Advances and Progress in Automated Urine Analyzers.

The clinical analysis of urine has classically focused on conventional chemical-based urinalysis and urine microscopy. Contemporary advances in both analysis subsets have started to employ new technologies such as automated image analysis, flow cytometry, and mass spectrometry. In addition to new detection technologies, current analyzers have incorporated more advanced imaging, automated sample handing, and machine learning analyses into their workflow. The most advanced semiautomated analyzers can be interfaced with hospital medical record systems, and in the point-of-care setting, smartphones can be used for image analysis. This review will discuss current technological advancements in the field of urinalysis and urine microscopy.

A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-Hour Urine Data.

Objectives: The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant limitation for clinical trials, where many patients must be enrolled to obtain sufficient stone events for analysis. In this study, we sought to use machine learning methods to identify a novel algorithm to predict stone recurrence. Subjects/Patients and Methods: Patients enrolled in the Registry for Stones of the Kidney and Ureter (ReSKU), a registry of nephrolithiasis patients collected between 2015-2020, with at least one prospectively collected 24-hour urine test (Litholink 24-hour urine test; Labcorp) were included in the training set. A validation set was obtained from chart review of stone patients not enrolled in ReSKU with 24-hour urine data. Stone events were defined as either an office visit where a patient reports symptomatic passage of stones or a surgical procedure for stone removal. Seven prediction classification methods were evaluated. Predictive analyses and receiver operator characteristics (ROC) curve generation were performed in R. Results: A training set of 423 kidney stone patients with stone event data and 24-hour urine samples were trained using the prediction classification methods. The highest performing prediction model was a Logistic Regression with ElasticNet machine learning model (area under curve [AUC] = 0.65). Restricting analysis to high confidence predictions significantly improved model accuracy (AUC = 0.82). The prediction model was validated on a validation set of 172 stone patients with stone event data and 24-hour urine samples. Prediction accuracy in the validation set demonstrated moderate discriminative ability (AUC = 0.64). Repeat modeling was performed with four of the highest scoring features, and ROC analyses demonstrated minimal loss in accuracy (AUC = 0.63). Conclusion: Machine-learning models based on 24-hour urine data can predict stone recurrences with a moderate degree of accuracy.

Trends in urine sampling rates of general practice patients with suspected lower urinary tract infections in England, 2015-2022: a population-based study.

OBJECTIVES: Inappropriate prescribing of antibiotics is a key driver of antimicrobial resistance. This study aimed to describe urine sampling rates and antibiotic prescribing for patients with lower urinary tract infections (UTIs) in English general practice. DESIGN: A retrospective population-based study using administrative data. SETTING: IQVIA Medical Research Database (IMRD) data from general practices in England, 2015-2022. PARTICIPANTS: Patients who have consulted with an uncomplicated UTI in England general practices captured in the IMRD. OUTCOME MEASURES: Trends in UTI episodes (episodes were defined as UTI diagnosis codes occurring within 14 days of each other), testing and antibiotic prescribing on the same day as initial UTI consultation were assessed from January 2015 to December 2022. Associations, using univariate and multivariate logistic regressions, were examined between consultation and demographic factors on the odds of a urine test. RESULTS: There were 743 350 UTI episodes; 50.8% had a urine test. Testing rates fluctuated with an upward trend and large decline in 2020. Same-day UTI antibiotic prescribing occurred in 78.2% of episodes. In multivariate modelling, factors found to decrease odds of a urine test included age ≥85 years (0.83, 95% CI 0.82 to 0.84), consultation type (remote vs face to face, 0.45, 95% CI 0.45 to 0.46), episodes in London compared with the South (0.74, 95% CI 0.72 to 0.75) and increasing practice size (0.77, 95% CI 0.76 to 0.78). Odds of urine tests increased in males (OR 1.11, 95% CI 1.10 to 1.13), for those episodes without a same-day UTI antibiotic (1.10, 95% CI 1.04 to 1.16) for episodes for those with higher deprivation status (Indices of Multiple Deprivation 8 vs 1, 1.51, 95% CI 1.48 to 1.54). Compared with 2015, 2016-2019 saw increased odds of testing while 2020 and 2021 saw decreases, with 2022 showing increased odds. CONCLUSION: Urine testing for UTI in general practice in England showed an upward trend, with same-day antibiotic prescribing remaining consistent, suggesting greater alignment to national guidelines. The COVID-19 pandemic impacted testing rates, though as of 2022, they began to recover.

