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Comparison of different autoanalyzers for the determination of lymphocyte and neutrophil counts in mouse blood

  • Saurabh Kumar Gupta , Dievya Gohil , Girish Ch. Panigrahi , Swati Vaykar , Pallavi Rane , Preeti Chavan and Vikram Gota EMAIL logo
Published/Copyright: December 1, 2021

Abstract

Objectives

Autoanalyzers are used in clinical haematology for analysis of blood samples in clinical as well as in nonclinical studies. The results from these analyzers vary from machine to machine. In this study, we compared the lymphocyte and neutrophil count of mouse blood between ADVIA 2120i, Horiba Yumizen H2500 and CellaVision analyzers against manual counting as gold standard.

Methods

Blood samples from 28 female BALB/c mice were collected and analyzed. Agreement between different autoanalyzers and manual counting were determined by Bland–Altman method.

Results

A high level of agreement was found between CellaVision and manual technique for lymphocyte (bias=4.75, 95% limits of agreement −14 to 24) and neutrophil count (bias=0.68 [−17 to 19]). Agreement in lymphocyte count was also observed between ADVIA and manual counting, but to a lesser extent compared to CellaVision (bias=13.9 [−10.45 to 38.27]). However, no agreement was observed for ADVIA (Neutrophils), Horiba (lymphocytes and neutrophils) with manual counting.

Conclusions

Our data suggests that CellaVision could be used for the differential counting of neutrophil and lymphocytes in mouse blood sample.


Corresponding author: Dr. Vikram Gota, Professor, Department of Clinical Pharmacology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Kharghar, Navi Mumbai 410210, India; and Homi Bhabha National Institute, Mumbai, India, E-mail:

Acknowledgments

We are thankful to laboratory animal facility, ACTREC for supply and maintenance of mice, we also express our sincere gratitude to Bharati Shriyan for guiding us with manuscript preparation and Khushboo Gandhi for helping us with the preclinical experiments.

  1. Research funding: None declared.

  2. Author contribution: SKG: Writing original draft, data collection, data analysis, investigation, visualization. DG: Data collection, Investigation. GCP: Data collection, Investigation. SV: Validation. PR: Statistical analysis. PC: Resources, validation, supervision, project administration. VG: Conceptualization, statistical analysis, resources, supervision, project administration, funding acquisition, writing – review & editing.All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Not applicable.

  5. Ethical approval: The study was approved by Institutional Animal Ethics Committee of Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial centre (TMC), Mumbai, India (Reg. no. 65/GO/ReBiBt/S/99/CPCSEA).

References

1. Miri-Dashe, T, Osawe, S, Daniel, MTN, Choji, RP, Mamman, I, Deme, K, et al.. Comprehensive reference ranges for hematology and clinical chemistry laboratory parameters derived from normal Nigerian adults. PLoS One 2014;9:e100601. https://doi.org/10.1371/journal.pone.0093919.Search in Google Scholar PubMed PubMed Central

2. Kakel, SJ. The evaluation of traditional and automatic Coulter method in estimation of haematological parameters in adult rats. Beni-Suef Univ J Basic Appl Sci 2013;2:31–5. https://doi.org/10.1016/j.bjbas.2013.09.004.Search in Google Scholar

3. Małecka, M, Ciepiela, O. A comparison of Sysmex-XN 2000 and Yumizen H2500 automated hematology analyzers. Pract Lab Med 2020;22:1–6.10.1016/j.plabm.2020.e00186Search in Google Scholar PubMed PubMed Central

4. Purushothaman, A. Comparison of manual vs. automated data collection method for haematological parameters. Biomed J Sci Tech Res 2019;15:11372–6. https://doi.org/10.26717/bjstr.2019.15.002702.Search in Google Scholar

5. Natiello, M, Kelly, G, Lamca, J, Zelmanovic, D, Chapman, RW, Phillips, JE. Manual and automated leukocyte differentiation in bronchoalveolar lavage fluids from rodent models of pulmonary inflammation. Comp Clin Pathol 2009;18:101–11. https://doi.org/10.1007/s00580-008-0772-9.Search in Google Scholar

6. McCarthy, JM, Capullari, T, Spellacy, WN. The correlation between automated hematology and manually read smears for the determination of nucleated red blood cells in umbilical cord blood. J Matern Fetal Neonatal Med 2005;17:199–201. https://doi.org/10.1080/14767050500073175.Search in Google Scholar PubMed

7. Ethier, JL, Desautels, D, Templeton, A, Shah, PS, Amir, E. Prognostic role of neutrophil-to-lymphocyte ratio in breast cancer: a systematic review and meta-analysis. Breast Cancer Res 2017;19:1–13. https://doi.org/10.1186/s13058-016-0794-1.Search in Google Scholar PubMed PubMed Central

8. Hoppe, BR, Lassen, ED. Blood smears and the use of Wright’s stain. Iowa State Univ Vet 1978;40:113–6.Search in Google Scholar

9. Kaufhold, AE, Hirschberger, J, Reese, S, Foerster, G, Hein, J. A comparison of manual counting of rabbit reticulocytes with ADVIA 2120i analyzer counting. J Vet Diagn Invest 2018;30:337–41. https://doi.org/10.1177/1040638717750428.Search in Google Scholar PubMed PubMed Central

10. Welles, EG, Hall, AS, Carpenter, DM. Canine complete blood counts: a comparison of four in-office instruments with the ADVIA 120 and manual differential counts. Vet Clin Pathol 2009;38:20–9. https://doi.org/10.1111/j.1939-165x.2008.00084.x.Search in Google Scholar

11. Ike, SO, Nubila, T, Ukaejiofo, EO, Nubila, IN, Shu, EN, Ezema, I. Comparison of haematological parameters determined by the Sysmex KX-2IN automated haematology analyzer and the manual counts. BMC Clin Pathol 2010;10:1–5. https://doi.org/10.1186/1472-6890-10-3.Search in Google Scholar PubMed PubMed Central

Received: 2021-07-08
Accepted: 2021-07-27
Published Online: 2021-12-01

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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