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Licensed Unlicensed Requires Authentication Published by De Gruyter April 20, 2022

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 ORCID logo EMAIL logo



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.


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.


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).


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.

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:

  1. Research funding: None declared.

  2. Author contributions: 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 local Institutional Review Board deemed the study exempt from review.


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Supplementary Material

The online version of this article offers supplementary material (

Received: 2021-12-07
Accepted: 2022-03-14
Published Online: 2022-04-20
Published in Print: 2022-05-25

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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