (Medtronic). After a 1-week run-in phase, families set up and used the mySentry system for a 3-week study phase. Opinion surveys were completed by parents, and pump and CGM data were collected and analyzed retrospectively. No formal hypothesis testing was performed, and the study was not powered to detect changes in nocturnal glycemia.

Results

Thirty-five families completed the study. Enrolled children (61.1% female) had a mean (± standard deviation) age of 11.9 ± 2.70 years and a mean age at initiation of pump therapy of 7.1 ± 3.19 years. Baseline survey results indicated that most parents were fearful of their unawareness of their children’s nocturnal glucose excursions. The mySentry system met the predefined acceptability criteria for general experience, product usability, and training materials. There were no unanticipated device-related adverse effects. Among children who experienced nocturnal hypo- or hyperglycemic episodes in both phases of the study, there was a trend toward less frequent and less prolonged episodes during mySentry use.

Conclusions

The mySentry system met all predefined criteria for acceptability and did not demonstrate safety issues. Alerting parents to abnormal glucose values or trends may attenuate nocturnal hypoglycemia and hyperglycemia by prompting appropriate and timely intervention.     

Effect of disinfectants on glucose monitors

Background

Monitoring blood glucose levels is an integral part of routine diabetes management. To minimize the risk of transmission of bloodborne pathogens during monitoring, the Centers for Disease Control and Prevention (CDC) recommends that glucose meters be disinfected after each use whenever they are used to test multiple patients. The objective of this study is to assess the compatibility of some common disinfectants with certain blood glucose meter systems.

Methods

We tested six disinfectants for adverse impact on meter performance or the exterior meter surfaces.The disinfectants tested were 0.525% sodium hypochlorite, 20% 2-propanol and 10% ethanol, 17.2% isopropanol, 55% isopropanol, 70% isopropanol, and hydrogen peroxide. To assess meter performance, we tested OneTouch® Ultra® blood glucose monitoring systems with control solution before and after application of either water or disinfectant. To assess the effect on exterior meter surfaces, we performed a soaking test to simulate long-term exposure to disinfectant.

Results

Paired t-test results showed that the control solution data associated with disinfectant and with water application were not significantly different for each meter type. However, most of the meter types were adversely affected by hydrogen peroxide and/or by the higher concentrations of alcohol-based disinfectants.

Conclusions

Although none of the six disinfectants affected meter performance, hydrogen peroxide and isopropanol >20% adversely affected the exterior surfaces of the tested meters. When complying with CDC instructions for meter disinfection, users should use caution and choose disinfectants that have been validated by the meter manufacturer.     

实时动态血糖监测对住院2型糖尿病患者血糖波动的控制

目的 评估实时动态血糖监测对血糖波动的影响.方法 2010年1月至2012年12月,选取住院胰岛素治疗的2型糖尿病患者122例,按随机数字表法分组为传统动态血糖监测（传统组,n=61）和实时动态血糖监测（实时组,n=61）.进行72 h持续血糖监测,安装当天为设备调试日（d0）,其后第1天（d1）和第2天（d2）为观察时限.传统组每日3次根据指尖末梢血糖调整血糖;实时组每日3次根据实时显示血糖曲线,调整降糖,并设定高低血糖报警界限.统计分析组内（d1和d2）和组间平均血糖波动幅度（MAGE）、平均血糖（MBG）、血糖标准差（SDBG）、日间血糖平均绝对差（MODD）、日内最大血糖波动幅度（LAGE）和低血糖情况.组间比较采用两独立样本均数比较t检验,计数资料采用x2检验.结果 （1）组内比较：实时组d1与d2的MAGE、MBG、SDBG、LAGE分别为（5.3±3.2）比（4.2±2.1）、（8.6±1.7）比（8.2±1.5）、（2.1±0.9）比（1.8±0.7）、（8.6±3.3）比（7.5±2.8）mmol/L（F=9.797、5.852、20.625、11.057,均P＜0.05）,低血糖持续时间为40（32.5 ～135） min比25（15 ～ 40） min（Z=2.456,P＜0.05）.传统组d1与d2的MAGE、MBG、LAGE差异均无统计学意义（F=0.229、0.246、0.635,均P＞0.05）;SDBG为（2.4±1.1）比（2.2±1.0） mmol/L（F=5.615,P＜0.05）.（2）组间比较：实时组和传统组d1、d2MAGE、LAGE差值之间的比较分别为0.7（-0.3 ～2.0）比0（-1.0～1.5）、0.9（-0.7～2.1）比0.1（-2.5 ～1.9）（Z值分别为2.002、2.023,均P＜0.05）;组间MODD比较1.8（1.3 ～2.6）比2.1（1.4～2.9） mmol/L（Z=1.572,P＞0.05）.结论 依据实时动态血糖监测,及时调整降糖策略,能减少血糖波动,使血糖更稳、更快达标.     

