[Erratum in "Point-of-Care Blood Glucose Testing: Post-Market Performance Assessment of the Accu-Chek Inform II Hospital-Use Glucose Meter" (DOI: 10.26442/00403660.2023.12.202522)]

In the article "Point-of-care blood glucose testing: post-market performance assessment of the Accu-Chek Inform II hospital-use glucose meter," published in the Terapevticheskii Arkhiv journal, Vol. 95, No.12, 2023 (DOI: 10.26442/00403660.2023.12.202522), errors were made: the term "measurements at the place of treatment" was changed, as well as the section "Conflict of interest." At the request of the authors' team, errors in the conflict of interest and the wording of the term have been corrected, and the section "Information about the authors" has been updated. The publisher replaced the original version of the published article with the corrected one; the information on the website was also corrected. Correct text of the section "Conflict of interest": Conflict of interest. All authors are not employees or consultants of Roche Diagnostics and have not received any compensation from Roche Diagnostics. Correct wording of the term in Russian: "измерения по месту лечения". Changes were made to the title of the article in Russian: "Измерения глюкозы по месту лечения: пострегистрационное испытание госпитального глюкометра Акку-Чек Информ II", the text of the abstract, keywords, citation, in the text of the article, and abbreviations. Information of the place of work has been updated: Center for Laboratory Diagnostics of the Russian Children Clinical Hospital, a Branch of the Pirogov Russian National Research Medical University. The publisher apologizes to readers and authors for the errors and is confident that the correction of errors will ensure the correct perception and interpretation of the results of the study described in the text.

Can a Basic Management App Paired With A Glucose Meter Help Reduce Glucose Levels Among Adults With Type 2 Diabetes? The REALL Study

OBJECTIVE

Evaluations of technology to help adults manage type 2 diabetes (T2D) have yielded mixed results. We analyzed the effectiveness of a free app linked to a glucose meter to study reductions in glucose levels over time among a self-selected sample of adults with T2D.

RESEARCH DESIGN AND METHODS

Adults with T2D >12 months, >21 years, ability to read English (insulin using-IU and non-insulin using-NIU) who independently elected to pair their CONTOUR NEXT ONE meter with the CONTOUR DIABETES App were invited to participate. Glucose data from baseline to 16 weeks were uploaded to the cloud (N = 461). Assessment of diabetes distress, medication taking, quality of life, and hypoglycemia concerns occurred at baseline, six, and 16 weeks.

RESULTS

Findings indicated a significant decrease in weekly glucose levels over time: baseline mean = 169 (62.0) (9.4 mmol/L; 3.44); 16-week mean = 146.5 (36.0) (8.1 mmol/L; 2.0) (P < .001), with no IU and NIU differences. Largest reductions occurred during the first six weeks, with no later rebound effects. Significant, though modest, improvements in global quality of life (P = .03), hypoglycemia concerns (P = .01), and diabetes distress (P < .001) occurred over 16 weeks.

CONCLUSIONS

Making an App for monitoring glucose easily available for download with a glucose meter can be helpful for self-selected adults with T2D. Effective utilization assumes that users are sufficiently motivated and engaged, are comfortable and trusting of the technology, and have sufficient knowledge of how to make use of the glucose data.

[Point-of-Care Blood Glucose Testing: Post-Market Performance Assessment of the Accu-Chek Inform II Hospital-Use Glucose Meter]

BACKGROUND

A point-of-care glucose testing (POCT) is an essential component of care in patients with hyperglycemia and hypoglycemia in inpatient and outpatient settings. In Russian medical facilities (MFs), conventional glucose meters designed for self-monitoring by patients with diabetes are commonly used for POCT. These home-use meters have two serious disadvantages: the first is large measurement bias and the second - they can't be integrated into laboratory information systems, so measurement data have to be recorded into patient charts manually. Both factors may lead to medical errors. It is reasonable to use in the MFs specialized POCT glucose meters, as they are superior to conventional ones in accuracy and may be easily connected to laboratory information systems. With this in mind, physicians at the Russian Children's Clinical Hospital decided to substitute conventional meters with the Accu-Chek Inform II POCT meter, however, after preliminary performance assessment of the model.

AIM

To test the Accu-Chek Inform II performance characteristics: accuracy, linearity, repeatability, and mean absolute relative difference (MARD).

MATERIALS AND METHODS

Performance of the Accu-Chek Inform II was tested by comparing the results of parallel CGL measurements with the meter and reference laboratory analyzer in capillary blood samples. Overall, 99 parallel CGL measurements were made in 45 samples. Accuracy was evaluated according to the ISO 15197-2013 and POCT12-A3 criteria.

RESULTS

The Accu-Chek Inform II meter met the requirements of ISO 15197-2013 and POCT12-A3 and demonstrated high linearity (correlation coefficient, r=1,0), good repeatability (mean coefficient of variation, CV=1,38%) and acceptable MARD (4,9%).

CONCLUSION

The Accu-Chek Inform II POCT glucose meter may be efficiently and safely used in inpatient and outpatient MFs and particularly in pediatric clinics.

Traditional Interference Experiments vs. Method Comparison Interference Experiments

Two papers have appeared evaluating interferences in glucose meters. These studies are method comparisons with the added information of the medication(s) taken by the subjects. This paper contrasts a traditional interference study with the method comparison protocols. Unlike the advice in CLSI EP7, a substance that interferes should be reported even if the level of interference is clinically acceptable. The evidence of no clinically important interference in the method comparison protocol is very weak, and there is no possibility to detect statistically significant interferences. I provide an example where vitamin C at a therapeutic level was within clinical error limits, but when the concentration was at levels used to treat cancer, there was bias well above clinically acceptable limits.

N-Acetylcysteine Interference with a Glucose Dehydrogenase Linked Glucose Meter

BACKGROUND

Our objective was to determine the effect of therapeutic concentrations of N-acetylcysteine, following intravenous infusion, on the measurement of blood glucose using a Roche Diagnostics glucose dehydrogenase-linked glucose meter compared to hospital laboratory methods.

