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Updated: Apr 22, 2026

Urinary Tract Infection in a Small Animal Model: Transurethral Catheterization of Male and Female Mice
Published on: December 1, 2017
Role of Flow Cytometry in the Diagnosis of Urinary Tract Infections
Emir Trnacevic1, Alma Trnacevic2, Mejrema Mahmutovic3
1Polyclinic of Laboratory Diagnostics/Medical Biochemistry and Laboratory Medicine, University Clinical Center Tuzla, Tuzla, BIH.
Introduction:
Traditional diagnostics rely on microscopy, dipstick tests, and the gold‑standard urine culture, which is reliable but time‑consuming. Flow cytometry for urinary analysis offers a fast, objective, and highly automated approach that can improve the selection of samples for culture and accelerate clinical decision‑making. Flow cytometry uses fluorescent and scatter detection to quantify cells, bacteria, and other particles in urine, processing thousands of events per sample and generating parameters that correlate with the presence of infection.
Methods:
This retrospective study included 200 hospitalized adult patients (>18 years) admitted to the Clinic for Infectious Diseases, University Clinical Center Tuzla in Tuzla, Bosnia and Herzegovina. A urinary tract infection (UTI) was diagnosed based on standardized clinical and laboratory criteria. Urine samples were analyzed using the Sysmex UF‑4000 flow cytometer, and diagnostic thresholds for leukocyte and bacterial counts were determined by receiver operating characteristic (ROC) analysis and Youden's Index.
Results:
Among 200 hospitalized patients, females predominated (124 vs. 76). Optimal cut-offs were ≥120/µL for leukocytes (area under the curve (AUC) 0.88, sensitivity 91.2%, specificity 75.3%) and ≥1367/µL for bacteria (AUC 0.95, sensitivity 90.3%, specificity 90.7%). Sex-specific analyses showed higher accuracy in males, with cut-offs of ≥1012/µL for bacteria (AUC 0.97) and ≥122/µL for leukocytes (AUC 0.94), while in females, the best thresholds were ≥1797/µL for bacteria (AUC 0.94) and ≥113/µL for leukocytes (AUC 0.84). The empirically developed UTI risk score (0-2) further improved stratification: Score 0 strongly predicted negative cultures (NPV >97%), while Score 2 was highly associated with positive cultures (PPV >94%).
Conclusions:
Automated urine flow cytometry offers a fast and accurate screening tool for UTIs, with bacterial counts outperforming leukocytes in diagnostic reliability. Sex-specific cut-offs and the UTI risk score enhance clinical applicability by improving stratification and reducing unnecessary cultures. While findings support integration of flow cytometry into routine practice, the single-center design, hospitalized cohort, and exclusion of pregnant women and children limit broader generalization, warranting validation in larger, multicenter studies.
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