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Background: Using self-measurements of blood glucose (SMBG) is daily routine for patients with insulin-treated diabetes, however measuring ß-ketones in blood is not widespread. How the use of a combined device, which can measure both, is accepted in daily routine by patients and will lead to better glycemic control is not well studied., Methods: This multicenter, prospective, noninterventional study assessed the impact of routine use of the GlucoMen® LX Plus on patient acceptance, usage and glycemic control among insulin-treated patients with diabetes mellitus type 1 and type 2. A1c and self-reported frequency of SMBG were evaluated at baseline and also postprandial SMBG, ß-ketone measurements, and use of reminders after 3 and 6 months of use. A total of 631 patients, 254 type 1/350 type 2 (27 no type specified), with mean (SD) baseline A1c 8.5% (1.5), age 54.6 (15.6) years, and 47.3% female were studied., Results: Frequent use of SMBG at baseline led to a higher decrease in A1c at 6 month (V3): -0.3% if SMBG measured up to 1/day versus -0.9% in 4-6/day. Increase of SMBG frequency during the study showed also a negative correlation to A1c, 9.2% at V1 versus 7.6% at V3. Postprandial SMBG was done by 77.7% and ß-ketone measurements by 45.5% of all patients; the reminders were used by 33.4% and led to an increased frequency of SMBG at 6 months., Conclusions: A combined device for SMBG and ß-ketone measurements is well accepted by patients with insulin-treated diabetes and can lead through the avoidance or detection of ketoacidosis/increased frequency of SMBG and increased awareness of the patients to an improved glycemic outcome., (© 2015 Diabetes Technology Society.)

Background: There is currently considerable discussion about the accuracy of blood glucose concentrations determined by personal blood glucose monitoring systems (BGMS). To date, the FDA has allowed new BGMS to demonstrate accuracy in reference to other glucose measurement systems that use the same or similar enzymatic-based methods to determine glucose concentration. These types of reference measurement procedures are only comparative in nature and are subject to the same potential sources of error in measurement and system perturbations as the device under evaluation. It would be ideal to have a completely orthogonal primary method that could serve as a true standard reference measurement procedure for establishing the accuracy of new BGMS., Methods: An isotope-dilution liquid chromatography/mass spectrometry (ID-UPLC-MRM) assay was developed using (13)C6-glucose as a stable isotope analogue to specifically measure glucose concentration in human plasma, and validated for use against NIST standard reference materials, and against fresh isolates of whole blood and plasma into which exogenous glucose had been spiked. Assay performance was quantified to NIST-traceable dry weight measures for both glucose and (13)C6-glucose., Results: The newly developed assay method was shown to be rapid, highly specific, sensitive, accurate, and precise for measuring plasma glucose levels. The assay displayed sufficient dynamic range and linearity to measure across the range of both normal and diabetic blood glucose levels. Assay performance was measured to within the same uncertainty levels (<1%) as the NIST definitive method for glucose measurement in human serum., Conclusions: The newly developed ID UPLC-MRM assay can serve as a validated reference measurement procedure to which new BGMS can be assessed for glucose measurement performance., (© 2015 Diabetes Technology Society.)