METHODS

N-acetylcysteine was added to aliquots of blood, with glucose promptly measured by the glucose meter, blood gas analyzer (glucose oxidase comparative method) and following centrifugation, plasma glucose measured with a hexokinase spectrophotometric comparative method. Glucose results were evaluated with linear regression and Bland Altman plots.

RESULTS

In the presence of NAC, at concentrations greater than 5 mg/dL (0.31 mmol/L), positively biased glucose meter results were compared to the clinical laboratory results. Multivariate linear regression revealed that NAC-mediated meter results are influenced by NAC and glucose concentrations.

CONCLUSIONS

The addition of therapeutic concentrations of NAC to blood produces statistically significant positive biases when measured with the glucose dehydrogenase linked glucose meter device.

More Focus is Needed to Reduce Adverse Events for Diabetes Devices

Advances in devices for people with diabetes have demonstrated many improvements; yet, the number of adverse events has almost doubled from 2018 to 2019. It is a challenge to examine these events due to a difficult query tool on the FDA website. There are several possible reasons why effort is not devoted to decreasing the number of adverse events including the fact that user error is a common cause. This commentary serves to raise awareness of the adverse event problem.

Unintended Consequence of High-Dose Vitamin C Therapy for an Oncology Patient: Evaluation of Ascorbic Acid Interference With Three Hospital-Use Glucose Meters

The use of high-dose vitamin C in cancer care has offered promising results for some patients. However, the intravenous (IV) doses used for these patients can reach concentrations that interfere with some strip-based glucose meters. We characterized the impact of vitamin C interference, from standard to the very high doses used for some cancer protocols, using three different hospital-use glucose meters. For two of the three devices tested, increasing concentrations of ascorbic acid caused false elevations in the glucose measurements. The third glucose meter did not provide inaccurate results, regardless of the vitamin C concentration present. Rather, above a certain threshold, the device generated error messages and no results could be obtained.

Agreement of blood glucose measured with glucose meter in arterial, central venous, and capillary samples in adult critically ill patients

BACKGROUND

The measurement of blood glucose in critically ill patients is still performed in many ICUs with glucose meters and capillary samples. Several prevalent factors in these patients affect the accuracy of the results and should be interpreted with caution. A weak recommendation from the Surviving Sepsis Campaign (SSC) suggests the use of arterial blood rather than capillary blood for point of care testing using glucose meters.

AIMS AND OBJECTIVES

To analyse the agreement between arterial, central venous, and capillary blood samples of glucose values measured by glucose meter in critically ill patients and study potential confounding factors.

DESIGN

Prospective cross-sectional study in a general intensive care unit (ICU). Patients needing insulin treatment (subcutaneous or intravenous) and blood glucose control were included.

METHODS

Standardized collection of blood samples and measurement of glucose values with a glucometer. Agreement was studied by the Bland-Altman method and stratified analysis of disagreement-survival plots was used to study the influence of haematocrit, pH range, SOFA score, capillary refilling time, intravenous insulin infusion, and lactic acid.

RESULTS

A total of 297 measurements from 54 patients were included. The mean arterial blood glucose was 150.42 (range 31-345 mg/dL). In the graphical analysis, there is a poor agreement both in capillary and venous central to arterial samples, but in opposite direction (underestimation of capillary and overestimation of central venous). Factors associated with a reduction in the agreement between arterial and capillary samples were elevated lactate, poor capillary refilling, and hemodynamic failure. Patients without hemodynamic compromise have an acceptable agreement with values for absolute differences of 16 mg/dL for a disagreement of 10%.

CONCLUSIONS

In critically ill patients, the measurement of blood glucose with a glucose meter should be performed with arterial samples whenever possible. Capillary samples do not accurately estimate arterial blood glucose values in patients with shock and/or vasoactive drugs and underestimate the values in the range of hypoglycemia. Venous samples are subject to error because of potential contamination.

RELEVANCE TO CLINICAL PRACTICE

This study adds support to the recommendation of using arterial blood rather than capillary or venous blood when using glucose meters in critically ill patients, especially in those with hemodynamic failure.

Point-of-Care Monitoring of Colitis Using Intestinal Alkaline Phosphatase in Inflammatory Bowel Disease

Intestinal Alkaline Phosphatase (IAP) was investigated as a potential biomarker to monitor colitis in a mouse model of Inflammatory Bowel Disease (IBD). We developed a Point-Of-Care (POC) assay to detect IAP with a glucose meter in 15 min. We synthesized a paracetamol-bearing compound specifically cleaved by IAP to release paracetamol, which can be detected with a personal glucometer. Interleukin 10 deficient (IL 10-/-) mouse model samples were used to compare the IAP level in mice with mild or severe colitis. The results showed that fecal IAP level was significantly lower in each mouse sample with severe colitis than with mild colitis. Mice treated with anti-Tumor Necrosis Factor-alpha (anti-TNF-α) to decrease inflammation exhibited a much higher level of IAP than those without treatment (IAP levels from anti-TNF-α treated vs nontreated = 2.80 U vs 0.11 U, P < 0.0001). Taken together, IAP can be considered as a potential biomarker to monitor colitis, and a rapid, user-friendly POC glucometer-based assay can be potentially used to monitor colitis levels and inflammation flareups in IBD.

Budget Impact of Improved Diabetes Management by Utilization of Glucose Meters With a Color-Range Indicator-Comparison of Five European Healthcare Systems

BACKGROUND AND AIM

Costs for the treatment of diabetes and its comorbidities are a major international issue. A recent randomized clinical trial showed that the introduction of color range indicator (CRI)-based glucose meters (GMs) positively affects the HbA1c of patients with type 1 and type 2 diabetes, when compared to GMs without a CRI. This budget impact analysis aimed to translate this beneficial effect of CRI-based GMs, OneTouch Verio Flex and OneTouch Verio, into potential monetary impact for the healthcare systems of five European countries, Germany, Spain, Italy, France, and the United Kingdom.

