title: Flow cytometry analysis using sysmex UF-1000i classifies uropathogens based on bacterial, leukocyte, and erythrocyte counts in urine specimens among patients with urinary tract infections.
abstract: Urinary tract infections (UTIs) are the second most common bacterial infection. Urine culture is the gold standard for diagnosis, but new techniques, such as flow cytometry analysis (FCA), have been introduced. The aim of the present study was to evaluate FCA characteristics regarding bacteriuria, leukocyturia, and erythrocyturia in relation to cultured uropathogens in specimens from patients with a suspected UTI. We also wanted to evaluate whether the FCA characteristics can identify uropathogens prior to culture. From a prospective study, 1,587 consecutive urine specimens underwent FCA prior to culture during January and February 2012. Outpatients and inpatients (79.6% and 19.4%, respectively) were included, of whom women represented 67.5%. In total, 620 specimens yielded growth, of which Escherichia coli represented 65%, Enterococcus spp. 8%, Klebsiella spp. 7%, and Staphylococcus spp. 5%. For the uropathogens, the outcome of FCA was compared against the results for specimens with E. coli and those with a negative culture. E. coli had high bacterial (median, 17,914/μl), leukocyte (median, 348/μl), and erythrocyte (median, 23/μl) counts. With the exception of Klebsiella spp., the majority of the uropathogens had considerable or significantly lower bacterial counts than that of E. coli. High leukocyte counts were found in specimens with Staphylococcus aureus, Proteus mirabilis, Pseudomonas aeruginosa, and group C streptococci. Elevated erythrocyte counts were found for P. vulgaris, P. aeruginosa, and group C streptococci, as well as for Staphylococcus saprophyticus. In essence, FCA adds new information about the bacterial, leukocyte, and erythrocyte counts in urine specimens for different uropathogens. Based on FCA characteristics, uropathogens can be classified and identified prior to culture. E. coli and Klebsiella spp. have similar FCA characteristics.
authors.affiliation: Department of Medical Microbiology, Umeå University, Umeå, Sweden tor.monsen@climi.umu.se.
authors.forename: Tor
authors.initials: T
authors.lastname: Monsen
authors.affiliation: Department of Mathematics and Mathematical Statistics, Umeå University, Umeå, Sweden Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.
authors.forename: Patrik
authors.initials: P
authors.lastname: Rydén
mesh_terms: D000328:Adult; D000368:Aged; D001424:Bacterial Infections / Q000175:diagnosis / Q000382:microbiology / Q000473:pathology; D058491:Bacterial Load / Q000379:methods*; D004906:Erythrocyte Count / Q000379:methods*; D005260:Female; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D007958:Leukocyte Count / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D014552:Urinary Tract Infections / Q000175:diagnosis* / Q000382:microbiology / Q000473:pathology; D014556:Urine / Q000166:cytology* / Q000382:microbiology*