Assessing glucose meter accuracy

A comprehensive review of non-invasive optical and microwave biosensors for glucose monitoring

Frequent glucose monitoring is essential for effective diabetes management. Currently, glucose monitoring is done using invasive methods such as finger-pricking and subcutaneous sensing. However, these methods can cause discomfort, heighten the risk of infection, and some sensing devices need frequent calibration. Non-invasive glucose monitoring technologies have attracted significant attention due to their potential to overcome the limitations of their invasive counterparts by offering painless and convenient alternatives. This review focuses on two prominent approaches to non-invasive glucose sensing: optical- and microwave-based methods. On one hand, optical techniques, including Raman and near-infrared (NIR) spectroscopy, leverage the unique spectral properties of glucose molecules to measure their concentration in tissues and biofluids. On the other hand, microwave sensing leverages the dielectric properties of glucose to detect concentration changes based on impedance measurements. Despite their promise, optical- and microwave-based technologies face challenges such as signal interference and high variability due to tissue heterogeneity, which impact their accuracy and reliability. This review provides a comprehensive overview of the advancements of these non-invasive methods, highlighting their technical implementation, limitations, and their future potential in revolutionizing glucose monitoring for diabetes care.

Fundamental Importance of Reference Glucose Analyzer Accuracy for Evaluating the Performance of Blood Glucose Monitoring Systems (BGMSs)

BACKGROUND

As blood glucose monitoring system (BGMS) accuracy is based on comparison of BGMS and laboratory reference glucose analyzer results, reference instrument accuracy is important to discriminate small differences between BGMS and reference glucose analyzer results. Here, we demonstrate the important role of reference glucose analyzer accuracy in BGMS accuracy evaluations.

METHODS

Two clinical studies assessed the performance of a new BGMS, using different reference instrument procedures. BGMS and YSI analyzer results were compared for fingertip blood that was obtained by untrained subjects' self-testing and study staff testing, respectively. YSI analyzer accuracy was monitored using traceable serum controls.

RESULTS

In study 1 (N = 136), 94.1% of BGMS results were within International Organization for Standardization (ISO) 15197:2013 accuracy criteria; YSI analyzer serum control results showed a negative bias (-0.64% to -2.48%) at the first site and a positive bias (3.36% to 6.91%) at the other site. In study 2 (N = 329), 97.8% of BGMS results were within accuracy criteria; serum controls showed minimal bias (<0.92%) at both sites.

CONCLUSIONS

These findings suggest that the ability to demonstrate that a BGMS meets accuracy guidelines is influenced by reference instrument accuracy.

Evaluation of two glucose meters and interference corrections for screening neonatal hypoglycemia

BACKGROUND

Many neonatal intensive care and maternal units still use self-monitoring of blood glucose (SMBG) devices as a tool to aid diagnosis despite the introduction of point-of-care testing (POCT) devices, which are known to have higher accuracy. We evaluated the performance of two glucose meters, the StatStrip (Nova Biomedical), a POCT device, and the Medisafe Mini (Terumo), an SMBG device, to detect hypoglycemia in neonates. In addition, we evaluated the interference of hematocrit, acetaminophen and ascorbic acid.

METHODS

Whole blood samples were drawn from neonates who were at risk of hypoglycemia and analyzed with the StatStrip and Medisafe Mini. The results were further confirmed with blood gas analyzers ABL825 and BM6050. To evaluate the interference of hematocrit, acetaminophen and ascorbic acid, concentrated solutions of glucose and interfering substances were gravimetrically prepared and analyzed.

RESULTS

Among the 222 blood samples analyzed, results from the StatStrip were more closely aligned to those of the ABL825 at all levels of glucose than the Medisafe Mini.

CONCLUSION

StatStrip appears to be unaffected by hematocrit, ascorbic acid or acetaminophen. We recommend its use in neonates in hospital. Further studies are required to identify other interference effects.

