Evaluation of Coefficients of Variation for Clinical Chemistry Tests Based on Internal Quality Control Data Across 5,425 Laboratories in China From 2013 to 2022

Background

Clinical chemistry tests are most widely used in clinical laboratories, and diverse measurement systems for these analyses are available in China. We evaluated the imprecision of clinical chemistry measurement systems based on internal QC (IQC) data.

Methods

IQC data for 27 general chemistry analytes were collected in February each year from 2013 to 2022. Four performance specifications were used to calculate pass rates for CVs of IQC data in 2022. Boxplots were drawn to analyze trends of CVs, and differences in CVs among different groups were assessed using the Mann-Whitney U-test or Kruskal-Wallis test.

Results

The number of participating laboratories increased significantly from 1,777 in 2013 to 5,425 in 2022. CVs significantly decreased for all 27 analytes, except creatine kinase and lipase. Triglycerides, total bilirubin, direct bilirubin, iron, and γ-glutamyl transferase achieved pass rates >80% for all goals. Nine analytes with pass rates <80% based on 1/3 allowable total error were further analyzed; the results indicated that closed systems exhibited lower CVs than open systems for all analytes, except total protein. For all nine analytes, differences were significant between tertiary hospitals and non-tertiary hospitals and between accredited and non-accredited laboratories.

Conclusions

The CVs of IQC data for clinical chemistry have seen a continuous overall improvement in China. However, there is ample room for imprecision improvement for several analytes, with stricter performance specifications.

Evaluation of imprecision in the different detection methods of Zn based on 5 years of data from an external quality assessment program in China

BACKGROUND

This study examines the imprecision of zinc (Zn) measurements across various clinical detection methods by analyzing the external quality assessment (EQA) data from 2018 to 2022. The findings of this study aim to offer recommendations for enhancing Zn measurements.

METHODS

Participating laboratories were grouped into peer categories based on the detection methods. The robust mean and coefficient of variation (CV) of the samples were calculated following ISO 13528 guidelines. The evaluation criteria for optimal, desirable, and minimum allowable imprecision in Zn estimation are 2.50%, 5.05%, and 7.55%, respectively, based on biological variation. Furthermore, the study examined inter-lab CVs, inter-method bias, and the passing rate. The impact of sample concentration on CVs and the pass rate was also investigated.

RESULTS

Over the past five years, 4283 laboratories participated in the EQA program, showing a high pass rate that improved as sample concentration increased. Differential pulse polarography (DPP) demonstrated stable and low CVs (0.61-1.86%). Although differential pulse stripping (DPS) was less stable than DPP, it still exhibited a low CV (0.71-3.10%). Graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) performed similarly and displayed stable CVs (2.39-4.42%) within the acceptable range of desirable imprecision (5.05%). However, the CVs for ICP-MS were unacceptable in three out of the five years (5.28-6.20%). In 2022, the number of participating laboratories for DDP, DPS, GFAAS, FAAS and ICP-MS is 131, 35, 35, 820 and 72, respectively.

CONCLUSION

This study provides reliable insights into the imprecision of Zn measurements in clinical laboratories. The findings indicate that additional efforts are required to reduce the imprecision of ICP-MS in Zn measurements.

Imprecision of high-sensitivity cardiac troponin assays at the female 99th-percentile

BACKGROUND

An analytical benchmark for high-sensitivity cardiac troponin (hs-cTn) assays is to achieve a coefficient of variation (CV) of ≤ 10.0 % at the 99th percentile upper reference limit (URL) used for the diagnosis of myocardial infarction. Few prospective multicenter studies have evaluated assay imprecision and none have determined precision at the female URL which is lower than the male URL for all cardiac troponin assays.

METHODS

Human serum and plasma matrix samples were constructed to yield hs-cTn concentrations near the female URLs for the Abbott, Beckman, Roche, and Siemens hs-cTn assays. These materials were sent (on dry ice) to 35 Canadian hospital laboratories (n = 64 instruments evaluated) participating in a larger clinical trial, with instructions for storage, handling, and monthly testing over one year. The mean concentration, standard deviation, and CV for each instrument type and an overall pooled CV for each manufacturer were calculated.

RESULTS

The CVs for all individual instruments and overall were ≤ 10.0 % for two manufacturers (Abbott CVpooled = 6.3 % and Beckman CVpooled = 7.0 %). One of four Siemens Atellica instruments yielded a CV > 10.0 % (CVpooled = 7.7 %), whereas 15 of 41 Roche instruments yielded CVs > 10.0 % at the female URL of 9 ng/L used worldwide (6 cobas e411, 1 cobas e601, 4 cobas e602, and 4 cobas e801) (CVpooled = 11.7 %). Four Roche instruments also yielded CVs > 10.0 % near the female URL of 14 ng/L used in the United States (CVpooled = 8.5 %).

