Evolution of Glucose Monitoring: From Glucose Monitors to the Ambulatory Glucose
Dr. Jothydev Kesavadev, Chairman & Managing Director at Jothydev’s Diabetes Research Centre, Kerala, India. He completed his M.B.B.S and MD from India and fellowship in Endocrinology training at Mayo clinic, USA and FRCP from London and Glasgow. He pioneered in publishing Consensus guidelines on insulin pump, glucose monitoring and vaccination in diabetes for India.
Gopika Krishnan, B Pharm, Msc, and Academic Head at Jothydev’s Diabetes Research Centre, Trivandrum, Kerala, India.
Glucose Monitoring has been around as a valuable tool since many years. However in spite of many advances, there have been important shortcomings of the current tools we have. The HbA1c is a highly validated and researched tool however, it only provides an 90 day retrospective average of a patients glucose and gives no major in-depth analysis of their glucose profile. One can use the self-monitoring tools and lab test to obtain their glucose profile but testing strip costs and finger stick blood pricks and pain limits their usability in patients. It is widely known that continuous glucose monitoring systems (CGMS) provide the best data for analysis, but its duration is too short or too cumbersome and costly for use in routine practice. In this regards the new tool, FreeStyle Libre Pro and its software reports that provide the Ambulatory Glucose Profile (AGP) is easy to use, and provides the complete glucose profile of a patient so that a doctor can make informed treatment decisions. It is an exciting time for Diabetes, with many new innovations in the pipeline that can ease the hurdles associated with proper monitoring.
Introduction
Monitoring glucose values at specified time intervals, based on need is a prerequisite to ensure success atany stage or type of diabetes.There is sufficient evidence to support the fact that increased frequency of blood glucose monitoring, significantly improves glycemic control, which invariably translates to a reduction in the micro and macrovascular complications of diabetes.
Though glucometers became popular way back in 1980s, this technology has not been widely accepted in India so far; the major limitation being the cost involved in the procurement of glucometer and strips and the concerns on inaccuracy of glucometer compared to laboratory values. Even among those who are willing and affordable to follow self-monitoring of blood glucose instructions, forgetfulness and laziness prevents them from regular monitoring. Ambulatory glucose profile (AGP) with flash monitoring systems is an innovation to overcome the hurdle.
The term, “AGP” dates back to 1987 when the data from glucometers obtained over a period of 14 days were collapsed into a graphical depiction. Though the concept failed initially, AGP from self-monitored blood glucose (SMBG) data later evolved into techniques for measuring amplitude and frequency of change in the glycemic levels. Currently, the term AGP is popular for the collated 14 day graphical pattern generated from the revolutionary Abbott FreeStyle flash glucose monitoring system.
History and Evolution of Home Blood Glucose Meters
The history of glucose monitoring can be traced to mediaeval times where attempts were made to identify various diseases by examining urine samples. Stanley Benedict devised an improved copper reagent for urine sugar in 1908 and this became, with modifications, the mainstay of urine monitoring of diabetes for over 50 years[1].
Continued research at the Miles-Ames Laboratory was destined to be a key element in the history of blood glucose meters. The quest for a more convenient and specific method culminated in a ‘dip and read’ urine reagent strip, Clinistix, in 1957[2]. In 1965, an Ames research team under Ernie Adams went on to develop the first blood glucose test strip, the Dextrostix, a paper reagent strip which used the glucose oxidase/peroxidase reaction[3].Around the same time, the German company Boehringer Mannheim developed a competitive blood glucose strip, the Chemstrip bG. Limitations of these strips became the triggering factor to develop an automatic, electronic glucose test strip reader to improve precision and give more quantitative blood glucose results[4].
This paved way for the development of Ames Reflectance Meter (ARM; Figure 1) by Anton H.Clemens to produce quantitative blood glucose results with Dextrostix in the late 1960s, and the first model became available in 1970[5,6]. He used reflected light from the surface of the solid strip, which was captured by a photoelectric cell to produce a signal equivalent to blood glucose. The first reported patient to use blood glucose meter was Richard Bernstein, who suffered from type 1 diabetes and had episodes of hypoglycaemia resulting in hospitalisation.
Figure 1. Ames Reflectance Glucometer
A major advancement came with the introduction of the Lifescan (Johnson & Johnson) OneTouch II in 1992, a reflectance blood glucose system that eliminated the need to time accurately the application of blood to the test strip and its removal prior to the measurement of the colour[7]. The number of smaller, handheld glucometers continued to increase and Bayer, Abbott and Roche purchased pioneer companies Ames, MediSense and Boehringer Mannheim, respectively, between 1995 and 1998.
