Abstract
Objectives
Our study aimed to determine the usefulness of duplicate testing in identifying irregular analytical errors and subsequent prevention of patient mismanagement.
Methods
In our laboratory, all requests for Na+, Ca2+, alkaline phosphatase (ALP), and high-sensitivity cardiac-troponin-I (hs-cTnI) are run in duplicate. Data from four separate weeks for Na+ (n=21,649), Ca2+ (n=14,803) and ALP (n=19,698); and a full year for hs-cTnI (n=17,036) were gathered. For each test, pre-defined limits for differences between duplicates were used to identify erroneous results (Fliers). We further characterised a subset of such fliers as “critical errors”, where duplicates fell on opposing sides of a reference/decision making threshold. The costs/benefits of running these tests in duplicate were then considered in light of increased number of tests analysed by this approach.
Results
For Na+, 0.03 % of duplicates met our flier defining criteria, and 0.01 % of specimens were considered critical errors. For Ca2+ requests, 4.58 % of results met our flier defining criteria and 0.84 % were critical errors. For ALP, 0.22 % of results were fliers, and 0.01 % were critical errors. For hs-cTnI, 1.58 % of results were classified as fliers, whilst 0.14 % were classified as a critical error. Depending on the test in question, running all analyses in duplicate increased annual costs by as little as €1,100 (for sodium), and as much as €48,000 (for hs-cTnI).
Conclusions
Duplicate testing is effective at identifying and mitigating irregular laboratory errors, and is best suited for assays predisposed to such error, where costs are minimal, and clinical significance of an incorrect result can justify the practice.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: Authors state no conflict of interest.
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Research funding: None declared.
References
1. Schultze, AE, Irizarry, AR. Recognizing and reducing analytical errors and sources of variation in clinical pathology data in safety assessment studies. Toxicol Pathol 2016;45:281–7. https://doi.org/10.1177/0192623316672945.Search in Google Scholar PubMed
2. Wauthier, L, Plebani, M, Favresse, J. Interferences in immunoassays: review and practical algorithm. Clin Chem Lab Med 2022;60:808–20. https://doi.org/10.1515/cclm-2021-1288.Search in Google Scholar PubMed
3. Vogeser, M, Seger, C. Irregular analytical errors in diagnostic testing – a novel concept. Clin Chem Lab Med 2018;56:386–96. https://doi.org/10.1515/cclm-2017-0454.Search in Google Scholar PubMed
4. Bonini, P, Plebani, M, Ceriotti, F, Rubboli, F. Errors in laboratory medicine. Clin Chem 2002;48:691–8. https://doi.org/10.1093/clinchem/48.5.691.Search in Google Scholar
5. Hammerling, JA. A review of medical errors in laboratory diagnostics and where we are today. Lab Med 2012;43:41–4. https://doi.org/10.1309/lm6er9wjr1ihqauy.Search in Google Scholar
6. Aita, A, Sciacovelli, L, Plebani, M. Laboratory-related errors: you cannot manage what you don’t measure. You manage what you know and measure. Diagnosis (Berl) 2017;4:193–5. https://doi.org/10.1515/dx-2017-0038.Search in Google Scholar PubMed
7. De Grande, LAC, Goossens, K, Van Uytfanghe, K, Stockl, D, Theinpont, LM. The Empower project – a new way of assessing and monitoring test comparability and stability. Clin Chem Lab Med 2015;53:1197–204. https://doi.org/10.1515/cclm-2014-0959.Search in Google Scholar PubMed
8. Neubig, S, Grotevendt, A, Kallner, A, Nauck, M, Petersmann, A. Analytical robustness of nine common assays: frequency of outliers and extreme differences identified by a large number of duplicate measurements. Biochem Med 2017;27:192–8. https://doi.org/10.11613/bm.2017.021.Search in Google Scholar
9. Sana, N, Moiz, B, Raheem, A. Clinical significance of repeat testing of critical results in a haematology laboratory. Int J Lab Hematol 2020;42:e132–4. https://doi.org/10.1111/ijlh.13166.Search in Google Scholar PubMed
10. Chima, HS, Ramarajan, V, Bhansali, D. Is it necessary to repeat critical values in the laboratory? Today’s technology may have the answers. Lab Med 2009;40:453–7. https://doi.org/10.1309/lmmy883okbzqqbku.Search in Google Scholar
11. Lehman, CM, Howanitz, PJ, Souers, R, Karcher, DS. Utility of repeat testing of critical values: a Q-probes analysis of 86 clinical laboratories. Arch Pathol Lab Med 2014;138:788–93. https://doi.org/10.5858/arpa.2013-0140-cp.Search in Google Scholar PubMed
12. McIntosh, E, Andrews, PJ. Is sodium chloride worth its salt? Crit Care 2014;17:150. https://doi.org/10.1186/cc12732.Search in Google Scholar PubMed PubMed Central
13. Braun, MM, Barstow, CH, Pyzocha, NJ. Diagnosis and management of sodium disorders: hyponatremia and hypernatremia. Am Fam Physician 2015;91:299–307.Search in Google Scholar
