Urine Particle Research Articles

Preservation of urine specimens for metabolic evaluation of recurrent urinary stone formers.

Stability of concentrations of urinary stone-related metabolites was analyzed from samples of recurrent urinary stone formers to assess necessity and effectiveness of urine acidification during collection and storage. First-morning urine was collected from 20 adult calcium-stone forming patients at Tomas Bata Hospital in the Czech Republic. Urine samples were analyzed for calcium, magnesium, inorganic phosphate, uric acid, sodium, potassium, chloride, citrate, oxalate, and urine particles. The single-voided specimens were collected without acidification, after which they were divided into three groups for storage: samples without acidification ("NON"), acidification before storage ("PRE"), or acidification after storage ("POST"). The analyses were conducted on the day of arrival (day 0, "baseline"), or after storage for 2 or 7days at room temperature. The maximum permissible difference (MPD) was defined as ±20 % from the baseline. The urine concentrations of all stone-related metabolites remained within the 20 % MPD limits in NON and POST samples after 2days, except for calcium in NON sample of one patient, and oxalate of three patients and citrate of one patient in POST samples. In PRE samples, stability failed in urine samples for oxalate of three patients, and for uric acid of four patients after 2days. Failures in stability often correlated with high baseline concentrations of those metabolites in urine. Detailed procedures are needed to collect urine specimens for analysis of urinary stone-related metabolites, considering both patient safety and stability of those metabolites. We recommend specific preservation steps.

Current urinalysis practices in Belgian laboratories towards the 2023 EFLM European urinalysis guideline

ABSTRACT Objectives/Background We aimed to investigate routine urinalysis practices in Belgian laboratories and verify these findings against the 2023 European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) European Urinalysis Guideline. Methods A questionnaire was developed to collect information on pre- to postanalytical aspects of urine test strip and particle analysis. The questionnaire was distributed by Sciensano to all Belgian laboratories, licensed to perform urine particle analysis. Results Sixty-six percent of the Belgian laboratories (75/113) participated. The responding laboratories served physicians in private (25%), hospital (60%) and university hospital (15%) setting. All laboratories performed test strip and particle analysis, predominantly automatically (97% and 96%, respectively). In addition, most laboratories (87%) used intelligent verification criteria to optimize diagnostic accuracy. Almost all laboratories (≥90%) screened and reported a minimal biochemistry panel (glucose, protein, pH, ketones) and particle count (red and white blood cells). Independent of the technology, a notable variability was observed regarding medical cut-off values and advanced particle differentiation and reporting. Internal quality control was extensively performed for urine test strip (91%) and particle analysis (96%), while external QC was less common (32% and 36%, respectively). Consequently, only few laboratories were ISO15189 accredited for urine test strip (15%) and particle analysis (17%). Conclusion There is considerable variability in current urinalysis performed in Belgian laboratories. The 2023 EFLM urinalysis guideline has the potential to guide clinical laboratories towards improving their urinalysis practices. Additional efforts are required to implement these recommendations into clinical practice in Belgium.

The EFLM European Urinalysis Guideline 2023.

The EFLM Task and Finish Group Urinalysis has updated the ECLM European Urinalysis Guidelines (2000) on urinalysis and urine bacterial culture, to improve accuracy of these examinations in European clinical laboratories, and to support diagnostic industry to develop new technologies. Graded recommendations were built in the following areas. Strategies of urine testing are described to patients with complicated or uncomplicated urinary tract infection (UTI), and high or low-risk to kidney disease. Patient preparation, and urine collection are supported with two quality indicators: contamination rate (cultures), and density of urine (chemistry, particles). Measurements of both urine albumin and α1-microglobulin are recommended for sensitive detection of kidney disease in high-risk patients. Performance specifications are given for urine protein measurements and quality control of multiproperty strip tests. Procedures for microscopy are reviewed for diagnostic urine particles, including urine bacteria. Technologies in automated particle counting and visual microscopy are updated with advice how to verify new instruments with the reference microscopy. Chromogenic agar is recommended as primary medium in urine cultures. Limits of significant growth are reviewed, with an optimised workflow for routine specimens, using leukocyturia to reduce less important antimicrobial susceptibility testing. Automation in bacteriology is encouraged to shorten turn-around times. Matrix assisted laser desorption ionization time-of-flight mass spectrometry is applicable for rapid identification of uropathogens. Aerococcus urinae, A. sanguinicola and Actinotignum schaalii are taken into the list of uropathogens. A reference examination procedure was developed for urine bacterial cultures.