CONCLUSIONS

The number of instruments achieving a CV ≤ 10.0 % at the female 99th-percentile URL varies by manufacturer and by instrument. Monitoring assay precision at the female URL is necessary for some assays to ensure optimal use of this threshold in clinical practice.

Signal-to-noise of linear and volume measures of left ventricular and left atrial size

BACKGROUND

Serial echocardiographic assessments are common in clinical cardiology, e.g., for timing of intervention in mitral and aortic regurgitation. When following patients with serial echocardiograms, each new measurement is a combination of true change and confounding noise. The current investigation compares linear chamber dimensions with volume estimates of chamber size. The aim is to assess which measure is best for serial echocardiograms, when the ideal parameter will be sensitive to change in chamber size and have minimal spurious variation (noise). We present a method that disentangles true change from noise. Linear regression of chamber size against elapsed time gives a slope, being the ability of the method to detect change. Noise is the scatter of individual points away from the trendline, measured as the standard error of the slope. The higher the signal-to-noise ratio (SNR), the more reliably a parameter will distinguish true change from noise.

METHODS

LV and LA parasternal dimensions and apical biplane volumes were obtained from serial clinical echocardiogram reports. Change over time was assessed as the slope of the linear regression line, and noise was assessed as the standard error of the regression slope. Signal-to-noise ratio is the slope divided by its standard error.

RESULTS

The median number of LV studies was 5 (4-11) for LV over a mean duration of 5.9 ± 3.0 years in 561 patients (diastole) and 386 (systole). The median number of LA studies was 5 (4-11) over a mean duration of 5.3 ± 2.0 years in 137 patients. Linear estimates of LV size had better signal-to-noise than volume estimates (p < 0.001 for diastolic and p = 0.035 for systolic). For the left atrium, the difference was not significant (p = 0.214). This may be due to sample size; the effect size was similar to that for LV systolic size. All three parameters had a numerical value of signal-to-noise that favoured linear dimensions over volumes.

CONCLUSION

Linear measures of LV size have better signal-to-noise than volume measures. There was no difference in signal-to-noise between linear and volume measures of LA size, although this may be a Type II error. The use of regression lines may be better than relying on single measurements. Linear dimensions may clarify whether changes in volumes are real or spurious.

GRADE guidance 37: rating imprecision in a body of evidence on test accuracy

OBJECTIVES

To provide guidance on rating imprecision in a body of evidence assessing the accuracy of a single test. This guide will clarify when Grading of Recommendations Assessment, Development and Evaluation (GRADE) users should consider rating down the certainty of evidence by one or more levels for imprecision in test accuracy.

STUDY DESIGN AND SETTING

A project group within the GRADE working group conducted iterative discussions and presentations at GRADE working group meetings to produce this guidance.

RESULTS

Before rating the certainty of evidence, GRADE users should define the target of their certainty rating. GRADE recommends setting judgment thresholds defining what they consider a very accurate, accurate, inaccurate, and very inaccurate test. These thresholds should be set after considering consequences of testing and effects on people-important outcomes. GRADE's primary criterion for judging imprecision in test accuracy evidence is considering confidence intervals (i.e., CI approach) of absolute test accuracy results (true and false, positive, and negative results in a cohort of people). Based on the CI approach, when a CI appreciably crosses the predefined judgment threshold(s), one should consider rating down certainty of evidence by one or more levels, depending on the number of thresholds crossed. When the CI does not cross judgment threshold(s), GRADE suggests considering the sample size for an adequately powered test accuracy review (optimal or review information size [optimal information size (OIS)/review information size (RIS)]) in rating imprecision. If the combined sample size of the included studies in the review is smaller than the required OIS/RIS, one should consider rating down by one or more levels for imprecision.

CONCLUSION

This paper extends previous GRADE guidance for rating imprecision in single test accuracy systematic reviews and guidelines, with a focus on the circumstances in which one should consider rating down one or more levels for imprecision.

The pipetting Olympics: Propagating proper pipetting a priori in clinical LC-MS/MS analysis

Introduction

Engaging pipetting events were developed to assess and challenge technicians' practical sample handling using matrices common to the clinical laboratory. As correct pipetting stands as a prerequisite for accurate clinical laboratory testing, this helped to understand sources of imprecision and bias attributed to the underlying step of aspirating and dispensing patient samples and internal standard in clinical LC-MS/MS assays while highlighting the importance for the clinical laboratory to evaluate this source of variability on an on-going basis and mitigate its impact.