Accuracy of blood glucose meters for self-monitoring affects glucose control and hypoglycemia rate in children and adolescents with type 1 diabetes

AIMS/HYPOTHESIS

This study investigated the accuracy of blood glucose meters for self-monitoring and its influence on glycated hemoglobin (HbA1c) levels and the frequency of hypoglycemic coma.

MATERIALS AND METHODS

Self-measured and simultaneously obtained laboratory blood glucose values from 9,163 patients with type 1 diabetes <18 years of age in the German/Austrian Diabetes Prospective Documentation Initiative registry were analyzed by investigating their compliance with the International Organization for Standardization (ISO) criteria (versions 2003 and 2013) and by error grid analyses. Regression models elucidated effects on glucose control and hypoglycemia rates.

RESULTS

Depending on the respective subgroup (defined by sex, age, duration of diabetes, mode of insulin therapy), 78.7-94.7% of the self-monitoring of blood glucose (SMBG) values met the old and 79.7-88.6% met the new ISO criteria. In Clarke and Parkes error grid analyses, the percentages of SMBG values in Zone A ranged between 92.8% and 94.6% (Clarke) and between 92.2% and 95.0% (Parkes). The patient group with SMBG devices measuring "far too low" (compared with the laboratory-obtained glucose levels) presented with a higher HbA1c level than those measuring "far too high," "too high," "identical/almost identical," or "too low" (based on quintiles of deviation). Performing "far too high" was associated with the highest rate of hypoglycemic coma in comparison with the other deviation quintiles.

CONCLUSIONS

This study showed that current SMBG devices fulfilled neither the previous nor the new ISO criteria. Large deviations of the SMBG values from the "true" glucose levels resulted in higher HbA1c levels and markedly increased rates of hypoglycemic events.

Performance of community blood glucose meters in calgary, alberta: an analysis of quality assurance data

OBJECTIVE

The self-monitoring of blood glucose plays a critical role in management of diabetes mellitus. Although laboratory comparisons of glucose meter accuracy are often acceptable, clinical comparisons show frequent inaccuracies. In this paper, we evaluate the accuracy of self-monitoring blood glucose meters using glucose meter and serum comparisons from a large Canadian laboratory.

METHODS

This study was performed using secondary data obtained from the Laboratory Information System of Calgary Services, the sole provider of laboratory testing to Calgary and surrounding areas. We examined anonymous quality assurance data for glucose meter comparisons performed on home glucose meters between January 1, 2010, and April 30, 2013.

RESULTS

A total of 39 542 comparisons were recorded on 18 540 different subjects. Overall, 6.7% of differences were greater than the current International Standards Organization standard of 15%, and 3.7% exceeded the Canadian guideline of 20%.

CONCLUSIONS

Glucose meter checks were infrequently performed (on average, once per 1.6 years). A significant subset of meter results was inaccurate.

Performance of point-of-care diagnostics for glucose, lactate, and hemoglobin in the management of severe malaria in a resource-constrained hospital in Uganda

Severe malaria is frequently managed without access to laboratory testing. We report on the performance of point-of-care tests used to guide the management of a cohort of 179 children with severe malaria in a resource-limited Ugandan hospital. Correlation coefficients between paired measurements for glucose (i-STAT and One Touch Ultra), lactate (i-STAT and Lactate Scout), and hemoglobin (Hb; laboratory and i-STAT) were 0.86, 0.85, and 0.73, respectively. The OneTouch Ultra glucometer readings deviated systematically from the i-STAT values by +1.7 mmol/L. Lactate Scout values were systematically higher than i-STAT by +0.86 mmol/L. Lactate measurements from either device predicted subsequent mortality. Hb estimation by the i-STAT instrument was unbiased, with upper and lower limits of agreement of -34 and +34 g/L, and it was 91% sensitive and 89% specific for the diagnosis of severe anemia (Hb < 50 g/L). New commercially available bedside diagnostic tools, although imperfect, may expedite clinical decision-making in the management of critically ill children in resource-constrained settings.

