Precision and accuracy of a point of care glucometer for detection of hypoglycaemia in horses

Point-of-care (POC) glucometry is commonly used in horses; however, measurement error with this method when analysing hypoglycaemic samples (<4 mmol/L) is unknown. The objective of this study was to determine the precision and accuracy of glucometry in hypoglycaemic horses in comparison to a laboratory method of glucose measurement (LAB). Repeatability coefficients were 0.47 mmol/L for POC and 0.09 mmol/L for LAB, and coefficients of variation were 10 % and 2.11 %, for the POC and LAB methods, respectively. Systemic bias with the POC method was present, with a mean bias of -0.26 mmol/L (95 % limits of agreement: -0.88 - 0.37) in comparison to LAB, and <70% of measurements were within 20 % of paired LAB results. Prior to use of glucometers, assessment of the diagnostic performance of the equipment is necessary, including determination of acceptable criteria and reference ranges for hypoglycaemic samples.

The Importance of Patient and Family Engagement, the Needs for Self-Monitoring of Blood Glucose (SMBG) - Our Perspectives Learned Through a Story of SMBG Assistive Devices Made by a Husband of the Patient with Diabetes

Despite some negative reports regarding the need for the self-monitoring of blood glucose (SMBG), including the issue of cost-effectiveness, there are still many users, and in diabetes treatment, which is largely dependent on the patient's self-care, SMBG remains an important tool in establishing such self-care habits, with several reports supporting this notion. In addition, devices are needed to assist in SMBG for patients with diabetes who have difficulty performing SMBG, such as the elderly or those with visual impairment. In current diabetes care, it is reported that patient-centered care that respects the preferences, needs, and values of individual patients and personalized care that consider the characteristics and comorbidities of each patient are important. Through a case study of a patient with diabetes who had difficulty performing SMBG due to visual impairment, we learned of the needs of SMBG and its assistive devices and the importance of patient and family engagement with emphasis on patient-centered and personalized care. We herein report what we learned through this case in the form of perspectives. Through this report, we hope that medical professionals involved in diabetes care will learn of the importance and needs of these issues and apply them to their actual clinical practice.

Current and emerging concepts in biological and analytical variation applied in clinical practice

A single laboratory result actually represents a range of possible values, and a given laboratory result is impacted not just by the presence or absence of disease, but also by biological variation of the measurand in question and analytical variation of the equipment used to make the measurement. Biological variation refers to variability in measurand concentration or activity around a homeostatic set point. Knowledge of biological and analytical variation can be used to facilitate interpretation of patient clinicopathologic data and is particularly useful for interpreting serial patient data and data at or near reference limits or clinical decision thresholds. Understanding how biological and analytical variation impact laboratory results is of increasing importance, because veterinarians evaluate serial data from individual patients, interpret data from multiple testing sites, and use expert consensus guidelines that include decision thresholds for clinicopathologic data interpretation. The purpose of our report is to review current and emerging concepts in biological and analytical variation and discuss how biological and analytical variation data can be used to facilitate clinicopathologic data interpretation. Inclusion of veterinary clinical pathologists having expertise in laboratory quality management and biological variation on research teams and veterinary practice guideline development teams is recommended, to ensure that various considerations for clinicopathologic data interpretation are addressed.

Analytical performance and user-friendliness of five novel point-of-care D-dimer assays

D-dimer testing combined with a clinical assessment has become a standard pathway for ruling-out venous thromboembolism (VTE). Recently, novel Point-of-Care (POC) D-dimer assays have been introduced, enabling low-volume blood sampling for rapid exclusion of VTE in a one-step procedure. We assessed the analytical validity and user-friendliness of a set of these novel POC D-dimer assays, and compared the results with a standard laboratory assay. Plasma samples were run on our reference assay (STA-Liatest D-di PLUS^®) and five POC assays: Nano-Checker 710^®, AFIAS-1^®; iChroma-II^®; Standard F200^® and Hipro AFS/1^®). After evaluating imprecision, Pearson Product-Moment correlation coefficients were calculated, Passing Bablok regression was performed and Bland-Altman plots were generated. User-friendliness was evaluated using the System Usability Scale (SUS). A set of 238 plasma samples of patients clinically suspected of VTE in general practice was available for analysis. Only one POC D-dimer assay (Nano-Checker 710) demonstrated an insufficient degree of imprecision. Pearson correlation coefficients and mean biases ranged from 0.68 to 0.93 and -165 to -53 μg/L respectively, and concordance with our reference assay varied from 71.8% to 89.5% using a 500 μg/L cut-off point. While we found considerable variation in overall user-friendliness, most devices were judged easy to use. In view of our findings regarding analytical performance and user-friendliness, we consider most of the novel POC D-dimer assays can be used in settings outside of the laboratory such as general practice, combining the possibility of multi-testing with low-volume capillary blood sampling and processing times of less than 15 min.

Diabetes mellitus and laboratory medicine in sub-Saharan Africa: challenges and perspectives

Diabetes mellitus is an increasing public health problem in sub-Saharan Africa with a substantial socioeconomic burden. Although laboratory medicine has been recognized as one of the six key public health functions, there are still gaps in strengthening of laboratory services in developing countries. In the last decades, a lot of progress has been made in the diagnostic field of infectious diseases, whereas the diagnosis of noncommunicable diseases is still insufficient and uneven. This article analyses the challenges encountered in diagnosing and monitoring of diabetes mellitus in sub-Saharan Africa and explores new alternative diagnostic tools.

