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- W2011978920 abstract "Although dried blood spot (DBS) sampling is increasingly receiving interest as a potential alternative to traditional blood sampling, the impact of hematocrit (Hct) on DBS results is limiting its final breakthrough in routine bioanalysis. To predict the Hct of a given DBS, potassium (K+) proved to be a reliable marker. The aim of this study was to evaluate whether application of an algorithm, based upon predicted Hct or K+ concentrations as such, allowed correction for the Hct bias. Using validated LC-MS/MS methods, caffeine, chosen as a model compound, was determined in whole blood and corresponding DBS samples with a broad Hct range (0.18–0.47). A reference subset (n = 50) was used to generate an algorithm based on K+ concentrations in DBS. Application of the developed algorithm on an independent test set (n = 50) alleviated the assay bias, especially at lower Hct values. Before correction, differences between DBS and whole blood concentrations ranged from −29.1 to 21.1 %. The mean difference, as obtained by Bland-Altman comparison, was −6.6 % (95 % confidence interval (CI), −9.7 to −3.4 %). After application of the algorithm, differences between corrected and whole blood concentrations lay between −19.9 and 13.9 % with a mean difference of −2.1 % (95 % CI, −4.5 to 0.3 %). The same algorithm was applied to a separate compound, paraxanthine, which was determined in 103 samples (Hct range, 0.17–0.47), yielding similar results. In conclusion, a K+-based algorithm allows correction for the Hct bias in the quantitative analysis of caffeine and its metabolite paraxanthine." @default.
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- W2011978920 date "2014-08-29" @default.
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- W2011978920 title "Potassium-based algorithm allows correction for the hematocrit bias in quantitative analysis of caffeine and its major metabolite in dried blood spots" @default.
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- W2011978920 doi "https://doi.org/10.1007/s00216-014-8114-z" @default.
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