Significance of scattered small echogenic foci floating in urinary bladder as ultrasonography finding in dogs.

BACKGROUND: Despite the prevalence of echogenic foci floating in the urinary bladder seen in ultrasonography in dogs, surprisingly little has been written on its significance, including its potential association with urinalysis. The objective of the study was to determine the diagnostic value of the echogenic foci floating in urinary bladders in dogs. RESULTS: - Cystosonography was performed on 45 dogs. Bladder contents were examined and divided into positive (containing echogenic particles) and negative (absent echogenic particles) groups according to the presence and absence of floating echogenic particles. Five mL of urine was collected via cystocentesis. Urine analysis and culture were done and the relationship between ultrasound evaluation and urinalysis results was investigated. In dogs with bladder echogenic particles in ultrasonography, the prevalence of hematuria, pyuria, bacteriuria, and lipiduria were 88.9%, 92.6%, 29.6%, and 70.3%, respectively. However, in dogs in which echogenic particles were not observed in their bladders, the prevalence of hematuria, pyuria, bacteriuria, and lipiduria was 77%, 50%, 5.5%, and 77%, respectively. There was a significant association between bladder debris and positive urine culture, with an odds ratio of 7.15 (95% confidence interval: 0.81-63.28) compared with matched controls. Furthermore, there was a significant relationship between the presence of floating echogenic particles with pyuria, and urine color ( p ≤ 0.05). CONCLUSION: In conclusion, the present results showed the detection of bladder debris on ultrasound can be a predictor for pyuria and positive urine culture in dogs.

Urine osmolality assessment through the integration of urea hydrolysis and impedance measurement.

We present the development and validation of an impedance-based urine osmometer for accurate and portable measurement of urine osmolality. The urine osmolality of a urine sample can be estimated by determining the concentrations of the conductive solutes and urea, which make up approximately 94% of the urine composition. Our method utilizes impedance measurements to determine the conductive solutes and urea after hydrolysis with urease enzyme. We built an impedance model using sodium chloride (NaCl) and urea at various known concentrations. In this work, we validated the accuracy of the impedance-based urine osmometer by developing a proof-of-concept first prototype and an integrated urine dipstick second prototype, where both prototypes exhibit an average accuracy of 95.5 ± 2.4% and 89.9 ± 9.1%, respectively in comparison to a clinical freezing point osmometer in the hospital laboratory. While the integrated dipstick design exhibited a slightly lower accuracy than the first prototype, it eliminated the need for pre-mixing or manual pipetting. Impedance calibration curves for conductive and non-conductive solutes consistently yielded results for NaCl but underscored challenges in achieving uniform urease enzyme coating on the dipstick. We also investigated the impact of storing urine at room temperature for 24 hours, demonstrating negligible differences in osmolality values. Overall, our impedance-based urine osmometer presents a promising tool for point-of-care urine osmolality measurements, addressing the demand for a portable, accurate, and user-friendly device with potential applications in clinical and home settings.

Automated identification and segmentation of urine spots based on deep-learning.

Micturition serves an essential physiological function that allows the body to eliminate metabolic wastes and maintain water-electrolyte balance. The urine spot assay (VSA), as a simple and economical assay, has been widely used in the study of micturition behavior in rodents. However, the traditional VSA method relies on manual judgment, introduces subjective errors, faces difficulty in obtaining appearance time of each urine spot, and struggles with quantitative analysis of overlapping spots. To address these challenges, we developed a deep learning-based approach for the automatic identification and segmentation of urine spots. Our system employs a target detection network to efficiently detect each urine spot and utilizes an instance segmentation network to achieve precise segmentation of overlapping urine spots. Compared with the traditional VSA method, our system achieves automated detection of urine spot area of micturition in rodents, greatly reducing subjective errors. It accurately determines the urination time of each spot and effectively quantifies the overlapping spots. This study enables high-throughput and precise urine spot detection, providing important technical support for the analysis of urination behavior and the study of the neural mechanism underlying urination.