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.

Accuracy of five systems for self-monitoring of blood glucose in the hands of adult lay-users and professionals applying ISO 15197:2013 accuracy criteria and potential insulin dosing errors

OBJECTIVE

In this study, accuracy in the hands of intended users was evaluated for five self-monitoring of blood glucose (SMBG) systems based on ISO 15197:2013, and possibly related insulin dosing errors were calculated. In addition, accuracy was assessed in the hands of study personnel.

METHODS

For each system (Accu-Chek ¹ Aviva Connect [A], Contour ² Next One [B], FreeStyle Freedom Lite ³ [C], GlucoMen ⁴ areo [D] and OneTouch Verio ⁵ [E]) one test strip lot was evaluated as required by ISO 15197:2013, clause 8. Number and percentage of SMBG measurements within ±15 mg/dl and ±15% of the comparison measurements at glucose concentrations <100 mg/dl and ≥100 mg/dl, respectively, were calculated. In addition, data is presented in surveillance error grids, and insulin dosing errors were modeled. The study was registered at ClinicalTrials.gov (NCT03033849).

RESULTS

Four systems (A, B, C, D) fulfilled the tested reagent system lot ISO 15197:2013 accuracy criteria with the tested reagent system lot with at least 95% (lay-users) and 99.5% (study personnel) of results within the defined limits. Measurements with all five systems were within the clinically acceptable zones of the consensus error grid and the surveillance error grid. Median modeled insulin dosing errors were between -0.8 and +0.6 units for measurements performed by lay-users and between -0.7 and +0.8 units for study personnel. Frequent lay-user errors were not checking the test strips' expiry date, applying blood incorrectly and handling the device incorrectly.

CONCLUSION

In this study, the systems showed slight differences in the number of results within ISO 15197:2013 accuracy limits. Inaccurate SMBG measurements can result in insulin dosing errors and adversely affect glycemic control.

Blood glucose monitoring in type 2 diabetes - Nepalese patients' opinions and experiences

Background: Blood glucose monitoring forms a vital component of diabetes care. Monitoring conducted at home using glucometers, and in laboratories by professionals, are two common methods of blood glucose monitoring in clinical practice.

Objective: To investigate Nepalese patients’ perceptions and practices of blood glucose monitoring in diabetes.

Methods: In-depth interviews were conducted with 48 Nepalese participants with type 2 diabetes in Sydney and Kathmandu. The interviews were audio-recorded, transcribed verbatim and thematically analysed.

Results: In Australia, most participants perceived home monitoring as useful; and both home and laboratory monitoring were conducted at fairly regular intervals. In Nepal, only a small number conducted home monitoring and the laboratory method formed the primary method of day-to-day monitoring. The laboratory method was preferred due to easy access to laboratories, lack of faith in glucometers and perceptions that home monitoring is costlier. However, overall monitoring was irregular in Nepal. In addition to the healthcare system which enabled cheaper self-monitoring in Australia, Nepalese in Australia also tended to have a better understanding about the purpose of home monitoring.

Conclusions: This study has highlighted the disparity in perceptions and practices related to blood glucose monitoring. Understanding the importance of blood glucose monitoring and access to affordable resources are critical facilitators for conducting regular monitoring. Both patient and health-system factors play a key role in ensuring continued diabetes monitoring and management.

User Performance Evaluation of Four Blood Glucose Monitoring Systems Applying ISO 15197:2013 Accuracy Criteria and Calculation of Insulin Dosing Errors

INTRODUCTION

The international standard ISO 15197:2013 requires a user performance evaluation to assess if intended users are able to obtain accurate blood glucose measurement results with a self-monitoring of blood glucose (SMBG) system. In this study, user performance was evaluated for four SMBG systems on the basis of ISO 15197:2013, and possibly related insulin dosing errors were calculated. Additionally, accuracy was assessed in the hands of study personnel.

METHODS

Accu-Chek® Performa Connect (A), Contour® plus ONE (B), FreeStyle Optium Neo (C), and OneTouch Select® Plus (D) were evaluated with one test strip lot. After familiarization with the systems, subjects collected a capillary blood sample and performed an SMBG measurement. Study personnel observed the subjects' measurement technique. Then, study personnel performed SMBG measurements and comparison measurements. Number and percentage of SMBG measurements within ± 15 mg/dl and ± 15% of the comparison measurements at glucose concentrations < 100 and ≥ 100 mg/dl, respectively, were calculated. In addition, insulin dosing errors were modelled.

RESULTS

In the hands of lay-users three systems fulfilled ISO 15197:2013 accuracy criteria with the investigated test strip lot showing 96% (A), 100% (B), and 98% (C) of results within the defined limits. All systems fulfilled minimum accuracy criteria in the hands of study personnel [99% (A), 100% (B), 99.5% (C), 96% (D)]. Measurements with all four systems were within zones of the consensus error grid and surveillance error grid associated with no or minimal risk. Regarding calculated insulin dosing errors, all 99% ranges were between dosing errors of - 2.7 and + 1.4 units for measurements in the hands of lay-users and between - 2.5 and + 1.4 units for study personnel. Frequent lay-user errors were not checking the test strips' expiry date and applying blood incorrectly.

CONCLUSIONS

Data obtained in this study show that not all available SMBG systems complied with ISO 15197:2013 accuracy criteria when measurements were performed by lay-users.

