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

BMC Infect Dis

University Hospital Basel, Division of Clinical Bacteriology and Mycology, University of Basel, Petersgraben 4, 4031, Basel, Switzerland.

Published: February 2021

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 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, 10 or 10 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).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7908726PMC
http://dx.doi.org/10.1186/s12879-021-05893-3DOI Listing

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