ArticleTransfusion2026
Automated cell count for blood component quality control.
Article in Transfusion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Erratum issued
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate quantification of residual leukocytes (rWBC) and red blood cells (rRBC) in leukoreduced blood components is essential to ensure product quality and transfusion safety. Conventional manual flow cytometry techniques are time-consuming and analyst-dependent. In this study, we validated the XN-1000 Blood Bank (BB) mode as an automated alternative and compared its performance with our standard quality control (QC) workflow. STUDY DESIGN AND
methodsThe BB mode was validated for precision, linearity, and carry-over in detecting residual cells in red blood cell concentrates, platelet concentrates, and plasma products. Results obtained were compared to those of manual flow cytometry (for rWBC and rRBC) and impedance-based hematology analysis (for platelet counts) across over 1000 blood components.
resultsMethods validation showed high linearity, acceptable precision at low cell concentrations, and no analytical interference. Comparison between workflows revealed similar results for hemoglobin, hematocrit, and leukocyte counts. rRBC values measured by BB mode were ~2.3-fold higher than those obtained by manual flow cytometry, although all values remained within product specifications. Platelet counts were consistently higher with BB mode (PLT-F) than with impedance, with a 15-51% increase depending on the product. Flow cytometry confirmed that PLT-F results better reflect the true platelet content than impedance.
conclusionThe XN-1000 BB mode is a reliable and efficient alternative to manual methods for QC monitoring of blood components. It offers accurate residual cell quantification, increases laboratory throughput, and simplifies workflows.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.