A novel approach to screening and managing the urinary tract infections suspected sample in the general human population - Szmulik, Magdalena; Trześniewska-Ofiara, Zuzanna; Mendrycka, Mariola; Woźniak-Kosek, Agnieszka (Frontiers in Cellular and Infection Microbiology, 2022)
Background: Urinary tract infections (UTIs) are some of the most common bacterial infections, affecting 150 million people each year worldwide. In the treatment of UTI excessive use of antibiotics is observed, including both broad-spectrum and niched antibiotics. Additionally, UTIs are the most frequent healthcare-associated infection, nosocomial as well as post-hospital infections. A clear multi-strategy to stop this widespread antimicrobial resistance and improve UTI diagnostic strategy is needed. Automated urine technology providing standard urinalysis data can be used to support clinicians in screening and managing the UTI suspected sample. Fully automated urinalysis systems have expanded in laboratory practice. Commonly were used devices based on digital imaging with automatic particles recognition and flow cytometry analysis. Methods: A total of 1131 urine samples were analyzed on both automated urinalysis systems. The chemical components of urinalysis (leukocyte esterase and nitrate-reductase), and sediment results (leukocytes and bacteria) were investigated as potential UTI indicators. Additionally, 106 specimens were analyzed on UF-5000 and compared with culture plating to establish cut-offs that can be suitable for standard urinalysis requirements and help to guide how to interpret urinalysis results in the context of cultivation reflex. Results: Satisfactory sensitivity 100%, specificity (83,7%), negative predictive value (100%) positive predictive value (75%) was obtained using indicators with cut-off values: leukocytes ≥ 40/µl or bacteria ≥ 300/µl Conclusions: Accurate urinalysis gives information about the count of bacteria and leukocytes as useful indicators in UTIs, which were substantiated by multiple studies. It can be a future tool to cross-link clinical and microbiology laboratories. However, the cut-off adjustments require individual optimization.