Analytical performance of eight enzymatic assays for ethanol in serum evaluated by data from the Belgian external quality assessment scheme.

OBJECTIVES: Fast and reliable ethanol assays analysis are used in a clinical context for patients suspected of ethanol intoxication. Mostly, automated systems using an enzymatic reaction based on ethanol dehydrogenase are used. The manuscript focusses on the evaluation of the performance of these assays. METHODS: Data included 30 serum samples used in the Belgian EQA scheme from 2019 to 2021 and concentrations ranged from 0.13 to 3.70 g/L. A regression line between target concentrations and reported values was calculated to evaluate outliers, bias, variability and measurement uncertainty. RESULTS: A total of 1,611 results were taken into account. Bias was the highest for Alinity c over the whole concentration range and the lowest for Vitros for low concentrations and Cobas 8000 using the c702 module for high concentrations. The Architect and Cobas c501/c502 systems showed the lowest variability over the whole concentration range. Highest variability was observed for Cobas 8000 using the 702 module, Thermo Scientific and Alinity c. Cobas 8000 using the c702 module showed the highest measurement uncertainty for lower concentrations. For higher concentrations, Alinity c, Thermo Scientific and Vitros were the methods with the highest measurement uncertainty. CONCLUSIONS: The bias of the enzymatic techniques is nearly negligible for all methods except Alinity c. Variability differs strongly between measurement procedures. This study shows that the Alinity c has a worse measurement uncertainty than other systems for concentrations above 0.5 g/L. Overall, we found the differences in measurement uncertainty to be mainly influenced by the differences in variability.

Application of the characteristic function to evaluate and compare analytical variability in an external quality assessment scheme for serum ethanol.

BACKGROUND: As a cornerstone of quality management in the laboratory, External Quality Assessment (EQA) schemes are used to assess laboratory and analytical method performance. The characteristic function is used to describe the relation between the target concentration and the EQA standard deviation, which is an essential part of the evaluation process. The characteristic function is also used to compare the variability of different analytical methods. METHODS: We fitted the characteristic function to data from the Belgian External Quality Assessment program for serum ethanol. Data included results from headspace gas chromatography and the enzymatic methods of Abbott, Roche, Siemens, and Ortho-Clinical Diagnostics. We estimated the characteristic function with weighted nonlinear regression. By introducing dummy variables, we rewrote the original formula of the characteristic function to assess statistical inference for comparing the variability of the different analytical methods. RESULTS: The characteristic function fitted the data precisely. Comparison between methods showed that there was little difference between the estimated variability for low concentrations, and that the increase in SD with increasing target concentration was slower for Abbott and Roche than for the other methods. CONCLUSIONS: The characteristic function can successfully be introduced in clinical schemes, although its applicability to fit the data should always be assessed. Because of its easy parameterization, it can be used to assess differences in performance between analytical methods and to assess laboratory performance. The characteristic function also offers an alternative framework for coefficients of variation to describe variability of analytical methods.