TRIAL REGISTRATION

The study was registered at ClinicalTrials.gov (NCT02916576).

FUNDING

Ascensia Diabetes Care Deutschland GmbH.

System Accuracy and User Performance Evaluation of an Improved System for Self-Monitoring of Blood Glucose

An improved test cassette for the integrated Accu-Chek® Mobile system (Roche Diabetes Care GmbH, Mannheim, Germany) has been developed. System accuracy of this improved system was evaluated based on ISO 15197:2013, clause 6.3, for three reagent system lots. According to this standard, at least 95% of the system's measurement results shall be within ±15 mg/dL and ±15% of the results of the comparison method at glucose concentrations <100 mg/dL and ≥100 mg/dL (accuracy criterion A), respectively, and at least 99% of results shall be within consensus error grid zones A and B (accuracy criterion B). In addition, accuracy was evaluated in the hands of users based on ISO 15197:2013, clause 8, with one reagent system lot.

Performance of strip-based glucose meters and cassette-based blood gas analyzer for monitoring glucose levels in a surgical intensive care setting

BACKGROUND

We verified the analytical performance of strip-based handheld glucose meters (GM) for prescription use, in a comparative split-sample protocol using blood gas samples from a surgical intensive care unit (ICU).

METHODS

Freestyle Precision Pro (Abbott), StatStrip Connectivity Meter (Nova), ACCU-CHEK Inform II (Roche) were evaluated for recovery/linearity, imprecision/repeatability. The GMs and the ABL90 (Radiometer) blood gas analyzer (BGA) were tested for relative accuracy vs. the comparator hexokinase glucose-6-phosphate-dehydrogenase (HK/G6PDH) assay on a Cobas c702 analyzer (Roche).

RESULTS

Recovery of spiked glucose was linear up to 19.3 mmol/L (347 mg/dL) with a slope of 0.91-0.94 for all GMs. Repeatability estimated by pooling duplicate measurements on samples below (n=9), in (n=51) or above (n=80) the 4.2-5.9 mM (74-106 mg/dL) range were for Freestyle Precision Pro: 4.2%, 4.0%, 3.6%; StatStrip Connectivity Meter: 4.0%, 4.3%, 4.5%; and ACCU-CHEK Inform II: 1.4%, 2.5%, 3.5%. GMs were in agreement with the comparator method. The BGA outperformed the GMs, with a MARD of 3.9% compared to 6.5%, 5.8% and 4.4% for the FreeStyle, StatStrip and ACCU-CHEK, respectively. Zero % of the BGA results deviated more than the FDA 10% criterion as compared to 9.4%, 3.7% and 2.2% for the FreeStyle, StatStrip and ACCU-CHEK, respectively. For all GMs, icodextrin did not interfere. Variation in the putative influence factors hematocrit and O2 tension could not explain observed differences with the comparator method.

CONCLUSIONS

GMs quantified blood glucose in whole blood at about the 10% total error criterion, proposed by the FDA for prescription use.

Self-monitoring Blood Glucose (SMBG): Now and the Future

In 2002, the cost of diabetes in the United States reached $132 billion. There is a well-established relationship between blood glucose control and the risk of diabetes-related complications. Tight blood glucose control, through intensive diabetes therapy, reduces the risk and delays the onset of diabetesrelated microvascular complications. Regular and consistent self-monitoring of blood glucose (SMBG) is and should be a part of all diabetes disease state management programs. Pharmacists can truly increase the numbers of patients who use SMBG by being aware and familiar with the monitoring devices available to patients and identifying the physical and psychological issues surrounding SMBG. Results from SMBG and hemoglobin A1C are the basis formost of the medical decisions made for patients with diabetes. This review discusses the best time for patients to test their blood glucose, information regarding blood glucose monitoring devices, alternative site testing, and the newest technology available in glucose monitoring.

Clinical relevance of the discrepancy in phenylalanine concentrations analyzed using tandem mass spectrometry compared with ion-exchange chromatography in phenylketonuria

Introduction

Metabolic control of phenylketonuria (PKU) and compliance with the low-phenylalanine (phe) diet are frequently assessed by measuring blood phe concentrations in dried blood spots (DBS) collected by patients instead of plasma phe concentrations.

Objective

Our objective was to investigate the difference in blood phe concentrations in DBS collected by subjects and analyzed using either a validated newborn screening tandem mass spectrometry (MS/MS) protocol or ion-exchange chromatography (IEC) compared to plasma phe concentrations obtained simultaneously and analyzed using IEC.

Design

Three to four fasting blood samples were obtained from 29 subjects with PKU, ages 15–49 years. Capillary blood was spotted on filter paper by each subject and the DBS analyzed using both MS/MS and IEC. Plasma was isolated from venous blood and analyzed using IEC.

Results

Blood phe concentrations in DBS analyzed using MS/MS are 28% ± 1% (n = 110, p < 0.0001) lower than plasma phe concentrations analyzed using IEC resulting in a blood phe concentration of 514 ± 23 μmol/L and a plasma phe concentration of 731 ± 32 μmol/L (mean ± SEM). This discrepancy is larger when plasma phe is > 600 μmol/L. Due to the large variability across subjects of 13.2%, a calibration factor to adjust blood phe concentrations is not recommended. Analysis of DBS using IEC reduced the discrepancy to 15 ± 2% lower phe concentrations compared to plasma analyzed using IEC (n = 38, p = 0.0001). This suggests that a major contributor to the discrepancy in phe concentrations is the analytical method.