Blood glucose monitoring was regarded as an integral part of intensive diabetes treatment and management after completion of both major diabetes studies, the UK Prospective Diabetes Study (UKPDS)[8] and the Diabetes Control and Complications Trial (DCCT)[9] and American Diabetes Association (ADA) lowered the target variation to 5% between meters and the laboratory method leading to acceptance of SMBG as an integral part of self-management of patients with diabetes[10,11].
Different types of glucometers are currently available in the Indian market. Newer models are more advanced in technology, providing better features yet come in lighter weight, smaller size and at more affordable prices.
There are three principle enzymatic reactions utilised by current glucometers: glucose oxidase, glucose dehydrogenase, and hexokinase[12]. More complex meters have features to aid in identifying trends and to graph reports for more comprehensive data tracking, particularly for patients who test several times a day.
Use in Type 1 diabetes & Type 2 Diabetes
Since the introduction of glucose meters in the 1980s, SMBG has become the cornerstone of management in type 1 diabetes. Home blood glucose monitoring is associated with improved glycemic control in patients with type 1 diabetes[13]. A database study of almost 27,000 children and adolescents with type 1 diabetes showed that, after adjustment for multiple confounders, increased daily frequency of SMBG was significantly associated with lower glycated haemoglobin (HbA1c) levels (20.2% per additional test per day, levelling off at five tests per day) and with fewer acute complications[14]. Evidence suggest that a strict glycemic control reduces the risk of microvascular and macrovascular complications and in the UKPDS Study, each 1% reduction in HbA1c was associated with a 37% decrease in risk for microvascular complications and a 21% decrease in risk for any end point or death related to diabetes[8].
Home blood glucose monitoring is recommended in type 2 diabetes patients to gather information on the fluctuating blood glucose levels at several time points and to adjust the therapeutic regimen accordingly. Though to a limited extend, it also helps the patient to adjust the diet and exercise pattern in day to day life. SMBG have been proven useful in recognizing hyperglycemic and hypoglycemic episodes and helps the physician to individualise the treatment targets for patients who have frequent hypoglycemic episodes, diabetes which is brittle etc. Further, home blood glucose monitoring empowers the patient to be more conscious of his blood sugar fluctuations and its relation to timing of meals and snacks and physical activity[15]. The Indian consensus guideline on blood glucose monitoring recommends SMBG protocols to be individualised to address each individual’s specific educational, behavioural, and clinical requirements and provider requirements to aid therapeutic decision making[16].
At Jothydev’s Diabetes Research Centres in Kerala, Diabetes Tele Management System (DTMS®) has been in vogue since 1998. This is a system in which home blood glucose monitoring is combined with a decision support system provided by a multidisciplinary team of doctors, diabetes educators, dieticians, nurses, pharmacists, psychologist etc. based on a patient customised software. Our studies have shown the benefit of SMBG not only in type 1 diabetes but also in type 2 diabetes on various therapies including patients only on oral medications in maintaining customised glycemic targets and in modifying diet, exercise and drug dosages[17].
Accuracy of Glucometers
Glucometers find widespread use in hospitals, outpatient clinics, emergency rooms, ambulatory medical care and home self-monitoring. The universal availability and use of glucometers mandate certain level of confidence in the accuracy of glucometers. However, accuracy of test results can be affected by varied factors including environmental effects, patient condition, medication, and other metabolic factors. The accuracy of glucometers may be considered as technical and clinical. Technical accuracy refers to the analytical result agreement of a glucometer to a comparative laboratory method. Clinical accuracy compares the medical decisions based on the test results[12].
A study evaluating the clinical significance of glucometer precision found that the analytical variability of a glucometer though only 5%, the clinical insulin doses varied in 8–23% of cases, depending on the glucose concentration when compared against dosage based on the laboratory result. A glucose meter total variability of 10% led to different insulin dosage in 16–45% of cases, and >10–15% led to a two-fold or greater discrepancy in insulin dosage. The study concluded that a glucose meter total precision of <1–2% was required to ensure similar insulin dosage compared to the laboratory methods >95% of the time. However, none of the current glucose meters available on the market are capable of providing this level of precision[18].
The ADA recommends glucometers to possess accuracy within ±15% of the laboratory method at all concentrations, with a future performance goal of ±5% agreement at all glucose concentration[19]. However, there is no single standard to assess the accuracy of glucometers so far.
