Performance of Afinion HbA1c measurements in general practice as judged by external quality assurance data.

Background It has been debated whether point-of care (POC) glycated hemoglobin (HbA1c) measurements methods can be used for diagnosing persons with diabetes mellitus. The aim of this study was to evaluate the analytical performance of the POC Afinion HbA1c system in the hands of the users, and to investigate which predictors that were associated with good participant performance. Methods External quality assurance (EQA) data from seven surveys in 2017-2018 with a total of 5809 Afinion participants from a POC total quality system in Norway were included in this study (response rate 90%). The control materials were freshly drawn pooled EDTA whole blood. Each participant was evaluated against the analytical performance specification of ±6% from the target value, while the Afinion system was evaluated against the pooled within-laboratory CV <2%, the between-laboratory CV <3.5%, and bias <0.3%HbA1c. Logistic regression analyses were used to investigate which factors were associated with good participant performance. Results The participant pass rates for each survey varied from 98.2% to 99.7%. The pooled within-laboratory CV varied from 1.3% to 1.5%, the between-laboratory CV varied from 1.5% to 2.1%, and bias varied between -0.17 and -0.01 %HbA1c in all surveys. Reagent lot was the only independent factor to predict good participant performance. Conclusions Afinion HbA1c fulfilled the analytical performance specifications and is robust in the hands of the users. It can therefore be used both in diagnosing and monitoring persons with diabetes mellitus, given that the instrument is monitored by an EQA system.

The Importance of Reagent Lot Registration in External Quality Assurance/Proficiency Testing Schemes.

BACKGROUND: Providers of external quality assurance (EQA)/proficiency testing schemes have traditionally focused on evaluation of measurement procedures and participant performance and little attention has been given to reagent lot variation. The aim of the present study was to show the importance of reagent lot registration and evaluation in EQA schemes. METHODS: Results from the Noklus (Norwegian Quality Improvement of Primary Care Laboratories) urine albumin/creatinine ratio (ACR) and prothrombin time international normalized ratio (INR) point-of-care EQA schemes from 2009-2015 were used as examples in this study. RESULTS: The between-participant CV for Afinion ACR increased from 6%-7% to 11% in 3 consecutive surveys. This increase was caused by differences between albumin reagent lots that were also observed when fresh urine samples were used. For the INR scheme, the CoaguChek INR results increased with the production date of the reagent lots, with reagent lot medians increasing from 2.0 to 2.5 INR and from 2.7 to 3.3 INR (from the oldest to the newest reagent lot) for 2 control levels, respectively. These differences in lot medians were not observed when native patient samples were used. CONCLUSIONS: Presenting results from different reagent lots in EQA feedback reports can give helpful information to the participants that may explain their deviant EQA results. Information regarding whether the reagent lot differences found in the schemes can affect patient samples is important and should be communicated to the participants as well as to the manufacturers. EQA providers should consider registering and evaluating results from reagent lots.

Point-of-care urine albumin in general practice offices: effect of participation in an external quality assurance scheme.

BACKGROUND: The Norwegian Quality Improvement of Primary Care Laboratories (Noklus) offers external quality assurance (EQA) schemes (EQASs) for urine albumin (UA) annually. This study analyzed the EQA results to determine how the analytical quality of UA analysis in general practice (GP) offices developed between 1998 (n=473) and 2012 (n=1160). METHODS: Two EQA urine samples were distributed yearly to the participants by mail. The participants measured the UA of each sample and returned the results together with information about their instrument, the profession and number of employees at the office, frequency of internal quality control (IQC), and number of analyses per month. In the feedback report, they received an assessment of their analytical performance. RESULTS: The number of years that the GP office had participated in Noklus was inversely related to the percentage of "poor" results for quantitative but not semiquantitative instruments. The analytical quality improved for participants using quantitative instruments who received an initial assessment of "poor" and who subsequently changed their instrument. Participants using reagents that had expired or were within 3 months of the expiration date performed worse than those using reagents that were expiring in more than 3 months. CONCLUSIONS: Continuous participation in the Noklus program improved the performance of quantitative UA analyses at GP offices. This is probably in part attributable to the complete Noklus quality system, whereby in addition to participating in EQAS, participants are visited by laboratory consultants who examine their procedures and provide practical advice and education regarding the use of different instruments.

Diagnosing diabetes mellitus: performance of hemoglobin A1c point-of-care instruments in general practice offices.

