Abstract
Objectives
To study the prevalence of trisodium citrate (Na3Citrate) contamination in hypernatraemic serum samples by direct measurement of citrate and to evaluate the performance of indirect markers for identification of Na3Citrate contamination.
Methods
Serum citrate was measured in all hypernatraemic serum samples (sodium ≥148 mmol/L) over a three-month period. The performance of serum chloride, sodium-chloride gap, indirect ion selective electrode (ISE)-direct ISE sodium disparity and osmolar gap in identification of Na3Citrate contaminated samples was assessed against the ‘gold-standard’ direct citrate measurement.
Results
In total, 27 Na3Citrate contaminated samples were identified based on serum citrate concentration ≥1.5 mmol/L. The prevalence of citrate contamination was 3.1 % of hypernatraemic samples (n=875) and 0.017 % of all samples received for urea and electrolyte analysis (n=153,404). Most contaminated samples were from patients receiving haemodialysis (59.3 %), and the rest from inpatients. Cut-offs to give 100 % sensitivity were chloride ≤105 nmol/L (specificity 93.4 %), sodium-chloride gap ≥47 mmol/L (specificity 95.3 %), indirect ISE-direct ISE sodium disparity ≥3 mmol/L (specificity 81.9 %), and osmolar gap ≥39 mOsm/kg (specificity 2.8 %).
Conclusions
Trisodium citrate contamination is uncommon. Most contaminated samples were from patients receiving haemodialysis, likely because of contamination with citrate catheter locking solution. Screening with serum chloride or sodium-chloride gap can confidently exclude Na3Citrate contamination in over 90 % of hypernatraemic samples, and in nearly all samples with sodium ≥155 mmol/L if metabolic alkalosis has been excluded. In the remaining samples, Na3Citrate contamination can only be definitively confirmed or excluded by measurement of serum citrate. We propose algorithms to identify spurious hypernatraemia.
Acknowledgments
Mr Steve Harris for data extraction from the Laboratory Information Management System.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: NL, TK and RG conceptualised the project. NL conducted the experiments and wrote the first draft. NL, TK and RG edited the manuscript. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cclm-2024-1389).
© 2025 Walter de Gruyter GmbH, Berlin/Boston
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- Perspectives
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- Candidate Reference Measurement Procedures and Materials
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