Evidence suggest that 91-97% of blood glucose errors is due to poor skill of the users like mechanical stress applied to the strips, failure to clean the site for testing, dirty meters, and sample issues like specimen clots, bubbles, and failure to apply an adequate amount of blood to the test[20,21]. Calibration errors are also common for those meters which require calibration.
History & Evolution of Continuous Glucose Monitoring
In the recent years, with advancements in technology, continuous glucose sensing has evolved as a useful tool to address insufficient glycemic management and to redefine the concept of SMBG in diabetes management. Continuous glucose monitoring (CGM) emerged as a research tool initially and later as an investigation to modify treatment to normalise glycemic excursions. Evolution of CGM can be traced back to the mid-1970s followed by the development of sensor technology and implantable glucose sensors in early 1980s. The first commercial CGM system known as CGMS Gold (CA, USA) came to
market following the US Food and Drug Administration (FDA) approval in 1999. Several CGMS are presently on the market. They can broadly be divided into systems providing retrospective or real time information on glucose patterns.
A typical CGM system consists of a glucose oxidase-based, electrochemical sensor inserted through the skin using a needle introducer, a transmitter that is fixed onto the sensor and a receiver that picks up the interstitial fluid signal. The oxidation of interstitial glucose by the sensor generates an electrical current. The electrical current data are filtered and cleared from background noise by the transmitter and sent to the receiver, which provides an approximation of the blood glucose level. The glucose data can be obtained at every 5 minutes intervals[22].
The sensor measures the interstitial fluid (IF) glucose where a lag of average 15 minutes is associated with the sensor glucose levels when compared to blood glucose levels due to the physiologic delay in transferring glucose between the blood and IF space (approximately 2–8 min), the transit time of IF glucose through the sensor membrane (1–2 min) and signal filtering (3–12 min).Due to this reason, CGM readings cannot be considered 100% accurate[23].
The glucose sensor must be calibrated against corresponding blood glucose meter levels to ensure the continuous accuracy of sensor data. Such calibrations transform the sensor signals into matching capillary glucose levels and assumes that the plasma to IF glucose gradient remains relatively constant[24].
Recalibration at fixed intervals is required to overcome signal drift issue[25]. Calibration should take place when blood glucose levels are relatively stable when the rate of change in sensor glucose values should be less than ±0.5 mg/dl/min[26,27]. Different CGM sensors available in the market include iPro2 Professional CGM, Guardian Real Time CGM system, Dexcom G4 Platinum etc.
Accuracy of CGM Sensors
Though sensor accuracy have improved over the years, the accuracy of sensors available for use in patients show varied results across clinical trials. In a comparison between Dexcom G4 sensor and Enlite sensor (guardian real-time system), the mean absolute relative difference (MARD) in blood glucose for the Dexcom G4 was significantly lower (13.9%) than for the Enlite sensor (17.8%) (P<0.0001)[28]. In yet another study, comparing the Navigator, G4 Platinum and Enlite, there was marked differences in both accuracy and precision and Navigator and G4 found to outperform the Enlite[29]. In a head to head comparison between DexcomG4 Platinum and Medtronic Paradigm Veo Enlite system at a clinical research centre (CRC) and in daily life conditions, overall MARD value standard deviation measured at the CRC was 13.6 (11.0)% for G4 Platinum and 16.6 (13.5)% for Veo Enlite system (P<0.0002). The overall MARD assessed at home was 12.2 (12.0)% for G4 Platinum and 19.9 (20.5)% for Veo Enlite system (P<0.0001)[30]. Interestingly both sensors showed lower accuracy in the hypoglycemic range which underscores the importance of supplementing CGM with SMBG[31]. Hence, CGM readings cannot be fully relied upon for therapeutic decision making.
A recent published article discussing the accuracy of the factory calibrated sensor showed that the overall MARD of the sensor was 11.4% when compared to capillary BG values.
History & Evolution of Ambulatory Glucose Profile
Beyond the traditional metrics, glycemic variability has been identified as a predictor of hypoglycaemia and is implicated in the pathogenesis of vascular diabetes complications. Assessment of glycemic variability is thus important, but exact quantification requires frequently sampled glucose measurements. In order to optimise diabetes treatment, there is a need for more advanced, user-friendly monitoring methods. For the meaningful measurement of inter-day glycemic variability, a CGM data for a longer period is required. This will help clinicians and patients easily visualise glycemic patterns to make therapeutic decisions.
