Filling in the GAPS: validation of anion gap (AGAP) measurement uncertainty estimates for use in clinical decision making

Jessica L. Gifford; Isolde Seiden-Long

doi:10.1515/cclm-2021-1279

Article

Filling in the GAPS: validation of anion gap (AGAP) measurement uncertainty estimates for use in clinical decision making

Jessica L. Gifford and Isolde Seiden-Long

Published/Copyright: April 20, 2022

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From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 60 Issue 6

Abstract

Objectives

We compare measurement uncertainty (MU) calculations to real patient result variation observed by physicians using as our model anion gap (AGAP) sequentially measured on two different instrument types. An approach for discretely quantifying the pre-analytical contributions and validating AGAP MU estimates for interpretation of patient results is proposed.

Methods

AGAP was calculated from sodium, chloride, and bicarbonate reported from chemistry or blood gas analyzers which employ different methodologies and specimen types. AGAP MU was calculated using a top-down approach both assuming no correlation between measurands and alternatively, including consideration of measurand correlation. MU-derived reference change values (RCV) were calculated between chemistry and blood gas analyzers results. Observational paired AGAP data (n=39,626 subjects) was obtained from retrospectively analyzed specimens from five urban tertiary care hospitals in Calgary, Alberta, Canada.

Results

The MU derived AGAP RCV for paired specimen data by the two platforms was 5.2–6.1 mmol/L assuming no correlation and 2.6–3.1 mmol/L assuming correlation. From the paired chemistry and blood gas data, total observed variation on a reported AGAP has a 95% confidence interval of ±6.0 mmol/L. When the MU-derived RCV assuming correlation is directly compared against the observed distribution of patient results, we obtained a pre-analytical variation contribution of 2.9–3.5 mmol/L to the AGAP observed variation. In contrast, assuming no correlation leads to a negligible pre-analytical contribution (<1.0 mmol/L).

Conclusions

MU estimates assuming no correlation are more representative of the total variation seen in real patient data. We present a pragmatic approach for validating an MU calculation to inform clinical decisions and determine the pre-analytical contribution to MU in this system.

Keywords: anion gap; blood gas instrumentation; clinical chemistry instrumentation; electrolytes; measurement uncertainty; pre-analytical variation

Corresponding author: Isolde Seiden-Long, Clinical Associate Professor, Alberta Precision Laboratories and Department of Pathology and Laboratory Medicine, University of Calgary, Foothills Medical Centre, McCaig Tower, Rm 7507, 7th Floor, 3134 Hospital Drive NW, Calgary, Canada, E-mail: isolde.seidenlong@aplabs.ca

Research funding: None declared.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
Informed consent: Not applicable.
Ethical approval: The local Institutional Review Board deemed the study exempt from review.

References

1. ISO/TS 20914:2019. Medical laboratories—practical guidance for the estimation of measurement uncertainty. International Organization for Standardization [Online]; 2019. Available from: https://www.iso.org/standard/69445.html.Search in Google Scholar

2. ISO. ISO 15189:2012. Medical laboratories—requirements for quality and competence. Int Organ Stand [Internet]; 2012. Available from: https://www.iso.org/standard/56115.html.Search in Google Scholar

3. Milinković, N, Jovičić, S, Ignjatović, S. Measurement uncertainty as a universal concept: can it be universally applicable in routine laboratory practice? Crit Rev Clin Lab Sci 2021;58:101–12. https://doi.org/10.1080/10408363.2020.1784838.Search in Google Scholar PubMed

4. Rigo-Bonnin, R, Canalias, F. Measurement uncertainty estimation for derived biological quantities. Clin Chem Lab Med 2020;59:E1–7. https://doi.org/10.1515/cclm-2020-1003.Search in Google Scholar PubMed

5. Farrance, I, Frenkel, R. Measurement uncertainty and the importance of correlation. Clin Chem Lab Med 2020;59:7–9. https://doi.org/10.1515/cclm-2020-1205.Search in Google Scholar PubMed

6. Goguen, J, Gilbert, J. Hyperglycemic emergencies in adults. Can J Diabetes 2018;42:S109–14. https://doi.org/10.1016/j.jcjd.2017.10.013.Search in Google Scholar PubMed

7. Braga, F, Panteghini, M. The utility of measurement uncertainty in medical laboratories. Clin Chem Lab Med 2020;58:1407–13. https://doi.org/10.1515/cclm-2019-1336.Search in Google Scholar PubMed

8. Padoan, A, Sciacovelli, L, Zhou, R, Plebani, M. Extra-analytical sources of uncertainty: which ones really matter? Clin Chem Lab Med 2019;57:1488–93. https://doi.org/10.1515/cclm-2019-0197.Search in Google Scholar PubMed

9. SLRE and AW, editors. Eurachem/CITAC guide: quantifying uncertainty in analytical measurement [Internet], 3rd ed.; 2012. Available from: http://www.eurachem.org.Search in Google Scholar

10. Fraser, CG. Reference change values. Clin Chem Lab Med 2012;50:807–12. https://doi.org/10.1515/cclm.2011.733.Search in Google Scholar PubMed

11. Fraser, CG. Biological variation: a rapidly evolving aspect of laboratory medicine. J Lab Precis Med 2017;2:35. https://doi.org/10.21037/jlpm.2017.06.09.Search in Google Scholar

12. CLSI. CLSI EP29-A. Expression of measurement uncertainty in laboratory medicine. Wayne, PA: CLSI; 2012.Search in Google Scholar

13. Dimeski, G, Morgan, TJ, Presneill, JJ, Venkatesh, B. Disagreement between ion selective electrode direct and indirect sodium measurements: estimation of the problem in a tertiary referral hospital. J Crit Care 2012;27:326.e9–16. https://doi.org/10.1016/j.jcrc.2011.11.003.Search in Google Scholar PubMed

14. Frezzotti, A, Maria, A, Gambini, M, Coppa, G, De Sio, G. Total carbon dioxide measured by the Vitros enzymatic method. Clin Chem Lab Med 1998;36:43–6. https://doi.org/10.1515/cclm.1998.008.Search in Google Scholar PubMed

Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2021-1279).

Received: 2021-12-07

Accepted: 2022-03-14

Published Online: 2022-04-20

Published in Print: 2022-05-25

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Supplementary Material Details

Articles in the same Issue

https://doi.org/10.1515/cclm-2021-1279

Keywords for this article

anion gap; blood gas instrumentation; clinical chemistry instrumentation; electrolytes; measurement uncertainty; pre-analytical variation