Urinary tract infections (UTIs) are among the most common bacterial infections, and while urine culture remains a frequently used diagnostic method in clinical microbiology laboratories, there is a growing need for rapid and accurate testing to ensure timely treatment [24]. This study evaluated the performance of urine flow cytometric screening using the UF-5000 and proposed an optimised workflow to efficiently differentiate between negative and likely positive urine samples while maintaining high diagnostic accuracy.
We analysed 4005 samples, comparing UFC results with culture results. Diagnostic cut-offs vary across laboratories due to differences in patient populations and different definitions used to classify significant bacteriuria. In our study, a UFC cut-off of < 30 cells/µl provided a balance between high sensitivity and reduced culture workload. Introduction of this method would decrease the need for urine cultures by > 30%, which is consistent with previous studies [12, 23, 25]. This reduction has substantial benefits, including lower costs, improved turnaround times, and decreased laboratory workload. Faster reporting of negative results allows > 30% of patients to receive same-day results. The rapid turnaround benefits both clinicians and patients by facilitating timely decision-making and improving antimicrobial stewardship. Despite these advantages, certain patient groups posed challenges. We observed lower agreement between flow cytometry and culture results in pregnant women, necessitating their exclusion from this workflow. Similarly, children showed reduced sensitivity and negative predictive value (NPV), leading to their exclusion as well. This aligns with Swedish UTI guidelines, which emphasise different diagnostic approaches for children and pregnant women [15]. Pregnant women are particularly at risk of complications, such as preterm birth and maternal hypertension, when bacteriuria remains untreated. Therefore, their urine samples should be cultured to detect uropathogens and group B streptococci [26]. Our data reinforce the recommendation that urine culture should remain the gold standard for these populations. Minimising false negatives is critical, as missing relevant infections can delay treatment.
False negatives are a known limitation of any screening approach. While false negatives do occur, they can be reduced through careful interpretation of the results and consideration of clinical factors. In our study, a total of 49 samples (1.5%) were negative by flow cytometry but positive by culture, of which three samples (0.09%) showed clinically significant bacteriuria (≥ 104 CFU/mL), representing the most relevant false negatives in our cohort (Tables 4 and S5). The remaining 46 samples either contained yeast (2/46), mixed flora (2/46) or had low bacterial counts (102–104 CFU/mL) (42/46). This highlights that most false negatives in urine screening involve low concentration uropathogens, which are more challenging to detect but may still be clinically relevant. Importantly, clinical context plays a critical role in interpretation. Our findings further highlight the importance of clear clinical communication. In many cases with low bacterial concentrations (102–104 CFU/mL), the absence of detailed clinical information led to uncertainty regarding the clinical significance and the need for AST. In 57% of these FN samples, the laboratory noted the clinical relevance as unclear, and in some cases, the indication for AST was not evident. This supports the need for improved dialogue between clinicians and the microbiology laboratory to ensure accurate interpretation and appropriate testing decisions, particularly in borderline or diagnostically complex cases. When available patient symptoms were taken into account (if provided to the laboratory), the number of potential false negatives dropped from 42 to 29 (0.89%), illustrating how combining clinical and laboratory information enhances diagnostic safety. This highlights the importance of clinicians providing accurate clinical information to support laboratory decision-making. Nevertheless, in specific high-risk populations, such as immunocompromised patients and those in intensive care, urine culture remains indispensable, even if screening results are negative. These groups may present with lower bacterial loads that are clinically important but harder to detect through screening alone. Therefore, while UFC offers substantial benefits in reducing unnecessary cultures and streamlining diagnostics, careful consideration of patient population and clinical presentation remains essential to avoid underdiagnosis. Tailored sensitivity thresholds or complementary testing may be appropriate in high-risk settings to ensure optimal patient care [27, 28]. To further reduce the risk of false negatives, especially in samples with low bacterial counts, laboratories may consider implementing a structured decision-making protocol that combines flow cytometry results with relevant available clinical information such as symptoms, history of recurrent infections, or other risk factors. Such a workflow can guide targeted antimicrobial susceptibility testing (AST) in borderline cases, ensuring that clinically relevant infections are not missed. This approach emphasises the importance of ongoing communication between clinicians and laboratory personnel to enhance diagnostic accuracy and patient care.
While elevated leukocyte counts are commonly associated with infection, our findings confirm that such parameters must be interpreted in the context of clinical information. In several cases (3), elevated leukocytes were observed in samples for which no AST was performed, as the clinical data did not indicate the need for further workup. This illustrates the inherent limitation of using UFC as a standalone tool and reinforces the essential role of clinical context in guiding appropriate diagnostics. A reliable screening algorithm must therefore be supported by accurate and accessible clinical information to optimise diagnostic decision-making. Each laboratory must carefully assess the risks and benefits of screening methods compared to urine culture to ensure appropriate diagnostic decisions.