Conclusion

Use of DBS analyzed using MS/MS to monitor blood phe concentrations in individuals with PKU yields significantly lower phe levels compared to plasma phe levels analyzed using IEC. Optimization of current testing methodologies for measuring phe in DBS, along with patient education regarding the appropriate technique for spotting blood on filter paper is needed to improve the accuracy of using DBS to measure phe concentrations in PKU management.

•

Phe concentration in dried blood spots is significantly lower than plasma phe.

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Blood phe concentration cannot be adjusted due to large variability across subjects.

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Analysis of dried blood spots using IEC instead of MS/MS improves accuracy.

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Plasma phe concentration using IEC is the most accurate for metabolic monitoring in PKU.

Clinical evaluation of a novel on-strip calibration method for blood glucose measurement

This study evaluated a novel technology for improving accuracy of self-monitoring of blood glucose (SMBG). The technology calibrates each and every test by measuring the response from a predetermined amount of glucose present in the sample chamber of each test strip. SMBG test strips were modified to include a lid coated with a fast dissolving formulation containing glucose. These test strips were characterized for hematocrit (Hct) and temperature induced error response to develop a calibration algorithm. The modified test strips were used in a clinical evaluation involving fingerstick blood samples from 160 subjects. Experiments involving Hct and temperature induced errors show that the technology generates a signal characteristic of the error conditions in any particular test, but independent of glucose concentration, allowing a correction algorithm to be derived. The approach substantially reduced Hct and temperature derived errors. Clinical evaluation using fingerstick blood directly applied to prototype strips showed the error (measured as MARD) was reduced from 11.1 to 5.9% by the on-strip correction approach and the number of outliers reduced by approximately 90%. This technology could improve the accuracy and precision of glucose monitoring systems and so reduce decision errors particularly in clinical situations where hematocrit and temperature may be significant confounders.

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.

System accuracy of blood glucose monitoring systems: impact of use by patients and ambient conditions

For self-monitoring of blood glucose by people with diabetes, the reliability of the measured blood glucose values is a prerequisite in order to ensure correct therapeutic decisions. Requirements for system accuracy are defined by the International Organization for Standardization (ISO) in the standard EN ISO 15197:2003. However, even a system with high analytical quality is not a guarantee for accurate and reliable measurement results. Under routine life conditions, blood glucose measurement results are affected by several factors. First, the act of performing measurements as well as the handling of the system may entail numerous possible error sources, such as traces of glucose-containing products on the fingertips, the use of deteriorated test strips, or the incorrect storage of test strips. Second, ambient and sampling conditions such as high altitude, partial pressure of oxygen, ambient temperature, and the use of alternate test sites can have an influence on measurement results. Therefore, the user-friendliness of a system and the quality of the manufacturer's labeling to reduce the risk of handling errors are also important aspects in ensuring reliable and accurate measurement results. In addition, the analytical performance of systems should be less prone to user errors and ambient conditions. Finally, people with diabetes must be aware of the information and instructions in the manufacturer's labeling and must be able to measure and interpret blood glucose results correctly.

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.

Lot-to-lot variability of test strips and accuracy assessment of systems for self-monitoring of blood glucose according to ISO 15197

BACKGROUND

Accurate and reliable blood glucose (BG) measurements require that different test strip lots of the same BG monitoring system provide comparable measurement results. Only a small number of studies addressing this question have been published.

METHODS

In this study, four test strip lots for each of five different BG systems [Accu-Chek® Aviva (system A), FreeStyle Lite® (system B), GlucoCheck XL (system C), Pura™/mylife™ Pura (system D), and OneTouch® Verio™ Pro (system E)] were evaluated with procedures according to DIN EN ISO 15197:2003. The BG system measurement results were compared with the manufacturer's measurement procedure (glucose oxidase or hexokinase method). Relative bias according to Bland and Altman and system accuracy according to ISO 15197 were analyzed. A BG system consists of the BG meter itself and the test strips.

RESULTS

The maximum lot-to-lot difference between any two of the four evaluated test strip lots per BG system was 1.0% for system E, 2.1% for system A, 3.1% for system C, 6.9% for system B, and 13.0% for system D. Only two systems (systems A and B) fulfill the criteria of DIN EN ISO 15197:2003 with each test strip lot.

CONCLUSIONS

Considerable lot-to-lot variability between test strip lots of the same BG system was found. These variations add to other sources of inaccuracy with the specific BG system. Manufacturers should regularly and effectively check the accuracy of their BG meters and test strips even between different test strip lots to minimize risk of false treatment decisions.

The Accu-Chek Mobile blood glucose monitoring system used under controlled conditions meets ISO 15197 standards in the hands of diabetes patients

BACKGROUND

Self-monitoring of blood glucose is a cornerstone of diabetes management. The aim of this study was to evaluate the analytical quality and the ease of use of the Accu-Chek Mobile, a new glucose monitoring system designed for capillary blood testing by diabetic patients.

MATERIALS AND METHODS

The performance of the Accu-Chek Mobile was evaluated both in the hands of a scientist and of diabetes patients. The designated comparative method was a hexokinase-based laboratory method (Architect ci8200). Diabetics (N = 88) with previous experience of self-testing were recruited for the study. Patient samples, containing glucose in concentrations mainly between ˜4 and ˜20 mmol/L, were analyzed in duplicates both on the Accu-Chek Mobile and with the comparative method. The patients answered a questionnaire about the ease of use of the meter.

