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Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations

BACKGROUND: Urinary tract infection (UTI) is diagnosed combining urinary symptoms with demonstration of urine culture growth above a given threshold. Our aim was to compare the diagnostic accuracy of Urine Flow Cytometry (UFC) with urine test strip in predicting bacterial growth and in identifying c...

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Autores principales: Gehringer, Christian, Regeniter, Axel, Rentsch, Katharina, Tschudin-Sutter, Sarah, Bassetti, Stefano, Egli, Adrian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7908726/
https://www.ncbi.nlm.nih.gov/pubmed/33632129
http://dx.doi.org/10.1186/s12879-021-05893-3
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author Gehringer, Christian
Regeniter, Axel
Rentsch, Katharina
Tschudin-Sutter, Sarah
Bassetti, Stefano
Egli, Adrian
author_facet Gehringer, Christian
Regeniter, Axel
Rentsch, Katharina
Tschudin-Sutter, Sarah
Bassetti, Stefano
Egli, Adrian
author_sort Gehringer, Christian
collection PubMed
description BACKGROUND: Urinary tract infection (UTI) is diagnosed combining urinary symptoms with demonstration of urine culture growth above a given threshold. Our aim was to compare the diagnostic accuracy of Urine Flow Cytometry (UFC) with urine test strip in predicting bacterial growth and in identifying contaminated urine samples, and to derive an algorithm to identify relevant bacterial growth for clinical use. METHODS: Species identification and colony-forming unit (CFU/ml) quantification from bacterial cultures were matched to corresponding cellular (leucocytes/epithelial cells) and bacteria counts per μl. Results comprise samples analysed between 2013 and 2015 for which urine culture (reference standard) and UFC and urine test strip data (index tests, Sysmex UX-2000) were available. RESULTS: 47,572 urine samples of 26,256 patients were analysed. Bacteria counts used to predict bacterial growth of ≥10(5) CFU/ml showed an accuracy with an area under the receiver operating characteristic curve of > 93% compared to 82% using leukocyte counts. The relevant bacteriuria rule-out cut-off of 50 bacteria/μl reached a negative predictive value of 98, 91 and 89% and the rule-in cut-off of 250 bacteria/μl identified relevant bacteriuria with an overall positive predictive value of 67, 72 and 73% for microbiologically defined bacteriuria thresholds of 10(5), 10(4) or 10(3) CFU/ml, respectively. Measured epithelial cell counts by UFC could not identify contaminated urine. CONCLUSIONS: Prediction of a relevant bacterial growth by bacteria counts was most accurate and was a better predictor than leucocyte counts independently of the source of the urine and the medical specialty ordering the test (medical, surgical or others). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-021-05893-3.
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spelling pubmed-79087262021-02-26 Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations Gehringer, Christian Regeniter, Axel Rentsch, Katharina Tschudin-Sutter, Sarah Bassetti, Stefano Egli, Adrian BMC Infect Dis Research Article BACKGROUND: Urinary tract infection (UTI) is diagnosed combining urinary symptoms with demonstration of urine culture growth above a given threshold. Our aim was to compare the diagnostic accuracy of Urine Flow Cytometry (UFC) with urine test strip in predicting bacterial growth and in identifying contaminated urine samples, and to derive an algorithm to identify relevant bacterial growth for clinical use. METHODS: Species identification and colony-forming unit (CFU/ml) quantification from bacterial cultures were matched to corresponding cellular (leucocytes/epithelial cells) and bacteria counts per μl. Results comprise samples analysed between 2013 and 2015 for which urine culture (reference standard) and UFC and urine test strip data (index tests, Sysmex UX-2000) were available. RESULTS: 47,572 urine samples of 26,256 patients were analysed. Bacteria counts used to predict bacterial growth of ≥10(5) CFU/ml showed an accuracy with an area under the receiver operating characteristic curve of > 93% compared to 82% using leukocyte counts. The relevant bacteriuria rule-out cut-off of 50 bacteria/μl reached a negative predictive value of 98, 91 and 89% and the rule-in cut-off of 250 bacteria/μl identified relevant bacteriuria with an overall positive predictive value of 67, 72 and 73% for microbiologically defined bacteriuria thresholds of 10(5), 10(4) or 10(3) CFU/ml, respectively. Measured epithelial cell counts by UFC could not identify contaminated urine. CONCLUSIONS: Prediction of a relevant bacterial growth by bacteria counts was most accurate and was a better predictor than leucocyte counts independently of the source of the urine and the medical specialty ordering the test (medical, surgical or others). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-021-05893-3. BioMed Central 2021-02-25 /pmc/articles/PMC7908726/ /pubmed/33632129 http://dx.doi.org/10.1186/s12879-021-05893-3 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Gehringer, Christian
Regeniter, Axel
Rentsch, Katharina
Tschudin-Sutter, Sarah
Bassetti, Stefano
Egli, Adrian
Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title_full Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title_fullStr Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title_full_unstemmed Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title_short Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
title_sort accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7908726/
https://www.ncbi.nlm.nih.gov/pubmed/33632129
http://dx.doi.org/10.1186/s12879-021-05893-3
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