Evidence Hub

Diagnostic Accuracy of Urine Flow Cytometry (UF) in Urinary Tract Infection (UTI) Detection and Management: A Systematic Review and Meta-Analysis

Kai-Wei Chang, Chung-You Tsai, Shin-Mei Wong, Jeff S. Chueh, Shang-Jen Chang

Diagnostics, 2026

1 citation

Abstract

Background: Urinary tract infections (UTIs) are prevalent bacterial infections associated with significant morbidity and healthcare burden. Traditional diagnosis relies on urine culture, which is limited by long turnaround times and potential contamination. Automated urine flow cytometry, particularly the UF-5000 (Sysmex Corporation, Kobe, Japan), offers rapid and precise screening through bacterial and white blood cell (WBC) quantification. This systematic review and meta-analysis evaluates the diagnostic accuracy of the UF-5000 for UTI screening. Methods: We searched PubMed, Embase, Science Direct, and Web of Science for studies assessing the UF-5000’s performance, including sensitivity and specificity, with a minimum sample size of 40 and at least 10 UTI cases. Quality assessment was performed using QUADAS-2. Pooled estimates for sensitivity, specificity, and agreement (kappa) were calculated using random-effects models. Results: Eighteen studies, encompassing 25,337 samples, were included in the analysis. Pooled sensitivity and specificity for bacterial count (nine studies) were 0.927 (95% CI, 0.872–0.959) and 0.751 (95% CI, 0.558–0.878), respectively. For WBC count (four studies), sensitivity was 0.897 (95% CI, 0.755–0.961) and specificity was 0.600 (95% CI, 0.293–0.844). The UF-5000 also demonstrated moderate agreement (pooled kappa 0.52, 95% CI, 0.08–0.79) in distinguishing Gram-negative bacteria. Conclusions: Despite heterogeneity across studies, the UF-5000…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free