Skip to main navigation Skip to search Skip to main content

Comparison of bacterial detection performance between UF-5000 and USCANNER(E) based on urine culture

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Rapid and accurate diagnosis of urinary tract infections (UTIs) is essential for timely antimicrobial therapy. Although urine culture remains the gold standard, its prolonged turnaround time necessitates more efficient screening methods. This study evaluated and compared the performance of two automated urine sediment analyzers with distinct detection principles: the flow cytometry-based Sysmex UF-5000 and the image analysis-based TOYOBO USCANNER(E). Methods: We analyzed 244 clinical urine specimens collected between June and December 2024. Bacterial detection results from both analyzers were compared with urine culture, with positivity defined as ≥1 × 10⁴ CFU/mL. Results: The UF-5000 demonstrated excellent diagnostic performance, exhibiting almost perfect agreement with culture results (κ = 0.845), high sensitivity (93.3 %), and high specificity (95.5 %). ROC analysis confirmed its robust predictive value, with further improvements observed when sex-specific cutoffs were applied. In contrast, the USCANNER(E) initially showed fair agreement (κ = 0.287), which improved to moderate agreement (κ = 0.508) only after manual image editing, indicating that operator intervention is critical for its accuracy. While Gram staining showed substantial agreement with culture, it remained labor-intensive. Conclusion: The UF-5000 provides rapid, reliable bacterial detection with high concordance to urine culture and the potential to estimate Gram-staining characteristics. Our findings suggest that flow cytometry-based analyzers are highly effective for UTI screening and can significantly accelerate clinical decision-making in laboratory medicine.

Original languageEnglish
Article number117455
JournalDiagnostic Microbiology and Infectious Disease
Volume116
Issue number2
DOIs
Publication statusPublished - 10-2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Microbiology (medical)
  • Infectious Diseases

Fingerprint

Dive into the research topics of 'Comparison of bacterial detection performance between UF-5000 and USCANNER(E) based on urine culture'. Together they form a unique fingerprint.

Cite this