RESULTS

The meter yields reproducible readings, with an imprecision CV <5% as required by the American Diabetes Association (ADA). Of the glucose concentrations obtained by both the scientist and the patients, more than 95% of the individual results were within ± 20% of the comparative method, meeting the ISO 15197 accuracy goal, but not the stricter ± 10% ADA goal.

CONCLUSION

Accu-Chek Mobile is a user-friendly glucometer that in a normo- and hyperglycemic range fulfils the ISO 15197 accuracy requirement, also in the hands of diabetes patients.

Integrated self-monitoring of blood glucose system: handling step analysis

Self-monitoring of blood glucose (SMBG) implicates a number of handling steps with the meter and the lancing device. Numerous user errors can occur during SMBG, and each step adds to the complexity of use. This report compares the required steps to perform SMBG of one fully integrated (the second generation of the Accu-Chek® Mobile), three partly integrated (Accu-Chek Compact Plus, Ascensia® Breeze®2, and Accu-Chek Aviva), and six conventional (Bayer Contour®, Bayer Contour USB, BGStar™, FreeStyle Lite®, OneTouch® Ultra® 2, and OneTouch Verio™Pro) systems. The results show that the fully integrated system reduces the number of steps to perform SMBG. The mean decrease is approximately 70% compared with the other systems. We assume that a reduction of handling steps also reduces the risk of potential user errors and improves the user-friendliness of the system.

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.

Precision, accuracy, and user acceptance of the OneTouch SelectSimple blood glucose monitoring system

BACKGROUND

The OneTouch® SelectSimple™ blood glucose monitoring system (BGMS) is a device for self-monitoring of blood glucose designed for ease of use. Alarms alert subjects to low [20-69 mg/dl (1.1-3.8 mmol/liter)], high [180-239 mg/dl (9.9-13.2 mmol/liter)], and very high [240-600 mg/dl (13.3-33.1 mmol/liter)] blood glucose readings.

METHODS

Repeatability in blood and intermediate precision with aqueous controls were examined using blood from one donor adjusted to different glucose concentrations, and tested with 10 meters and 1 test-strip lot. System accuracy was evaluated with blood samples from 100 diabetes patients tested on 3 test-strip lots, compared with a reference system (YSI 2300 STAT). To test user accuracy, patients (n = 156) and health care professionals (HCPs) tested subject blood with the SelectSimple twice. Health care professionals evaluated subject BGMS technique after a 3-5 day home-testing period. Users evaluated the instructions for use and responded to a user acceptance questionnaire.

RESULTS

In repeatability and intermediate precision testing, the SelectSimple BGMS had a coefficient of variation of ≤ 5% or standard deviation of ≤ 5 mg/dl. In the clinical accuracy study, 100% of measurements <75 mg/dl (4.2 mmol/liter) were within ± 15 mg/dl (0.8 mmol/liter) of reference value, and 99.6% of measurements ≥ 75 mg/dl (4.2 mmol/liter) were within ±20%. Patients were able to use the BGMS appropriately and evaluated it as easy to use. Acceptance of the SelectSimple BGMS was within predefined limits.

CONCLUSIONS

In these studies, the SelectSimple BGMS met all criteria for precision, system, and user accuracy, was easy to use, and was well accepted by patients.

Analysis of the performance of the OneTouch SelectSimple blood glucose monitoring system: why ease of use studies need to be part of accuracy studies

The article entitled "Precision, Accuracy, and User Acceptance of the OneTouch SelectSimple Blood Glucose Monitoring System" by Philis-Tsimikas and colleagues in this issue of Journal of Diabetes Science and Technology demonstrates that the OneTouch® SelectSimple™ glucose meter meets current regulatory expectations for glucose meter performance. These authors describe three studies: precision, accuracy, and ease of use. Accuracy study analysis includes the effects of accuracy and precision. The ease-of-use study was analyzed separately, as recommended by the International Organization for Standardization 15197 glucose standard. The ultimate goal of an evaluation is to estimate the distribution of errors (from any source) that will be experienced in routine use. To accomplish this, ease-of-use results need to be part of the accuracy dataset.

Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus

BACKGROUND

Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association.

CONTENT

In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (HbA(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed.

SUMMARY

The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus

BACKGROUND

Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association.

CONTENT

In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed.

SUMMARY

The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

Wavesense technology glucometer Linus for routine self-monitoring and clinical practice

Conventional glucometer systems for plasma/blood glucose monitoring are based on colorimetry or static electrochemistry using a fixed input signal. The recent glucometer Linus, Wellion, Agamatrix, USA, based on wavesense dynamic electrochemistry, uses a time-varying input signal to give a more accurate glucose reading. The purpose of this study was to compare the plasma glucose (PG) readings obtained by nursing staff from glucometer Linus and PG values estimated on an approved analyzer Daytona™, Randox, Global Medical Instrumentation, Inc., MN, USA. In the course of 5 weeks, 221 fingerprick capillary blood samples were taken from persons with diabetes at different times and investigated using glucometer Linus. Within two following minutes, blood from the same fingerprick was also collected in a tube and centrifuged; the plasma was analyzed on the Daytona™ analyzer. Statistical analysis was performed using the software SPSS v. 15.0, SPSS Inc., Chicago, IL, USA. A total of 221 paired PG values were plotted on the error grid diagram indicating that 218 values (98.6%) of the glucose readings (Linus vs. Daytona) were within the clinically accurate zone A (maximum difference ±20%) and 3 values (1.4%) within the acceptable zone B. Daytona showed 4 PG values <4.2 mmol/l (75 mg/dl) and their difference of respective Linus readings was always <0.83 mmol/l (15 mg/dl). Correlation of results was strong (r = 0.992). Glucometer Linus readings correspond to the ISO and FDA standards. So, Linus appears to be an accurate device for PG-self-monitoring and clinical practice.