In previous studies, meters employing dynamic electrochemistry (DE), have been shown to correct for hematocrit (HCT) interference. This laboratory investigation assessed the HCT stability of MyStar Extra (Sanofi) in comparison to 7 competitive devices (Accu-Chek Aviva Nano & Accu-Chek Performa, Roche Diagnostics; Contour XT and Contour Link, Bayer; FreeStyle Freedom Lite, Abbott; MyLife Pura, Ypsomed; OneTouch Verio Pro, LifeScan). Venous heparinized blood was freshly drawn, immediately aliquoted, and manipulated to contain 3 different blood glucose concentrations (50-80 mg/dL, 150-180 mg/dL, and 350-400 mg/dL) and 5 different HCT levels (20-25%, 30-35%, 40-45%, 50-55%, and 60-65%). After careful oxygenation to normal blood oxygen pressure, each of the 15 different samples was measured 8 times with 2 devices and 2 strip lots of each meter (32 measurements/meter/sample). YSI Stat 2300 served as laboratory reference method. Next to determination of the mean absolute relative deviation (MARD), stability to HCT influence was assumed, when less than 10% difference occurred between the highest and lowest mean glucose deviations in relation to HCT over all tested glucose ranges (HIF: hematocrit interference factor). Four of the devices showed stable performance: Contour XT (MARD: 1.3%/HIF: 6.1%), MyStar Extra (4.7%/7.1%), OneTouch Verio Pro (4.5%/7.3%), and Contour Link (6.3%/9.3%). The 4 other meters were influenced by HCT (Accu-Chek Performa: 4.7%/20.9%, Accu-Chek Aviva Nano: 4.5%/22.4%, FreeStyle Freedom Lite: 4.8%/24.5%; MyLife Pura: 6.4%/28.7%). In this study, all meters showed a good accuracy, but only 50% of them, including MyStar Extra, were shown to reliably correct for potential hematocrit influence on the meter results., (© 2014 Diabetes Technology Society.)

Glycemic control in hospitalized patients with diabetes requires accurate near-patient glucose monitoring systems. In the past decade, point-of-care blood glucose monitoring devices have become the mainstay of near-patient glucose monitoring in hospitals across the world. In this article, we focus on its history, accuracy, clinical use, and cost-effectiveness. Point-of-care devices have evolved from 1.2 kg instruments with no informatics to handheld lightweight portable devices with advanced connectivity features. Their accuracy however remains a subject of debate, and new standards for their approval have now been issued by both the International Organization for Standardization and the Clinical and Laboratory Standards Institute. While their cost-effectiveness remains to be proved, their clinical value for managing inpatients with diabetes remains unchallenged. This evidence-based review provides an overall view of its use in the hospital setting., (© 2014 Diabetes Technology Society.)

This pilot study evaluated the difference in accuracy between the Bayer Contour® Next (CN) and HemoCue® (HC) glucose monitoring systems in children with type 1 diabetes participating in overnight closed-loop studies. Subjects aged 10-18 years old were admitted to a clinical research center and glucose values were obtained every 30 minutes overnight. Glucose values were measured using whole blood samples for CN and HC readings and results were compared to Yellow Springs Instrument (YSI) reference values obtained with plasma from the same sample. System accuracy was compared using mean absolute relative difference (MARD) and International Organization for Standardization (ISO) accuracy standards. A total of 28 subjects were enrolled in the study. Glucose measurements were evaluated at 457 time points. CN performed better than HC with an average MARD of 3.13% compared to 10.73% for HC (P < .001). With a limited sample size, CN met ISO criteria (2003 and 2013) at all glucose ranges while HC did not. CN performed very well, and would make an excellent meter for future closed-loop studies outside of a research center., (© 2014 Diabetes Technology Society.)

The blood glucose meter (BGM) is the most successful and widely used portable device for point-of-care (POC) tests. However, its usage is limited to self-monitoring of blood glucose level only. To expand the targets that BGM can monitor while taking advantage of more than 50 years of technology development, we report herein the use of BGM to detect and quantify insulin and glycated hemoglobin (HbA1c), which are useful hormone for diabetes treatment and biomarker for diabetes monitoring, respectively. The method is based on invertase enzyme-linked immunosorbent assay (iELISA) and phosphatase enzyme-linked immunosorbent assay (pELISA) that convert BGM-inert sucrose or glucose-1-phosphate into glucose in the presence of insulin and glycated hemoglobin, respectively. In both assays, monoclonal antibodies specific to the targets (insulin or HbA1c) are immobilized onto magnetic beads to capture the targets in samples, followed by the formation of sandwich complex with the polyclonal antibodies conjugated to either invertase or phosphatase. The quantification of the targets is then realized by the production of glucose from the biochemical reactions catalyzed by the polyclonal antibody-enzyme conjugates bound on the surface of the magnetic beads. Such a method can be generally applied to a wide range of other biomarkers using the corresponding antibodies., (© 2014 Diabetes Technology Society.)