Utilizing Raman spectroscopy for urinalysis to diagnose acute kidney injury stages in cardiac surgery patients.

BACKGROUND: The successful treatment and improvement of acute kidney injury (AKI) depend on early-stage diagnosis. However, no study has differentiated between the three stages of AKI and non-AKI patients following heart surgery. This study will fill this gap in the literature and help to improve kidney disease management in the future. METHODS: In this study, we applied Raman spectroscopy (RS) to uncover unique urine biomarkers distinguishing heart surgery patients with and without AKI. Given the amplified risk of renal complications post-cardiac surgery, this approach is of paramount importance. Further, we employed the partial least squares-support vector machine (PLS-SVM) model to distinguish between all three stages of AKI and non-AKI patients. RESULTS: We noted significant metabolic disparities among the groups. Each AKI stage presented a distinct metabolic profile: stage 1 had elevated uric acid and reduced creatinine levels; stage 2 demonstrated increased tryptophan and nitrogenous compounds with diminished uric acid; stage 3 displayed the highest neopterin and the lowest creatinine levels. We utilized the PLS-SVM model for discriminant analysis, achieving over 90% identification rate in distinguishing AKI patients, encompassing all stages, from non-AKI subjects. CONCLUSIONS: This study characterizes the incidence and risk factors for AKI after cardiac surgery. The unique spectral information garnered from this study can also pave the way for developing an in vivo RS method to detect and monitor AKI effectively.

[Importance of Measuring the Urine Protein/Creatinine Ratio in Patients with Advanced Hepatocellular Carcinoma Receiving Atezolizumab plus Bevacizumab Treatment].

INTRODUCTION: When we administer atezolizumab plus bevacizumab treatment to patients with advanced hepatocellular carcinoma, we often encounter inconsistent results between the qualitative dipstick urinalysis and the urine protein/creatinine ratio(UPCR)measurements. In this study, we investigated the relationship between qualitative dipstick urinalysis and UPCR in these patients, and assessed whether incorporating UPCR into the testing protocol could prevent unnecessary interruptions during bevacizumab treatment. SUBJECTS AND METHODS: This study analyzed 298 urine samples collected from 61 patients of advanced hepatocellular carcinoma, who were treated with atezolizumab plus bevacizumab at our institution between October 1, 2020, and August 31, 2021. We used UPCR as an alternative test to the 24-hour urine protein and set the discontinuation criteria for bevacizumab at a UPCR of 2.0 or higher. RESULTS: Among the 41 samples that tested positive for 2+ on the dipstick test, only one(2.4%)had a UPCR exceeding 2.0. Additionally, among the 44 samples that showed a 3+ result, 24 samples(54.5%)had a UPCR higher than 2.0. If our decision to discontinue bevacizumab had been based on a dipstick urinalysis result of 2+, we could have continued administering bevacizumab in 97.6%(40/41)of the cases. Even if the decision had been based on a dipstick urinalysis result of 3+, we could have continued administering bevacizumab in almost half of the cases(45.5%, 20/44). CONCLUSIONS: Our findings suggest that the addition of UPCR to the qualitative dipstick urinalysis during atezolizumab plus bevacizumab treatment for patients with advanced hepatocellular carcinoma could help prevent unnecessary interruptions of bevacizumab and offer more clinical benefits in real-world practice, compared to using qualitative dipstick urinalysis alone.

The applicability of the urine color scale in pediatric urology.

