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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Ed. by Gillery, Philippe / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Payne, Deborah A. / Schlattmann, Peter / Tate, Jillian R.

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IMPACT FACTOR 2016: 3.432

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1437-4331
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Volume 53, Issue 7 (Jun 2015)

Issues

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

Mathias Bruegel / Dorothea Nagel / Manuela Funk / Petra Fuhrmann / Johannes Zander / Daniel Teupser
Published Online: 2015-01-13 | DOI: https://doi.org/10.1515/cclm-2014-0945

Abstract

Background: Various types of automated hematology analyzers are used in clinical laboratories. Here, we performed a side-by-side comparison of five current top of the range routine hematology analyzers in the setting of a university hospital central laboratory.

Methods: Complete blood counts (CBC), differentials, reticulocyte and nucleated red blood cell (NRBC) counts of 349 patient samples, randomly taken out of routine diagnostics, were analyzed with Cell-Dyn Sapphire (Abbott), DxH 800 (Beckman Coulter), Advia 2120i (Siemens), XE-5000 and XN-2000 (Sysmex). Inter-instrument comparison of CBCs including reticulocyte and NRBC counts and investigation of flagging quality in relation to microscopy were performed with the complete set of samples. Inter-instrument comparison of five-part differential was performed using samples without atypical cells in blood smear (n=292). Automated five-part differentials and NRBCs were additionally compared with microscopy.

Results: The five analyzers showed a good concordance for basic blood count parameters. Correlations between instruments were less well for reticulocyte counts, NRBCs, and differentials. The poorest concordance for NRBCs with microscopy was observed for Advia 2120i (Kendall’s τb=0.37). The highest flagging sensitivity for blasts was observed for XN-2000 (97% compared to 65%–76% for other analyzers), whereas overall specificity was comparable between different instruments.

Conclusions: 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.

This article offers supplementary material which is provided at the end of the article.

Keywords: complete blood count; differential; flagging quality; hematology analyzer; inter-instrument comparison

References

  • 1.

    Tan BT, Nava AJ, George TI. Evaluation of the Beckman Coulter UniCel DxH 800, Beckman Coulter LH 780, and Abbott Diagnostics Cell-Dyn Sapphire hematology analyzers on adult specimens in a tertiary care hospital. Am J Clin Pathol 2011;135:939–51.Web of ScienceGoogle Scholar

  • 2.

    Meintker L, Ringwald J, Rauh M, Krause SW. Comparison of automated differential blood cell counts from Abbott Sapphire, Siemens Advia 120, Beckman Coulter DxH 800, and Sysmex XE-2100 in normal and pathologic samples. Am J Clin Pathol 2013;139:641–50.Web of ScienceGoogle Scholar

  • 3.

    Hotton J, Broothaers J, Swaelens C, Cantinieaux B. Performance and abnormal cell flagging comparisons of three automated blood cell counters: Cell-Dyn Sapphire, DxH-800, and XN-2000. Am J Clin Pathol 2013;140:845–52.Web of ScienceGoogle Scholar

  • 4.

    Briggs C, Longair I, Kumar P, Singh D, Machin SJ. Performance evaluation of the Sysmex haematology XN modular system. J Clin Pathol 2012;65:1024–30.Web of ScienceGoogle Scholar

  • 5.

    ICSH guidelines for the evaluation of blood cell analysers including those used for differential leucocyte and reticulocyte counting. International Council for Standardization in Haematology, Writing Group: Briggs C, Culp N, Davis B, d`Onofrio G, Zini G, Machin SJ; the International Council for Standardization of Haematology. Int J Lab Hematol 2014;36:613–27.Web of ScienceGoogle Scholar

  • 6.

    Clinical and Laboratory Standards Institute. Reference leukocyte (WBC) differential count (proportional) and evaluation of instrumental methods; CLSI document H20-A2 Approved Standard, 2nd ed. Wayne, PA: CLSI, 2007.Google Scholar

  • 7.

    International Society for Laboratory Hematology. Consensus rules: consensus guidelines-positive smear findings. Available from: http://www.islh.org/2010/index.php?page=consensus_smear. Accessed on December 22, 2014.

  • 8.

    Müller R, Mellors I, Johannessen B, Aarsand AK, Kiefer P, Hardy J, et al. European multi-center evaluation of the Abbott Cell-Dyn sapphire hematology analyzer. Lab Hematol 2006;12:15–31.CrossrefPubMedGoogle Scholar

  • 9.

    Jean A, Boutet C, Lenormand B, Callat MP, Buchonnet G, Barbay V, et al. The new haematology analyzer DxH 800: an evaluation of the analytical performances and leucocyte flags, comparison with the LH 755. Int J Lab Hematol 2011;33:138–45.Web of ScienceGoogle Scholar

  • 10.