The precision study: examining the inter- and intra-assay variability of replicate measurements of BGStar, iBGStar and 12 other blood glucose monitors

OBJECTIVE

Self-monitoring of blood glucose is a key element in diabetes management. Accurate and precise performance of blood glucose monitors (BGMs) ensures that valid values are obtained to guide treatment decisions by patients and physicians. BGStar and iBGStar are hand-held BGMs that use dynamic electrochemistry to correct for potential interferences and thereby minimize system errors.

RESEARCH DESIGN AND METHODS

A single-center, in vitro diagnostic device performance evaluation with heparinized oxygenated venous blood samples (intra-assay precision) and control solutions (interassay precision) was performed in a laboratory setting, comparing BGStar and iBGStar with 12 competitors.

MAIN OUTCOME MEASURES

The primary outcome was the coefficient of variation percent (CV%) of the BGMs investigated.

RESULTS

In inter-assay precision analyses, all but GlucoMen LX had a CV <5%, and in intra-assay precision analyses, 10 of the 14 devices tested had CV <5%. BGStar and iBGStar had a CV <5% in both the inter- and intra-assay precision analyses. The smallest variation was found in the near-normoglycemic glucose range (5.3 - 8.0 mmol/l) for both BGStar and iBGStar in the inter-assay precision analysis.

CONCLUSIONS

BGStar and iBGStar were proven to have very good inter-assay and high intra-assay precision, demonstrating low scattering of replicate measurements with both clinical samples and control solutions.

Spurious elevation of glucose concentration during administration of high dose of ascorbic acid in a patient with type 2 diabetes on hemodialysis

We describe herein a case of life-threatening hypoglycemia due to spurious elevation of glucose concentration during the administration of ascorbic acid in a type 2 diabetic patient. A 31-year-old female was admitted for proliferative diabetic retinopathy treatment and prescribed high dose ascorbic acid. During hospitalization, she suddenly lost her consciousness and her glucose concentration was 291 mg/dL, measured using self-monitoring blood glucose (SMBG) device, while venous blood glucose concentration was 12 mg/dL. After intravenous injection of 50% glucose solution, the patient became alert. We reasoned that glucose measurement by SMBG device was interfered by ascorbic acid. Physicians should be aware of this interference; high dose ascorbic acid may cause spurious elevation of glucose concentration when measuring with SMBG devices.

Impact of prandial status on the comparison of capillary glucose meter and venous plasma glucose measurements in healthy volunteers

BACKGROUND

There is a negative glucose gradient between the capillary and venous systems, produced by glucose uptake into peripheral tissues. This gradient is augmented by oral glucose ingestion in healthy volunteers; thus prandial status may impact on capillary glucose meter performance. Our primary aim was to investigate whether the (capillary-venous plasma) glucose difference changed in relation to prandial status, in healthy volunteers.

METHODS

Glucose was measured fasting and also one hour after an ad libitum breakfast, in 103 healthy volunteers. Duplicate capillary (finger stick) measurements were undertaken at both time points, using both the FreeStyle Lite and AccuChek Performa meters. Simultaneous venous (antecubital fossa) samples were centrifuged immediately after collection and plasma glucose was measured using the laboratory hexokinase method. Results were compared by Bland-Altman difference analysis.

RESULTS

The mean (95% CI) pre- and postprandial (capillary-plasma) glucose differences (mmol/L) were calculated for each meter. For the Freestyle Lite, the preprandial difference was -0.51 (-0.58 to -0.45) and postprandial difference was 0.81 (0.69-0.94). Corresponding differences for the Performa were -0.13 (-0.20 to -0.06) and 1.19 (1.07-1.31), respectively. T-test comparison of participants' paired pre- and postprandial (capillary-plasma) glucose differences confirmed a significant meal-related change in glucose estimation for both meters (P < 0.0001). Also, both meters read highest at lower glucose concentrations.