AIMS: To determine the level of agreement between healthcare professionals, patients and their parents/guardians in the interpretation of the urine color scale (UCS) in cases of urinary dysfunction, analyzing the applicability of the scale as a diagnostic tool determining the hydration status. METHODS: This was a cross-sectional study involving 5-17-year-old patients with lower urinary tract symptoms (LUTS) and enuresis. The study was conducted in a public healthcare referral center for pediatric urology in the Brazilian state of Bahia between October 2019 and March 2020. The Kolmogorov-Smirnov test was used to assess the distribution of the variables. Agreement was assessed using the kappa coefficient and weighted kappa. The z-test was used to determine significant differences between the kappa and weighted kappa. The statistical analysis was conducted using SPSS, version 14, and significance was established at p < 0.05. RESULTS: Forty-four patients were included. The kappa value was 32.4% (p = 0.000) for the agreement between healthcare professionals and patients, 41.9% (p = 0.000) for agreement between healthcare professionals and parents/guardians, and 25.0% (p = 0.001) for agreement between patients and parents/guardians. The weighted kappa was 70.6% (p = 0.000) for agreement between healthcare professionals and patients, 82.4% (p = 0.000) for agreement between healthcare professionals and parents/guardians, and 51.5% (p = 0.001) for agreement between patients and parents/guardians. There was a statistically significant difference in kappa values when the healthcare professionals were compared with the other groups. CONCLUSIONS: Although there were some inconsistencies in interpretation, the UCS proved to be a useful tool with which to evaluate patients' hydration status.

An artificial intelligence-driven support tool for prediction of urine culture test results.

BACKGROUND AND AIMS: We aimed to develop an easily deployable artificial intelligence (AI)-driven model for rapid prediction of urine culture test results. MATERIAL AND METHODS: We utilized a training dataset (n = 34,584 urine samples) and two separate, unseen test sets (n = 10,083 and 9,289 samples). Various machine learning models were compared for diagnostic performance. Predictive parameters included urinalysis results (dipstick and flow cytometry), patient demographics (age and gender), and sample collection method. RESULTS: Although more complex models achieved the highest AUCs for predicting positive cultures (highest: multilayer perceptron (MLP) with AUC of 0.884, 95% CI 0.878-0.89), multiple logistic regression (MLR) using only flow cytometry parameters achieved a very good AUC (0.858, 95% CI 0.852-0.865). To aid interpretation, prediction results of the MLP and MLR models were categorized based on likelihood ratio (LR) for positivity: highly unlikely (LR 0.1), unlikely (LR 0.3), grey zone (LR 0.9), likely (LR 5.0), and highly likely (LR 40). This resulted in 17%, 28%, 34%, 9%, and 13% of samples falling into each respective category for the MLR model and 20%, 26%, 31%, 7%, and 16% for the MLP model. CONCLUSIONS: In conclusion, this robust model has the potential to assist clinicians in their decision-making process by providing insights prior to the availability of urine culture results in a significant portion of samples (∼2/3rd).

Blending Samples to Increase Accuracy and Precision of 1H NMR Urine Metabolomics.

Urine is an equally attractive biofluid for metabolomics analysis, as it is a challenging matrix analytically. Accurate urine metabolite concentration estimates by Nuclear Magnetic Resonance (NMR) are hampered by pH and ionic strength differences between samples, resulting in large peak shift variability. Here we show that calculating the spectra of original samples from mixtures of samples using linear algebra reduces the shift problems and makes various error estimates possible. Since the use of two-dimensional (2D) NMR to confirm metabolite annotations is effectively impossible to employ on every sample of large sample sets, stabilization of metabolite peak positions increases the confidence in identifying metabolites, avoiding the pitfall of oranges-to-apples comparisons.

Evaluation of the DxU 850m Iris automated urine microscopy analyzer for identifying culture-negative urine samples: From a perspective of reducing urine culture number.

We evaluated the DxU 850m Iris Urine Microscopy analyzer as a screening tool for excluding negative urine samples (n = 1337). At a cutoff of 103 colony counts·mL-1, sensitivity was 55.1 %, specificity 68.6 %. The DxU 850m Iris does not offer acceptable prediction of culture-negative urine samples at the tested cutoff.

The Impact of Polymerase Chain Reaction Urine Testing on Clinical Decision-Making in the Management of Complex Urinary Tract Infections.