Methods

The events involved pipetting water, methanol, serum, and whole blood. Gravimetric analysis was used to determine the exact volumetric delivery of each matrix using two different techniques. Imprecision and bias were calculated based on the volume derived from the mass and density of each matrix, using literature values for each matrix type.

Results

Low imprecision and bias were observed when pipetting water, as in common commercial pipetting assessment programs. Significantly increased imprecision and bias were observed in more applicable matrices (i.e., serum, whole blood, and methanol), indicating that water-based pipetting proficiency assessment leads to a false sense of technical ability. Additionally, the events within illuminated areas for training, leading to improved imprecision and bias. It was shown that pre-rinsing (aspirating and dispensing matrix three times to coat the tip) improved bias, particularly for delivery of methanol and whole blood.

Conclusions

Precise and accurate pipetting within the clinical laboratory should not be taken for granted, nor implicitly inferred from proficiency assessment using aqueous solutions. The engaging and collegial events fostered training opportunities. Assay-specific patient sample delivery considerations (pipets and matrices) can inform the practicality of these events - the Pipetting Olympics - and drive improvements within the laboratory.

Is canine calprotectin in serum stabile after storage at low temperature?

BACKGROUND

In human and veterinary medicine calprotectin is most widely used in diagnosing different gastro-intestinal diseases. The aim of this study was to assess the stability of canine calprotectin (cCP) in serum after storage at low temperatures and imprecision of the method.

METHODS

Blood samples were collected from dogs with different clinical diagnoses. Twenty-two dogs were included in this study. Calprotectin concentration was measured 4 hours after serum separation (T0), and after being frozen at - 80 °C for 8 (T1) and 16 weeks (T2). The maximum permissible difference (MPD) was derived from the equation for calculating total error (TE) TE = %Bias + (1.96 x %CV), where bias and coefficient of variation (CV) were defined by the manufacturer. The dogs enrolled in this study were patients admitted during the morning (9-12 a.m.), on the day the first measurement was performed. All sample analysis for determination of stability were done in duplicates. For determination of within-run precision, the two patients' serum samples were analyzed in 20 replicates. Imprecision was assessed by analyzing 20 replicates on one plate on two samples where high and low concentrations were anticipated.

RESULTS

The calculated value of MPD was 32.52%. Median calprotectin concentrations were higher at T1 114.08 μg/L (IQR = 55.05-254.56) and T2 133.6 μg/L (IQR = 100.57-332.98) than at T0 83.60 μg/L (IQR = 50.38-176.07). Relative and absolute bias at T1 (49.3%; 45.98 μg/L) and T2 (109.93%; 94.09 μg /L) have shown that calprotectin concentrations increase after long term storage at - 80 °C.

CONCLUSION

The results of the present study indicate that c-CP was not stable for 16 weeks at low storage temperature (- 80 °C). Considering the observed change in the concentration of c-CP at T1, a storage time of 8 weeks should be safely applied. The method imprecision was not satisfactory, especially in the lower concentration range.

Evidence-based Urology: When Is a Study or Meta-analysis Big Enough?

Both designing a clinical study and drawing conclusions from studies about the effect of treatments require justification of the sample size via judicious choice of the endpoint and power. Such an a priori power calculation limits the chances of mistakenly claiming a lack of clinical significance if no statistically significant difference between two treatments can be detected. Calculating the sample size for a new trial furthermore requires assessment of existing evidence to determine if its results will contribute to an updated meta-analysis. To rate the power of a meta-analysis, determination of the optimal information size is suggested, following the same principles as for calculating the power of a single trial. Even though these sample size considerations might seem like an additional hurdle, they are necessary to conduct clinical studies and meta-analysis that provide the optimal benefit for both clinicians and patients. PATIENT SUMMARY: Before conducting a clinical trial, researchers should determine how many patients need to be included to detect a difference between treatments. Even though a study might find a statistical difference between treatments, this does not necessarily mean that the difference is relevant for clinical use. These analyses before starting a study are important for producing worthwhile usable evidence for clinicians and patients.