MATERIAL AND METHODS

Data from a randomized controlled trial, evaluating the effect of CRI-based GMs, were used to estimate the ten-year risk of patients for fatal myocardial infarction (MI) as calculated by the UK Prospective Diabetes Study (UKPDS) risk engine. On the basis of assessed risks for MI, the potential monetary impact for the healthcare systems in five European countries was modeled.

RESULTS

Based on a mean HbA1c reduction of 0.36%, as demonstrated in a randomized controlled trial, the UKPDS risk engine estimated a reduction of 2.4% of the ten-year risk of patients for fatal MI. When applied to our economic model, substantial potential cost savings for the healthcare systems of five European countries were calculated: €547 472 (France), €9.0 million (Germany), €6.0 million (Italy), €841 799 (Spain), and €421 069 (United Kingdom) per year.

CONCLUSION

Improving metabolic control in patients with diabetes by the utilization of CRI-based GMs may have substantial positive effects on the expenditure of the healthcare systems of several European countries.

Inaccurate point-of-care blood glucose measurement in a dog with secondary erythrocytosis

BACKGROUND

Point-of-care (POC) portable blood glucose meters (PBGMs) are convenient and inexpensive tools for assessing patient blood glucose concentrations. They are often used to quickly diagnose hypoglycemia or collect serial glucose readings in diabetic patients. However, POC meters have been previously identified in human and veterinary literature to be inaccurate when utilized in patients with abnormal HCT. This problem may not be reflected in manufacturer guidelines referenced by practitioners in the POC setting.

KEY FINDINGS

A 1.5-year-old dog, previously diagnosed with multiple congenital cardiac malformations, right-to-left cardiac shunting and secondary erythrocytosis, presented to a veterinary emergency center minimally responsive and without detectable pulses. PBGM measurement identified hypoglycemia. Following stabilization of the dog, serial glucose assessments showed discordant results between PBGMs and the reference laboratory biochemistry analyzer. A pathological cause for hypoglycemia was not identified and PBGM readings were determined to be erroneously low due to the dog's abnormally high HCT.

SIGNIFICANCE

This case demonstrates the limitations of using PBGMs to assess blood glucose in a dog with secondary erythrocytosis. The report emphasizes the need for judicious use of PBGMs in critically ill patients and that these glucometers may not be reliable in patients with abnormal HCT values.

Analysis of kombucha to teach biochemical concepts and techniques to undergraduate students

Laboratory exercises for undergraduate biochemistry students are described in which changes in sugar content during fermentation of the trendy beverage kombucha are analyzed by three methods: thin layer chromatography, a 3,5-dinitrosalicylic acid assay, and a standard commercial blood glucose meter. Each of the three analyses can be completed in a typical laboratory session lasting two to three hours. The exercises are designed to reinforce concepts typically covered in an undergraduate biochemistry course as well as to teach a variety of laboratory techniques. The exercises have been used with positive results in an upper level biochemistry laboratory course for junior/senior students majoring in chemistry or biology. © 2019 International Union of Biochemistry and Molecular Biology, 47(4):459-467, 2019.

Why the Details of Glucose Meter Evaluations Matters

In an article in the Journal of Diabetes Science and Technology, Macleod and coworkers describe an evaluation of LifeScan glucose meters that focus on the effects of sample types and comparison methods. They make a valid point that these factors influence the accuracy observed in evaluations and recommend the comparison method be the one recommended by the manufacturer for the sample type in the intended use statement. Yet, the recommended comparison method is not a reference method. The accuracy hierarchy of definitive, reference, and field methods originally described by Tietz should remind one that virtually all glucose meter evaluations use commercially available field methods as the comparison method. Finally, one should not neglect the FDA adverse event database as a way to assess glucose meter performance.

Biocomputing for Portable, Resettable, and Quantitative Point-of-Care Diagnostics: Making the Glucose Meter a Logic-Gate Responsive Device for Measuring Many Clinically Relevant Targets

It is recognized that biocomputing can provide intelligent solutions to complex biosensing projects. However, it remains challenging to transform biomolecular logic gates into convenient, portable, resettable and quantitative sensing systems for point-of-care (POC) diagnostics in a low-resource setting. To overcome these limitations, the first design of biocomputing on personal glucose meters (PGMs) is reported, which utilizes glucose and the reduced form of nicotinamide adenine dinucleotide as signal outputs, DNAzymes and protein enzymes as building blocks, and demonstrates a general platform for installing logic-gate responses (YES, NOT, INHIBIT, NOR, NAND, and OR) to a variety of biological species, such as cations (Na+ ), anions (citrate), organic metabolites (adenosine diphosphate and adenosine triphosphate) and enzymes (pyruvate kinase, alkaline phosphatase, and alcohol dehydrogenases). A concatenated logical gate platform that is resettable is also demonstrated. The system is highly modular and can be generally applied to POC diagnostics of many diseases, such as hyponatremia, hypernatremia, and hemolytic anemia. In addition to broadening the clinical applications of the PGM, the method reported opens a new avenue in biomolecular logic gates for the development of intelligent POC devices for on-site applications.

Impact on Diabetes Self-Management and Glycemic Control of a New Color-Based SMBG Meter

BACKGROUND

Self-monitoring of blood glucose (SMBG) is a key pillar of personal diabetes management. The objective of this observational study was to analyze diabetes self-management (DSM) and glycemic outcomes before and during system implementation in real-life settings of a blood glucose meter system with a color-coded display of glucose levels, which helps identify out-of-range levels.

METHODS

A total of 193 insulin-treated diabetes patients (11% T1DM; 55% male, age 60 ± 4 years, mean diabetes duration 14 ± 9 years, HbA1c 8.68 ± 1.2%) were enrolled into the study. Both the Diabetes Self-Management Questionnaire (DSMQ) and glycemic control were analyzed at baseline and 3 and 6 months after study initiation.