While urinary polymerase chain reaction (PCR) testing is effective in organism identification in patients with complex urinary tract infections (cUTI), limited data exists on the clinical usefulness of this test. We serially surveyed physicians treating symptomatic patients with cUTI both at presentation and after PCR, and urine culture (UC) results were available to ascertain how the test results modified the therapy. A total of 96 unique surveys completed by 21 providers were included in the data analysis. The mean age for female and male patients was 69.4 ± 15.5 and 71.6 ± 12.7 years, respectively. The test positivity and line-item concordance for UC and PCR were consistent with prior reports. The PCR results modified or confirmed treatment in 59/96 (61.5%) and 25/96 (26.0%) of the cases, respectively, with 12/29 (41.4%) and 47/67 (70.1%) having negative and positive PCR results, respectively, resulting in treatment change (difference 28.7%, p < 0.01). Of these, 55/59 (57.3%) were alterations in the antibiotic regimen. PCR use to modify treatment was similar across providers and not statistically different when stratified by patient age, gender, or prior empiric therapy. In 31/59 (52.5%) of the cases, the PCR results modified the treatment where UC would not; conversely, UC would have modified the treatment in 3/37 (8.1%) of the cases where PCR did not (difference 44.4%, p < 0.01). We find that PCR test results are used by clinicians in managing cUTI, and use of this test provides an opportunity to improve antibiotic stewardship in this difficult-to-treat subset of patients.

Enhancing clinical decision-making: Sysmex UF-5000 as a screening tool for bacterial urinary tract infection in children.

BACKGROUND: A rapid screening test for urinary tract infections (UTIs) in children is needed to avoid unnecessary cultures and provide prompt reports to make appropriate clinical decisions. We have evaluated for the first time the performance of the Sysmex UF-5000 flow cytometer as a screening tool for UTIs in children. METHODS: This study included 4445 pediatric patients, with urinary sediment and urine culture data collected from January 2020 to September 2023. The Sysmex UF-5000 analyzer was utilized to measure urine white blood cell (WBC) and bacteria (BACT), with the findings being compared to the culture results. RESULTS: At ≥ 104 colony-forming unit (CFU)/mL, 513 samples were culture-positive (400 samples presented 104-105 CFU/mL, and 113 demonstrated ≥ 105 CFU/mL bacterial growth). Optimal indicators for positive cultures were BACT counts of 92.2/µL (AUC: 0.944) and WBC counts of 40.8/µL (AUC:0.863). False negative rate were 0.9% when using a 7.8 bacteria/µL cut-off and avoiding unnecessary cultures in 28.1%. The UF-5000 has a higher consistency rate for Gram-negative (GN) bacteria (90.3%) than Gram-positive (GP) bacteria (86.8%). For samples with 105 CFU/mL, UF-5000's Bacteria -Information flags showed superior concordance for samples with 104-105 CFU/mL bacteria. CONCLUSIONS: Screening pediatric urine cultures with the UF-5000 showed potential application value in identifying negative cultures and significant bacterial growth, although performance may vary depending on the study population. Furthermore, detecting Gram typing aids in guiding early clinical empirical medication, particularly for UTIs caused by GN bacteria.

Clinical utility of dipstick urinalysis in assessing fitness to dive in military divers, submariners, and hyperbaric personnel.

Introduction: Routine dipstick urinalysis is part of many dive medical assessment protocols. However, this has a significant chance of producing false-positive or false-negative results in asymptomatic and healthy individuals. Studies evaluating the value of urinalysis in dive medical assessments are limited. Methods: All results from urinalysis as part of dive medical assessments of divers, submarines, and hyperbaric personnel of the Royal Netherlands Navy from 2013 to 2023 were included in this study. Additionally, any information regarding additional testing, referral, or test results concerning the aforementioned was collected. Results: There were 5,899 assessments, resulting in 46 (0.8%) positive dipstick urinalysis results, predominantly microscopic haematuria. Females were significantly overrepresented, and revisions resulted in significantly more positive test results than initial assessments. Lastly, almost half of the cases were deemed fit to dive, while the other half were regarded as temporarily unfit. These cases required additional testing, and a urologist was consulted three times. Conclusions: To our knowledge, this is the most extensive study evaluating urinalysis in dive medical assessments. In our military population, the incidence of positive test results is very low, and there have not been clinically relevant results over a period of 10 years. Therefore, routinely assessing urine in asymptomatic healthy military candidates is not cost-effective or efficacious. The authors advise taking a thorough history for fitness to dive assessments and only analysing urine when a clinical indication is present.