New introduction to the field of sensor technology in this regard, is the ambulatory glucose profile (AGP) where the glucose data over a period of 14 days is collated to form a graph as if they occurred in a single 24-hour period. It has been observed that the glycemic glycemic pattern over the first 4 days of CGM cannot ideally predict the subsequent days and it is only over 7 days that the pattern tends to stabilize. The 14 days of glucose data help predict the glucose pattern over the next 30 days with 90–95% certainty, making it easier to visualise glycemic patterns. Thus, AGP combines inputs from multiple days of CGM data and collates them into a single 24-hour period, making glycemic patterns more recognizable.
The history of AGP dates back to 1987, where Mazze et al[32] used specifically modified reflectance meters containing memory chips which enabled them to store 440 individual blood glucose values with corresponding time and date. These data were organised into 14 day periods and collapsed into a graphical depiction which came to be known as AGP. The AGP was introduced as a solution to two major problems related to the use of reflectance meters. It was observed that 75% of the patients who practiced SMBG reported values which were significantly different from the actual values. Secondly, physicians had to heavily depend on logbooks to search for glycemic patterns and the efficiency of this subjective method was seriously questioned. Though the introduction of computer partially solved this problem with the help of software and graphics, substantial errors in the entry of data into the system was a major limiting factor. Thus, AGP was a novel step which systematically presented SMBG data and reflected features beyond glycemic control including amplitude and frequency of changes in the glycemic level.
However, this technology was wrought by several limitations including that AGP being a day time profile and not a continuous monitoring system. It did not consider variables including diet, exercise, timing of medications etc. Moreover, frequent and sustained SMBG was required for the construction of AGP[32].
Interest on AGP rekindled when an expert panel of diabetes specialists met in Florida, to discuss the utility of CGM in clinical practice and research applications where they were introduced to a universal software report, the AGP, created by Mazze et al. and further developed by the International Diabetes Centre (IDC)[33], Minneapolis, MN, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. The panel observed that standardizing glucose reporting and analysis, with tools such as AGP, may be one step toward optimizing clinical decision making in diabetes.
Ambulatory Glucose Profile in India
Abbott launched the FreeStyle Libre Pro Flash Glucose Monitoring System in India, first time ever in the world in March 2015. It consists of a small, round sensor, which is applied on the back of the patient’s upper arm. It requires no patient interaction or glucose meter calibration and is performed up to a period of 14 days.
The sensor continuously measures glucose in interstitial fluid through a small (5mm long, 0.4mm wide) filament which is inserted just under the skin and records glucose levels every 15 minutes, capturing up to 1340 glucose results over 14 days. After 14 days, a FreeStyle Libre Pro reader device is used to scan the sensor and download the glucose results that are stored in the sensor in 5 seconds. The personal system, FreeStyle Libre Flash Glucose Monitoring (not yet available in India), was launched in European markets in October 2014. Holding the reader within 1.5 inches of the sensor obtains the real-time value and past eight hours of glucose information along with a trend arrow on a line graph, just like traditional CGM.
The scanning process works through many layers of clothing, allowing for excellent discretion and flexibility. It also provides the option to add tags to each scan, such as carbs, insulin, exercise, and customizable options.
Figure 2. Flash Glucose Monitoring. Sensor gets applied to Back of Arm of patient and Doctor uses the Reader to get glucose data to obtain the AGP profile
The AGP sensor which works using wired enzyme technology comes factory calibratedprecluding the need for glucometer calibrations and with a MARD 11.4 % Flash glucose monitoring (Figure 2). In a study, which looked into the feasibility of using this modified version of the sensor found in the Freestyle Libre Pro CGM for 14 days, sensors using wired enzyme technology showed excellent in vivo stability, with no significant sensitivity loss over the 14 day wear period[34].
The AGP graph consists of five curves: 25th and 75th percentile curves also known as the inter quartile range (IQR), median curve and 10th and 90th percentile curves. The IQR shows the daily, nightly and postprandial span of 50% of glucose values and the shape of the median curve can provide insight into intraday glucose variability. Glucose variability is said to exist when glucose values are widely spread i.e., when the IQR and 10th and 90th percentile curves cover a large area. AGP help assess target, identify degree of variability and risk of hypoglycaemia. AGP results were found to be an effective basis for education, helping achieve better understanding of glycemic variability and increasing involvement in diabetes self-management[35,36].