CONCLUSIONS

In healthy volunteers, both glucose meters showed a systematic positive bias one hour after breakfast. The significance of this finding in diabetes remains to be determined.

Clinical assessment of the accuracy of blood glucose measurement devices

OBJECTIVES

Blood glucose meters for patient self-measurement need to comply with the accuracy standards of the ISO 15197 guideline. We investigated the accuracy of the two new blood glucose meters BG*Star and iBG*Star (Sanofi-Aventis) in comparison to four other competitive devices (Accu-Chek Aviva, Roche Diagnostics; FreeStyle Freedom Lite, Abbott Medisense; Contour, Bayer; OneTouch Ultra 2, Lifescan) at different blood glucose ranges in a clinical setting with healthy subjects and patients with type 1 and type 2 diabetes. BGStar and iBGStar are employ dynamic electrochemistry, which is supposed to result in highly accurate results.

METHODS

The study was performed on 106 participants (53 female, 53 male, age (mean ± SD): 46 ± 16 years, type 1: 32 patients, type 2: 34 patients, and 40 healthy subjects). Two devices from each type and strips from two different production lots were used for glucose assessment (∼200 readings/meter). Spontaneous glucose assessments and glucose or insulin interventions under medical supervision were applied to perform measurements in the different glucose ranges in accordance with the ISO 15197 requirements. Sample values <50 mg/dL and >400 mg/dL were prepared by laboratory manipulations. The YSI glucose analyzer (glucose oxidase method) served as the standard reference method which may be considered to be a limitation in light of glucose hexokinase-based meters.

RESULTS

For all devices, there was a very close correlation between the glucose results compared to the YSI reference method results. The correlation coefficients were r = 0.995 for BGStar and r = 0.992 for iBGStar (Aviva: 0.995, Freedom Lite: 0.990, Contour: 0.993, Ultra 2: 0.990). Error-grid analysis according to Parkes and Clarke revealed both 100% of the readings to be within the clinically acceptable areas (Clarke: A + B with BG*Star (100 + 0), Aviva (97 + 3), and Contour (97 + 3); and 99.5% with iBG*Star (97.5 + 2), Freedom Lite (98 + 1.5), and Ultra 2 (97.5 + 2)).

CONCLUSIONS

This study demonstrated the very high accuracy of BG*Star, iBG*Star, and the competitive blood glucose meters in a clinical setting.

Accuracy of point-of-care glucose measurements

Control of blood glucose (BG) in an acceptable range is a major therapy target for diabetes patients in both the hospital and outpatient environments. This review focuses on the state of point-of-care (POC) glucose monitoring and the accuracy of the measurement devices. The accuracy of the POC glucose monitor depends on device methodology and other factors, including sample source and collection and patient characteristics. Patient parameters capable of influencing measurements include variations in pH, blood oxygen, hematocrit, changes in microcirculation, and vasopressor therapy. These elements alone or when combined can significantly impact BG measurement accuracy with POC glucose monitoring devices (POCGMDs). In general, currently available POCGMDs exhibit the greatest accuracy within the range of physiological glucose levels but become less reliable at the lower and higher ranges of BG levels. This issue raises serious safety concerns and the importance of understanding the limitations of POCGMDs. This review will discuss potential interferences and shortcomings of the current POCGMDs and stress when these may impact the reliability of POCGMDs for clinical decision-making.

Within-subject biological variation of glucose and HbA(1c) in healthy persons and in type 1 diabetes patients

BACKGROUND

Several articles describing within-subject biological variation of fasting glucose and HbA(1c) in healthy populations have been published, but information about biological variation of glucose and HbA(1c) in patients with type 1 diabetes is scarce. It is reasonable to assume that type 1 diabetics differ from their healthy counterparts in this matter. The aim of our study was to estimate the biological variation of glucose and HbA(1c) in healthy subjects and in patients with type 1 diabetes.

METHODS

Fifteen healthy individuals and 15 type 1 diabetes patients were included. Biological variations were calculated based on blood samples collected weekly for 10 consecutive weeks from the healthy and the eligible of the type 1 diabetes patients.

