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Updated: Feb 27, 2026

Bergmeyer Glucose Quantification for Microbiological Samples
Published on: January 17, 2025
Blood Gas Analyzer Accuracy of Glucose Measurements
Yafen Liang1, Jonathan Wanderer1, James H Nichols2
1Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN.
Objective:
To investigate the comparability of glucose levels measured with blood gas analyzers (BGAs) and by central laboratories (CLs).
Material And Methods:
Glucose measurements obtained between June 1, 2007, and March 1, 2016, at the Vanderbilt University Medical Center were reviewed. The agreement between CL and BGA results were assessed using Bland-Altman, consensus error grid (CEG), and surveillance error grid (SEG) analyses. We further analyzed the BGAs' performance against the US Food and Drug Administration (FDA) 2014 draft guidance and 2016 final guidance for blood glucose monitoring and the International Organization for Standardization (ISO) 15197:2013 standard.
Results:
We analyzed 2671 paired glucose measurements, including 50 pairs of hypoglycemic values (1.9%). Bland-Altman analysis yielded a mean bias of -3.1 mg/dL, with 98.1% of paired values meeting the 95% limits of agreement. In the hypoglycemic range, the mean bias was -0.8 mg/dL, with 100% of paired values meeting the 95% limits of agreement. When using CEG analysis, 99.9% of the paired values fell within the no risk zone. Similar results were found using SEG analysis. For the FDA 2014 draft guidance, our data did not meet the target compliance rate. For the FDA 2016 final guidance, our data partially met the target compliance rate. For the ISO standard, our data met the target compliance rate.
Conclusion:
In this study, the agreement for glucose measurement between common BGAs and CL instruments met the ISO 2013 standard. However, BGA accuracy did not meet the stricter requirements of the FDA 2014 draft guidance or 2016 final guidance. Fortunately, plotting these results on either the CEG or the SEG revealed no results in either the great or extreme clinical risk zones.
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