Setting analytical performance specifications using HbA1c as a model measurand

Analytical performance specifications (APS) for measurands describe the minimum analytical quality requirements for their measurement. These APS are used to monitor and contain the systematic (trueness/bias) and random errors (precision/imprecision) of a laboratory measurement to ensure the results are "fit for purpose" in informing clinical decisions about managing a patient's health condition. In this review, we highlighted the wide variation in the setting of APS, using different levels of evidence, as recommended by the Milan Consensus, and approaches. The setting of a priori defined outcome-based APS for HbA1c remains challenging. Promising indirect alternatives seek to link the clinical utility of HbA1c and APS by defining statistical confidence for interpreting the laboratory values, or through simulation of clinical performance at varying levels of analytical performance. APS defined based on biological variation estimates in healthy individuals using the current formulae are unachievable by nearly all routine laboratory methods for HbA1c testing. On the other hand, the APS employed in external quality assurance programs have been progressively tightened, and greatly facilitate the improved quality of HbA1c testing. Laboratories should select the APS that fits their intended clinical use and should document the data and rationale underpinning those selections. Where possible common APS should be adopted across a region or country to facilitate the movement of patients and patient data across health care facilities.

GRADE guidelines 33: Addressing imprecision in a network meta-analysis

OBJECTIVE

This article describes GRADE guidance for assessing imprecision when rating the certainty of the evidence from network meta-analysis.

STUDY DESIGN AND SETTING

A project group within the GRADE working group conducted iterative discussions, computer simulations, and presentations at GRADE working group meetings to produce and obtain approval for this guidance.

RESULTS

When addressing imprecision of a network estimate, reviewers should consider the 95% confidence or credible interval, and the optimal information size. If the 95% confidence or credible interval crosses a pre-specified threshold, reviewers should rate down the certainty of the evidence. If the 95% confidence interval does not cross any pre-specfied threshold, reviewers should consider the optimal information size. Because addressing the optimal information size may be challenging, reviewers can use the effect size to decide if any calculations are necessary. When the size of the effect is modest or the optimal information size is met, reviewers should not rate down for imprecision.

CONCLUSION

Reviewers should use this guidance when to appropriately address imprecision in the context of the assessment of certainty of evidence from network meta-analysis.

[GRADE guidelines 20: Assessing the certainty of evidence in the importance of outcomes or values and preferences-inconsistency, imprecision, and other domains]

OBJECTIVE

To provide Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidance for assessing inconsistency, imprecision, and other domains for the certainty of evidence about the relative importance of outcomes.

STUDY DESIGN AND SETTING

We applied the GRADE domains to rate the certainty of evidence in the importance of outcomes to several systematic reviews, iteratively reviewed draft guidance, and consulted GRADE members and other stakeholders for feedback.

RESULTS

We describe the rationale for considering the remaining GRADE domains when rating the certainty in a body of evidence for the relative importance of outcomes. As meta-analyses are not common in this context, inconsistency and imprecision assessments are challenging. Furthermore, confusion exists about inconsistency, imprecision, and true variability in the relative importance of outcomes. To clarify this issue, we suggest that the true variability is neither equivalent to inconsistency nor imprecision. Specifically, inconsistency arises from population, intervention, comparison and outcome and methodological elements that should be explored and, if possible, explained. The width of the confidence interval and sample size inform judgments about imprecision. We also provide suggestions on how to detect publication bias and discuss the domains to rate up the certainty.

CONCLUSION

We provide guidance and examples for rating inconsistency, imprecision, and other domains for a body of evidence describing the relative importance of outcomes.

Interpreting plural predication: homogeneity and non-maximality

Plural definite descriptions across many languages display two well-known properties. First, they can give rise to so-called non-maximal readings, in the sense that they 'allow for exceptions' (Mary read the books on the reading list, in some contexts, can be judged true even if Mary didn't read all the books on the reading list). Second, while they tend to have a quasi-universal quantificational force in affirmative sentences ('quasi-universal' rather than simply 'universal' due to the possibility of exceptions we have just mentioned), they tend to be interpreted existentially in the scope of negation (a property often referred to as homogeneity, cf. Löbner in Linguist Philos 23:213-308, 2000). Building on previous works (in particular Krifka in Proceedings of SALT VI, Cornell University, pp 136-153, 1996 and Malamud in Semant Pragmat, 5:1-28, 2012), we offer a theory in which sentences containing plural definite expressions trigger a family of possible interpretations, and where general principles of language use account for their interpretation in various contexts and syntactic environments. Our theory solves a number of problems that these previous works encounter, and has broader empirical coverage in that it offers a precise analysis for sentences that display complex interactions between plural definites, quantifiers and bound variables, as well as for cases involving non-distributive predicates. The resulting proposal is briefly compared with an alternative proposal by Križ (Aspects of homogeneity in the semantics of natural language, University of Vienna, 2015), which has similar coverage but is based on a very different architecture and sometimes makes subtly different predictions.