Accurate calculation and adjustment of insulin doses is integral to maintaining glycemic control in insulin treated patients. Difficulties with insulin dose calculations may lead to poor adherence to blood glucose monitoring and insulin treatment regimes, resulting in poor metabolic control. The main objective of this study was to evaluate ease of use and user preference of a high specification touch screen blood glucose meter, which has an in-built insulin calculator, compared to patients' usual method of testing blood glucose and deciding insulin doses. Patients with diabetes on a multiple daily injection insulin regime used the Test Meter without the insulin calculator and 1 of 3 comparator meters, each for a 7-day period. They then used the Test Meter with the in-built calculator for 10 days. Patients completed an ease of use questionnaire after each 7-day period, a preference questionnaire after the second 7-day period, and a questionnaire comparing the Test Meter with their usual method after the final 10-day period. Of 164 patients who completed the study, 76% stated a preference for the Test Meter as a diabetes management tool compared to their usual method. A small number of patients preferred familiar methods and/or calculating insulin doses themselves. The log book function of meters was important to most patients. The Test Meter system with in-built insulin calculator supports people to better manage their diabetes and increases their confidence. Patients have different needs and preferences which should be acknowledged and supported in a patient centered health service., (© 2014 Diabetes Technology Society.)

The effectiveness and safety of continuous glucose monitors (CGMs) is dependent on their accuracy and reliability. The objective of this study was to compare 3 CGMs in adult and pediatric subjects with type 1 diabetes under closed-loop blood-glucose (BG) control. Twenty-four subjects (12 adults) with type 1 diabetes each participated in one 48-hour closed-loop BG control experiment. Venous plasma glucose (PG) measurements obtained every 15 minutes (4657 values) were paired in time with corresponding CGM glucose (CGMG) measurements obtained from 3 CGMs (FreeStyle Navigator, Abbott Diabetes Care; G4 Platinum, Dexcom; Enlite, Medtronic) worn simultaneously by each subject. The Navigator and G4 Platinum (G4) had the best overall accuracy, with an aggregate mean absolute relative difference (MARD) of all paired points of 12.3 ± 12.1% and 10.8 ± 9.9%, respectively. Both had lower MARDs of all paired points than Enlite (17.9 ± 15.8%, P < .005). Very large errors (MARD > 50%) were less common with the G4 (0.5%) than with the Enlite (4.3%, P = .0001) while the number of very large errors with the Navigator (1.4%) was intermediate between the G4 and Enlite (P = .1 and P = .06, respectively). The average MARD for experiments in adolescent subjects were lower than in adult subjects for the Navigator and G4, while there was no difference for Enlite. All 3 devices had similar reliability. A comprehensive head-to-head-to-head comparison of 3 CGMs revealed marked differences in both accuracy and precision. The Navigator and G4 were found to outperform the Enlite in these areas., (© 2014 Diabetes Technology Society.)

