Improving clinical performance of urine sediment analysis by implementation of intelligent verification criteria
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Matthijs Oyaert
,
Sena Maghari
Abstract
Objectives
Urinary test strip and sediment analysis integrated with intelligent verification criteria can help to select samples that need manual review. This study aimed to evaluate the improvement in the diagnostic performance of combined urinary test strip and urinary sediment analysis using intelligent verification criteria on the latest generation automated test strip and urinary fluoresce flow cytometry (UFFC) analysers.
Methods
Urine test strip and sediment analysis were performed using the Sysmex UC-3500 and UF-5000 (Kobe, Japan) on 828 urinary samples at the clinical laboratory of the Ghent University Hospital. The results were compared to manual microscopy using phase-contrast microscopy as a reference. After the application of the intelligent verification criteria, we determined whether the diagnostic performance of urine sediment analysis could be improved.
Results
Application of intelligent verification criteria resulted in an increase in specificity from 88.5 to 96.8% and from 88.2 to 94.9% for red blood cells and white blood cells, respectively. Implementing review rules for renal tubular epithelial cells and pathological casts increased the specificity from 66.7 to 74.2% and from 96.2 to 100.0%, respectively; and improved the diagnostic performance of urinary crystals and atypical cells.
Conclusions
The implementation of review rules improved the diagnostic performance of UFFC, thereby increasing the reliability and quality of urine sediment results.
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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: The local Insitutional Review Board deemed the study exempt from review.
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2022-0617).
© 2022 Walter de Gruyter GmbH, Berlin/Boston
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