The UF-5000 Atyp.C parameter is an independent risk factor for bladder cancer

Bladder carcinoma (BC) accounts for > 90% of all urothelial cancers. Pathological diagnosis through cytoscopic biopsy is the gold standard, whereas non-invasive diagnostic tools remain lacking. The “Atyp.C” parameter of the Sysmex UF-5000 urine particle analyzer represents the ratio of nucleus to cytoplasm and can be employed to detect urinary atypical cells. The present study examined the association between urinary Atyp.C values and BC risk. This two-center, retrospective case–control study identified clinical primary or newly recurrent BC (study period, 2022–2023; n = 473) cases together with controls with urinary tract infection randomly matched by age and sex (1:1). Urinary sediment differences were compared using non-parametric tests. The correlations between urinary Atyp.C levels and BC grade or infiltration were analyzed using Spearman’s rank correlation. The BC risk factor odds ratio of Atyp.C was calculated using conditional logistic regression, and potential confounder effects were adjusted using stepwise logistic regression (LR). Primary risk factors were identified by stratified analysis according to pathological histological diagnosis. The mean value of urinary Atyp.C in BC cases (1.30 ± 3.12) was 8.7 times higher than that in the controls (0.15 ± 0.68; P < 0.001). Urinary Atyp.C values were positively correlated with BC pathological grade and invasion (r = 0.360, P < 0.001; r = 0.367, P < 0.001). Urinary Atyp.C was an independent risk factor for BC and closely related with BC pathological grade and invasion. Elevated urinary Atyp.C values was an independent risk factor for BC. Our findings support the use of Atyp.C as a marker that will potentially aid in the early diagnosis and long-term surveillance of new and recurrent BC cases.

Urine particle analysis in detection of kidney diseases

Urine particle analysis in detection of kidney diseases

The performance of a Fully Automated Urine Particle Analyzer, Sysmex UF-5000, in detecting fastidious bacteria in urine samples

Several types of fastidious bacteria can cause tract infections. We evaluated the performance of counting fastidious bacteria using a Fully Automated Urine Particle Analyzer UF-5000. The results showed that UF-5000 counts fastidious bacteria in urine without the need for culture using measurement principles based on flow cytometry.

Consistency Analysis of the UF-1500 and UF-5000 Automated Urine Particle Analyzers.

The aim was to evaluate the consistency of the results between the UF-1500 and UF-5000, fully automated urine particle analyzers. A total of 554 randomly selected inpatient and outpatient urine samples were collected for analysis using the UF-1500, the UF-5000, and by manual microscopic examination. The coincidence rate, intraday repeatability, and interday reproducibility were evaluated on the UF-1500 and UF-5000. To analyze the review flags from the UF-1500, the UF-1500 results were compared to manual microscopy as the gold standard. The repeatability of red blood cells (RBCs), white blood cells (WBCs), epithelial cells (ECs), casts, and bacteria using the UF-1500 and UF-5000 is expressed as the relative standard deviations of the intraday and inter-day measurements. For the UF-1500, the relative standard deviation values ranged from 5.9% to 12.6% and 4.9% to 17.2% for the low and 1.6% to 9.3% and 2.3% to 16.9% for the high samples, respectively. The correlation co-efficient for RBCs, WBCs, ECs, SECs, casts, crystals, and bacteria for the UF-1500 were 0.981, 0.993, 0.968, 0.963, 0.821, 0.783, and 0.992, respectively. Review samples from the UF-1500 were confirmed by microscopic examination. Review flags for all 554 samples included 3 samples with "DEBRIS High" and 23 samples with "RBCs/YLC Abnormal classification". The identification of various urine components by both instruments meets laboratory requirements. These two instruments with different performances have specific characteristics and should be used based upon the needs of each laboratory.

Kidney macrophages tap the stream

Tissue-resident macrophages are essential for maintaining organismal homeostasis, but the precise mechanisms that macrophages use to perform this function are not fully understood. In this issue of Immunity, He etal. demonstrate that renal macrophages surveil and sample urine particles, ensuring optimal collecting duct flow and preventing kidney stone development.

