XN-1000 Hematology Analyzer as an Alternative to Flow Cytometry for Measuring Residual Cells in Blood Components
Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies. Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured i...
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Published in | Annals of laboratory medicine Vol. 45; no. 4; pp. 437 - 449 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
Korean Society for Laboratory Medicine
01.07.2025
대한진단검사의학회 |
Subjects | |
Online Access | Get full text |
ISSN | 2234-3806 2234-3814 2234-3814 |
DOI | 10.3343/alm.2024.0448 |
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Abstract | Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies.
Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS).
rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in >90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively.
Sysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates. |
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AbstractList | Background: Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies.
Methods: Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytom- etry (fluorescence-activated cell sorting; FACS).
Results: rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15–0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correla- tion coefficients of 0.82–0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33–0.84) and rRBCs (0.61, 0.35–0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in >90% of RBC concen- trates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively.
Conclusions: Sysmex XN-1000 is suitable for residual cell measurements in RBC concen- trates and plasma, with some limitations for PLT concentrates. KCI Citation Count: 0 Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies.BackgroundMeasuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies.Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS).MethodsResidual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS).rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in ⟩90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively.ResultsrWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in ⟩90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively.Sysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates.ConclusionsSysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates. Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies. Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS). rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in >90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively. Sysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates. |
Author | Schmidt, Daniela Seekircher, Lisa Tschiderer, Lena Willeit, Peter Siller, Anita Schennach, Harald Amato, Marco |
AuthorAffiliation | 3 Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK 1 Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria 2 Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria |
AuthorAffiliation_xml | – name: 2 Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria – name: 1 Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria – name: 3 Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK |
Author_xml | – sequence: 1 givenname: Anita orcidid: 0009-0003-7860-7144 surname: Siller fullname: Siller, Anita organization: Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria – sequence: 2 givenname: Lisa orcidid: 0000-0003-0260-3262 surname: Seekircher fullname: Seekircher, Lisa organization: Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria – sequence: 3 givenname: Daniela orcidid: 0009-0002-4578-5086 surname: Schmidt fullname: Schmidt, Daniela organization: Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria – sequence: 4 givenname: Lena orcidid: 0000-0001-7988-853X surname: Tschiderer fullname: Tschiderer, Lena organization: Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria – sequence: 5 givenname: Peter orcidid: 0000-0002-1866-7159 surname: Willeit fullname: Willeit, Peter organization: Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK – sequence: 6 givenname: Harald orcidid: 0009-0005-8536-8780 surname: Schennach fullname: Schennach, Harald organization: Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria – sequence: 7 givenname: Marco orcidid: 0009-0002-4296-9760 surname: Amato fullname: Amato, Marco organization: Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH, Innsbruck, Austria |
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Keywords | Residual cells Flow cytometry Blood components Blood bank mode Sysmex XN-1000 |
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Snippet | Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy... Background: Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared... |
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SubjectTerms | Blood Platelets - cytology Erythrocytes - cytology Flow Cytometry - methods Humans Leukocytes - cytology Original Plasma - cytology 병리학 |
Title | XN-1000 Hematology Analyzer as an Alternative to Flow Cytometry for Measuring Residual Cells in Blood Components |
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