RESULTS

The within-subject variations of glucose were approximately 5% in healthy individuals and 30% in diabetes patients, and for HbA(1c) they were 1.2% in healthy individuals and 1.7% in diabetes patients.

CONCLUSIONS

In conclusion, we found a high within-subject biological variation of glucose in diabetes patients as expected compared to healthy individuals (30% vs. 5%). The short-term (2 months) within-subject biological variation of HbA(1c) did not differ significantly between well regulated type 1 diabetes patients and healthy individuals (1.7% vs. 1.2%).

The accuracy of home glucose meters in hypoglycemia

BACKGROUND

Home glucose meters (HGMs) may not be accurate enough to sense hypoglycemia. We evaluated the accuracy and the capillary and venous comparability of five different HGMs (Optium Xceed [Abbott Diabetes Care, Alameda, CA, USA], Contour TS [Bayer Diabetes Care, Basel, Switzerland], Accu-Chek Go [Roche Ltd., Basel, Switzerland], OneTouch Select [Lifescan, Milpitas, CA, USA], and EZ Smart [Tyson Bioresearch Inc., Chu-Nan, Taiwan]) in an adult population.

METHODS

The insulin hypoglycemia test was performed to 59 subjects (56 males; 23.6 +/- 3.2 years old). Glucose was measured from forearm venous blood and finger capillary samples both before and after regular insulin (0.1 U/kg) was injected. Venous samples were analyzed in the reference laboratory by the hexokinase method. In vitro tests for method comparison and precision analyses were also performed by spiking the glucose-depleted venous blood.

RESULTS

All HGMs failed to sense hypoglycemia to some extend. EZ Smart was significantly inferior in critical error Zone D, and OneTouch Select was significantly inferior in the clinically unimportant error Zone B. Accu-Chek Go, Optium Xceed, and Contour TS had similar performances and were significantly better than the other two HGMs according to error grid analysis or International Organization for Standardization criteria. The in vitro tests were consistent with the above clinical data. The capillary and venous consistencies of Accu-Chek Go and OneTouch Select were better than the other HGMs.

CONCLUSIONS

The present results show that not all the HGMs are accurate enough in low blood glucose levels. The patients and the caregivers should be aware of these restrictions of the HGMs and give more credit to the symptoms of hypoglycemia than the values obtained by the HGMs. Finally, these results indicate that there is a need for the revision of the accuracy standards of HGMs in low blood glucose levels.

Evaluation of a glucose meter in determining the glycemic index of chinese traditional foods

BACKGROUND

The purpose of this study was to evaluate whether the Glucometer Elite((R)) meter (Bayer Diagnostics, Kyoto, Japan) (POG) could be used for determining the glycemic index (GI) values of Chinese traditional foods, compared with the YSI (Yellow Springs, OH) glucose analyzer (YSI).

METHODS

After consumption of either glucose or one of 11 test foods, the 2-h postprandial glucose responses were measured separately by POG and YSI. GI values and incremental area under the blood glucose response curve (IAUC) values were then calculated to make comparisons between POG and YSI.

RESULTS

The mean glucose concentration measured by POG was higher than that measured by YSI (5.54 +/- 0.03 vs. 5.30 +/- 0.03 mmol/L, P < 0.01). The mean IAUC calculated by POG data was also higher than that calculated by YSI data (112.93 +/- 4.04 vs. 106.76 +/- 4.06 mmol.min/L, P < 0.01). However, there were no differences in the mean GI value determined by POG and YSI data for each test food.

CONCLUSIONS

Although the glucose concentrations measured by POG were higher than that measured by YSI glucose analyzer, it seemed to be an appropriate instrument to determine the GI values of Chinese traditional foods. However, this conclusion should be cautiously applied to other kinds of glucose meters.