Renal macrophages monitor and remove particles from urine to prevent tubule obstruction

When the filtrate of the glomerulus flows through the renal tubular system, various microscopic sediment particles, including mineral crystals, are generated. Dislodging these particles is critical to ensuring the free flow of filtrate, whereas failure to remove them will result in kidney stone formation and obstruction. However, the underlying mechanism for the clearance is unclear. Here, using high-resolution microscopy, we found that the juxtatubular macrophages in the renal medulla constitutively formed transepithelial protrusions and "sampled" urine contents. They efficiently sequestered and phagocytosed intraluminal sediment particles and occasionally transmigrated to the tubule lumen to escort the excretion of urine particles. Mice with decreased renal macrophage numbers were prone to developing various intratubular sediments, including kidney stones. Mechanistically, the transepithelial behaviors of medulla macrophages required integrin β1-mediated ligation to the tubular epithelium. These findings indicate that medulla macrophages sample urine content and remove intratubular particles to keep the tubular system unobstructed.

Microscopic urinary particle detection by different YOLOv5 models with evolutionary genetic algorithm based hyperparameter optimization

The diagnosis of kidney disease often involves analysing urine sediment particles. Traditionally, urinalysis was performed manually by collecting urine samples and using a centrifuge, which was prone to manual errors and relied on labour-intensive processes. Automated urine sediment microscopy, based on machine learning models, requires segmentation and feature extraction, which can hinder model performance due to intrinsic characteristics of microscopic images. Deep learning models based on convolutional neural networks (CNNs) often rely on a large number of manually annotated data, making the system computationally complex. This study propose an advanced deep learning model based on YOLOv5, which offers faster performance and requires comparatively less data. The proposed model used five variants of the YOLOv5 model (YOLOv5n, YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) to detect six categories of urine particles (erythrocyte, leukocyte, crystals, cast, mycete, epithelial cells) from microscopic urine sediment images. The dataset involved 5376 images of urine sediments with 6 particles. There are 30 sets of hyperparamreteres are employed in the YOLOv5 model. To optimize the hyperparameters and fine-tune with the urine sediment dataset and for training each model, the system employed a genetic algorithm (GA) based on evolutionary principles named as Evolutionary Genetic Algorithm (EGA). Among the six categories of detected particles mycete achieved maximum performance with a mAP of 97.6 % and crystals achieved minimum performance with a mAP of 81.7 % with YOLOv5x model compared to other particles. To optimize the hyperparameters for training each model, the system employed a genetic algorithm (GA) based on evolutionary principles named as Evolutionary Genetic Algorithm (EGA). Among all the models, YOLOv5l and YOLOv5x performed the best. YOLOv5l achieved a mean average precision (mAP) of 85.8 % while YOLOv5x achieved a mAP of 85.4 % at an IoU threshold of 0.5. The detection speed per image was 23.4 ms for YOLOv5l and 28.4 ms for YOLOv5x. The proposed method developed a faster and better automated microscopic model using advanced deep learning techniques to detect urinary particles from microscopic urine sediment images for kidney disease identification. The method demonstrated strong performance in urinalysis.

Evaluation of the fully automated urine particle analyzer UF-1500.

This study primarily assessed the performance of the UF-1500, the novel and compact model of the fully automated urine particle analyzer and evaluated its performance against the existing UF-5000 instrument. A total of 648 residual urine specimens were randomly collected and examined using both the UF-1500 and UF-5000 instruments as well as manual microscopy. For each parameter, the concordance rates and detection accuracy of the UF-1500 against manual microscopy were compared with the UF-5000. The concordance rates between the UF-1500 and manual microscopy were 75.3%-98.5%. The UF-1500 concordance rates within one group agreement were observed to be >90%, for all parameters except for YLCs. The differences within one group agreement between the UF-1500 and manual microscopy were insignificant, in comparison to the UF-5000, with exceptions noted for ECs and YLCs. The sensitivity and specificity of the UF-1500 for RBCs, WBCs, Squa.ECs, and BACT exceeded 80%, while the positive predictive values of ECs and CASTs were below 70%. The UF-1500 exhibited a performance that was comparable to the existing instrument, the UF-5000, and was suitable to be introduced in clinical practice. For the samples with suspected false-positive or false-negative results, a manual microscopic examination is required for accurate testing.

Proteomic profiling of urinary extracellular vesicles differentiates breast cancer patients from healthy women.