Evaluation of a Minimally Invasive System for Measuring Glucose Area under the Curve during Oral Glucose Tolerance Tests: Usefulness of Sweat Monitoring for Precise Measurement

Aims:

We developed a system for measuring glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET). Sweat contamination during interstitial fluid glucose (IG) extraction affects the accuracy of glucose AUC measurement, because this technology uses extracted sodium ion levels as an internal standard. Therefore, we developed a sweat monitoring patch to reduce this effect and investigated its efficacy in volunteers undergoing oral glucose tolerance tests (OGTTs).

Materials and Methods:

Fifty diabetes mellitus inpatients and 10 healthy subjects undergoing the 75 g OGTT were included. Two sites on the forearm were pretreated with microneedle arrays, then hydrogels for interstitial fluid extraction were placed on the treated sites. Simultaneously, hydrogels for sweat monitoring were placed on untreated sites near the treated sites. Plasma glucose (PG) levels were measured every 30 min for 2 h to calculate reference AUC values. Using MIET, IG AUC was calculated from extracted glucose and sodium ion levels after attachment of the hydrogel for 2 h.

Results:

Good correlation between IG AUC measurements using MIET and reference AUCs measured using PG levels was confirmed over a wide AUC range (202–610 mg/h/dl) after correction for the sweat-induced error detected by the hydrogel patches on the nonpretreated skin. Strong correlation between IG AUC and peak glucose levels indicates that glucose spikes can be easily detected by this system.

Conclusion:

We confirmed the effectiveness of a sweat monitoring patch for precise AUC measurement using MIET. This novel, easy-to-use system has potential for glucose excursion evaluation in daily clinical practice.     

床边血糖管理系统监测住院糖尿病患者低血糖发生特点

目的分析住院糖尿病患者低血糖发生特点及其危险因素。方法利用医用SureStepFlexx床边血糖管理系统回顾性分析2008年1月至2011年12月3634例住院不同糖尿病分型的患者共203802次血糖监测数据中的低血糖发生的特点,探讨其相关危险因素。两组或多组间率的比较采用列联表分析。结果研究期间在广东省人民医院内分泌科住院的糖尿病患者共3634例（男／女：1805／1829例）。平均年龄为（59±15）岁。血糖监测共203802次,监测密度最大为早餐前（33567／203802,16．5％）,最小在凌晨（17701／203802,8．7％）,午餐前（21271／203802,10．4％）亦较低。共发生低血糖事件2453次,发生密度为1．2％。凌晨（506／2453,20．6％）及午餐前（406／2453,16．5％）低血糖发生率最高。有近1／3患者（1127／3634,31．0％）住院期间发生过低血糖,其中单次低血糖占52．4％（590／1127）,2～3次低血糖为32．8％（370／1127）,4次以上者达14．8％（167／1127）。以逐步筛选法进行二项分类logistic回归分析发现,住院低血糖的主要危险因素是：1型糖尿病（OR：2．478,95％CI：1．067～5．754）、多次胰岛素治疗[胰岛素泵：2．254（1．283～3．959）、三或四段胰岛素：2．307（1．310～4．065）、预混胰岛素：2．119（1.179～3．808）、糖化血红蛋白（HbAlc）〈7．0％：2．008（1．560～2．583）]。结论住院期间糖尿病患者低血糖最多发生在凌晨,其次到午餐前,恰是血糖监测密度最少时段,关注凌晨及午餐前血糖监测有利于及时发现低血糖。对于1型糖尿病、胰岛素强化治疗及HbAlc〈7．0％患者在控制血糖达标同时要特别注意防止低血糖发生。     