Estimating plasma glucose from interstitial glucose: the issue of calibration algorithms in commercial continuous glucose monitoring devices

Evaluation of metabolic control of diabetic people has been classically performed measuring glucose concentrations in blood samples. Due to the potential improvement it offers in diabetes care, continuous glucose monitoring (CGM) in the subcutaneous tissue is gaining popularity among both patients and physicians. However, devices for CGM measure glucose concentration in compartments other than blood, usually the interstitial space. This means that CGM need calibration against blood glucose values, and the accuracy of the estimation of blood glucose will also depend on the calibration algorithm. The complexity of the relationship between glucose dynamics in blood and the interstitial space, contrasts with the simplistic approach of calibration algorithms currently implemented in commercial CGM devices, translating in suboptimal accuracy. The present review will analyze the issue of calibration algorithms for CGM, focusing exclusively on the commercially available glucose sensors.

SKML-Quality Mark for point-of-care test (POCT) glucose meters and glucose meters for home-use

BACKGROUND

Point-of-care glucose meters are used increasingly in semi- and non-professional context. The quality of glucose measurements depends on the quality of the equipment, the quality of use, and the pre-analytical conditions. In this article, a External Quality Assessment Scheme (SKML)-Quality Mark for point-of-care test (POCT) and self-test glucose meters is proposed, assessing analytical quality and technical quality. The analytical requirements are based on the biological variation concept, and a system to assess meters for the SKML-Quality Mark is described. Using the proposed system as an example, 14 meters were tested.

METHODS

The analytical quality of the POCT and self-test equipment was assessed for plasma calibrated glucose values by comparison with a trueness verified method traceable to the IFCC reference method in an accredited clinical laboratory. The concept is based on the biological variation system. The SKML-Quality Mark comprises the following criteria for blood glucose equipment: 1) Fulfilment of compliance with ISO 15197 and/or TNO guideline criterion; 2) Fulfilment of the total allowable error (TAE) criterion; 3) Fulfilment of the total allowable linearity bias criterion; 4) Fulfilment of the total allowable interfering substances bias criterion; and 5) Fulfilment of the haematocrit criterion.

RESULTS

The proposed SKML-Quality Mark system was tested on 14 commercial home-use meters. The TAE criterion is violated by two meters. The main reason for the violation is bias. For the majority of meters, the Passing and Bablok regression confidence interval does not include the intercept of 0.0 and slope of 1.0. In addition, Syx indicates dispersion around the line or non-linearity. The bias and total error at three different concentrations were investigated as part of the quality mark, resulting in disapproval of the Dicomed Sensocard Plus meter. The bias was significant for the Wellion Linus. With respect to interfering substances, bias of the same magnitude and sign as the bias without additive was seen for all meters for acetaminophen, indicating no additional interference. For ascorbic acid, an additional bias was seen for several meters. However, significant bias was demonstrated for the Sensocard Plus and Glucocard X-meter.

CONCLUSIONS

The biological variation concept offers a scientific basis for assessment of acceptable deviation. The concept is extended in the SKML-Quality Mark correcting for the limited number of measurements that can be performed while assessing home-use or POCT meters. The results show that three out of 14 meters fail the proposed quality mark.

Diagnostic Accuracy and User-Friendliness of 5 Point-of-Care D-Dimer Tests for the Exclusion of Deep Vein Thrombosis

BACKGROUND

Point-of-care D-dimer tests have recently been introduced to enable rapid exclusion of deep venous thrombosis (DVT) without the need to refer a patient for conventional laboratory-based D-dimer testing. Before implementation in practice, however, the diagnostic accuracy of each test should be validated.

METHODS

We analyzed data of 577 prospectively identified consecutive primary care patients suspected to have DVT, who underwent 5 point-of-care D-dimer tests—4 quantitative (Vidas®, Pathfast™, Cardiac®, and Triage®) and 1 qualitative (Clearview Simplify®)—and ultrasonography as the reference method. We evaluated the tests for the accuracy of their measurements and submitted a questionnaire to 20 users to assess the user-friendliness of each test.

RESULTS

All D-dimer tests showed negative predictive values higher than 98%. Sensitivity was high for all point-of-care tests, with a range of 0.91 (Clearview Simplify) to 0.99 (Vidas). Specificity varied between 0.39 (Pathfast) and 0.64 (Clearview Simplify). The quantitative point-of-care tests showed similar and high discriminative power for DVT, according to calculated areas under the ROC curves (range 0.88–0.89). The quantitative Vidas and Pathfast devices showed limited user-friendliness for primary care, owing to a laborious calibration process and long analyzer warm-up time compared to the Cardiac and Triage. For the qualitative Clearview Simplify assay, no analyzer or calibration was needed, but interpretation of a test result was sometimes difficult because of poor color contrast.

CONCLUSIONS

Point-of-care D-dimer assays show good and similar diagnostic accuracy. The quantitative Cardiac and Triage and the qualitative Clearview Simplify D-dimer seem most user-friendly for excluding DVT in the doctor's office.

