A STUDY TO ESTABLISH THE AGREEMENT BETWEEN THE RESULTS OF ELECTROLYTES (SERUM SODIUM AND POTASSIUM) ESTIMATED BY A WET CHEMISTRY INSTRUMENT (EASYLYTE) WITH THAT OBTAINED BY A DRY CHEMISTRY ANALYZER (VITROS 350)

Authors

  • SHARMISTHA CHATTERJEE Department of Biochemistry, College of Medicine and Sagore Dutta Hospital, Kolkata, West Bengal, India.
  • DIVYA M Department of Biochemistry, College of Medicine and Sagore Dutta Hospital, Kolkata, West Bengal, India.
  • KAUSHIK MAJUMDER Department of Biochemistry, College of Medicine and Sagore Dutta Hospital, Kolkata, West Bengal, India. https://orcid.org/0009-0008-9793-6310
  • INDRANIL CHAKRABORTY Department of Biochemistry, College of Medicine and Sagore Dutta Hospital, Kolkata, West Bengal, India. https://orcid.org/0000-0003-0135-2270

DOI:

https://doi.org/10.22159/ajpcr.2024.v17i6.50511

Keywords:

Measurement of electrolytes, Wet chemistry (easylyte),, Dry chemistry (vitros 300).

Abstract

Objectives: The objective of the study was to assess the agreement between results of electrolytes (serum sodium and potassium) estimated by a wet chemistry instrument with that obtained by a dry chemistry analyzer.

Methods: It was an observational analytical cross-sectional study done in the Departmental clinical laboratory. The samples were selected randomly from the usual lab workflow. All the samples were first run on the Easylyte (wet chemistry) and then run on the Vitros 350 (dry chemistry). The paired data thus obtained were compiled and tabulated and then statistically analyzed.

Results: The agreement of the results between the two methods was evaluated using the Bland–Altman difference plot and the Passing–Bablok Regression Equation and the Deming regression studies. By analyzing the diagram of Bland–Altman, it is seen that for sodium, the average bias is of −2.22; limits of agreement being −26.12–21.77. For potassium, Bland Altman plots show a bias of −0.21; limits of agreement −0.61–0.19. Passing Bablock regression calculated an intercept of −56.86, 95% confidence interval (CI) (−100, −28) and Slope of 1.43 for sodium measurements and calculated an intercept of −0.706, 95% CI (−0.66, −0.45) and Slope of 1.2 for potassium estimation.

Conclusion: Statistical analysis revealed conflicting solutions. There is a great discrepancy between the results of the electrolyte estimation by the two methods since the methodologies are not identical.

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References

Xi L, Hao YC, Liu J, Wang W, Wang M, Li GQ, et al. Associations between serum potassium and sodium levels and risk of hypertension: A community-based cohort study. J Geriatr Cardiol. 2015 Mar;12(2):119-26. doi: 10.11909/j.issn.1671-5411.2015.02.009, PMID 25870614.

Baruch HR, Hassan W, Mehta S. Eight steps to method validation in a clinical diagnostic laboratory. Am Soc Clin Lab 2018 Jan;31(1):43-7. doi: 10.29074/ascls.2018000307.

Westgard JO, Carey RN, Wold S. Criteria for judging precision and accuracy in method development and evaluation. Clin Chem. 1974;20(7):825-33. doi: 10.1093/clinchem/20.7.825, PMID 4835236.

Pant V, Tumbapo A, Karki B. Inter-instrumental comparison for the measurement of electrolytes in patients admitted to the intensive care unit. Int J Gen Med. 2017;10:145-9. doi: 10.2147/IJGM.S135788, PMID 28553133.

Passing H, Bablok. 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 Nov;21(11):709-20. doi: 10.1515/cclm.1983.21.11.709, PMID: 6655447.

Passing H, Bablok W. Comparison of several regression procedures for method comparison studies and determination of sample sizes. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part II. J Clin Chem Clin Biochem. 1984;22(6):431-45. doi: 10.1515/cclm.1984.22.6.431, PMID 6481307

Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986 Feb 8;1(8476):307-10. doi: 10.1016/j.ijnurstu.2009.10.001, PMID 2868172.

Giavarina D. Understanding Bland Altman analysis. Biochem Med (Zagreb). 2015 Jun 5;25(2):141-51. doi: 10.11613/BM.2015.015, PMID 26110027.

Bilic´ć-Zulle L. Comparison of methods: Passing and Bablok regression. Biochem Med (Zagreb). 2011;21(1):49-52. doi: 10.11613/ bm.2011.010, PMID 22141206.

Sutton A, Dawson H, Hoff B, Grift E, Shoukri M. Analyte comparisons between 2 clinical chemistry analyzers. Can Vet J. 1999 Apr;40(4):255- 60. PMID: 10200882, PMCID: PMC1539705.

Clinical and Laboratory Standards Institute. CLSI-EP09-A3: Method Comparison and Bias Estimation Using Patient Samples; Approved Guideline. 3rd ed., Vol. 33. Wayne, PA: Clinical and Laboratory Standards Institute; 2013.

Alumuri T, Merugu K, Amarababu NL, Kurnool A. Peramivir and related impurities in rat plasma and its applications in pharmacokinetic studies (bioanalytical method development and Validation by Lc-Ms/ Ms). Int J Appl Pharm. 2022;14(5):53-61.

Raikar PR, Dandagi PM. Functionalized polymeric nanoparticles: A novel targeted approach for oncology care. Int J Appl Pharm. 2021;13(6):1-18. doi: 10.22159/ijap.2021v13i6.42714.

Published

07-06-2024

How to Cite

CHATTERJEE, S., D. M, K. MAJUMDER, and I. CHAKRABORTY. “A STUDY TO ESTABLISH THE AGREEMENT BETWEEN THE RESULTS OF ELECTROLYTES (SERUM SODIUM AND POTASSIUM) ESTIMATED BY A WET CHEMISTRY INSTRUMENT (EASYLYTE) WITH THAT OBTAINED BY A DRY CHEMISTRY ANALYZER (VITROS 350)”. Asian Journal of Pharmaceutical and Clinical Research, vol. 17, no. 6, June 2024, pp. 122-6, doi:10.22159/ajpcr.2024.v17i6.50511.

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