Figure 3. Ambulatory Glucose Profile of a Patient: the 14 day CGM data is Collapsed to Look Like a Model 24-h Graph
Ambulatory Glucose Profile (AGP) report of 14 days of Continuous Glucose Monitoring (CGM) data, displayed bytime to show the spread of glucose values within each time interval. The dark blue line is the mediun curve (50th percentile) and shows the median glucose value for each time point. The blue shaded area represents the interquartile range (IQR). The outlier values (lowest and highest 10%) are represented by the light blue shaded area.
Zoomed Image of Figure 4
FreeStyle Libre Pro Flash glucose monitoring system is considered a revolutionary product as it does not require expertise for sensor insertion precludes glucometer calibration and displays glucose values. In contrast, conventional CGM systems involve sophisticated devices, demand expertise, can be used only up to a maximum of one week and are much more expensive.
Conclusion
The benefits of home blood glucose monitoring in the prevention of long term complications of diabetes are well proven. This benefit is observed only in those individuals in whom therapeutic and lifestyle changes are incorporated based on monitored parameters. For such changes to be made, either the patient should be highly educated and motivated or should receive directions from experts at frequent intervals.
Considering the fact that home blood glucose monitoring is a cost effective modality in preventing the expensive complications of diabetes, this procedure should be recommended by health care professionals in all eligible patients irrespective of the medications.
In the history of diabetes, AGP with FreeStyle Libre Pro is the first device to provide glucose values without the need for additional pricking the fingers. As the system measures glucose from the interstitial fluid, the values may not exactly reflect the blood glucose readings, this revolutionary technology could be the first one to replace conventional glucose meters and existing continuous glucose monitoring systems.
Refrences:
[1] Benedict SR. A reagent for the detection of reducing sugars. 1908. J Biol Chem. 2002;277(16):e5.
[2] Free AH, Adams EC, Kercher ML, Free HM, Cook MH. Simple specific test for urine glucose. Clin Chem. 1957;3(3):163-168.
[3] Kohn J. A rapid method of estimating blood-glucose ranges. Lancet. 1957;273(6986):119-121.
[4] Cheeley RD, Joyce SM. A clinical comparison of the performance of four blood glucose reagent strips. Am J Emerg Med. 1990;8(1):11-15.
[5] Cheah JS, Wong AF. A rapid and simple blood sugar determination using the Ames reflectance meter and Dextrostix system: a preliminary report. Singapore Med J. 197;15(1):51-52.
[6] Mazzaferri EL, Skillman TG, Lanese RR, Keller MP. Use of test strips with colour meter to measure blood-glucose. Lancet. 1970;1(7642):331-333.
[7] Strowing SM, Raskin P. Improved glycemic control in intensively treated type 1 diabetic patients using blood glucose meters with storage capability and compute-assisted analysis. Diabetes Care. 1998;21(10):1694-1698.
[8] UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). The Lancet. 1998;352(9131):837-853.
[9] The Diabetes Control and Complications Trial Research Group. The Effect of Intensive Treatment of Diabetes on the Development and Progression of Long-Term Complications in Insulin-Dependent Diabetes Mellitus. N Engl J Med. 1993;329(14):977-986.
[10] American Diabetes Association: clinical practice recommendations 1996. Diabetes Care. 1996;19 Suppl 1:S1–118.
[11] Clarke SF, Foster JR. A history of blood glucose meters and their role in self-monitoring of diabetes mellitus. Br J Biomed Sci. 2012;69(2):83-93.
[12] Tonyushkina K, Nichols JH. Glucose Meters: A Review of Technical Challenges to Obtaining Accurate Results. J Diabetes Sci Technol Online. 2009;3(4):971-980.
[13] Evans JMM, Newton RW, Ruta DA, MacDonald TM, Stevenson RJ, Morris AD. Frequency of blood glucose monitoring in relation to glycemic control: observational study with diabetes database. BMJ. 1999;319(7202):83-86.
[14] Ziegler R, Heidtmann B, Hilgard D, et al. Frequency of SMBG correlates with HbA1c and acute complications in children and adolescents with type 1 diabetes. Pediatr Diabetes. 2011;12(1):11-17.
[15] Benjamin EM. Self-Monitoring of Blood Glucose: The Basics. Clin Diabetes. 2002;20(1):45-47.
[16] Kesavadev J, Sadikot S, Wangnoo S, et al. Consensus guidelines for glycemic monitoring in type 1/type 2 & GDM. Diabetes Metab Syndr. 2014;8(3):187-195.