RESULTS

DSMQ general perception improved significantly by the end of the study period ("Sum Scale," P < .05). Moreover, after 6 months patient's attitudes on self-care (Q16, P = .0046) and nutrition ("Dietary Control," P = .004) showed significant improvements. Use of the blood glucose meter resulted in improved glycemic control, as shown by mean HbA1c levels, which decreased from 8.68 ± 1.2% at baseline to 8.13 ± 1.02% after 3 months ( P < .0001) and to 7.9 ± 1.1% at 6 months ( P < .0001). Both patients and diabetes educators agreed in the advantages of the color-coded indicator and on its helpfulness in assisting patients on their diabetes management, as drawn from the results of the self-reported satisfaction questionnaire.

CONCLUSION

This real-world study demonstrates that SMBG implemented via this new blood glucose meter not only leads to an improvement in metabolic control, but also is associated with a significant improvement in diabetes management.

Barriers to Patient Use of Control Solution for Glucose Meters: Surveys of Patients, Pharmacists, and Providers in a Metropolitan Area

BACKGROUND

An important factor in controlling diabetes is self-monitoring of blood glucose. Manufacturers of glucose meters recommend routine use of control solution to ensure accuracy. Previous studies have demonstrated that glucose meters vary in accuracy and that patients are not using control solution as recommended. The purpose of this study is to identify potential barriers to control solution use from multiple perspectives including patient, pharmacist, and provider.

METHODS

This study was a prospective, observational survey design. First, 25 randomly selected chain and independent pharmacies in the Tulsa metropolitan area were audited for control solution accessibility. These pharmacies were then used to survey pharmacists, via telephone, regarding control solution inventory and perception of importance of use. Next, providers were electronically surveyed on their routine practice recommendations, while 60 patients with diabetes were randomly selected for telephone survey on use and perceptions of control solution.

RESULTS

Twenty-five pharmacies were audited and 23 pharmacists, 60 patients, and 29 providers were surveyed. Only 39% of pharmacies stated they supplied control solution, however, only 1 pharmacy visibly stocked it. The only patient factor that appeared to have an impact on control solution usage was having type 1 versus type 2 diabetes (38% vs 15%). Providers are aware of what control solution is (62%), but only half felt it should be routine practice with 44% of those never recommending it.

CONCLUSION

This study raises awareness for the need to educate patients, providers, and pharmacists about use of control solution to ensure glucose meter accuracy.

Comparative Accuracy of 17 Point-of-Care Glucose Meters

BACKGROUND

The accuracy of point-of-care blood glucose (BG) meters is important for the detection of dysglycemia, calculation of insulin doses, and the calibration of continuous glucose monitors. The objective of this study was to compare the accuracy of commercially available glucose meters in a challenging laboratory study using samples with a wide range of reference BG and hemoglobin values.

METHODS

Fresh, discarded blood samples from a hospital STAT laboratory were either used without modification, spiked with a glucose solution, or incubated at 37°C to produce 347 samples with an even distribution across reference BG levels from 20 to 440 mg/dl and hemoglobin values from 9 to 16 g/dl. We measured the BG of each sample with 17 different commercially available glucose meters and the reference method (YSI 2300) at the same time. We determined the mean absolute relative difference (MARD) for each glucose meter, overall and stratified by reference BG and by hemoglobin level.

RESULTS

The accuracy of different meters widely, exhibiting a range of MARDs from 5.6% to 20.8%. Accuracy was lower in the hypoglycemic range, but was not consistently lower in samples with anemic blood hemoglobin levels.

CONCLUSIONS

The accuracy of commercially available glucose meters varies widely. Although the sample mix in this study was much more challenging than those that would be collected under most use conditions, some meters were robust to these challenges and exhibited high accuracy in this setting. These data on relative accuracy and robustness to challenging samples may be useful in informing the choice of a glucose meter.

The Effects of Temperature and Relative Humidity on Point-of-Care Glucose Measurements in Hospital Practice in a Tropical Clinical Setting

BACKGROUND

Hospitals in tropical countries experience conditions that exceed manufacturer temperature and humidity limits for point-of-care (POC) glucose reagents. Our goal was to assess the effects of out-of-limits storage temperature, operating temperature, and operating humidity on POC glucose measurement reliability.

METHODS

Quality control measurements were performed monthly using glucose test strips stored under controlled conditions and in inpatient wards under ambient conditions. Glucose test strips were evaluated in groups organized by operating temperatures of 24-25 (group 1), 28-29 (group 2), and 33-34°C (group 3), and relative humidity (RH) of ≤70 (group A), ~80 (group B), and ~90% (group C).

RESULTS

Glucose results for different storage conditions were inconsistent. Measurements at higher operating temperatures had lower values with mean differences of -2.4 (P < .001) and -36.5 (P < .001) mg/dL (28-29 vs 24-25°C), and -3.6 (P < .001) and -37.4 (P < .001) mg/dL (33-34 vs 24-25°C) for low and high control levels, respectively. Measurements at higher RH had lower values with mean differences of -4.0 (P < .001) and -13.2 (P < .001) mg/dL (~80 vs ≤70% RH), and -5.8 (P < .001) and -16.6 (P < .001) mg/dL (~90 vs ≤70% RH) for low and high levels, respectively.

CONCLUSIONS

High temperature and high RH decreased glucose concentrations for the POC oxidase-based system we evaluated. We recommend that individual hospitals perform stress testing, then determine if maximum absolute differences, which represent highest risk for patients, are clinically significant for decision making by using error grid analysis.

Requirements for Successful Adoption of a Glucose Measurement System Into a Hospital POC Program

Widespread and successful implementation of any glucose measurement system in a hospital point-of-care (POC) program requires a number of features in addition to accurate and reliable analytical performance. Such features include, but are not limited to, a system's glucose-hematocrit dependence, durability, information technology capabilities, and battery capacity and battery life. While the study of Ottiger et al in this issue supports the analytical accuracy and reliability of Bayer's CONTOUR XT® blood glucose monitoring system, the suitability of other features of this system for a hospital POC program remains to be established.

Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting

BACKGROUND

Blood glucose monitoring is an essential component of diabetes management. Inaccurate blood glucose measurements can severely impact patients' health. This study evaluated the performance of 3 blood glucose monitoring systems (BGMS), Contour® Next USB, FreeStyle InsuLinx®, and OneTouch® Verio™ IQ, under routine hospital conditions.