14. George, JC, Zafar, W, Bucaloiu, ID, Chang, AR. Risk factors and outcomes of rapid correction of severe hyponatremia. Clin J Am Soc Nephrol 2018;13:984–92. https://doi.org/10.2215/cjn.13061117.Search in Google Scholar
15. Ruppe, MD. Medications that affect calcium. Endocr Pract 2011;17(1 Suppl):S26–30. https://doi.org/10.4158/ep10281.ra.Search in Google Scholar PubMed
16. Bazydlo, LAL, Needham, M, Harris, NS. Calcium, magnesium and phosphate. Lab Med 2014;45:e44–50. https://doi.org/10.1309/lmglmz8ciymfnogx.Search in Google Scholar
17. Epstein, E, Kiechle, FL, Artiss, JD, Zak, B. The clinical use of alkaline phosphatase enzymes. Clin Lab Med 1986;6:491–505. https://doi.org/10.1016/s0272-2712(18)30795-9.Search in Google Scholar
18. Vogelsang, H, Hamwi, H, Ferenci, P. Elevated liver isoenzymes of alkaline phosphatase and disease activity in patients with crohn’s disease. Digestion 1996;57:11–15. https://doi.org/10.1159/000201306.Search in Google Scholar PubMed
19. Sharma, U, Pal, D, Prasad, R. Alkaline phosphatase: an overview. Indian J Clin Biochem 2014;29:269–78. https://doi.org/10.1007/s12291-013-0408-y.Search in Google Scholar PubMed PubMed Central
20. Lee, GR, Browne, TCA, Guest, B, Khan, I, Murphy, E, McGorrian, C, et al.. Transitioning high sensitivity cardiac troponin I (hs-cTnI) into routine diagnostic use: more than just a sensitivity issue. Pract Lab Med 2016;4:62–75. https://doi.org/10.1016/j.plabm.2016.01.001.Search in Google Scholar PubMed PubMed Central
21. Ungerer, JPJ, Pretorius, CJ, Dimeski, G, O’Rourke, PK, Tyack, SA. Falsely elevated troponin I results due to outliers indicate a lack of analytical robustness. Ann Clin Biochem 2010;47:242–7. https://doi.org/10.1258/acb.2010.010012.Search in Google Scholar PubMed
22. Jaffe, AS. Troponin-past, present, and future. Curr Probl Cardiol 2012;37:209–28. https://doi.org/10.1016/j.cpcardiol.2012.02.002.Search in Google Scholar PubMed
23. Sawyer, N, Blennerhassett, J, Lambert, R, Sheehan, P, Vasikaran, SD. Outliers affecting cardiac troponin I measurement: comparison of a new high sensitivity assay with a contemporary assay on the Abbott ARCHITECT analyser. Ann Clin Biochem 2014;51:476–84. https://doi.org/10.1177/0004563213499737.Search in Google Scholar PubMed
24. Okyay, K, Yıldırır, A. The preanalytical and analytical factors responsible for false-positive cardiac troponins. Anatol J Cardiol 2015;15:264–5. https://doi.org/10.5152/akd.2015.6006.Search in Google Scholar PubMed PubMed Central
25. Favresse, J, Bayart, JL, Gruson, D, Bernardini, S, Clerico, A, Perrone, M. The underestimated issue of non reproducible cardiac troponin I and T results: case series 2 and systematic review of the literature. Clin Chem Lab Med 2020;59:1201–11. https://doi.org/10.1515/cclm-2020-1564.Search in Google Scholar PubMed
26. Nevraumont, A, Deltombe, M, Favresse, J, Guillaume, L, Chapelle, V, Twerenbold, R, et al.. Interferences with cardiac biomarker assays: understanding the clinical impact. Eur Heart J 2022;43:2286–8. https://doi.org/10.1093/eurheartj/ehab924.Search in Google Scholar PubMed
27. Favresse, J, Bayart, JL, Gruson, D, Bernardini, S, Clerico, A, Perrone, M. The underestimated issue of non-reproducible cardiac troponin I and T results: case series and systematic review of the literature. Clin Chem Lab Med 2021;59:1201–11. https://doi.org/10.1515/cclm-2020-1564.Search in Google Scholar
28. Panteghini, M, Ceriotti, F, Jones, G, Oosterhuis, W, Plebani, M, Sandberg, S, et al., Task Force on Performance Specifications in Laboratory Medicine of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). Strategies to define performance specifications in laboratory medicine: 3 years on from the milan strategic conference. Clin Chem Lab Med 2017;55:1849–56. https://doi.org/10.1515/cclm-2017-0772.Search in Google Scholar PubMed
29. Diaz-Garzon, J, Fernandez-Calle, P, Sandberg, S, Özcürümez, M, Bartlett, WA, Coskun, A, et al.. European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation and Task Group for the Biological Variation Database. Biological variation of cardiac troponins in health and disease: a systematic review and meta-analysis. Clin Chem 2021;67:256–64. https://doi.org/10.1093/clinchem/hvaa261.Search in Google Scholar PubMed
30. Aarsand, AK, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database. https://biologicalvariation.eu/ [Accessed 16 Jun 2022].Search in Google Scholar
31. Braga, F, Panteghini, M. Performance specifications for measurement uncertainty of common biochemical measurands according to Milan models. Clin Chem Lab Med 2021;59:1362–8. https://doi.org/10.1515/cclm-2021-0170.Search in Google Scholar PubMed
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