Frequency of lactose malabsorption among healthy southern and northern Indian populations by genetic analysis and lactose hydrogen breath and tolerance tests

BACKGROUND

Lactose malabsorption (LM), the inability to break down lactose into glucose and galactose, is due to a deficiency in the small intestinal lactase phlorizin hydrolase enzyme. Ethnic and geographic variations of LM are known.

OBJECTIVE

The aim of this study was to compare the frequency of LM in healthy southern and northern Indian populations.

DESIGN

A total of 153 healthy volunteers (76 from southern and 77 from northern India) were evaluated for LM by using a lactose tolerance test (LTT), a lactose hydrogen breath test (lactose HBT), and polymerase chain reaction-restriction fragment length polymorphism to identify the lactase gene C/T-13910 polymorphism (confirmed by sequencing).

RESULTS

Volunteers from southern and northern India were comparable in age and sex. The LTT result was abnormal in 88.2% of southern Indians and in 66.2% of northern Indians (P = 0.001). The lactose HBT result was abnormal in 78.9% of southern Indians and in 57.1% of northern Indians (P = 0.003). The CC genotype was present in 86.8% and 67.5% (P = 0.002), the CT genotype was present in 13.2% and 26.0% (P = 0.036), and the TT genotype was present in 0% and 6.5% (P = 0.03) of southern and northern Indians, respectively. The frequency of symptoms after the lactose load (47.4% compared with 15.6%; P < 0.001) and peak concentrations of breath hydrogen (88.5 +/- 71.9 compared with 55.4 +/- 61.9 ppm; P = 0.003), both of which might indicate the degree of lactase deficiency, were higher in southern than in northern Indians.

CONCLUSION

The frequency and degree of LM is higher in southern than in northern Indian healthy populations because of genetic differences in these populations.

Analytical and clinical performance of blood glucose monitors

BACKGROUND

The objective of this study was to understand the level of performance of blood glucose monitors as assessed in the published literature.

METHODS

Medline from January 2000 to October 2009 and reference lists of included articles were searched to identify eligible studies. Key information was abstracted from eligible studies: blood glucose meters tested, blood sample, meter operators, setting, sample of people (number, diabetes type, age, sex, and race), duration of diabetes, years using a glucose meter, insulin use, recommendations followed, performance evaluation measures, and specific factors affecting the accuracy evaluation of blood glucose monitors.

RESULTS

Thirty-one articles were included in this review. Articles were categorized as review articles of blood glucose accuracy (6 articles), original studies that reported the performance of blood glucose meters in laboratory settings (14 articles) or clinical settings (9 articles), and simulation studies (2 articles). A variety of performance evaluation measures were used in the studies. The authors did not identify any studies that demonstrated a difference in clinical outcomes. Examples of analytical tools used in the description of accuracy (e.g., correlation coefficient, linear regression equations, and International Organization for Standardization standards) and how these traditional measures can complicate the achievement of target blood glucose levels for the patient were presented. The benefits of using error grid analysis to quantify the clinical accuracy of patient-determined blood glucose values were discussed.

CONCLUSIONS

When examining blood glucose monitor performance in the real world, it is important to consider if an improvement in analytical accuracy would lead to improved clinical outcomes for patients. There are several examples of how analytical tools used in the description of self-monitoring of blood glucose accuracy could be irrelevant to treatment decisions.

Performance analysis of the OneTouch UltraVue blood glucose monitoring system

BACKGROUND

OneTouch UltraVue is a new meter for self-monitoring of blood glucose that includes a color display, used-strip ejector, and no-button interface. The system uses an electrochemical biosensor technology based on glucose oxidase chemistry to detect glucose concentrations from 20 to 600 mg/dl (1.1 to 33.3 mmol/liter).

METHODS

Accuracy and reproducibility were evaluated over a wide range of glucose concentrations according to standard criteria. Clinical accuracy was assessed by health care providers (HCPs) in two studies and by diabetes patients in the second study. Reference glucose levels were determined by a YSI 2300 analyzer. Same-day reproducibility and day-to-day reproducibility were also evaluated.

