European Journal of Therapeutics
Original Article

Comparison of Urine Culture and Flow Cytometric Methods for Detecting Bacteriuria by Using a Simulation Model


Department of Medical Biochemistry, Gaziantep University Faculty of Medicine, Gaziantep, Turkey


Department of Medical Microbiology, Gaziantep University Faculty of Medicine, Gaziantep, Turkey

Eur J Ther 2021; 27: 206-209
DOI: 10.5152/eurjther.2021.21051
Read: 423 Downloads: 273 Published: 29 September 2021

Objective: We aimed to simulate and assess a new screening model to determine and exclude culture negative urine samples before culturing for patients with preliminary diagnosis of urinary tract infections (UTIs). This prospective and single-center research included a simulation model that studied in a central laboratory between March and April 2020. All samples studied fluorescent flow cytometry (FC) analyzer and then inoculated to medium.

Methods: Simulations of infected urine were created by mixing certain amounts microorganisms with the urine. Standard Escherichia coli, Enterococcus faecalis, Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans strains, one Lactobacillus spp., and one Staphylococcus epidermidis clinical isolate were used in the study. After the dilution process, 42 infected urine samples were analyzed using UF5000i FC device and urine culture method. Correlation between the methods (culture and FC) for bacterial counts was assessed with the in-class correlation coefficient and Spearman correlation coefficient.

Results: A significant agreement was observed between the methods only for the urine dilution containing 105 CFU mL1 pathogen.

Conclusion: The flow cytometric system failed to predict bacteriuria and the risk of urinary tract infection in our simulation model. Further research in combination with other parameters is needed to see the real power of flow cytometric methods for screening UTIs.

How to cite: Isbilen E, Zer Y, Gazel D, C eylan K. Comparison of Urine Culture and Flow Cytometric Methods for Detecting Bacteriuria by Using a Simulation Model. Eur J Ther 2020; 27(3): 206-209.

EISSN 2564-7040