Home Paediatric reference intervals for haematology parameters analysed on Sysmex XN-9000: a comparison of methods in the framework of indirect sampling
Article
Licensed
Unlicensed Requires Authentication

Paediatric reference intervals for haematology parameters analysed on Sysmex XN-9000: a comparison of methods in the framework of indirect sampling

  • Kristina Laugesen EMAIL logo and Anne Winther-Larsen
Published/Copyright: November 25, 2024

Abstract

Objectives

To provide age- and sex-specific paediatric reference intervals (RIs) for 13 haematological parameters analysed on Sysmex XN-9000 and compare different methods for estimating RIs after indirect sampling.

Methods

Via the Danish Laboratory Information System, we conducted a population-based study. We identified samples from children aged 0–18 years analysed at Aarhus University Hospital from 2019 to 2023, including samples from general practitioners only. Information about all parameters were available for all samples via linkage to the local laboratory middleware. Then, we applied two different methods. First, we excluded potential pathological samples by predefined criteria: if the child had other abnormal blood measurements at date of request, or had a blood sample of any type analysed in the period two months before to two months after. We estimated RIs stratified by age- and sex using the non-parametric percentile method. Second, we used refineR (an open source automated algorithm) to exclude pathological samples and for RI estimation. Finally, we compared our data to results from a study using the direct method.

Results

We identified 22,786 samples. After exclusion by predefined criteria, the population comprised 10,199 samples from 8,736 children (57 % of samples were from females and median age was 13 years). We estimated RIs for red blood cell, white blood cell and platelet indices. The two different methods showed agreement. Furthermore, our data provided results comparable to direct sampling.

Conclusions

Our study provided age- and sex-specific paediatric RIs for 13 haematology parameters useful for laboratories worldwide. RIs were robust using different methods in the framework of indirect sampling. Finally, our data showed agreement with the direct method, indicating that indirect sampling could be useful for establishing RIs on haematology parameters in the future.


Corresponding author: Kristina Laugesen, Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus, Denmark; and Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Allé 43, 8200 Aarhus, Denmark, E-mail:

  1. Research ethics: The head of Aarhus University Hospital approved the study. Ethical approval is not required for this type of study.

  2. Informed consent: Not applicable.

  3. Author contributions: KL and AWL contributed to the design of the study and acquired the data. KL and AWL directed the analyses, which were carried out by KL. KL and AWL wrote the draft and contributed to the discussion and interpretation of the results. KL and AWL approved the final version for submission. KL is the guarantor. The corresponding author attests that both authors meet authorship criteria and that no others meeting the criteria have been omitted.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interests: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Owing to data protection rules, we are not allowed to share individual level data. Other researchers who fulfil the requirements set by the data providers could obtain similar data.

References

1. Jones, GRD, Haeckel, R, Loh, TP, Sikaris, K, Streichert, T, Katayev, A, et al.. Indirect methods for reference interval determination–review and recommendations. Clin Chem Lab Med 2018;57:20–9. https://doi.org/10.1515/cclm-2018-0073.Search in Google Scholar PubMed

2. Sysmex XN-9000. Available from: https://www.sysmex-ap.com/product/xn-9000/.Search in Google Scholar

3. Mrosewski, I, Dähn, T, Hehde, J, Kalinowski, E, Lindner, I, Meyer, TM, et al.. Indirectly determined hematology reference intervals for pediatric patients in Berlin and Brandenburg. Clin Chem Lab Med 2022;60:408–32. https://doi.org/10.1515/cclm-2021-0853.Search in Google Scholar PubMed

4. Mrosewski, I, Dähn, T, Hehde, J, Kalinowski, E, Lindner, I, Meyer, TM, et al.. Indirectly determined reference intervals for automated white blood cell differentials of pediatric patients in Berlin and Brandenburg. Clin Chem Lab Med 2023;61:1116–22. https://doi.org/10.1515/cclm-2022-1265.Search in Google Scholar PubMed

