Abstract
Objectives
Lipemia is the presence of abnormally high lipoprotein concentrations in serum or plasma samples that can interfere with laboratory testing. There is little guidance available from manufacturers or professional bodies on processing lipemic samples to produce clinically acceptable results. This systematic review summarizes existing literature on the effectiveness of lipid removal techniques in reducing interference in clinical chemistry tests.
Methods
A PubMed search using terms relating to lipid removal from human samples for clinical chemistry tests produced 1,558 studies published between January 2010 and July 2021. 15 articles met the criteria for further analyses.
Results
A total of 66 analytes were investigated amongst the 15 studies, which showed highly heterogenous study designs. High-speed centrifugation was consistently effective for 13 analytes: albumin, alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, creatine kinase (CK), creatinine (Jaffe method), gamma-glutamyl transferase (GGT), glucose (hexokinase-based method), lactate dehydrogenase (LDH), phosphate, potassium, and urea. Lipid-clearing agents were uniformly effective for seven analytes: ALT, AST, total bilirubin, CK, creatinine (Jaffe method), lipase, and urea. Mixed results were reported for the remaining analytes.
Conclusions
For some analytes, high-speed centrifugation and/or lipid-clearing agents can be used in place of ultracentrifugation. Harmonized protocols and acceptability criteria are required to allow pooled data analysis and interpretation of different lipemic interference studies.
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Research funding: None declared.
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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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Informed consent: Not applicable.
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Ethical approval: Not applicable.
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2021-0979).
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