METHODS

Venous blood samples (N = 236) obtained for routine laboratory procedures were collected at a Spanish hospital, and blood glucose (BG) concentrations were measured with each BGMS and with the available reference (hexokinase) method. Accuracy of the 3 BGMS was compared according to ISO 15197:2013 accuracy limit criteria, by mean absolute relative difference (MARD), consensus error grid (CEG) and surveillance error grid (SEG) analyses, and an insulin dosing error model.

RESULTS

All BGMS met the accuracy limit criteria defined by ISO 15197:2013. While all measurements of the 3 BGMS were within low-risk zones in both error grid analyses, the Contour Next USB showed significantly smaller MARDs between reference values compared to the other 2 BGMS. Insulin dosing errors were lowest for the Contour Next USB than compared to the other systems.

CONCLUSIONS

All BGMS fulfilled ISO 15197:2013 accuracy limit criteria and CEG criterion. However, taking together all analyses, differences in performance of potential clinical relevance may be observed. Results showed that Contour Next USB had lowest MARD values across the tested glucose range, as compared with the 2 other BGMS. CEG and SEG analyses as well as calculation of the hypothetical bolus insulin dosing error suggest a high accuracy of the Contour Next USB.

Impact of Glucose Meter Error on Glycemic Variability and Time in Target Range During Glycemic Control After Cardiovascular Surgery

BACKGROUND

We retrospectively studied the impact of glucose meter error on the efficacy of glycemic control after cardiovascular surgery.

METHOD

Adult patients undergoing intravenous insulin glycemic control therapy after cardiovascular surgery, with 12-24 consecutive glucose meter measurements used to make insulin dosing decisions, had glucose values analyzed to determine glycemic variability by both standard deviation (SD) and continuous overall net glycemic action (CONGA), and percentage glucose values in target glucose range (110-150 mg/dL). Information was recorded for 70 patients during each of 2 periods, with different glucose meters used to measure glucose and dose insulin during each period but no other changes to the glycemic control protocol. Accuracy and precision of each meter were also compared using whole blood specimens from ICU patients.

RESULTS

Glucose meter 1 (GM1) had median bias of 11 mg/dL compared to a laboratory reference method, while glucose meter 2 (GM2) had a median bias of 1 mg/dL. GM1 and GM2 differed little in precision (CV = 2.0% and 2.7%, respectively). Compared to the period when GM1 was used to make insulin dosing decisions, patients whose insulin dose was managed by GM2 demonstrated reduced glycemic variability as measured by both SD (13.7 vs 21.6 mg/dL, P < .0001) and CONGA (13.5 vs 19.4 mg/dL, P < .0001) and increased percentage glucose values in target range (74.5 vs 66.7%, P = .002).

CONCLUSIONS

Decreasing glucose meter error (bias) was associated with decreased glycemic variability and increased percentage of values in target glucose range for patients placed on intravenous insulin therapy following cardiovascular surgery.

Infection Transmission Associated with Point of Care Testing and the Laboratory's Role in Risk Reduction

Lack of knowledge and confusion exists regarding safe and appropriate use of blood glucose monitoring equipment. Increasing numbers of diabetics, and exponential growth in blood glucose monitoring presents increased opportunities for infection transmission between patients. Diabetics have increased exposure to blood and blood borne pathogens from frequent blood glucose monitoring. Risk factors have been identified in infectious outbreaks and by analysis of testing practice. Point of care blood glucose meters are frequently contaminated by blood. Bacterial and viral organisms survive on surfaces and in dried blood. Instrumentation is shared between patients, and is heavily utilized in institutional settings, so that serial testing is performed on multiple patients within a short timeframe. Hand hygiene, glove changes and meter disinfection between testing events has been found to be inconsistent. Time pressure for meter usage competes with proper cleaning and disinfection procedures. Meter storage areas are frequently contaminated by blood. Multi-use lancets, improperly used for serial patient blood sampling, are a source for infection transmission. Test strips in vials, frequently contaminated by bacterial organisms, present potential hazard. The responsibility of the clinical laboratory is to insure successful implementation of practices that insure patient safety. Risk reduction strategies include single-use auto-disabling skin puncture devices for blood sampling; hand hygiene and glove change for every testing event; effective meter cleaning and disinfection for every testing event; meter use restriction to a single patient; safe practices for glucose meter storage; infection control practices to reduce contamination of blood glucose test strips or changes in test strip packaging and test strip dispensing.

Analytical performance of glucose monitoring systems at different blood glucose ranges and analysis of outliers in a clinical setting

We investigated the analytical accuracy of 27 glucose monitoring systems (GMS) in a clinical setting, using the new ISO accuracy limits. In addition to measuring accuracy at blood glucose (BG) levels < 100 mg/dl and > 100 mg/dl, we also analyzed devices performance with respect to these criteria at 5 specific BG level ranges, making it possible to further differentiate between devices with regard to overall performance. Carbohydrate meals and insulin injections were used to induce an increase or decrease in BG levels in 37 insulin-dependent patients. Capillary blood samples were collected at 10-minute intervals, and BG levels determined simultaneously using GMS and a laboratory-based method. Results obtained via both methods were analyzed according to the new ISO criteria. Only 12 of 27 devices tested met overall requirements of the new ISO accuracy limits. When accuracy was assessed at BG levels < 100 mg/dl and > 100 mg/dl, criteria were met by 14 and 13 devices, respectively. A more detailed analysis involving 5 different BG level ranges revealed that 13 (48.1%) devices met the required criteria at BG levels between 50 and 150 mg/dl, whereas 19 (70.3%) met these criteria at BG levels above 250 mg/dl. The overall frequency of outliers was low. The assessment of analytical accuracy of GMS at a number of BG level ranges made it possible to further differentiate between devices with regard to overall performance, a process that is of particular importance given the user-centered nature of the devices' intended use.