Importance of the pre-analytical phase in blood glucose analysis

Blood glucose levels are characterized by a relatively large intra-individual biological variability due to food intake, physical activity and the body's homeostatic response. Careful attention to the pre-analytical phase is essential to ensure accurate glucose measurements. Blood samples should be drawn in the morning after an overnight fast. Proper sample processing after blood collection is crucial. When fast separation of the cells is not possible, blood should be collected into a tube containing a glucose preservative. Glucose concentrations may also differ according to the blood sampling site (venous, arterial or capillary blood). Plasma and whole blood glucose values are not interchangeable. The International Federation of Clinical Chemistry and Laboratory Medicine recommends reporting the glucose concentration in plasma to avoid clinical misinterpretations irrespective of the sample type and method of measurement. Point-of-care testing (POCT) glucose meters are widely used by both health professionals and diabetic patients to monitor blood glucose levels. However, one should take into account that the reliability of POCT glucose measurements depends upon a variety of factors including underlying disease, patient drug regimens and interfering substances as well as instrument analytical performance and user proficiency. It is recommended to perform a laboratory blood glucose analysis if the POCT glucose value is in the critical hypoglycaemic or hyperglycaemic range.

Review article: glucose measurement in the operating room: more complicated than it seems

Abnormalities of blood glucose are common in patients undergoing surgery, and in recent years there has been considerable interest in tight control of glucose in the perioperative period. Implementation of any regime of close glycemic control requires more frequent measurement of blood glucose, a function for which small, inexpensive, and rapidly responding point-of-care devices might seem highly suitable. However, what is not well understood by many anesthesiologists and other staff caring for patients in the perioperative period is the lack of accuracy of home glucose meters that were designed for self-monitoring of blood glucose by patients. These devices have been remarketed to hospitals without appropriate additional testing and without an appropriate regulatory framework. Clinicians who are accustomed to the high level of accuracy of glucose measurement by a central laboratory device or by an automated blood gas analyzer may be unaware of the potential for harmful clinical errors that are caused by the inaccuracy exhibited by many self-monitoring of blood glucose devices, especially in the hypoglycemic range. Knowledge of the limitations of these meters is essential for the perioperative physician to minimize the possibility of a harmful measurement error. In this article, we will highlight these areas of interest and review the indications, technology, accuracy, and regulation of glucose measurement devices used in the perioperative setting.

A review of standards and statistics used to describe blood glucose monitor performance

Glucose performance is reviewed in the context of total error, which includes error from all sources, not just analytical. Many standards require less than 100% of results to be within specific tolerance limits. Analytical error represents the difference between tested glucose and reference method glucose. Medical errors include analytical errors whose magnitude is great enough to likely result in patient harm. The 95% requirements of International Organization for Standardization 15197 and others make little sense, as up to 5% of results can be medically unacceptable. The current American Diabetes Association standard lacks a specification for user error. Error grids can meaningfully specify allowable glucose error. Infrequently, glucose meters do not provide a glucose result; such an occurrence can be devastating when associated with a life-threatening event. Nonreporting failures are ignored by standards. Estimates of analytical error can be classified into the four following categories: imprecision, random patient interferences, protocol-independent bias, and protocol-dependent bias. Methods to estimate total error are parametric, nonparametric, modeling, or direct. The Westgard method underestimates total error by failing to account for random patient interferences. Lawton's method is a more complete model. Bland-Altman, mountain plots, and error grids are direct methods and are easier to use as they do not require modeling. Three types of protocols can be used to estimate glucose errors: method comparison, special studies and risk management, and monitoring performance of meters in the field. Current standards for glucose meter performance are inadequate. The level of performance required in regulatory standards should be based on clinical needs but can only deal with currently achievable performance. Clinical standards state what is needed, whether it can be achieved or not. Rational regulatory decisions about glucose monitors should be based on robust statistical analyses of performance.

Challenges to glycemic measurement in the perioperative and critically ill patient: a review

Accurate monitoring of glucose in the perioperative environment has become increasingly important over the last few years. Because of increased cost, turnaround time, and sample volume, the use of central laboratory devices for glucose measurement has been somewhat supplanted by point-of-care (POC) glucose devices. The trade-off in moving to these POC systems has been a reduction in accuracy, especially in the hypoglycemic range. Furthermore, many of these POC devices were originally developed, marketed, and received Food and Drug Administration regulatory clearance as home use devices for patients with diabetes. Without further review, many of these POC glucose measurement devices have found their way into the hospital environment and are used frequently for measurement during intense insulin therapy, where accurate measurements are critical. This review covers the technology behind glucose measurement and the evidence questioning the use of many POC devices for perioperative glucose management.

Clinical performance of the TRUE2go blood glucose system--a novel integrated system for meter and strips

BACKGROUND

The complications of diabetes may be minimized by adequate glycemic control, which is aided by self-monitoring of blood glucose (SMBG) levels. A new SMBG system, TRUE2go (Home Diagnostics, Inc., Fort Lauderdale, FL), does not require calibration of test strips, thereby eliminating the potential source of error in blood glucose determination associated with mis-calibration. This study tested the performance of the TRUE2go system. The very small size and attachment of the meter to a vial of test strips make the TRUE2go system unique.

