Evidence map›Paper›PMID 42011471›Full record

ArticleCureus2026

Role of Flow Cytometry in the Diagnosis of Urinary Tract Infections.

Emir Trnacevic, Alma Trnacevic, Mejrema Mahmutovic, Humera Porobic Jahic, Amela Becirovic, Jasmina Selimovic

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Emir TrnacevicPolyclinic of Laboratory Diagnostics/Medical Biochemistry and Laboratory Medicine, University Clinical Center Tuzla, Tuzla, BIH.
Alma TrnacevicClinic of Infectious Diseases/Infectious Diseases, University Clinical Center Tuzla, Tuzla, BIH.
Mejrema MahmutovicPolyclinic of Laboratory Diagnostics, University Clinical Center Tuzla, Tuzla, BIH.
Humera Porobic JahicClinic of Infectious Diseases/Infectious Diseases, University Clinical Center Tuzla, Tuzla, BIH.
Amela BecirovicPolyclinic of Laboratory Diagnostics/Microbiology, University Clinical Center Tuzla, Tuzla, BIH.
Jasmina SelimovicClinic of Cardiovascular Surgery/Anesthesiology, University Clinical Center Tuzla, Tuzla, BIH.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTraditional 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.

methodsThis 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.

resultsAmong 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%).

conclusionsAutomated 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.

Indexed as

bacterial countbacteriuriaflow cytometryleukocyte counturinary tract infection

Identifiers

PMID42011471
PMCPMC13092099

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.