RESULTS

In the accuracy studies, 99.7% and 98.7% of tests by HCPs and 97.0% of tests by patients were within +/-15 mg/dl (+/-0.8 mmol/liter) of the YSI reference for blood glucose <75 mg/dl (<4.2 mmol/liter), and within +/-20% for blood glucose > or =75 mg/dl (> or =4.2 mmol/liter), respectively. Consensus error grid analysis showed that 99.7% and 95.3% of tests by HCPs and 97.0% of tests by patients fell within zone A (i.e., has no effect on clinical action); all other results were in zone B (i.e., altered clinical action, little or no effect on clinical outcome). In the reproducibility studies, the standard deviation was <1.5 mg/dl (<0.1 mmol/liter) for glucose concentrations <100 mg/dl (<5.6 mmol/liter), and the coefficient of variation was <2% for concentrations > or = 100 mg/dl (> or =5.6 mmol/liter).

CONCLUSIONS

OneTouch UltraVue meets standard acceptability criteria for accuracy and reproducibility across a wide range of glucose concentrations. Its simple interface and lack of contact with used strips make it a viable option for older patients and their caregivers.

Glucose meters: a review of technical challenges to obtaining accurate results

Glucose meters are universally utilized in the management of hypoglycemic and hyperglycemic disorders in a variety of healthcare settings. Establishing the accuracy of glucose meters, however, is challenging. Glucose meters can only analyze whole blood, and glucose is unstable in whole blood. Technical accuracy is defined as the closeness of agreement between a test result and the true value of that analyte. Truth for glucose is analysis by isotope dilution mass spectrometry, and frozen serum standards analyzed by this method are available from the National Institute of Standards and Technology. Truth for whole blood has not been established, and cells must be separated from the whole blood matrix before analysis by a method like isotope dilution mass spectrometry. Serum cannot be analyzed by glucose meters, and isotope dilution mass spectrometry is not commonly available in most hospitals and diabetes clinics to evaluate glucose meter accuracy. Consensus standards recommend comparing whole blood analysis on a glucose meter against plasma/serum centrifuged from a capillary specimen and analyzed by a clinical laboratory comparative method. Yet capillary samples may not provide sufficient volume to test by both methods, and venous samples may be used as an alternative when differences between venous and capillary blood are considered. There are thus multiple complexities involved in defining technical accuracy and no clear consensus among standards agencies and professional societies on accuracy criteria. Clinicians, however, are more concerned with clinical agreement of the glucose meter with a serum/plasma laboratory result. Acceptance criteria for clinical agreement vary across the range of glucose concentrations and depend on how the result will be used in screening or management of the patient. A variety of factors can affect glucose meter results, including operator technique, environmental exposure, and patient factors, such as medication, oxygen therapy, anemia, hypotension, and other disease states. This article reviews the challenges involved in obtaining accurate glucose meter results.

Self-monitoring of blood glucose in diabetes: is it worth it?

Self-monitoring of blood glucose (SMBG) is advocated as a valuable aid in the management of diabetes. The volume and cost of monitoring continues to increase. SMBG has a number of theoretical advantages/disadvantages which might impact on treatment, outcome and wellbeing. Investigating and quantifying the effect of self-monitoring in a condition where self-management plays a central role poses major methodological difficulties because of the need to minimize confounding factors. Despite the absence of definitive evidence, some situations where monitoring is generally accepted to be beneficial include patients on insulin, during pregnancy, in patients with hypoglycaemia unawareness and while driving. An area of controversy is the role of monitoring in non-insulin-requiring type-2 diabetes where observational and controlled studies give conflicting results. The available evidence does not support the general use of monitoring by all patients with type-2 diabetes, although further research is needed to identify specific subgroups of patients or specific situations where monitoring might be useful. The best use of SMBG in patients with type-2 diabetes might be for those receiving insulin and those on sulphonylurea drugs. The impact of monitoring on patient wellbeing must also be considered, with some studies suggesting adverse psychological effects. Given the large increase in the prevalence of type-2 diabetes, it will be important to define the role of SMBG so that resources can be used appropriately. Presently, the widespread use of SMBG (particularly in type-2 diabetes patients) is a good example of self-monitoring that was adopted in advance of robust evidence of its clinical efficacy.