Urinary extracellular vesicles (uEVs) reflect the biological conditions of the producing cells. The protein profiling of uEVs allow us to better understand cancer progression in several cancers such as bladder cancer, prostate cancer and kidney cancer but has not been reported in breast cancer. We have, herein, aimed at quantifying the concentration and at generating the proteomic profile of uEVs in patients with breast cancer (BC) as compared to that of healthy controls (CT). Urine samples were collected from 29 CT and 47 patients with BC. uEVs were isolated by using differential ultracentrifugation, and were then characterized by Western blotting and transmission electron microscopy. Moreover, a nanoparticle tracking analysis was used in order to measure the concentration and the size distribution of urine particles and uEVs. The proteomic profiling of the uEVs was facilitated through LC-MS/MS. The uEV concentration was not significantly different between the assessed groups. The undertaken proteomic analysis revealed 15,473 and 11,278 proteins in the BC patients' group and the CT group, respectively. Furthermore, a heat map analysis revealed a differential protein expression, while a principal component analysis highlighted two clusters. The volcano plot indicated 259 differentially expressed proteins (DEPs; 155 up- and 104 down-regulated proteins) in patients with BC compared with CT. The up-regulated proteins from BC-derived uEVs were enriched in pathways related to cancer progression (i.e., cell proliferation, cell survival, cell cycle, cell migration, carbohydrate metabolism, and angiogenesis). Moreover, we verified the expression of the upregulated DEPs using UALCAN for web-based validation. Remarkably, the results indicated that 6 of 155 up-regulated proteins (POSTN, ATAD2, BCAS4, GSK3β, HK1, and Ki-67) were overexpressed in BC compared with normal samples. Since these six proteins often act as markers of cell proliferation and progression, they may be potential biomarkers for BC screening and diagnosis. However, this requires validation in larger cohorts.

HantaNet: A New MicrobeTrace Application for Hantavirus Classification, Genomic Surveillance, Epidemiology and Outbreak Investigations.

Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, analytics and reporting. With the possibility of hantavirus cases going undetected and spreading over international borders, a significant reporting delay can miss linked transmission events and impedes timely, targeted public health interventions. To overcome these challenges, we built HantaNet, a standalone visualization engine for hantavirus genomes that facilitates viral surveillance and classification for early outbreak detection and response. HantaNet is powered by MicrobeTrace, a browser-based multitool originally developed at the Centers for Disease Control and Prevention (CDC) to visualize HIV clusters and transmission networks. HantaNet integrates coding gene sequences and standardized metadata from hantavirus reference genomes into three separate gene modules for dashboard visualization of phylogenetic trees, viral strain clusters for classification, epidemiological networks and spatiotemporal analysis. We used 85 hantavirus reference datasets from GenBank to validate HantaNet as a classification and enhanced visualization tool, and as a public repository to download standardized sequence data and metadata for building analytic datasets. HantaNet is a model on how to deploy MicrobeTrace-specific tools to advance pathogen surveillance, epidemiology and public health globally.

B-029 Validation of an Automated Analyzer for Urine Microscopic Examination

Abstract Background Microscopic examination of urine sediment can be time-consuming and labor intensive. Automated analyzers can help to standardize resulting and reduce manual work. Urinalysis has traditionally utilized semi-quantitative grading scales, eg. “0–3/high power field”. The Sysmex UF 5000 (Symex, Kobe, JP) uses flow cytometry to enumerate microscopic particles including white and red blood cells (WBC, RBC), bacteria, casts, and epithelial cells (EC). We sought to validate the counting of these microscopic particles against our reference manual method, and also determine if the research parameters from the analyzer could be used to accurately measure other particles in urine (eg. crystals). Methods Residual urine samples were analyzed for microscopic particles both by the UF 5000 and manually using KOVA tubes (KOVA International, Garden Grove, CA). Particles were enumerated using the laboratory’s current semi-quantitative grading system. Exact agreement and agreement +/- one level were calculated. Results Conclusion The analyzer results were comparable to manual resulting; in discrepant cases, the UF result was typically higher than manual, which may reflect the increased sensitivity of this method. Additional studies are ongoing to determine if the UF 5000 research parameters are accurate for semi-quantitative reporting of pathologic casts, crystals, and yeast.

