A novel, nondestructive, dried blood spot-based hematocrit prediction method using noncontact diffuse reflectance spectroscopy

Dried blood spot (DBS) sampling is recognized as a valuable alternative sampling strategy both in research and in clinical routine. Although many advantages are associated with DBS sampling, its more widespread use is hampered by several issues, of which the hematocrit effect on DBS-based quantitation remains undoubtedly the most widely discussed one. Previously, we developed a method to derive the approximate hematocrit from a nonvolumetrically applied DBS based on its potassium content. Although this method yielded good results and was straightforward to perform, it was also destructive and required sample preparation. Therefore, we now developed a nondestructive method which allows to predict the hematocrit of a DBS based on its hemoglobin content, measured via noncontact diffuse reflectance spectroscopy. The developed method was thoroughly validated. A linear calibration curve was established after log/log transformation. The bias, intraday and interday imprecision of quality controls at three hematocrit levels and at the lower and upper limit of quantitation (0.20 and 0.67, respectively) were less than 11%. In addition, the influence of storage and the volume spotted was evaluated, as well as DBS homogeneity. Application of the method to venous DBSs prepared from whole blood patient samples (n = 233) revealed a good correlation between the actual and the predicted hematocrit. Limits of agreement obtained after Bland and Altman analysis were -0.076 and. +0.018. Incurred sample reanalysis demonstrated good method reproducibility. In conclusion, mere scanning of a DBS suffices to derive its approximate hematocrit, one of the most important variables in DBS analysis

Potassium-based algorithm allows correction for the hematocrit bias in quantitative analysis of caffeine and its major metabolite in dried blood spots

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

A challenging diagnosis of a nonsecretor plasma cell dyscrasia with pleomorphic plasmablastic morphology

This report highlights the importance of integrating clinical, radiological, genetic, and pathological laboratory findings to make a correct diagnosis especially with challenging and rare entities

Hematocrit prediction in volumetric absorptive microsamples

Recently, volumetric absorptive microsampling (VAMS) has been suggested as an alternative to DBS sampling. With VAMS, a fixed volume of blood (approximately 10 L) is wicked up by the absorbent tip of a collection device, independent of the hematocrit (HT) of the blood sample. This way, VAMS effectively avoids the HT bias which occurs in partial-punch DBS analysis. Nonetheless, the HT remains an important variable in VAMS analysis, particularly if VAMS-based blood results need to be converted to serum or plasma values to allow comparison with e.g. plasma-based therapeutic intervals. Indeed, an analyte’s plasma to whole blood ratio may be HT-dependent. Therefore, we developed two straightforward methods to derive the HT value from aVAMS sample based on its potassium content. One ofthese methods uses an aqueous extraction procedure, whereas the other one requires an organic extraction. Both methods have the potential to be seamlessly integrated with most existing VAMS analyses, allowing both target analyte quantitation and potassium analysis on a single VAMS extract

Prediction of the hematocrit of dried blood spots via potassium measurement on a routine clinical chemistry analyzer

The potential of dried blood spot (DBS) sampling as an alternative for classical venous sampling is increasingly recognized, with multiple applications in, e.g., therapeutic drug monitoring and toxicology. Although DBS sampling has many advantages, it is associated with several issues, the hematocrit (Hct) issue being the most widely discussed challenge, given its possible strong impact on DBS-based quantitation. Hitherto, no approaches allow Hct prediction from nonvolumetrically applied DBS. Following a simple and rapid extraction protocol, K+ levels from 3 mm DBS punches were measured via indirect potentiometry, using the Roche Cobas 8000 routine chemistry analyzer. The extracts’ K+ concentrations were used to calculate the approximate Hct of the blood used to generate DBS. A linear calibration line was established, with a Hct range of 0.19 to 0.63 (lower limit of quantification, LLOQ, to upper limit of quantification, ULOQ). The procedure was fully validated; the bias and imprecision of quality controls (QCs) at three Hct levels and at the LLOQ and ULOQ was less than 5 and 12%, respectively. In addition, the influence of storage (pre- and postextraction), volume spotted, and punch homogeneity was evaluated. Application on DBS from patient samples (n = 111), followed by Bland and Altman, Passing and Bablok, and Deming regression analysis, demonstrated a good correlation between the “predicted Hct” and the “actual Hct”. After correcting for the observed bias, limits of agreement of ±0.049 were established. Incurred sample reanalysis demonstrated assay reproducibility. In conclusion, potassium levels in extracts from 3 mm DBS punches can be used to get a good prediction of the Hct, one of the most important “unknowns” in DBS analysis