Influence of reagent lots and multiple measuring systems on estimating the coefficient of variation from quality control data; implications for uncertainty estimation and interpretation of QC results
Background Clinical laboratories use internal quality control (QC) data to calculate standard deviation (SD) and coefficient of variation (CV) to estimate uncertainty of results and to interpret QC results. We examined the influence of different instruments, and QC and reagent lots on the CV calcula...
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Veröffentlicht in: | Clinical chemistry and laboratory medicine 2020-11, Vol.58 (11), p.1829-1835 |
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Zusammenfassung: | Background Clinical laboratories use internal quality control (QC) data to calculate standard deviation (SD) and coefficient of variation (CV) to estimate uncertainty of results and to interpret QC results. We examined the influence of different instruments, and QC and reagent lots on the CV calculated from QC data. Methods Results for BioRad Multiqual frozen liquid QC samples over a 2-year interval were partitioned by QC and reagent lots. The mean and CV were calculated for each partition for each of three Abbott Architect c8000 instruments for measuring serum alanine amino transferase (ALT), creatinine (enzymatic), glucose and sodium. Results CVs differed among partitions and instruments for two QC levels by 5.8- and 3.3-fold for ALT, by 4.7- and 2.1-fold for creatinine, by 2.0- and 2.6-fold for glucose, and by 2.1- and 2.0-fold for sodium. Pooled CVs for two QC levels varied among instruments by 1.78- and 1.11-fold for ALT, by 1.63- and 1.11-fold for creatinine, by 1.08- and 1.06-fold for glucose, and by 1.24- and 1.31-fold for sodium. Conclusions The CVs from QC data varied substantially among QC and reagent lots and for different identical specification instruments. The CV used to estimate uncertainty for a measurement result or as the basis for interpreting individual QC results must be derived over a sufficient time interval to obtain a pooled CV that represents "typical" performance of a measuring system. An estimate of uncertainty provided to users of laboratory results will itself have uncertainty that can influence medical decisions. |
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ISSN: | 1434-6621 1437-4331 |
DOI: | 10.1515/cclm-2020-0320 |