YOLOv5 based detector for eight different urine particles components on single board computer

AbstractUrine sediment examination (USE) is an important issue in the detection of urinary system diseases and is a prerequisite, especially in the diagnosis of kidney diseases. The low‐contrast urine sediment images contain many particles, and these particles are superimposed or adherent, making it difficult to detect and interpret the particles. In this paper, a YOLOv5‐based urine analysis system, which is one of the fastest and most successful architectures used for object detection, is presented to identify particles in urine. The artificial intelligence‐based system, which can recognize bacteria, leukocytes, erythrocytes, crystals, yeast, cylinders, epithelium, and other particles, provides counting and reporting of components in the images obtained from the centrifuged urine sample through a microscope. The system consists of taking images from the microscope and recording them on SBC (Single Board Computer), artificial intelligence‐based software running on SBC, and database systems where urine analysis results are recorded. Different YOLOv5x architectures were used to evaluate the performance of the system and Precision, Recall, mAP, and F1_score values were obtained as metrics. According to the results obtained with the YOLOv5n, YOLOv5s, and YOLOv5m architectures, the highest mAP value of the system, which can recognize eight different particles, was 95.8% with YOLOv5m. This artificial intelligence‐based system, which will help laboratory workers, will not only save time but also eliminate the standardization differences in manual microscopy and will provide benefits as full‐time educational material.

Comparison of the clinical performance of the Atyp.C parameter of the UF-5000 fully automated urine particle analyzer with that of microscopic urine sediment analysis

a) ObjectivesUrinalysis is one of the most common laboratory screening tests to detect problems in the renal and urinary system; however, they cannot detect atypical cells (Atyp.Cs). The Sysmex UF-5000, a fully automated urine particle analyzer, can detect Atyp.Cs via its Atyp.C parameter. This study aimed to compare the clinical value of the Atyp.C parameter with that of urine sediment microscopy. b) MethodA total of 471 leftover urine samples were submitted to the Department of Clinical Laboratory at the University of Tokyo Hospital for urinalysis by manual sediment microscopy examination and UF-5000 Atyp.C analysis. c) ResultOf 471 submitted samples, 117 were positive for Atyp.Cs by urine sediment and 354 samples were negative. The histological subtypes of the Atyp.Cs included 105 cases of suspected urothelial carcinoma cells, 10 suspected squamous carcinoma cells, and 2 of suspected adenocarcinoma cells. The Atyp.C values for the Atyp.C-positive and -negative groups were 2.64 ± 0.69 and 0.38 ± 0.16, respectively. The optimal Atyp.C cutoff value determined by the receiver operating characteristic curve analysis was 0.4/μL. The area under the curve was 0.856, with a sensitivity of 79.5% and specificity of 85.1%. Atyp.C values of the UF-5000 showed high predictive performance for Atyp.C-positive specimens identified by urine sediment microscopy. d) ConclusionsThis study shows that a combination of UF-5000 analysis and microscopic examination of urine sediment improves Atyp.C detection in urine sediment analysis. These results suggest that Atyp.C measured by UF-5000 could be a useful screening parameter in routine testing of urine samples.

Effect of hematuria on the kidney disease progression in IgA nephropathy patients with mild proteinuria and well-preserved renal function

ObjectiveTo investigate whether hematuria is a risk factor in IgA nephropathy (IgAN) patients with mild proteinuria and well-preserved renal function. MethodsThis retrospective study included a total of 63 IgAN patients, with complete clinical data available for 50 patients. Hematuria assessment was conducted using two methods: 1) an automated method using a urine particle analyzer, and 2) a manual method performed by a skilled examiner to examine microscopic urine sediment. ResultsThe results of hematuria measurement using both automated and manual methods showed a strong linear correlation (r = 0.78, P < 0.001). In IgAN patients, those with high urinary red blood cell count (U-RBCs) exhibited higher serum IgA levels compared to patients with low U-RBCs. Additionally, patients with crescent formation had higher levels of proteinuria compared to those without crescents. Patients who received immunosuppressive treatment displayed higher levels of systolic blood pressure (SBP) and mean arterial pressure (MAP), as well as lower levels of serum hemoglobin and albumin. They also had a higher prevalence of T1 lesions compared to patients who did not undergo immunosuppression. Furthermore, among patients with crescent formation, those who received immunosuppressive agents exhibited higher levels of SBP, diastolic blood pressure (DBP), MAP, and U-RBCs, as well as lower levels of albumin and proteinuria at the time of renal biopsy. No composite kidney endpoint events were observed in these groups of patients. The U-RBCs level was not identified as a risk factor influencing the decline of estimated glomerular filtration rate (eGFR) in IgAN. ConclusionsThe presence of hematuria at the time of biopsy was not found to be associated with kidney disease progression in IgAN patients who had mild proteinuria and well-preserved renal function. This suggests that it is possible that these patients may not derive significant benefits from immunosuppressive therapy.