The Danger of Using Total Error Models to Compare Glucose Meter Performance

Glucose meter performance specifications provide limits for 95% of results, which is the same as total error. A popular total error model is that total error equals (average) bias plus 2 times imprecision. This model has been used to specify combinations of average bias and imprecision that satisfy total error goals. But this model is incomplete and its conclusions are suspect. It is shown that when interferences occur in glucose meters as exemplified by hematocrit interference, the total error model proposed by Boyd and Bruns cannot distinguish between meters that differ in performance. The CLSI standard EP21-A, does not have this problem because it directly estimates total error bypassing the need for a model. An example illustrates these points.

The new glucose standard POCT12-A3 misses the mark

POCT12-A3 is a Clinical Laboratory Standards Institute standard for hospitals about hospital glucose meter procedures and performance standards. I have reviewed this standard based on the attributes of an ideal performance standard. POCT12-A3 has tighter limits than its predecessor for 95% of results, the limits widen for 98% of results, and there are no limits for 2% of results. It is hard to fathom that 2% of the results are unspecified and could cause life-threatening results, as glucose meters do not perform this poorly. There should be a specification for unreported results since, by definition, point-of-care-testing assays are time sensitive. POCT12-A3 provides useful advice about the glucose testing procedure but provides evaluation guidance only about analytical performance. Moreover, the recommended protocol to assess meter performance is biased and likely to underestimate the observed performance. The guideline would be improved if its specification were based on an error grid and contained evaluation protocols for user errors.

Analysis: New point-of-care blood glucose monitoring system for the hospital demonstrates satisfactory analytical accuracy using blood from critically ill patients--an important step toward improved blood glucose control in the hospital

Patients managed in the intensive care units (ICUs) and general wards of the hospital experience a high incidence of hyperglycemia, hypoglycemia, and glycemic variability, despite significant hospital resources devoted to glucose control. Optimized glucose meters and monitoring systems are required to improve the safety and efficacy of insulin delivery and glucose control in the hospital. Safe insulin dosing requires timely and accurate glucose measurements, especially during dynamic changes in nutrition, insulin sensitivity, and physiological stress. In the current issue of Journal of Diabetes Science and Technology, Mitsios and coauthors describe the analytical accuracy of the new Accu-Check® Inform II blood glucose (BG) monitoring system commercialized by F. Hoffmann-La Roche Ltd. The point-of-care glucose meter achieved the desired degree of accuracy and precision, as defined by Clinical and Laboratory Standards Institute POCT12-A3 guidelines when evaluated using venous blood from 600 critically ill patients from multiple ICUs at two medical centers. Venous whole blood samples were used to obtain glucose meter results in duplicate. The remaining blood sample was centrifuged to obtain plasma for central hospital laboratory testing using the hexokinase method within 5 min of meter testing. A total of 98.8% of the 1200 Accu-Check Inform II meter's glucose values were within ± 12.5% (± 12 mg/dl) of the mean laboratory glucose value, and 99.8% were within ± 20% (± 20 mg/dl), thus meeting the Clinical and Laboratory Standards Institute criteria. Future studies are required to evaluate the clinical performance of the new BG monitoring system in the intended-use patient populations and critical care environments, using arterial, peripheral venous, central venous, and capillary blood samples.

Accuracy evaluation of five blood glucose monitoring systems: the North American comparator trial

BACKGROUND

This study evaluated differences in accuracy between the CONTOUR® NEXT EZ (EZ) blood glucose monitoring system (BGMS) and four other BGMSs [ACCU-CHEK® Aviva (ACAP), FreeStyle Freedom Lite® (FFL), ONE TOUCH® Ultra®2 (OTU2), and TRUEtrack® (TT)].

METHODS

Up to three capillary blood samples (N = 393) were collected from 146 subjects with and without diabetes. One sample per subject was tested with fresh (natural) blood; the other samples were glycolyzed to lower blood glucose to <70 mg/dl. Meter results were compared with results from plasma from the same sample tested on a Yellow Springs Instruments (YSI) 2300 STAT PlusTM glucose analyzer. Blood glucose monitoring system accuracy was compared using mean absolute relative difference (MARD; from laboratory reference method results) and other analyses. Separate analyses on fresh (natural) samples only were conducted to determine potential effects of glycolysis on MARD values of systems utilizing glucose-oxidase-based test strip chemistry.

RESULTS

Across the tested glucose range, the EZ had the lowest MARD of 4.7%; the ACAP, FFL, OTU2, and TT had MARD values of 6.3%, 18.3%, 23.4%, and 26.2%, respectively. For samples with glucose concentrations <70 mg/dl, the EZ had the lowest MARD (0.65%), compared with the ACAP (2.5%), FFL (18.3%), OTU2 (22.4%), and TT (33.2%) systems.

CONCLUSIONS

The EZ had the lowest MARD across the tested glucose ranges when compared with four other BGMSs when all samples were analyzed as well as when natural samples only were analyzed.

The relationships between common measures of glucose meter performance

BACKGROUND

Glucose meter performance is commonly measured in several different ways, including the relative bias and coefficient of variation (CV), the total error, the mean absolute relative deviation (MARD), and the size of the interval around the reference value that would be necessary to contain a meter measurement at a specified probability. This fourth measure is commonly expressed as a proportion of the reference value and will be referred to as the necessary relative deviation. A deeper understanding of the relationships between these measures may aid health care providers, patients, and regulators in comparing meter performances when different measures are used.

METHODS

The relationships between common measures of glucose meter performance were derived mathematically.

RESULTS

Equations are presented for calculating the total error, MARD, and necessary relative deviation using the reference value, relative bias, and CV when glucose meter measurements are normally distributed. When measurements are also unbiased, the CV, total error, MARD, and necessary relative deviation are linearly related and are therefore equivalent measures of meter performance.

CONCLUSIONS

The relative bias and CV provide more information about meter performance than the other measures considered but may be difficult for some audiences to interpret. Reporting meter performance in multiple ways may facilitate the informed selection of blood glucose meters.