Measurement Uncertainty Impacts Diagnosis of Diabetes Mellitus: Reliable Minimal Difference of Plasma Glucose Results

INTRODUCTION

The diagnosis of diabetes mellitus is based on suitable cut-off values of specific biomarkers, such as the concentration of glucose in plasma. The German Diabetes Association has very recently published a clinical practice guideline on the definition, classification and diagnosis of diabetes mellitus that recommends measurements of plasma glucose concentration have an imprecision defined as a minimal difference (MD) of at a fasting plasma glucose concentration of 7.0 mmol/L. To obtain reliable values for the MD, we investigated long-term and short-term measurement uncertainty.

METHODS

The imprecision was determined by two approaches: (1) a long-term dataset with imprecision based on the Guideline of the German Medical Association on Quality Assurance in Medical Laboratory Examinations (Rili-BAEK), in a medical laboratory operating 24/7, using internal quality control (IQC) data for four concentrations during a 10-year period; and (2) a detailed short-term dataset with imprecision assessed by hourly measurements of control materials. These datasets were used to calculate the MD cut-off (MD_cut-off) as: [Formula: see text]  = 2  [Formula: see text], where SD is the standard deviation and k = 2 represents a confidence level of 95%.

RESULTS

The MD_cut-off of ≤ 0.7 mmol/L at a fasting plasma glucose concentration of 7.0 mmol/L (MD_cut-off 7.0) for the long-term and the short-term approaches were 0.44 and 0.40 mmol/L, respectively. The MD_cut-off 7.0 from both approaches was therefore below the recommended value of 0.7 mmol/L. It was noted that the variability in performance within and between instruments can be covered by reporting the long-term MD_cut-off 7.0 across all connected instruments. In this study, stable results for the MD_cut-off 7.0 were obtained after 1 year.

CONCLUSION

Imprecision as measured by IQC data is remarkably stable over many years of operation. Current imprecision assessment usually focuses on only single instruments, whereas clinicians perceive the measurement as the result of the combined analytical performance of all instruments used for a certain assay. In the clinical setting, the MD may be a more useful measure of imprecision, and we suggest deriving the MD_cut-off combined from all instruments and control cycles that are used in the patient care setting for a given analyte.

Assessment of quality control system by sigma metrics and quality goal index ratio: A roadmap towards preparation for NABL

AIM

To study sigma metrics and quality goal index ratio (QGI).

METHODS

The retrospective study was conducted at the Clinical Biochemistry Laboratory, PGIMS, Rohtak, which recently became a National Accreditation Board for Testing and Calibration of Laboratories accredited lab as per the International Organization for Standardization 15189:2012 and provides service to a > 1700-bed tertiary care hospital. Data of 16 analytes was extracted over a period of one year from January 2017 to December 2017 for calculation of precision, accuracy, sigma metrics, total error, and QGI.

RESULTS

The average coefficient of variation ranged from 2.12% (albumin) to 5.42% (creatinine) for level 2 internal quality control and 2% (albumin) to 3.62% (high density lipoprotein-cholesterol) for level 3 internal quality control. Average coefficient of variation of all the parameters was below 5%, reflecting very good precision. The sigma metrics for level 2 indicated that 11 (68.5%) of the 16 parameters fall short of meeting Six Sigma quality performance. Of these, five failed to meet minimum sigma quality performance with metrics less than 3, and another six just met minimal acceptable performance with sigma metrics between 3 and 6. For level 3, the data collected indicated eight (50%) of the parameters did not achieve Six Sigma quality performance, out of which three had metrics less than 3, and five had metrics between 3 and 6. QGI ratio indicated that the main problem was inaccuracy in the case of total cholesterol, aspartate transaminase, and alanine transaminase (QGI > 1.2), imprecision in the case of urea (QGI < 0.8), and both imprecision and inaccuracy for glucose.

CONCLUSION

On the basis of sigma metrics and QGI, it may be concluded that the Clinical Biochemistry Laboratory, PGIMS, Rohtak was able to achieve satisfactory results with world class performance for many analytes one year preceding the accreditation by the National Accreditation Board for Testing and Calibration of Laboratories. Aspartate transaminase and alanine transaminase required strict external quality assurance scheme monitoring and modification in quality control procedure as their QGI ratio showed inaccuracy.