Assessing the quality of Bionime self-monitoring blood glucose system Rightest GM110: a critical evaluation of interference and ambient circumstances

BACKGROUND

The key issue in preventing chronic diabetic complications is to maintain near-normoglycemia. Analytical evaluation of Bionime self-monitoring blood glucose (SMBG) Rightest GM110 was carried out in this study.

METHODS

The evaluation was executed according to the Standards for Reporting Diagnostic Accuracy (STARD) and the Clinical and Laboratory Standards Institute (CLSI). The evaluation procedure mainly focused on analytical performance. The accuracy tests included hematocrit, interferants, temperature, humidity, altitude and clinical evaluations.

RESULTS

Good linearity response (R(2)>0.99) and satisfactory precision (CVs: 1.1-2.8%) were observed in glucose concentrations of 0.6-30.5 mmol/l. In hematocrit test, the Rightest GM110 was suitable for use in sample containing hematocrit in the range of 30-55%. Interfering test indicated that almost all substances tested were insignificant, with bias <10% in medium- and hyper-glycemia samples. Satisfactory stability was also found under various ambient circumstances, with bias within +/-10%. In clinical trials, values within the acceptable zone (A+B) were 100% and values within zone A exceed 95% in error grid analysis.

CONCLUSIONS

The Bionime Rightest GM110 is reliable to display accurate glucose concentrations in specimens with irresistible interfering factors.

Assessing glucose monitor performance--a standardized approach

BACKGROUND

Glucose monitor evaluations must be carefully designed and executed in order to control protocol-specific bias and random patient interferences. Although published guidelines and recommendations exist, investigators rarely incorporate consensus standards or quality guidelines into glucose monitor evaluation studies.

METHODS

We performed a literature search for "best practice" quality guidelines for conducting and reporting glucose monitor evaluation studies. These guidelines included: Standards for Reporting Diagnostic Accuracy (STARD); Clinical and Laboratory Standards Institute (CLSI) C30-A2 and EP9-A2; U.S. Food and Drug Administration (FDA); International Federation of Clinical Chemistry (IFCC); Netherlands Organization for Applied Scientific Research (TNO); U.K. Medicines and Healthcare products Regulatory Agency (MHRA); Scandinavian evaluation of laboratory equipment for primary health care (SKUP); National Standard of the People's Republic of China (China GB/T 19634); and International Standards Organization (ISO 15197).

RESULTS

We constructed a checklist that outlines a standardized approach to glucose monitor evaluations, along with associated references applicable to international standards and consensus recommendations. We expect that the checklist could be used as the basis for a protocol that is (1) evidence-based, (2) scientifically defensible, and (3) sufficiently descriptive to allow for test and result reproducibility.

CONCLUSIONS

We propose a standardized 14-step checklist that facilitates the incorporation of international consensus standards, quality guidelines, and acceptance criteria into the design and reporting of glucose monitor evaluation protocols.

Assessing glycemic control with self-monitoring of blood glucose and hemoglobin A(1c) measurements

Hemoglobin A(1c) (HbA(1c)) is the gold standard for monitoring glycemic control and serves as a surrogate for diabetes-related complications. Although HbA(1c) measures mean glycemic exposure during the preceding 2 to 3 months, it does not provide iInformation about day-to-day changes in glucose levels. Self-monitoring of blood glucose represents an important adjunct to HbA(1c) because it can distinguish among fasting, preprandial, and postprandial hyperglycemia; detect glycemic excursions; identify hypoglycemia; and provide immediate feedback to patients about the effect of food choices, activity, and medication on glycemic control.