5. Pogorzelska, K, Krętowska, A, Krawczuk-Rybak, M, Sawicka-Żukowska, M. Characteristics of platelet indices and their prognostic significance in selected medical condition - a systematic review. Adv Med Sci 2020;65:310–5. https://doi.org/10.1016/j.advms.2020.05.002.Search in Google Scholar PubMed

6. Zierk, J, Arzideh, F, Rechenauer, T, Haeckel, R, Rascher, W, Metzler, M, et al.. Age- and sex-specific dynamics in 22 hematologic and biochemical analytes from birth to adolescence. Clin Chem 2015;61:964–73. https://doi.org/10.1373/clinchem.2015.239731.Search in Google Scholar PubMed

7. Ammer, T, Schützenmeister, A, Prokosch, HU, Rauh, M, Rank, CM, Zierk, J. refineR: a novel algorithm for reference interval estimation from real-world data. Sci Rep 2021;11:16023. https://doi.org/10.1038/s41598-021-95301-2.Search in Google Scholar PubMed PubMed Central

8. Bohn, MK, Higgins, V, Tahmasebi, H, Hall, A, Liu, E, Adeli, K, et al.. Complex biological patterns of hematology parameters in childhood necessitating age- and sex-specific reference intervals for evidence-based clinical interpretation. Int J Lab Hematol. 2020;42:750–60. https://doi.org/10.1111/ijlh.13306.Search in Google Scholar PubMed

9. Aarhus kommune. Available from: https://ledelsesinformation.aarhuskommune.dk/Embed#vfs://global/AARHUS-I-TAL/BEFOLKNING_I_TAL.xview.Search in Google Scholar

10. Arendt, JFH, Hansen, AT, Ladefoged, SA, Sørensen, HT, Pedersen, L, Adelborg, K. Existing data sources in clinical epidemiology: laboratory information system databases in Denmark. Clin Epidemiol 2020;12:469–75. https://doi.org/10.2147/clep.s245060.Search in Google Scholar

11. Schmidt, M, Schmidt, SAJ, Adelborg, K, Sundboll, J, Laugesen, K, Ehrenstein, V, et al.. The Danish health care system and epidemiological research: from health care contacts to database records. Clin Epidemiol 2019;11:563–91. https://doi.org/10.2147/clep.s179083.Search in Google Scholar

12. Haeckel, R, Wosniok, W, Arzideh, F. Equivalence limits of reference intervals for partitioning of population data. Relevant Diff Ref Limt 2016;40:199–205. https://doi.org/10.1515/labmed-2016-0002.Search in Google Scholar

13. Holmes, DT, van der Gugten, JG, Jung, B, McCudden, CR. Continuous reference intervals for pediatric testosterone, sex hormone binding globulin and free testosterone using quantile regression. J Mass Spectrom Adv Clin Lab 2021;22:64–70. https://doi.org/10.1016/j.jmsacl.2021.10.005.Search in Google Scholar PubMed PubMed Central

14. Aldrimer, M, Ridefelt, P, Rödöö, P, Niklasson, F, Gustafsson, J, Hellberg, D. Population-based pediatric reference intervals for hematology, iron and transferrin. Scand J Clin Lab Invest 2013;73:253–61. https://doi.org/10.3109/00365513.2013.769625.Search in Google Scholar PubMed

15. Tahmasebi, H, Higgins, V, Bohn, MK, Hall, A, Adeli, K. CALIPER hematology reference standards (I). Am J Clin Pathol 2020;154:330–41. https://doi.org/10.1093/ajcp/aqaa059.Search in Google Scholar PubMed PubMed Central

16. Strand, MF, Fredriksen, PM, Lindberg, M. Hematology reference intervals in 6-12-year-old children: the health-oriented pedagogical project (HOPP). Scand J Clin Lab Invest 2022;82:404–9. https://doi.org/10.1080/00365513.2022.2100820.Search in Google Scholar PubMed

17. Horowitz, G, Altaie, S, Boyd, C, Ceriotti, F, Garg, U, Horn, P, et al.. Defining, establishing, and verifying reference intervals in the clinical laboratory; approved guideline, 3rd ed. Wayne: Clinical and Laboratory Standards Institute; 2008. EP28-A3-c.Search in Google Scholar


Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2024-1179).