[17] Kesavadev J, Shankar A, Pillai PBS, Krishnan G, Jothydev S. Cost-effective use of telemedicine and self-monitoring of blood glucose via Diabetes Tele Management System (DTMS) to achieve target glycosylated hemoglobin values without serious symptomatic hypoglycemia in 1,000 subjects with type 2 diabetes mellitus–a retrospective study. Diabetes Technol Ther. 2012;14(9):772-776.
[18] Boyd JC, Bruns DE. Quality specifications for glucose meters: assessment by simulation modeling of errors in insulin dose. Clin Chem. 2001;47(2):209-214.
[19] American Diabetes Association. Self-monitoring of blood glucose. Diabetes Care. 1994;17(1):81-86.
[20] Kristensen GBB, Nerhus K, Thue G, Sandberg S. Standardized evaluation of instruments for self-monitoring of blood glucose by patients and a technologist. Clin Chem. 2004;50(6):1068-1071.
[21] Skeie S, Thue G, Nerhus K, Sandberg S. Instruments for self-monitoring of blood glucose: comparisons of testing quality achieved by patients and a technician. Clin Chem. 2002;48(7):994-1003.
[22] Cengiz E, Sherr JL, Weinzimer SA, Tamborlane WV. New-generation diabetes management: Glucose sensor-augmented insulin pump therapy. Expert Rev Med Devices. 2011;8(4):449-458.
[23] Cengiz E, Tamborlane WV. A Tale of Two Compartments: Interstitial Versus Blood Glucose Monitoring. Diabetes Technol Ther. 2009;11(S1):S11-S16.
[24] Rebrin K, Steil GM. Can interstitial glucose assessment replace blood glucose measurements? Diabetes Technol Ther. 2000;2(3):461-472.
[25] Koschinsky T, Heinemann L. Sensors for glucose monitoring: technical and clinical aspects. Diabetes Metab Res Rev. 2001;17(2):113-123.
[26] Aye T, Block J, Buckingham B. Toward closing the loop: an update on insulin pumps and continuous glucose monitoring systems. Endocrinol Metab Clin North Am. 2010;39(3):609-624.
[27] Wolpert HA. The nuts and bolts of achieving end points with real-time continuous glucose monitoring. Diabetes Care. 2008;31 Suppl 2:S146-S149.
[28] Matuleviciene V, Joseph JI, Andelin M, et al. A clinical trial of the accuracy and treatment experience of the Dexcom G4 sensor (Dexcom G4 system) and Enlite sensor (guardian REAL-time system) tested simultaneously in ambulatory patients with type 1 diabetes. Diabetes Technol Ther. 2014;16(11):759-767.
[29] Damiano ER, McKeon K, El-Khatib FH, Zheng H, Nathan DM, Russell SJ. A comparative effectiveness analysis of three continuous glucose monitors: the Navigator, G4 Platinum, and Enlite. J Diabetes Sci Technol. 2014;8(4):699-708.
[30] Kropff J, Bruttomesso D, Doll W, et al. Accuracy of two continuous glucose monitoring systems: a head-to-head comparison under clinical research centre and daily life conditions. Diabetes Obes Metab. 2015;17(4):343-349.
[31] Nakamura K, Balo A. The Accuracy and Efficacy of the Dexcom G4 Platinum Continuous Glucose Monitoring System. J Diabetes Sci Technol. 2015 Mar 23.
[32] Mazze RS, Lucido D, Langer O, Hartmann K, Rodbard D. Ambulatory Glucose Profile: Representation of Verified Self-Monitored Blood Glucose Data. Diabetes Care. 1987;10(1):111-117.
[33] Mazze RS, Strock E, Wesley D, et al. Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis. Diabetes Technol Ther. 2008;10(3):149-159.
[34] Hoss U, Budiman ES, Liu H, Christiansen MP. Continuous glucose monitoring in the subcutaneous tissue over a 14-day sensor wear period. J Diabetes Sci Technol. 2013;7(5):1210-1219.
[35] Matthaei, S. Assessing the value of ambulatory glucose profile (AGP) in clinical practice. Br J Diabetes Vasc Dis 2014;4:148-152.
[36] Matthaei S, DeAlaiz RA, Bosi E, et al. Consensus recommendations for the use of Ambulatory Glucose Profile in clinical practice. Br J Diabetes Vasc Dis. 2014;4:153-157.
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