    Harris N, Jou JM, Devoto G, Lotz J, Pappas J, Wranovics D, et al. Performance evaluation of the ADVIA 2120 hematology analyzer: an international multicenter clinical trial. Lab Hematol 2005;11:62–70.PubMedCrossrefGoogle Scholar

  • 11.

    Passing H, Bablok W. A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, part I. J Clin Chem Clin Biochem 1983;21:709–20.PubMedGoogle Scholar

  • 12.

    Kendall MG. The treatment of ties in ranking problems. Biometrika 1945;33:239–51.Google Scholar

  • 13.

    Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10.Google Scholar

  • 14.

    Pipitone S, Pavesi F, Testa B, Bardi M, Perri GB, Gennari D, et al. Evaluation of automated nucleated red blood cells counting on Sysmex XE5000 and Siemens ADVIA 2120. Clin Chem Lab Med 2012;50:1857–9.Google Scholar

  • 15.

    Kwon MJ, Nam MH, Kim SH, Lim CS, Lee CK, Cho Y, et al. Evaluation of the nucleated red blood cell count in neonates using the Beckman Coulter UniCel DxH 800 analyzer. Int J Lab Hematol 2011;33:620–8.Web of ScienceGoogle Scholar

  • 16.

    Barnes PW, Eby CS, Shimer G. Blast flagging with the UniCel DxH 800 Coulter Cellular Analysis System. Lab Hematol 2010;16:23–5.Google Scholar

  • 17.

    Kim SJ, Kim Y, Shin S, Song J, Choi JR. Comparison study of the rates of manual peripheral blood smear review from 3 automated hematology analyzers, Unicel DxH 800, ADVIA 2120i, and XE 2100, using international consensus group guidelines. Arch Pathol Lab Med 2012;136:1408–13.Web of ScienceGoogle Scholar

  • 18.

    Trabuio E, Valverde S, Antico F, Manoni F, Gessoni G. Performance of automated platelet quantification using different analyzers in comparison with an immunological reference method in thrombocytopenic patients. Blood Transfus 2009;7:43–8.Web of ScienceGoogle Scholar

  • 19.

    Tanaka Y, Tanaka Y, Gondo K, Maruki Y, Kondo T, Asai S, et al. Performance evaluation of platelet counting by novel fluorescent dye staining in the XN-series automated hematology analyzers. J Clin Lab Anal 2014;28:341–8.Web of ScienceCrossrefPubMedGoogle Scholar

  • 20.

    Grimaldi E, Carandente P, Scopacasa F, Romano MF, Pellegrino M, Bisogni R, et al. Evaluation of the monocyte counting by two automated haematology analyzers compared with flow cytometry. Clin Lab Haematol 2005;27:91–7.Google Scholar

  • 21.

    Baschat AA, Gungor S, Kush ML, Berg C, Gembruch U, Harman CR. Nucleated red blood cell counts in the first week of life: a critical appraisal of relationships with perinatal outcome in preterm growth-restricted neonates. Am J Obstet Gynecol 2007;197:286.e1–8.Web of ScienceGoogle Scholar

  • 22.

    Stachon A, Segbers E, Holland-Letz T, Kempf R, Hering S, Krieg M. Nucleated red blood cells in the blood of medical intensive care patients indicate increased mortality risk: a prospective cohort study. Crit Care 2007;11:R62.CrossrefGoogle Scholar

  • 23.

    Tan BT, Nava AJ, George TI. Evaluation of the Beckman Coulter UniCel DxH 800 and Abbott Diagnostics Cell-Dyn Sapphire hematology analyzers on pediatric and neonatal specimens in a tertiary care hospital. Am J Clin Pathol 2011;135:929–38.Web of ScienceGoogle Scholar

  • 24.

    Eilertsen H, Vøllestad NK, Hagve TA. The usefulness of blast flags on the Sysmex XE-5000 is questionable. Am J Clin Pathol 2013;139:633–40.Web of ScienceGoogle Scholar

  • 25.

    Buttarello M, Plebani M. Automated blood cell counts: state of the art. Am J Clin Pathol 2008;130:104–16.Google Scholar

  • 26.

    Sandhaus LM, Osei ES, Agrawal NN, Dillman CA, Meyerson HJ. Platelet counting by the coulter LH 750, sysmex XE 2100, and advia 120: a comparative analysis using the RBC/platelet ratio reference method. Am J Clin Pathol 2002;118:235–41.Google Scholar

About the article

Corresponding author: Mathias Bruegel, Institute of Laboratory Medicine, Ludwig-Maximilians-University Munich, Marchioninistrasse 15, 81377 Munich, Germany, Phone: +49 89 4400 73209, Fax: +49 89 4400 78888, E-mail:


Received: 2014-09-24

Accepted: 2014-12-07

Published Online: 2015-01-13

Published in Print: 2015-06-01


Citation Information: Clinical Chemistry and Laboratory Medicine (CCLM), ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2014-0945.

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