Urine transfer devices may impact urinary particle results: a pre-analytical study.

Well-standardized procedures in the pre-analytical phase of urine diagnostics is of utmost importance to obtain reliable results. We investigated the effect of different urine collection methods and the associated urine transfer tubes on urine test strip and particle results. In total, 146 selected urine samples were subdivided into three different collection containers and subsequently transferred into its accompanying transfer tube (BD, Greiner, Sarstedt vacuum and Sarstedt aspiration). As reference, the original urine sample was directly measured on the analyser. Both chemical test strip analysis (Sysmex UC-3500) and fluorescence flow cytometry particle analysis (Sysmex UF-5000) were performed on all samples. No statistically significant differences in test strip results were found between the studied transfer methods. On the contrary, transfer of urine samples to the secondary tubes affected their particle counts. Clinically significant reductions in counts of renal tubular epithelial cells and hyaline casts were observed using the BD and Greiner transfer tubes and in counts of pathological casts using the BD, Greiner and Sarstedt vacuum tubes. The results of this study indicate that the use of urine transfer tubes may impact counts of fragile urine particles. Clinical laboratories need to be aware about the variation that urine collection methods can induce on urine particle counts.

Urachal Adenocarcinoma: a Case Report and Review of the Literature.

Urachal adenocarcinoma is one of the rare and aggressive neoplasms that often presents at an advanced stage and has a poor prognosis. Urachal adenocarcinoma makes up 0.17 to 0.34% of all bladder carcinomas. Patients commonly present with hematuria. Wide local excision of urachal mass with umbilicus and surrounding soft tissue en bloc combined with partial or radical cystectomy and bilateral pelvic lymphadenectomy is considered to be the primary surgical management. However, many publications in literature report that en bloc removal of tumor with umbilicus, entire urachal ligament, and bladder dome alone has long-term survival and disease-free period. Here, we present a case of a 50-year-old post-menopausal female patient with a fungating mass in the umbilical region of size approximately 10 cm in maximum diameter with mucopurulent discharge from the mass. The patient had no history of any hematuria, mucinuria, burning micturition, or any particles in urine. A laparotomy was performed, and tumor mass along with the cuff of the bladder dome was removed as en bloc along with umbilectomy. This case report highlights a rare case of urachal adenocarcinoma with a fungating mass of large size in a female patient which is otherwise more commonly seen in males. A review of published literature is also presented.

Combination of UC-3500 and UF-5000 as a quick and effective method to exclude bacterial urinary tract infection

BackgroundOur study aims to evaluate the performance of the combination of Sysmex urine dry chemistry analyzer UC-3500 and urine particle analyzer UF-5000 in screening bacterial urinary tract infection (UTI). MethodsWe analyzed 2000 urine specimens from patients with suspected UTI by using a urine dry chemistry analyzer (UC-3500) and a fully automated sediment analyzer (UF-5000). After being tested by the instrument, all specimens were sent to our clinical microbiology laboratory for culture. In addition, 600 urine specimens were selected to evaluate the accuracy of the six screening strategies established in this study. ResultsThe consistency of UF-5000 bacterial classification and bacterial culture was fair (Kappa = 0.339). The counts of WBC and BACT elevated with sequential group designs (P < 0.001). The cut-off value of WBC was 32.20/μL for males (AUC, 0.942, 95%CI, 0.930–0.955) and 39.15/μL for females (AUC, 0.931, 95%CI, 0.914–0.948). The sensitivity and specificity of WBC were relatively higher than those of BACT. Strategy④ and Strategy⑥ in all six strategies had a good negative predictive value (NPV) which was 98.73%. ConclusionUF-5000 bacterial classification cannot be used as a practical reference. 32.20/μL (male) and 39.15/μL (female) for WBC as well as 22.35/μL (male) and 127.25/μL (female) for BACT were used as cut-off values to effectively determine whether UTI occurs. WBC, BACT and LEU joint screening programs were suitable to rapidly and effectively exclude bacterial UTI.