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.

Label-Free Analysis of Urine Samples with In-Flow Digital Holographic Microscopy

Urinary tract infections are among the most frequent infectious diseases and require screening a great amount of urine samples from patients. However, a high percentage of samples result as negative after urine culture plate tests (CPTs), demanding a simple and fast preliminary technique to screen out the negative samples. We propose a digital holographic microscopy (DHM) method to inspect fresh urine samples flowing in a glass capillary for 3 min, recording holograms at 2 frames per second. After digital reconstruction, bacteria, white and red blood cells, epithelial cells and crystals were identified and counted, and the samples were classified as negative or positive according to clinical cutoff values. Taking the CPT as reference, we processed 180 urine samples and compared the results with those of urine flow cytometry (UFC). Using standard evaluation metrics for our screening test, we found a similar performance for DHM and UFC, indicating DHM as a suitable and fast screening technique retaining several advantages. As a benefit of DHM, the technique is label-free and does not require sample preparation. Moreover, the phase and amplitude images of the cells and other particles present in urine are digitally recorded and can serve for further investigation afterwards.

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 Objectives

Urinalysis 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 Method

A 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 Result

Of 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 Conclusions

This 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.

Evaluation of the Atellica® UAS 800: a new member of the automated urine sediment analyzer family

BACKGROUND

In 2017 the Atellica^® UAS 800 urine sediment analyzer was introduced by Siemens Healthineers. We investigated its applicability in the standardization and automation of the laboratory urinalysis workflow, including the prediction of urine culture outcome and glomerular pathology.

METHODS

We evaluated the performance characteristics of the Atellica^® UAS 800 and its correlation with the iQ200 (Beckman Coulter). In addition, we studied the agreement between Atellica^® UAS 800 and CLINITEK Novus^® and determined the predictive value of bacteria and leukocyte counts for urine culture outcome. Furthermore, we investigated the ability of Atellica^® UAS 800 to identify pathological casts and dysmorphic erythrocytes in comparison to manual microscopy.

RESULTS

Erythrocyte and leukocyte analyses indicated high intra- and inter-run precisions and good correlations with the iQ200. We found that the Atellica^® UAS 800 detects bacteria with higher sensitivity than the iQ200. The Atellica^® UAS 800 and CLINITEK Novus^® showed a high degree of conformity. We determined seven combinations of clinical cut-off values of bacteria and leukocytes for predicting urine culture outcome with sensitivity, specificity, and negative predictive values of 95%, 52%, and 93%, respectively. Using the Atellica^® UAS 800, hyaline casts, erythrocyte casts, leukocyte casts, and dysmorphic erythrocytes were correctly recognized in 76%, 22%, 2%, and 39% of the samples, respectively.

CONCLUSIONS

The Atellica^® UAS 800 is a robust, fast, and user-friendly analyzer, which accurately quantifies erythrocytes, leukocytes, bacteria and squamous epithelial cells, and may be utilized for predicting positive urine cultures. The detection of clinically important pathological casts and dysmorphic erythrocytes proved insufficient.

The Italian External Quality Assessment (EQA) program on urinary sediment by microscopy examination: a 20 years journey

OBJECTIVES

In spite of the introduction of automated systems for urinary sediment analysis, microscopy examination remains the gold standard, and it is more than ever important to perform it with a good and reliable quality. External Quality Assessment (EQA) programs on urinary sediment are rare. The present paper provides an analysis of results from 2001 to date of the EQA Italian program which involves today 230 laboratories.

METHODS

The program includes four surveys per year. Participants are asked the identification and clinical associations of urinary sediment particles, shown as phase contrast microscopy images in the website of the Center of Biomedical Research (CRB) (2 surveys), and the diagnosis of clinical cases presented by both images and a short clinical history (2 surveys). The results of each survey are then scored and commented. In 20 years, 298 images were presented: 90 cells (9 types), 23 lipids (5 types), 87 casts (21 types), 53 crystals (14 types), 22 microorganisms (5 types), and 23 contaminants (9 types). Moreover, 27 clinical cases, covering a wide spectrum of conditions with different degrees of complexity, were presented to participants.