Effect of short-term use of a continuous glucose monitoring system with a real-time glucose display and a low glucose alarm on incidence and duration of hypoglycemia in a home setting in type 1 diabetes mellitus

Background

The objective of this study was to examine whether setting the low glucose alarm of a Guardian^® REAL-Time continuous glucose monitoring system (CGMS) to 80 mg/dl for 3 days and providing instructions to users reduce the risk of hypoglycemia under free-living conditions in individuals with type 1 diabetes mellitus (T1DM).

Methods

Fourteen participants with T1DM aged 26.1 ± 6.0 years (mean ± standard deviation) were fitted with a CGMS and assigned for 3 days to either an alarm [low and high blood glucose (BG) alarms set at 80 and 200 mg/dl, respectively] or no alarm condition, with each treatment administered to all participants following a counterbalanced design. All participants were given detailed instructions on how to respond appropriately to low glucose alarms.

Results

The CGMS with alarm reduced the incidence of hypoglycemia (CGMS readings ≤65 mg/dl) by 44% as well as the time spent below this hypoglycemic threshold by 64% without increasing average BG levels. However, the CGMS with alarm had no effect on the incidence of symptomatic hypoglycemia.

Conclusions

Short-term use of the CGMS with alarm, together with appropriate instructions for users, reduces the incidence and duration of hypoglycemia, but only to a limited extent, in part because it overestimates BG in the low glucose range.     

Accuracy performance of the Medtronic NexSensor™ for 6 days in an inpatient setting using abdomen and buttocks insertion sites

Background

Users of continuous glucose monitoring are concerned with product accuracy and choice of insertion site. The Medtronic NexSensor™ was evaluated for accuracy during 6 days of wear when inserted in the abdomen and buttocks areas.

Methods

Adults (ages 18–75) with type 1 diabetes wore two sensors simultaneously for 6 days, one each inserted in the abdomen and buttocks. Subjects underwent a frequent blood sampling study for 12 hours, during which time reference blood glucose values were obtained every 15 minutes and compared to sensor values.

Results

Sixty-three subjects were enrolled, and 61 subjects completed the study. The mean agreement rate between sensor and blood glucose values was 75.5% [95% confidence interval (CI), 69.5, 81.4] at the abdomen site, 73.8% (95% CI, 68.8, 78.8) at the buttocks site, and 75.6% (95% CI, 70.8, 80.4) when sensor and reference data were combined between sites. Over 90% of paired sensor-reference values on Clarke error grids were within the A and B ranges. The mean absolute relative differences were 17.1% at the abdomen site, 16.5% at the buttocks site, and 16.8% when sites were combined.

Conclusion

The NexSensor was accurate for inpatient, frequent-sample testing for 6 days when inserted into the abdomen and buttocks. The results of this study also provide evidence that both the abdomen and buttocks are suitable as sensor insertion sites.     