UFC has long been recognised as an effective tool for identifying bacteriuria [13]. However, its predictive performance varies across patient subpopulations. Our study found that the positive predictive value (PPV) for pregnant women was only 62.2%, whereas in children, it was notably high at 96.9%, suggesting that flow cytometry could be useful for paediatric patients as previously shown [29]. In the subgroup analysis excluding pregnant women (n = 3574), a bacterial cut-off value of > 4000 cells/µl demonstrated strong diagnostic performance (96.4% sensitivity, 95.3% PPV). This is in line with previous studies and highlights the methods’ potential to accurately identify relevant bacteriuria across a broad patient population [4, 9, 14]. The 40 (1.1%) false positive samples were mostly due to mixed flora, indicating contamination or polymicrobial infections that are difficult to distinguish using flow cytometry alone. Given that all screening-positive samples proceed to culture, these cases can be clarified through confirmatory urine culture, ensuring accurate reporting and minimising the risk of misclassification.
Identification of the UTI-causing bacteria as soon as possible is important, especially in cases of UTI complicated by bacteraemia or sepsis, where targeted therapy could improve patient outcomes. In this study, we evaluated the performance of the Bact Info-flag “Gram Neg?” in a subpopulation excluding pregnant women. Our findings demonstrate that the flag was activated in 61% of samples classified as positive based on bacterial count (> 4000/µl). Notably, all flagged samples were culture-positive, underscoring the high specificity of this indicator for detecting true bacterial infections. A key observation was the strong concordance between the Gram classification provided by the flag and the culture results. In 96% of cases, there was full agreement between the flag and the Gram-negative species identified in culture. Additionally, partial agreement, where both Gram-negative and Gram-positive bacteria were detected, occurred in 3.3% of samples. Discrepancies were observed in only two cases (0.37%), suggesting a minimal rate of misclassification. The high specificity of the “Gram Neg?” flag highlights its potential use in laboratory workflows, particularly in rapidly distinguishing Gram-negative infections. This aligns with previous findings, where the “Gram Neg?” flag demonstrated good sensitivity and optimal specificity for predicting Gram-negative bacteria in culture, with an overall agreement of 99.8% when Gram negatives were present alone or together with Gram positives, and a very low discordance rate of 0.2% [4]. Given that Gram-negative bacteria often are associated with more severe UTIs and may require specific antibiotic treatments, early identification can support timely clinical decision-making. In urgent cases where immediate treatment is necessary, the ‘Gram Neg?’ flag may support early, targeted antibiotic initiation prior to culture confirmation. This could be particularly valuable in emergency settings or for vulnerable patient groups where treatment delays may have serious consequences. While further validation is needed, the flag may serve as a useful adjunct to guide empiric therapy decisions in appropriate clinical contexts. This could be particularly valuable in emergency settings or for vulnerable patient groups where treatment delays may have serious consequences. While further validation is needed, the flag may serve as a useful adjunct to guide empiric therapy decisions in appropriate clinical contexts.
Our proposed workflow for sorting urine samples based on screening results aims to optimise the laboratory workflow by reducing unnecessary cultures while maintaining diagnostic accuracy. The application of a < 30 BACT/µl rule for negative samples led to a 32% reduction in cultures, with a 55% decrease among negative samples in a population were pregnant women and children are excluded. This supports previous findings where a similar strategy was proposed highlighting the potential of such an approach in reducing laboratory workload while maintaining diagnostic safety [14]. The ability to confidently exclude a significant proportion of negative samples without additional testing is crucial for improving laboratory efficiency and resource allocation. For ruling in relevant bacteriuria, we established a cut-off of > 4000 cells/µl, providing a reliable indicator of clinically significant bacterial presence. The intermediate group with bacterial counts between 30 and 4000 cells/µl (51%) represents a diagnostic grey zone where culture remains necessary. Clinical context and additional diagnostic information are essential for safe decision-making until further refinements or supporting tools become available. The overall performance of our algorithm, as summarised in Table 8, supports its feasibility in routine laboratory practice, both for in- and out-patient samples. By implementing a structured decision-making process based on screening results, we can streamline urine diagnostics, minimising unnecessary cultures while ensuring that clinically significant cases are properly identified. Future studies should further validate these cut-offs in larger and more diverse populations, particularly in settings with different patient demographics or clinical guidelines. Additionally, integrating this algorithm with automated reporting systems could further enhance its practical application in high-throughput laboratories. Carryover and cross-contamination were minimal, which is crucial for microbiology screening, as the same tube is used for urine culture when the screening result is positive.
Limitations of the study: This study has several limitations. Its retrospective design may introduce selection bias and limits the control over sample handling and data collection. According to the manufacturer’s protocol, Sysmex UF-5000 analysis should ideally be performed on fresh urine samples within 4 h without preservatives. However, some outpatient samples required longer transport times and these could not be separately identified or excluded. This may affect the generalisability of our results to other settings where sample transport and processing times differ. Additionally, diagnostic cut-offs and bacteriological significance thresholds vary between laboratories and countries, which may limit direct applicability of our proposed cut-offs beyond our local context. European guidelines also highlight the importance of considering local epidemiology and clinical context when implementing new screening protocols [16, 22]. Future prospective studies in diverse clinical settings would help confirm the robustness and transferability of our findings.