Analysis of an electrochemical blood glucose monitoring system with hematocrit compensation: improved accuracy by design

The article entitled "Hematocrit Compensation in Electrochemical Blood Glucose Monitoring Systems" by Teodorczyk and colleagues in this issue of Journal of Diabetes Science and Technology demonstrates that the OneTouch(®) Verio™ glucose meter meets current regulatory expectations for glucose meter performance and is relatively free from interference by hematocrit. The lack of influence of hematocrit on whole blood glucose results is a valuable attribute for hospital applications, where greater variation of hematocrit among patients is anticipated. The choice of reference method for evaluation of glucose meters is an important consideration, and it is not clear to what extent reference methods used to evaluate glucose meters are also free from hematocrit interferences.

Intraoperative accuracy of a point-of-care glucose meter compared with simultaneous central laboratory measurements

BACKGROUND

Concerns have been raised about the use of point-of-care (POC) glucose meters in the hospital setting. Accuracy has been questioned especially in critically ill patients. Although commonly used in intensive care units and operating rooms, POC meters were not approved by the Food and Drug Administration for such use. Data on POC glucose meter performance during anesthesia are lacking. We evaluated accuracy of a POC meter in the intraoperative setting.

METHODS

We retrospectively reviewed 4,333 intraoperative records in which at least one intraoperative glucose was measured using electronic medical records at a large academic hospital. We evaluated the accuracy of a POC glucose meter (ACCU-CHEK® Inform, Roche Pharmaceuticals) based on the 176 simultaneous central laboratory (CL) blood glucose (BG) measurements that were found (i.e., documented collection times within 5 minutes). Point-of-care and central lab BG differences were analyzed by Bland-Altman and revised error grid analysis (rEGA).

RESULTS

Mean POC BG was 163.4 ± 64.7 mg/dl [minimum (min) 48 mg/dl, maximum (max) 537 mg/dl] and mean CL BG was 162.6 ± 65.1 mg/dl (min 44 mg/dl, max 502 mg/dl). Mean absolute difference between POC and CL BG was 24.3 mg/dl. Mean absolute relative difference was 16.5% with standard deviation 26.4%. Point-of-care measurements showed a bias of 0.8 relative to the corresponding CL value, with a precision of 39.0 mg/dl. Forty (23%) POC BG values fell outside the Clinical and Laboratory Standards Institute guideline and 3.4% POC measurements fell in zones C and D of the rEGA plot.

CONCLUSIONS

The tested POC glucose meter performed poorly compared to a CL analyzer intraoperatively. Perioperative clinicians should be aware of limitations of specific POC glucose meters, and routine use of POC glucose meters as sole measurement devices in the intraoperative period should be carefully considered.

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.

Evaluation of the analytical performance of the coulometry-based Optium Omega blood glucose meter

BACKGROUND

The goal of diabetes treatment is maintaining near normoglycemia based on self-monitoring of blood glucose (SMBG). In this study, an evaluation of the analytical performance of the coulometry-based Optium Omega™ glucose meter designed for SMBG has been carried out.

METHODS

The assessment of precision and between-lot variability was based on glucose measurements in ethylene-diaminetetraacetic acid venous blood samples. Glucose concentrations measured in 289 fresh capillary blood samples using the Omega glucose meter and the Biosen C_line analyzer were compared.

RESULTS

Within-run imprecision coefficient of variation for the lower and higher glucose concentrations amounted to 5.09 and 2.1%, respectively. The relative lot-dependent differences found for the lower and higher glucose concentrations were equal to 6.8 and 2.6%, respectively. The glucose meter error calculated for various concentration ranges amounted from 2.22 to 4.48%. The glucose meter error met the accuracy criteria recommended by the International Organization for Standardization and the American Diabetes Association. The Passing-Bablok agreement test and error grid analysis with 96% of results in zone A indicated good concordance of results, including glucose concentrations below 100 mg/dl.

CONCLUSIONS

The evaluated Optium Omega glucose meter fits the analytical requirements for its use in blood glucose monitoring in diabetes patients.

Disinfected so it is safe and works

There has been an upsurge in interest in monitoring the cleanliness of the health care environment as it relates to disease transmission. Cleaning and disinfecting practices are nothing new in health care facilities. However, continued development of analytical medical products such as point-of-care devices or, as in this review, glucose meters, has created potential risks to patients on a number of levels. Examples are (1) inappropriate disinfection of glucose meters so that the risk of disease transmission is increased and (2) cleaning agents potentially affecting glucose reading accuracy. Cleaning and disinfection recommendations have become available to address these issues. In this issue of Journal of Diabetes Science and Technology, Sarmaga and colleagues discuss the impact of a disinfecting agent on results generated from a particular device, which suggests that not all equipment are created equal and not all practices/products used to clean and disinfect are the same. It appears that more interaction must take place between vendors of these technologies as well as vendors of cleaning/disinfecting agents and the end users who will be performing all the requisite tasks to ensure a high quality product as well as care.

Analysis of the evaluation of a new glucose meter with integrated self-management software and USB connectivity

Glucose meter technology has not kept up with the advances that have occurred in other sectors in mobile and health care technology. A new device that combines strip-based capillary blood glucose monitoring and USB flash drive technology is evaluated in an industry-funded study in a cohort of patients and health care professionals. The expanded memory capacity of flash drives allows the software program to be stored on the device for analyzing the blood glucose readings in memory. The study analyzes the device for precision and accuracy as well as for ease of adaptability and usage. This analysis focuses on shortcomings in the design of the study and methodology in addition to features of the hardware device itself. Although the device has distinct advantages over many devices on the market, a challenge is made to device manufacturers to encourage further innovation.

Reducing patient identification errors related to glucose point-of-care testing

BACKGROUND

Patient identification (ID) errors in point-of-care testing (POCT) can cause test results to be transferred to the wrong patient's chart or prevent results from being transmitted and reported. Despite the implementation of patient barcoding and ongoing operator training at our institution, patient ID errors still occur with glucose POCT. The aim of this study was to develop a solution to reduce identification errors with POCT.

