Literature DB >> 26782662

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

Nicholas M Mohr1,2, Karisa K Harland1, Victoria Crabb3, Rachel Mutnick1, David Baumgartner1, Stephanie Spinosi1, Michael Haarstad1, Azeemuddin Ahmed1, Marin Schweizer4,5, Brett Faine1,6.   

Abstract

OBJECTIVES: The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination.
METHODS: Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria.
RESULTS: A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]).
CONCLUSIONS: Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures.
© 2016 by the Society for Academic Emergency Medicine.

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Year:  2016        PMID: 26782662     DOI: 10.1111/acem.12894

Source DB:  PubMed          Journal:  Acad Emerg Med        ISSN: 1069-6563            Impact factor:   3.451


  6 in total

1.  Urinary Lipidomics: evidence for multiple sources and sexual dimorphism in healthy individuals.

Authors:  J Graessler; C S Mehnert; K-M Schulte; S Bergmann; S Strauss; T D Bornstein; J Licinio; M-L Wong; A L Birkenfeld; S R Bornstein
Journal:  Pharmacogenomics J       Date:  2017-06-13       Impact factor: 3.550

2.  Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques.

Authors:  Martin Müller; Nadine Sägesser; Peter M Keller; Spyridon Arampatzis; Benedict Steffens; Simone Ehrhard; Alexander B Leichtle
Journal:  Diagnostics (Basel)       Date:  2022-04-16

3.  Influence of Storage Conditions and Preservatives on Metabolite Fingerprints in Urine.

Authors:  Xinchen Wang; Haiwei Gu; Susana A Palma-Duran; Andres Fierro; Paniz Jasbi; Xiaojian Shi; William Bresette; Natasha Tasevska
Journal:  Metabolites       Date:  2019-09-27

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

Authors:  Stefano Bassetti; Adrian Egli; Christian Gehringer; Axel Regeniter; Katharina Rentsch; Sarah Tschudin-Sutter
Journal:  BMC Infect Dis       Date:  2021-02-25       Impact factor: 3.090

5.  Urine collection devices to reduce contamination in urine samples for diagnosis of uncomplicated UTI: a single-blind randomised controlled trial in primary care.

Authors:  Gail Hayward; Sam Mort; Ly-Mee Yu; Merryn Voysey; Margaret Glogowska; Caroline Croxson; Yaling Yang; Julie Allen; Johanna Cook; Sarah Tearne; Nicola Blakey; Sharon Tonner; Vanshika Sharma; Meena Patil; Sadie Kelly; Christopher C Butler
Journal:  Br J Gen Pract       Date:  2022-02-24       Impact factor: 5.386

6.  The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.

Authors:  Martin Müller; Ruth Seidenberg; Sabine K Schuh; Aristomenis K Exadaktylos; Clyde B Schechter; Alexander B Leichtle; Wolf E Hautz
Journal:  PLoS One       Date:  2018-02-23       Impact factor: 3.240

  6 in total

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