BACKGROUND: Hemoglobin A1c (Hb A1c) measurement by hospital laboratory instruments, but not by point-of-care (POC) instruments, has been recommended for use to diagnose diabetes mellitus. We evaluated results from 13 Hb A1c external quality assurance (EQA) surveys over a 6-year period in Norway, from both POC instruments used in general practice (GP) offices and instruments in hospital laboratories, against the analytical quality specifications recommended for use of Hb A1c to diagnose diabetes mellitus. METHODS: All GP offices (n = 1288) and hospital laboratories (n = 52) measuring Hb A1c in Norway participated in the EQA survey. The percentage of participants that performed measurements within the quality specifications was calculated. Pooled within-laboratory CVs were estimated for the Afinion, DCA 2000, DCA 2000+, DCA Vantage(TM), and Nycocard Hb A1c Reader instruments and for hospital laboratory instruments. RESULTS: Between 60% to 90% of Afinion and DCA users and hospital laboratories performed Hb A1c measurements within the quality specifications for both trueness (6.0%) and imprecision (CV ≤2.0%) at 2 levels in each EQA survey. The pooled within-laboratory CVs for the Afinion and DCA instruments and hospital laboratories were below the recommended limit of 2.0% for most of the surveys. CONCLUSIONS: A large proportion of GP offices using Afinion and DCA POC instruments to measure Hb A1c fulfill the analytical quality specifications for diagnosing diabetes mellitus, and these instruments demonstrate analytical quality comparable to that of hospital laboratory instruments. When GP offices participate in a stringent quality assurance program and generate Hb A1c measurements that meet analytical quality specifications, these measurements can be recommended for use to diagnose diabetes mellitus.

How to deal with semi-quantitative tests? Application of an ordinal scale model to measurements of urine glucose.

BACKGROUND: The interpretation of semi-quantitative methods has always been difficult, because the different kitmanufacturers use varying concentration values and there is a considerable overlap between kit-defined concentrations within the same kit (Kit: 'Ready-to-use' measuring system specific for each manufacturer's product). MATERIAL: More than 2000 private practitioners and laboratories participated in three external quality control surveys on urine-glucose performed with a total of six control materials with known concentrations. METHOD: The ordinal scale model for evaluation of dichotomous methods based on rankit transformation of fractions of positive results (Petersen et al. Scand J Clin Lab Invest 2008;68:298-311) has been extended and modified to handle semi-quantitative data. Here, the percentages of results larger than the kit-concentration is calculated for each control sample and applied as a dichotomous method. Thereafter, these percentages are separated into all the defined kit-concentrations. RESULTS: A total of eight kits had more than 50 measurements on at least four control materials which made them eligible for the calculations of logarithmic mean and standard deviation and thereby geometric mean and coefficient of variation for each of the kit-concentrations of each kit. Based on these parameters, the true concentration for selected percentages of each kit-concentration could be estimated. Moreover, the percentages of the different kit-concentrations could be calculated for each known true concentration. CONCLUSIONS: The present model is a powerful tool for improved characterization of semi-quantitative kits, which makes it possible to evaluate and validate kits and to optimize external quality control.

Between-lot variation in external quality assessment of glucose: clinical importance and effect on participant performance evaluation.

BACKGROUND: External quality assessment schemes (EQAS) are conducted to evaluate user performance (participant assessment) and to assess different methods and instruments (method assessment). The quality of control materials is crucial to achieving these goals. Inconsistencies in between-lot variations detected by use of different control and sample materials may affect EQAS outcomes. METHODS: For the Accu-Chek Sensor, Precision Xtra, Ascensia Elite, and HemoCue 201 glucometers, 3 different lots of glucose strips were used with each instrument. Method assessment results from analysis of capillary blood and 3 control materials were used to calculate between-lot differences. A simulation study was performed to evaluate the effect of between-lot variation on participant assessment results. RESULTS: With the Precision Xtra, the results obtained with EQA control material mirrored those obtained with capillary blood, but for the other instruments, we found between-lot differences of as much as 1.3 mmol/L, which were substantially greater than those found with capillary blood and of clinical importance at decision limits. The simulation study showed an effect on participant assessment results related to the target values, with the percentage of poor results decreasing (38%, 10%, and 4%) with the use of common, method-specific, and lot-specific target values, respectively. CONCLUSIONS: Between-lot variation may influence participant EQA results for participant and method assessments. The clinical relevance of between-lot variation discovered in EQAS using noncommutable control materials should be examined by use of native blood samples.