Objectives: The proper use of many types of self-monitored blood glucose (SMBG) meters requires calibration to match strip code. Studies have demonstrated the occurrence and impact on insulin dose of coding errors with SMBG meters. This paper reflects additional analyses performed with data from Raine et al. (JDST, 2:205-210, 2007). It attempts to relate potential insulin dose errors to possible adverse blood glucose outcomes when glucose meters are miscoded., Methods: Five sets of glucose meters were used. Two sets of meters were autocoded and therefore could not be miscoded, and three sets required manual coding. Two of each set of manually coded meters were deliberately miscoded, and one from each set was properly coded. Subjects (n = 116) had finger stick blood glucose obtained at fasting, as well as at 1 and 2 hours after a fixed meal (Boost((R)); Novartis Medical Nutrition U.S., Basel, Switzerland). Deviations of meter blood glucose results from the reference method (YSI) were used to predict insulin dose errors and resultant blood glucose outcomes based on these deviations., Results: Using insulin sensitivity data, it was determined that, given an actual blood glucose of 150-400 mg/dl, an error greater than +40 mg/dl would be required to calculate an insulin dose sufficient to produce a blood glucose of less than 70 mg/dl. Conversely, an error less than or equal to -70 mg/dl would be required to derive an insulin dose insufficient to correct an elevated blood glucose to less than 180 mg/dl. For miscoded meters, the estimated probability to produce a blood glucose reduction to less than or equal to 70 mg/dl was 10.40%. The corresponding probabilities for autocoded and correctly coded manual meters were 2.52% (p < 0.0001) and 1.46% (p < 0.0001), respectively. Furthermore, the errors from miscoded meters were large enough to produce a calculated blood glucose outcome less than or equal to 50 mg/dl in 42 of 833 instances. Autocoded meters produced zero (0) outcomes less than or equal to 50 mg/dl out of 279 instances, and correctly coded manual meters produced 1 of 416., Conclusions: Improperly coded blood glucose meters present the potential for insulin dose errors and resultant clinically significant hypoglycemia or hyperglycemia. Patients should be instructed and periodically reinstructed in the proper use of blood glucose meters, particularly for meters that require coding.

Background: This article reviews the literature to date and reports on a new study that documented the frequency of manual code-requiring blood glucose (BG) meters that were miscoded at the time of the patient's initial appointment in a hospital-based outpatient diabetes education program., Method: Between January 1 and May 31, 2007, the type of BG meter and the accuracy of the patient's meter code (if required) and procedure for checking BG were checked during the initial appointment with the outpatient diabetes educator. If indicated, reeducation regarding the procedure for the BG meter code entry and/or BG test was provided., Results: Of the 65 patients who brought their meter requiring manual entry of a code number or code chip to the initial appointment, 16 (25%) were miscoded at the time of the appointment. Two additional problems, one of dead batteries and one of improperly stored test strips, were identified and corrected at the first appointment., Conclusions: These findings underscore the importance of checking the patient's BG meter code (if required) and procedure for testing BG at each encounter with a health care professional or providing the patient with a meter that does not require manual entry of a code number or chip to match the container of test strips (i.e., an autocode meter).

Objective: The objective of this study was to determine inaccuracies of miscoded blood glucose (BG) meters and potential errors in insulin dose based on values from these meters., Research Design: Fasting diabetic subjects at three clinical centers participated in a 2-hour meal tolerance test. At various times subjects' blood was tested on five BG meters and on a Yellow Springs Instruments laboratory glucose analyzer. Some meters were purposely miscoded. Using the BG values from these meters, along with three insulin dose algorithms, Monte Carlo simulations were conducted to generate ideal and simulated-meter glucose values and subsequent probability of insulin dose errors based on normal and empirical distribution assumptions., Results: Maximal median percentage biases of miscoded meters were +29% and -37%, while maximal median percentage biases of correctly coded meters were only +0.64% and -10.45% (p = 0.000, chi(2) test, df = 1). Using the low-dose algorithm and the normal distribution assumption, the combined data showed that the probability of insulin error of +/-1U, +/-2, +/-3, +/-4, and +/-5U for miscoded meters could be as high as 49.6, 50.0, 22.3, 1.4, and 0.04%, respectively. This is compared to manually, correctly coded meters where the probability of error of +/-1, +/-2, and +/-3U could be as high as 44.6, 7.1, and 0.49%, respectively. There was no instance of a +/-4 or +/-5U insulin dose error with a manually, correctly coded meter. For autocoded meters, the probability of +/-1 and +/-2U could be as high as 35.4 and 1.4%, respectively. For autocoded meters there were no calculated insulin dose errors above +/-2U. The probability of insulin misdosing with either manually, correctly coded or autocoded meters was significantly lower than that with miscoded meters. Results using empirical distributions showed similar trends of insulin dose errors., Conclusions: Blood glucose meter coding errors may result in significant insulin dosing errors. To avoid error, patients should be instructed to code their meters correctly or be advised to use an autocoded meter that showed superior performance over manually, correctly coded meters in this study.