空腹和餐后手指末梢血糖与静脉血糖浓度差异的比较分析

目的分析比较空腹和餐后2h手指末梢全血、血浆与静脉全血、血浆4种不同血样葡萄糖浓度之间的差异。方法2010年8月至12月共140例1型或2型糖尿病患者纳入试验。其中男56例、女84例,年龄（54±10）岁。空腹血糖82例．餐后2h血糖58例,每例患者采集手指末梢全血、血浆以及静脉全血、血浆4种血样。用OneTouchVerio血糖监测系统和YSI2300葡萄糖测定仪,分别检测末梢血血糖（CBG）、静脉血糖（VBG）与末梢血浆血糖（CPG）、静脉血浆血糖（VPG）。并对Verio血糖监测系统的精准性进行评估。血糖数值差异分析采用配对t检验法。结果Verio血糖监测系统的精准性符合IS015197（2003）标准要求。空腹状态下血糖仪检测的CBG与VBG分别为（6．7±2．4）、（6．7±2．3）mmol／L,相对误差为0．40％（t=0．62,P〉0．05）,YSI检测的CPG与VPG分别为（6．4±2．5）、（6．4±2．4）mmol／L,相对误差为0．25（t=0．39,P〉0．05）,CBG略高于VPG5．89％（P〈0．05）;餐后2hCBG明显高于VBG,分别为（8．5±3．6）、（7．9±3．6）mmol／L,相对误差为7．58％（t=9．55,P〈0．05）;CPG亦明显高于VPG水平,分别为（8．1±3．8）、（7．6±3．8）mmol／L,相对误差为6．08％（t=10．9,P〈0．05）,CBG高于VPG11．6％（P〈0．05）。结论OneTouchVerio血糖监测系统适合临床对患者进行日常血糖检测,其检测的空腹CBG与VPG值较为接近,餐后CBG高于VPG值。     

Automated Inpatient Blood Sampling for Glucose Measurement: Evaluation of the VIA? Blood Chemistry Monitor for Glucose in Healthy and Diabetic Volunteers

Background

Manual methods of blood glucose monitoring are labor-intensive, costly, prone to error, and expose the caregiver to blood. The VIA® blood chemistry monitor for glucose can automatically measure plasma glucose (PG) every 5 minutes for 72 hours using blood sampled from a peripheral vein/artery or a central vein.

Methods

VIA performance was evaluated in eight normal and five type 1 diabetic (T1DM) subjects in 15 separate experiments. The VIA device was connected to a peripheral vein and reported a PG value every 5 minutes during each 510-minute experiment. Blood samples were collected manually every 10 minutes and assayed using a HemoCue® β-glucose analyzer (HC). Whole blood HC measurements were corrected to PG values. Paired HC/VIA measurements (n = 717) were analyzed.

Results

Mean PG was 90 ± 14 and 96 ± 12 mg/dl in normal subjects and 194 ± 64 and 173 ± 48 mg/dl in T1DM subject as measured by the HC and VIA, respectively. Clark error grid analysis revealed 86% points in zone A, 11% points in zone B, and 2% points in zone D. Linear regression analysis yielded the following equation: VIA = 0.732 × HC + 30.5 (r² = 0.954). Residual analysis revealed a glucose-dependent bias between the HC and the VIA. VIA data were transformed using the linear regression equation to correct for bias. After the correction, the mean absolute relative difference between the VIA and the HC was less than 10%, and 99.6% of data were in zones A and B. The VIA was able to sample blood automatically every 5 minutes for more than 8 hours in the laboratory setting. On average, the VIA reported glucose values for 94% of the samples it attempted to obtain.

Conclusions

This study demonstrated that the VIA blood chemistry monitor for glucose can reliably sample blood frequently for a prolonged period of time safely and effectively in diabetic and nondiabetic volunteers. Agreement between the two devices was the closest at normal glucose concentrations. After correcting for a glucose-dependent bias between the devices, the MARD was consistently less than 10% for all glucose ranges.     

The Business of Self-Monitoring of Blood Glucose: A Market Profile

The market for self-monitoring of blood glucose (SMBG) approached $8.8 billion worldwide in 2008. Yet despite dramatic double-digit growth in sales of SMBG products since 1980, the business is now facing declining prices and slower dollar growth. Given that SMBG meters and test strips are viewed by consumers and insurers as essentially generic products, it will be extremely challenging for new market entrants to displace well-entrenched existing competitors without a truly innovative technology. Also, in the face of declining glucose test strip prices, market expansion can only occur through identification of more of the undiagnosed diabetes population and convincing existing diabetes patients to adopt glucose testing or to test more frequently. Ultimately, a combination of technology innovations, patient education, and economic incentives may be needed to significantly expand the SMBG market and build sustainable long-term dollar growth for SMBG vendors.