[Urinary cytology for the detection of urothelial lesions]. / Rôle de la cytologie urinaire dans le dépistage des lésions urothéliales.

Urine cytology is a long-used technique for the detection of high grade neoplastic urothelial lesions. Since 2016, «The Paris System¼ classification has revolutionized this field by introducing a standardized terminology widely adopted by cytopathologists and urologists. In this article, we explain this classification and discuss its impact on the clinical management of patients with urothelial lesions, as well as its role in the secondary prevention of these lesions.

La cytologie urinaire est une technique utilisée depuis longtemps dans la détection des lésions urothéliales tumorales de haut grade. Depuis 2016, la classification «The Paris System¼ a révolutionné ce domaine en introduisant une terminologie standardisée largement adoptée par les cytopathologistes et les urologues. Dans cet article, nous expliquons cette classification et discutons de son impact sur la prise en charge clinique des lésions urothéliales, ainsi que son rôle dans la prévention secondaire de ces lésions.

Accuracy of Urinalysis for UTI in Spina Bifida.

OBJECTIVES: Urinary tract infections (UTIs) are common, but overdiagnosed, in children with spina bifida. We sought to evaluate the diagnostic test characteristics of urinalysis (UA) findings for symptomatic UTI in children with spina bifida. METHODS: Retrospective cross-sectional study using data from 2 centers from January 1, 2016, to December 31, 2021. Children with myelomeningocele aged <19 years who had paired UA (and microscopy, when available) and urine culture were included. The primary outcome was symptomatic UTI. We used generalized estimating equations to control for multiple encounters per child and calculated area under the receiver operating characteristics curve, sensitivity, and specificity for positive nitrites, pyuria (≥10 white blood cells/high-powered field), and leukocyte esterase (more than trace) for a symptomatic UTI. RESULTS: We included 974 encounters from 319 unique children, of which 120 (12.3%) met our criteria for UTI. Pyuria had the highest sensitivity while nitrites were the most specific. Comparatively, nitrites were the least sensitive and pyuria was the least specific. When the cohort was limited to children with symptoms of a UTI, pyuria remained the most sensitive parameter, whereas nitrites remained the least sensitive. Nitrites continued to be the most specific, whereas pyuria was the least specific. Among all encounters, the overall area under the receiver operating characteristics curve for all components of the UA was lower in children who use clean intermittent catheterizations compared with all others. CONCLUSIONS: Individual UA findings have moderate sensitivity (leukocyte esterase or pyuria) or specificity (nitrites) but overall poor diagnostic accuracy for symptomatic UTIs in children with spina bifida.

Uropathogens and clinical manifestations of pyuria-negative urinary tract infections in young infants: A single center cross-sectional study.

BACKGROUND: Urine leukocyte count under microscopy is one of the most frequently used routine screening tests for urinary tract infection (UTI). Nevertheless, it is observed that pyuria is lacking in 10-25% of children with UTI. This study aims to determine the factors related to pyuria-negative UTI in young infants aged under four months old. METHOD: This retrospective cross-sectional study was conducted on 157 patients aged under 4 months old with UTI. All subjects had paired urinalysis and urine culture, which were collected via transurethral catheterization. According to the results of their urinalysis, the patients were then classified as UTI cases with pyuria and UTI cases without pyuria. The clinical characteristics and outcomes of both groups were analyzed. RESULT: Among the 157 UTI patients, the prevalence of pyuria-negative UTI was 44%. Significant risk factors associated with pyuria-negative UTI included non-E.coli pathogens, younger age, shorter duration of fever prior to hospital visit, lower white blood cell (WBC) count upon hospital visit, and absence of microscopic hematuria. CONCLUSIONS: We found that non-E.coli uropathogens were the strongest factor related to pyuria-negative UTI. The absence of pyuria cannot exclude the diagnosis of UTI in young infants, and it's reasonable to perform both urinalysis and urine culture as a part of the assessment of febrile or ill-looking young infants.