Uncertainty, imprecision, and many-valued logics in protein bioinformatics

Understanding proteins, their structures, functions, mutual interactions, activity in cellular reactions, interactions with drugs, and expression in body cells is a key to efficient medical diagnosis, drug production, and treatment of patients. Machine learning and data exploration methods supported by many-valued logics allow to grasp the imprecision and uncertainties that naturally occur in proteins and other biomolecules. Many-valued logics, like Łukasiewicz logic or fuzzy logic, are non-classical logics that do not restrict the number of truth values to only two values of true or false, but they allow for a larger set of truth degrees. In this paper, we briefly review the use of many-valued logics, especially the fuzzy logic, in bioinformatics. Then, we focus on protein bioinformatics, and present selected applications of many-valued logics in the analysis of complex protein structures, including; (1) potential-based protein similarity searching, (2) matching proteins on the basis of secondary structures, (3) 3D protein structure alignment, (4) prediction of intrinsically disordered proteins, and (5) fuzzy querying in large collections of Big macromolecular Data. Results of presented studies show that the utilization of many-valued logics can enrich the investigations of protein molecules, in which uncertainty and imprecision are prevalent problems. The paper discusses all observed benefits brought by the application of many-valued logics in investigations related to selected protein analyzes carried out by the author.

Deriving proper measurement uncertainty from Internal Quality Control data: An impossible mission?

Measurement uncertainty (MU) is a "non-negative parameter characterizing the dispersion of the quantity values being attributed to a measurand, based on the information used". In the clinical laboratory the most convenient way to calculate MU is the "top down" approach based on the use of Internal Quality Control data. As indicated in the definition, MU depends on the information used for its calculation and so different estimates of MU can be obtained. The most problematic aspect is how to deal with bias. In fact bias is difficult to detect and quantify and it should be corrected including only the uncertainty derived from this correction. Several approaches to calculate MU starting from Internal Quality Control data are presented. The minimum requirement is to use only the intermediate precision data, provided to include 6 months of results obtained with a commutable quality control material at a concentration close to the clinical decision limit. This approach is the minimal requirement and it is convenient for all those measurands that are especially used for monitoring or where a reference measurement system does not exist and so a reference for calculating the bias is lacking. Other formulas including the uncertainty of the value of the calibrator, including the bias from a commutable certified reference material or from a material specifically prepared for trueness verification, including the bias derived from External Quality Assessment schemes or from historical mean of the laboratory are presented and commented. MU is an important parameter, but a single, agreed upon way to calculate it in a clinical laboratory is not yet available.

ASVCP guidelines: Allowable total error hematology

The purpose of this document is to provide total allowable error (TE_a ) recommendations for commonly analyzed hematology measurands for veterinary personnel. These guidelines define relevant terminology and highlight considerations specific to hematology measurands. They also provide reasons and guidelines for using TE_a in instrument performance evaluation, including recommendations for when the total observed error exceeds the recommended TE_a . Biological variation-based quality specifications are briefly discussed. The appendix describes the derivation of the hematology TE_a recommendations and provides resources for external quality assurance/proficiency testing programs and a worksheet for implementation of the guidelines.

Analytical and pre-analytical performance characteristics of a novel cartridge-type blood gas analyzer for point-of-care and laboratory testing

BACKGROUND

Point-of-care blood gas test results may benefit therapeutic decision making by their immediate impact on patient care. We evaluated the (pre-)analytical performance of a novel cartridge-type blood gas analyzer, the GEM Premier 5000 (Werfen), for the determination of pH, partial carbon dioxide pressure (pCO₂), partial oxygen pressure (pO₂), sodium (Na⁺), potassium (K⁺), chloride (Cl^-), ionized calcium (_iCa²⁺), glucose, lactate, and total hemoglobin (tHb).

METHODS

Total imprecision was estimated according to the CLSI EP5-A2 protocol. The estimated total error was calculated based on the mean of the range claimed by the manufacturer. Based on the CLSI EP9-A2 evaluation protocol, a method comparison with the Siemens RapidPoint 500 and Abbott i-STAT CG8+ was performed. Obtained data were compared against preset quality specifications. Interference of potential pre-analytical confounders on co-oximetry and electrolyte concentrations were studied.

RESULTS

The analytical performance was acceptable for all parameters tested. Method comparison demonstrated good agreement to the RapidPoint 500 and i-STAT CG8+, except for some parameters (RapidPoint 500: pCO₂, K⁺, lactate and tHb; i-STAT CG8+: pO₂, Na⁺, _iCa²⁺ and tHb) for which significant differences between analyzers were recorded. No interference of lipemia or methylene blue on CO-oximetry results was found. On the contrary, significant interference for benzalkonium and hemolysis on electrolyte measurements were found, for which the user is notified by an interferent specific flag.

CONCLUSION

Identification of sample errors from pre-analytical sources, such as interferences and automatic corrective actions, along with the analytical performance, ease of use and low maintenance time of the instrument, makes the evaluated instrument a suitable blood gas analyzer for both POCT and laboratory use.