MATERIALS AND METHODS

Glucose POCT was performed by approximately 2,400 clinical operators throughout our health system. Patients are identified by scanning in wristband barcodes or by manual data entry using portable glucose meters. Meters are docked to upload data to a database server which then transmits data to any medical record matching the financial number of the test result. With a new model, meters connect to an interface manager where the patient ID (a nine-digit account number) is checked against patient registration data from admission, discharge, and transfer (ADT) feeds and only matched results are transferred to the patient's electronic medical record. With the new process, the patient ID is checked prior to testing, and testing is prevented until ID errors are resolved.

RESULTS

When averaged over a period of a month, ID errors were reduced to 3 errors/month (0.015%) in comparison with 61.5 errors/month (0.319%) before implementing the new meters.

CONCLUSION

Patient ID errors may occur with glucose POCT despite patient barcoding. The verification of patient identification should ideally take place at the bedside before testing occurs so that the errors can be addressed in real time. The introduction of an ADT feed directly to glucose meters reduced patient ID errors in POCT.

Accuracy and reliability of the Nova StatStrip® glucose meter for real-time blood glucose determinations during glucose clamp studies

AIMS/HYPOTHESIS

The Andres clamp technique, which requires accurate and timely determination of glucose, utilizes the Beckman or Yellow Springs Instruments (YSI) glucose analyzers. Both instruments require maintenance, a dedicated operator, preparation of a plasma sample, and a duplicate measurement that takes ≥2 minutes. The Nova StatStrip glucose meter was evaluated for accuracy, reliability, and near-real-time availability of glucose.

METHODS

Blood samples from 24 patients who underwent 6-hour clamp studies and 12 patients who had a standardized meal tolerance test (SMT) were measured. Specimens were analyzed simultaneously and immediately upon collection by Beckman, YSI, and Nova.

RESULTS

Of 1004 data pairs for the Nova device versus Beckman, the Nova data points ranged from 32 to 444, while Beckman ranged from 42 to 412. The coefficient for the slope of Beckman versus Nova was 1.009 (r = 0.978). Using error grid analysis, the number and percentage of values for Nova were 976 (97.2%) in the A zone and 28 (2.8%) in the B zone. Of 399 data pairs for the Nova device versus YSI, the Nova data points ranged from 46 to 255, whereas YSI ranged from 47 to 231. The coefficient for the slope of YSI versus Nova was 1.023 (r = 0.989). All Nova readings fell in the A zone. Time required for final reading, in duplicate, was 15 seconds for Nova and 120-180 seconds for Beckman and YSI.

CONCLUSIONS

The simplicity of Nova and its reliability, accuracy, and speed make it an acceptable replacement device for Beckman and YSI in the conduct of clamps, especially when perturbations require rapid glucose determination.

Variable classifications of glycemic index determined by glucose meters

The study evaluated and compared the differences of glucose responses, incremental area under curve (IAUC), glycemic index (GI) and the classification of GI values between measured by biochemical analyzer (Fuji automatic biochemistry analyzer (FAA)) and three glucose meters: Accue Chek Advantage (AGM), BREEZE 2 (BGM), and Optimum Xceed (OGM). Ten healthy subjects were recruited for the study. The results showed OGM yield highest postprandial glucose responses of 119.6 ± 1.5, followed by FAA, 118.4 ± 1.2, BGM, 117.4 ± 1.4 and AGM, 112.6 ± 1.3 mg/dl respectively. FAA reached highest mean IAUC of 4156 ± 208 mg × min/dl, followed by OGM (3835 ± 270 mg × min/dl), BGM (3730 ± 241 mg × min/dl) and AGM (3394 ± 253 mg × min/dl). Among four methods, OGM produced highest mean GI value than FAA (87 ± 5) than FAA, followed by BGM and AGM (77 ± 1, 68 ± 4 and 63 ± 5, p<0.05). The results suggested that the AGM, BGM and OGM are more variable methods to determine IAUC, GI and rank GI value of food than FAA. The present result does not necessarily apply to other glucose meters. The performance of glucose meter to determine GI value of food should be evaluated and calibrated before use.

"No coding" of glucose test strips: a roche perspective

INTRODUCTION

Glucose test strips vary slightly from batch to batch. These variations are accounted for by a batch-specific "code": a set of parameters defining the relationship between the signal change induced on the glucose test strip and the blood glucose concentration.

METHODS

We assessed the impact on accuracy of miscoding the ACCU-CHEK Aviva system across a wide range of glucose test strip batches and glucose levels, throughout the shelf life of the glucose test strips.

RESULTS

The deviations in coding that we investigated had no effect on clinical action. Additionally, we showed, with mathematical modeling of a worst-case scenario, that the probability of an error altering clinical action is low. The batch-specific code of glucose test strips ensures the accuracy and safety of each blood glucose measurement. In addition to the parameters directly related to the blood glucose measurement, the electronic code chip contains the expiration date of the test strips and can deliver firmware updates for upgrades to the glucose meter.

CONCLUSIONS

We eliminated the handling step of coding and retained all the advantages of coding. In Roche's newest all-in-one glucose meter, the ACCU-CHEK Compact Plus system, the batch-specific code is integrated into the drum that contains the glucose test strips. As a result, changing the drum containing the glucose test strips automatically changes the glucose test strip code. Patients with diabetes who use the ACCU-CHEK Compact Plus glucose meter do not have to be concerned with coding.

Quality control of self-monitoring of blood glucose: why and how?

The control of analytical quality of self-monitoring of blood glucose (SMBG) is recommended as a routine procedure in diabetes management. This control procedure should be easily accessible to patients, convenient, not time-consuming, and provide a reliable assessment of glucose meter performance. Optimally it should be located in the diabetes outpatient clinic. Presently there are two approaches to carrying out SMBG quality control. The first is based on the comparison of results obtained by a controlled glucose meter and use of the laboratory method or point-of-care testing device as a surrogate reference analyzer. The second one is a traditionally organized external quality assessment scheme with use of a dedicated control material, which is distributed to all participants. The recommended allowable meter error in SMBG can be realistically set at 10%.