Comparison of five automated hematology analyzers in a university hospital setting: Abbott Cell-Dyn Sapphire, Beckman Coulter DxH 800, Siemens Advia 2120i, Sysmex XE-5000, and Sysmex XN-2000
Abstract:To the best of our knowledge, this is the most comprehensive side-by-side comparison of five current top of the range routine hematology analyzers. Variable analyzer quality and parameter specific limitations must be considered in defining laboratory algorithms in clinical practice.
“…In considering the difference from our results, the two studies are not comparable due to a different study design, timing of data collection and instrumental acquisition. We used a newer automated NRBCs enumeration analyzer, which has a higher performance and sensitivity than previous instruments (Briggs et al, 2012b;Tantanate and Klinbua, 2015;Bruegel et al, 2015). The use of the same fully automated system and a microscopic verification for all our samples according to the CLSI standard H20-A2 (Koepke et al, 2010), ICSH (Briggs et al, 2014) and ISLH (Barnes et al, 2005) strengthens our results.…”
“…In considering the difference from our results, the two studies are not comparable due to a different study design, timing of data collection and instrumental acquisition. We used a newer automated NRBCs enumeration analyzer, which has a higher performance and sensitivity than previous instruments (Briggs et al, 2012b;Tantanate and Klinbua, 2015;Bruegel et al, 2015). The use of the same fully automated system and a microscopic verification for all our samples according to the CLSI standard H20-A2 (Koepke et al, 2010), ICSH (Briggs et al, 2014) and ISLH (Barnes et al, 2005) strengthens our results.…”
“…They are comparable only to a limited degree due to different representations as absolute and relative values. The literature has also described fluctuations due to different analyzers on multiple occasions [38,42,43]. Sysmex GmbH has described decreasing trends in adulthood [37], which partially matches the findings of this study.…”
Section: Discussionsupporting
confidence: 88%
“…It is virtually impossible for the generated measured values to harmonize perfectly due to the technical particulars of the different analyzers (different manufacturers, but also different models from a single manufacturer) [37]. As has been demonstrated, especially in the case of hemoglobin, the differences between various analyzers are minor compared to other hematological parameters [38]. Furthermore, differences can also be attributed to different criteria of inclusion and exclusion, as well as to the different statistical methods employed in the various studies.…”
Background: Pediatric reference intervals for iron-related parameters are determined continuously over time from a highly standardized sample collection by application of the R-package generalized additive models for location, scale and shape (GAMLSS), which is little known in laboratory medicine. Methods: Two thousand seven hundred and seventy-eight samples from Leipzig research center for civilization diseases (LIFE) Child participants at the age of 2.5-19 years were analyzed on a Sysmex XN-9000 for hemoglobin and reticulocytes and on a Roche Cobas 8000 for transferrin and ferritin. Reference intervals were established by repeated model calculation by use of the LMS (λ-μ-σ) method from Cole with specifically weighted subsamples. Results: Continuous and gender-specific reference intervals as well as smoothed percentile curves were
“…Briefly, this automated hematology analyzer uses scatter light and fluorescence labeling information to uniquely differentiate cell types 17 . This automated analyzer has been shown to perform well compared to other commercial methods or manual microscopy evaluations 18 . Data were reported for each sample as absolute counts of nucleated red blood cells (nRBCs), eosinophils, lymphocytes, monocytes, neutrophils, and basophils.…”
Cord blood is widely used as surrogate tissue in epigenome-wide association studies of prenatal conditions. Cell type composition variation across samples can be an important confounder of epigenome-wide association studies in blood that constitute a mixture of cells. We evaluated a newly developed cord blood reference panel to impute cell type composition from DNA methylation levels, including nucleated red blood cells (nRBCs). We estimated cell type composition from 154 unique cord blood samples with available DNA methylation data as well as direct measurements of nucleated cell types. We observed high correlations between the estimated and measured composition for nRBCs (r = 0.92, R2 = 0.85), lymphocytes (r = 0.77, R2 = 0.58), and granulocytes (r = 0.72, R2 = 0.52), and a moderate correlation for monocytes (r = 0.51, R2 = 0.25) as well as relatively low root mean square errors from the residuals ranging from 1.4 to 5.4%. These results validate the use of the cord blood reference panel and highlight its utility and limitations for epidemiological studies.
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