The significance of reporting to the thousandths place: Figuring out the laboratory limitations

OBJECTIVES

A request to report laboratory values to a specific number of decimal places represents a delicate balance between clinical interpretation of a true analytical change versus laboratory understanding of analytical imprecision and significant figures. Prostate specific antigen (PSA) was used as an example to determine if an immunoassay routinely reported to the hundredths decimal place based on significant figure assessment in our laboratory was capable of providing analytically meaningful results when reported to the thousandths places when requested by clinicians.

DESIGN AND METHODS

Results of imprecision studies of a representative PSA assay (Roche MODULAR E170) employing two methods of statistical analysis are reported. Sample pools were generated with target values of 0.01 and 0.20 μg/L PSA as determined by the E170. Intra-assay imprecision studies were conducted and the resultant data were analyzed using two independent statistical methods to evaluate reporting limits.

RESULTS

These statistical methods indicated reporting results to the thousandths place at the two assessed concentrations was an appropriate reflection of the measurement imprecision for the representative assay. This approach used two independent statistical tests to determine the ability of an analytical system to support a desired reporting level. Importantly, data were generated during a routine intra-assay imprecision study, thus this approach does not require extra data collection by the laboratory.

CONCLUSIONS

Independent statistical analysis must be used to determine appropriate significant figure limitations for clinically relevant analytes. Establishing these limits is the responsibility of the laboratory and should be determined prior to providing clinical results.

Practical application of biological variation and Sigma metrics quality models to evaluate 20 chemistry analytes on the Beckman Coulter AU680

OBJECTIVES

This study aimed to evaluate the imprecision and bias data generated for 20 routine chemistry analytes against both the biological variation fitness for purpose (FFP) and Sigma metrics (SM) criteria.

DESIGN AND METHOD

Twenty serum/plasma analytes were evaluated on the Beckman Coulter AU680. Third party commercial lyophilized internal quality control samples of human origin were used for day-to-day imprecision calculations. Commercial external quality assurance (EQA) samples were used to determine the systematic error between the test method result and the instrument group mean result from the EQA program for each analyte. Biological variation data was used to calculate the minimum, desirable and optimal imprecision and bias for determination of FFP. The desirable total allowable error was determined from biological variation data and applied to the SM calculation. The outcomes of both quality approaches were then compared.

RESULTS

The day-to-day imprecision of most tested analytes (except sodium and chloride) were smaller than the allowable imprecision (ranging from minimum to optimum). Most analytes achieved at least minimum bias. The SM varied with analyte concentration with six analytes producing low Sigma values. Comparing the quality processes eleven analytes produced a green light for both FFP and SM. There was some difference seen in interpretation for the other nine analytes.

CONCLUSIONS

The individual interpretation of bias and imprecision using FFP criteria allowed for the clear determination of the major source of error. Whereas, SM provided a summative evaluation of method performance. But the selection of total allowable error (TEa) is fundamental to this interpretation and harmonisation of the TEa calculation is needed.

Gestational diabetes mellitus prevalence: Effect of the laboratory analytical variation

AIMS

To highlight the effect of laboratory analytic variation, assessed by glucose (a) total analytic laboratory error (TAEL) present in one index laboratory and (b) total recommended allowable error (TAEa) universally applicable to all laboratories, on the prevalence of gestational diabetes mellitus (GDM).

METHODS

2337 pregnant women underwent a 75-g oral glucose tolerance test (OGTT) for universal GDM screening. Since the true value of every laboratory result fluctuates within a range, the glucose TAEL and TAEa were used to define a lower and an upper diagnostic threshold (95% confidence interval, CI) for the three glucose OGTT cut-offs of the criteria of the American Diabetes Association, ADA (2003); the Canadian Diabetes Association, CDA (2013) and the International Association of Diabetes and Pregnancy Study Groups, IADPSG (2010).

RESULTS

For the ADA, CDA and IADPSG criteria, respectively, the GDM prevalence [95% CI, (glucose TAEL) (glucose TAEa)] was 13.3% [(8.0-21.8) (6.3-25.9)], 30% [(17.3-53.1) (14.3-61.3)] and 45.3% [(27.0-71.0) (22.3-79.2)]. Using the lower and higher assigned OGTT glucose thresholds for TAEL, respectively, among the different criteria, either 200 (8.6%)-601 (25.7%) additional or 122 (5.2%)-426 (18.3%) fewer women would be identified with GDM (p<0.0001).

CONCLUSIONS

Independent of the diagnostic criteria, any reported GDM prevalence can potentially vary between one half to two times even for laboratories meeting recommended quality specifications. To avoid misclassifying women with GDM substantially, individual laboratories can significantly reduce this disparity by improving analytic performance. All physicians must ensure that their laboratory meets acceptable quality standards for optimal patient care.