Received: 2024-08-22
Accepted: 2024-11-13
Published Online: 2024-11-25
Published in Print: 2025-03-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Beyond test results: the strategic importance of metadata for the integration of AI in laboratory medicine
  4. Reviews
  5. Reference, calibration and referral laboratories – a look at current European provisions and beyond
  6. How has the external quality assessment/proficiency testing of semen analysis been developed in the past 34 years: a review
  7. Opinion Papers
  8. Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?
  9. A comprehensive survey of artificial intelligence adoption in European laboratory medicine: current utilization and prospects
  10. Guidelines and Recommendations
  11. Guidelines for the correct use of the nomenclature of biochemical indices of bone status: a position statement of the Joint IOF Working Group and IFCC Committee on Bone Metabolism
  12. Candidate Reference Measurement Procedures and Materials
  13. Absolute quantitation of human serum cystatin C: candidate reference method by 15N-labeled recombinant protein isotope dilution UPLC-MS/MS
  14. General Clinical Chemistry and Laboratory Medicine
  15. Performance evaluation of the introduction of full sample traceability system within the specimen collection process
  16. Pre-analytical stability of haematinics, lactate dehydrogenase and phosphate in whole blood at room temperature up to 24 h, and refrigerated serum stability of lactate dehydrogenase, folate and vitamin B12 up to 72 h using the CRESS checklist
  17. Comparison of capillary finger stick and venous blood sampling for 34 routine chemistry analytes: potential for in hospital and remote blood sampling
  18. Performance evaluation of enzymatic total bile acid (TBA) routine assays: systematic comparison of five fifth-generation TBA cycling methods and their individual bile acid recovery from HPLC-MS/MS reference
  19. Clinical performance of a new lateral flow immunoassay for xylazine detection
  20. Evaluation of revised UK-NEQAS CSF-xanthochromia method for subarachnoid hemorrhage: outcome data provide evidence for clinical value
  21. Strategies to verify equimolar peptide release in mass spectrometry-based protein quantification exemplified for apolipoprotein(a)
  22. Evaluation of the clinical performance of anti-mutated citrullinated vimentin antibody and 14-3-3 eta testing in rheumatoid arthritis
  23. Diagnostic performance of specific biomarkers for interstitial lung disease: a single center study
  24. Reference Values and Biological Variations
  25. Neonatal reference intervals for serum steroid hormone concentrations measured by LC-MS/MS
  26. Paediatric reference intervals for haematology parameters analysed on Sysmex XN-9000: a comparison of methods in the framework of indirect sampling
  27. Cardiovascular Diseases
  28. Analytical characteristics and performance of a new hs-cTnI method: a multicenter-study
  29. Diabetes
  30. Use of labile HbA1c as a screening tool to minimize clinical misinterpration of HbA1c
  31. Letters to the Editor
  32. Current trends and future projections in the clinical laboratory test market: implications for resource management and strategic planning
  33. Particulate matter in water: an overlooked source of preanalytical error producing erroneous chemistry test results
  34. “Activation” of macro-AST by pyridoxal-5-phosphate in the assay for aspartate aminotransferase
  35. The correlation of albumin with total protein concentrations in cerebrospinal fluid across three automated analysers – relevance to the diagnosis of subarachnoid haemorrhage in clinical chemistry practice
  36. Adult reference intervals for serum thyroid‐stimulating hormone using Abbott Alinity i measuring system
  37. Cell population data in venous thrombo-embolism and erysipelas: a potential diagnostic tool?
  38. Diagnostic performances and cut-off verification of blood pTau 217 on the Lumipulse platform for amyloid deposition in Alzheimer’s disease
  39. The first case of Teclistamab interference with serum electrophoresis and immunofixation
  40. Congress Abstracts
  41. Annual meeting of the Royal Belgian Society of Laboratory Medicine (RBSLM): “A Neurological Journey: Brain Teasers for Laboratory Medicine”
Downloaded on 13.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2024-1179/html
Scroll to top button