METHODS

The studies were carried out with adult patients with type 1 or 2 diabetes, using procedures for testing accuracy as specified in International Organization for Standardization (ISO) 15197:2003. The evaluation included patients' compliance with the TRUE2go system's written instructions, ease of understanding the supplied instructions, and ease of use of the system.

RESULTS

The study demonstrated the accuracy and precision of the TRUE2go system, with 100% of glucose test results falling within ISO-recommended limits for glucose concentrations ranging from 24 mg/dL to 549 mg/dL. There was agreement between data obtained with TRUE2go when used by healthcare professionals and by lay users on capillary blood from both fingertip and a forearm sticks. Lay users' understanding of and compliance with TRUE2go system instructions were excellent, as was their satisfaction with the system.

CONCLUSIONS

The TRUE2go system is accurate and convenient to use, and its instructions are easily understood by lay users. TRUE2go features that contribute to convenience, and therefore could improve compliance with monitoring regimens, include its small size, attachment to the vial of strips, easy-to-read display, automatic calibration for test strips, and suitability for fingertip as well as forearm testing.

Quality specifications for seminal parameters based on clinicians' opinions

BACKGROUND

The aim of this study was to identify analytical quality specifications for seminal parameters based on clinicians' opinions, and to compare with those based on biological variability and state of the art.

MATERIAL AND METHODS

Two questionnaires with case histories were sent to laboratories participating in the Spanish programme of external quality on semen analysis for distribution to as many specialist clinicians as possible. Our intention was to determine the critical difference (CD), defined as the difference needed between two consecutive results obtained from semen analysis to be 95 % confident that the two results actually are different. Subsequently, we calculated the specifications of analytical quality in accordance with the clinicians' opinions.

RESULTS

The CDs obtained from the median value of the differences between the initial value and that given in the clinicians' replies were similar in clinical situations of improvement or worsening in the infertile normozoospermic male, and also in worsening situations for male patients presenting a significant alteration in seminal parameters. For improvement in this latter case, the CD cited as necessary in the clinicians' opinion was much higher than that for the other clinical situations. At a desirable level of quality, for concentration and total motility the coefficients of variation in the clinicians' opinion were below those based on biological variability and the state of the art. However, for type "a+b" motility, type "a" motility, morphology and vitality the coefficients of variation based on the clinicians' opinions were higher than those based on biological variability and lower than those based on the state of the art.

CONCLUSIONS

Quality specifications for seminal parameters based on clinicians' opinions depend to a large extent on the clinical situation and on the seminal parameter being analysed.

Sources of glycemic variability--what type of technology is needed?

People on insulin therapy are challenged with evaluation of numerous factors affecting the blood glucose in order to select the optimal dose for reaching their glucose target. Following medical recommendations precisely still results in considerable blood glucose unpredictability, often resulting in frustration in the short term due to hypoglycemia and hyperglycemia, and, in the long term, will likely result in complications. The kinetics of insulin do indeed vary significantly and have become an important focus when developing new insulin analogues and delivery systems; however, numerous of other factors impact glycemic variability. These have different dependences and interactions and are therefore difficult to characterize. Some of the factors are highly dependent and influenced by the type of insulin and devices used in therapy. Development of future therapy products is therefore highly focused on how to minimize glycemic variability.

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.

Does POCT reduce the risk of error in laboratory testing?

Point-of-care testing (POCT), the fastest growing segment of the current clinical laboratory testing market, is a rapid means for providing test results in different clinical settings. In theory, this tool eliminates some of the more problematic steps in the testing process, including specimen transport and result distribution. However, POCT has created new challenges, and sources of potential errors; moreover, while the upsurge in its use has generated concerns regarding the quality of test results, few data are available in the literature on errors with POCT. Nor are data available for the evaluation of errors, and the risk of errors in POCT based on all steps in the entire testing process, including test requesting and result utilization. According to a modified Kost model, which takes into account all steps of the testing process and latent conditions for error, POCT reduces errors and the risk of error in only a few steps of the testing process. There is therefore an urgent need for an evaluation of errors and risks of error in POCT that is based on the entire testing process and uses well-designed studies aiming to improve clinical outcomes and increase patient safety.

Standardized evaluation of nine instruments for self-monitoring of blood glucose

BACKGROUND

Instruments for self-monitoring of blood glucose (SMBG) should undergo a standardized evaluation including a user-test before being marketed. In this study the results from standardized evaluations of nine different SMBG instruments are presented, and the standardized evaluation is discussed.

METHODS

Approximately 80 diabetes patients using three lots of test strips participated in each evaluation. Half of the patients were educated in how to use the meter, and the evaluations were carried out by both medical laboratory technologists (MLTs) and patients. Questionnaires were used to assess the user manual and the user-friendliness of the instrument.

RESULTS

The imprecision obtained by the patients (coefficients of variation [CVs] of 3.2-8.1%) were generally higher compared to that by the MLT (CVs of 2.3-5.9%). Three of the nine instruments did not achieve the quality goal based on the recommendation in the International Organization for Standardization's ISO 15197 guideline in the hands of diabetes patients. The bias from the comparison method ranged from -10.4% to +3.2%. There were significant lot-to-lot variations and hematocrit effects for some of the instruments. Temperature difference between the instruments and the test strip caused deterioration of the quality in one instrument. The user-friendliness was in general acceptable.

CONCLUSIONS

The quality of instruments for SMBG seems to have improved during recent years, although there are still analytical problems. A standardized evaluation protocol is necessary and should be regularly revised taking into account the development of new technology and the needs of the patients.