Application of sigma metrics for the assessment of quality control in clinical chemistry laboratory in Ghana: A pilot study

BACKGROUND

Sigma metrics provide a uniquely defined scale with which we can assess the performance of a laboratory. The objective of this study was to assess the internal quality control (QC) in the clinical chemistry laboratory of the University of Cape Cost Hospital (UCC) using the six sigma metrics application.

MATERIALS AND METHODS

We used commercial control serum [normal (L1) and pathological (L2)] for validation of quality control. Metabolites (glucose, urea, and creatinine), lipids [triglycerides (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-C)], enzymes [alkaline phosphatase (ALP), alanine aminotransferase (AST)], electrolytes (sodium, potassium, chloride) and total protein were assessed. Between-day imprecision (CVs), inaccuracy (Bias) and sigma values were calculated for each control level.

RESULTS

Apart from sodium (2.40%, 3.83%), chloride (2.52% and 2.51%) for both L1 and L2 respectively, and glucose (4.82%), cholesterol (4.86%) for L2, CVs for all other parameters (both L1 and L2) were >5%. Four parameters (HDL-C, urea, creatinine and potassium) achieved sigma levels >1 for both controls. Chloride and sodium achieved sigma levels >1 for L1 but <1 for L2. In contrast, cholesterol, total protein and AST achieved sigma levels <1 for L1 but >1 for L2. Glucose and ALP achieved a sigma level >1 for both control levels whereas TG achieved a sigma level >2 for both control levels.

CONCLUSION

Unsatisfactory sigma levels (<3) where achieved for all parameters using both control levels, this shows instability and low consistency of results. There is the need for detailed assessment of the analytical procedures and the strengthening of the laboratory control systems in order to achieve effective six sigma levels for the laboratory.

Evaluation of imprecision, bias and total error of clinical chemistry analysers

Context Two Biosystems analysers are used in our laboratory, a fully automated A25 and a semi-automated BTS-350. Internal quality control is done for both but external quality control only for A25. As BTS-350 is used for backup, it is important that the results of both analysers are not just comparable but also within predefined limits of systematic, random and total error (TE). Aim To evaluate the imprecision, bias and TE of the two Biosystem analysers. Materials and Methods Biosystems level-1 quality control sera lot number 70A was run in duplicate for 32 days on both the analysers. Between day imprecision (measured by the coefficient of variation), bias and TE were calculated for ten analytes and were checked to see whether they are within the acceptable minimum limits, desirable limits and optimum limits of allowable error based on specifications on Westgard's website updated in 2014. Results On both the analysers, all the analytes except alkaline phosphatase were within the acceptable minimum limits of TE and most analytes were within the desirable limits of TE. Only TG on A25 was within the optimum limit of TE. Conclusion The two Biosystem analysers performed comparably with errors within acceptable limits for most analytes. BTS-350 was found to be a suitable and ready backup analyser for A25.

Multisite evaluation of a monoclonal IMMULITE erythropoietin immunoassay

BACKGROUND

Erythropoietin (EPO) measurements are useful in diagnosing anemias and polycythemias. We conducted a multisite evaluation of a monoclonal IMMULITE® EPO immunoassay.(1) DESIGN AND METHODS: The IMMULITE EPO assay is a solid-phase enzyme-labeled chemiluminescent immunometric assay. Method comparison to the Beckman ACCESS 2 assay using clinically characterized samples and reproducibility studies were conducted at three external independent laboratories. Internal evaluation conducted at Siemens included comparison of IMMULITE® 2000 and IMMULITE® 1000 assays to the ACCESS 2 assay; imprecision; linearity; limit of blank (LoB), limit of detection (LoD), and functional sensitivity; potential interference and cross-reactants; and reference interval determination.

RESULTS

External method comparison gave Deming regression of (IMMULITE 2000)=0.96(ACCESS 2)+2.57IU/L, r=0.98 (n=217). Reproducibility ranged from 6.1% to 16.2%. Internal method comparisons gave Deming regressions of (IMMULITE 2000)=1.09(ACCESS 2)-3.51IU/L, r=0.98 and (IMMULITE 1000)=0.95(ACCESS 2)+0.52IU/L, r=0.95. Total imprecision ranged from 6.4% to 10.3% and linearity was confirmed from 3.5 to 562IU/L. LoB, LoD, and functional sensitivity were 0.5, 1.0, and 1.5IU/L, respectively. The assay was highly specific for EPO. Nonparametric reference interval was 4.3 to 29.0IU/L (n=170).

CONCLUSIONS

The monoclonal IMMULITE EPO assay showed acceptable performance for EPO measurement.