RESULTS

Identification: among urinary particle categories, the correct identification rate (obtained for each particle from the sum of correct + partially correct answers) was very high for micro-organisms (mean ± SD: 96.2 ± 3.5%), high for lipids (88.0 ± 11.8%) and crystals (87.0 ± 16.5%) followed, in decreasing order, by cells (82.1 ± 15.9%), casts (81.8 ± 14.8%), and contaminants (76.7 ± 22.1%). Clinical associations (n=67): the rate of correct answers was 93.5 ± 5.7% ranging from 75.0 to 100% for all but one clinical association (i.e., acute glomerulonephritis: 55.4%). Clinical cases: throughout surveys, due to the overall rate of particle misidentification, only 59.8 ± 17.1%, (range 32.5-88.7%) of participants achieved access to clinical diagnosis. Of these, 88.7 ± 10.6% (range 59.9-99.3%) were able to indicate the correct diagnosis.

CONCLUSIONS

Our program can be used as a tool to improve the identification of urine particles and the knowledge of their clinical meaning and to encourage specialists of laboratory medicine to correlate urinary findings with other laboratory data and the clinical history, an aspect that improves the value of the day by day work.

How Reliable Is Automated Urinalysis in Acute Kidney Injury?

OBJECTIVE

Examination of urine sediment is crucial in acute kidney injury (AKI). In such renal injury, tubular epithelial cells, epithelial cell casts, and dysmorphic red cells may provide clues to etiology. The aim of this study was to compare automated urinalysis findings with manual microscopic analysis in AKI.

METHODS

Samples from patients diagnosed with AKI and control patients were included in the study. Red blood cells, white blood cells, renal tubular epithelial cells/small round cells, casts, and pathologic (path) cast counts obtained microscopically and by a UF1000i cytometer were compared by Spearman test. Logistic regression analysis was used to assess the ability to predict AKI from parameters obtained from the UF1000i.

RESULTS

There was poor correlation between manual and automated analysis in AKI. None of the parameters could predict AKI using logistic regression analysis. However, the increment in the automated path cast count increased the odds of AKI 93 times.

CONCLUSION

Automated urinalysis parameters are poor predictors of AKI, and there is no agreement with manual microscopy.

Cytological examination of cerebrospinal fluid: Sysmex UF-1000i versus optical microscopy

We evaluated the body fluid module on Sysmex UF-1000i (UF-1000i-BF) for analysis of white blood cell (WBC) and red blood cell (RBC) in cerebrospinal fluid. We collected 93 cerebrospinal fluid samples and compared the results of the UF-1000i-BF mode with the Fast-Read 102 disposable counting cell. Results shows a good correlation between the UF-1000i and the microscopic examination. The concordance percentage is 99.06% for white blood cells and 85.18% for red blood cells. The UF-1000i-BF mode offers rapid and reliable total WBC and RBC counts for initial screening of cerebrospinal fluid, and can improve the workflow in a routine laboratory.

Automated urinalysis combining physicochemical analysis, on-board centrifugation, and digital imaging in one system: A multicenter performance evaluation of the cobas 6500 urine work area

BACKGROUND

We evaluated the analytical performance of the fully automated cobas® 6500 urine work area and its automated components-cobas u 601 and cobas u 701.

DESIGN AND METHODS

The study was conducted at three European centers using un-centrifuged surplus routine urine samples; all measurements were performed within 2 h of sample collection. Precision, sample carry-over, and method comparisons were evaluated per Clinical and Laboratory Standards Institute guidelines. Method comparisons: cobas u 601 versus Urisys 2400 and cobas u 411 urine test strips; and cobas u 701 versus KOVA® visual microscopy and iQ200 analyzer. Operability and functionality were assessed using questionnaires.

RESULTS

Precision of the entire cobas 6500 system was within predefined acceptance limits and no significant carry-over was observed. Erythrocytes, leukocytes, nitrites, and protein were in good agreement (≥93%) with cobas u 411 reflectometry. High correlation was shown between the cobas u 701 analyzer and KOVA visual microscopy for red blood cells (RBC; slope, 0.89; Pearson's r, 0.95) and white blood cells (WBC; slope, 0.96; Pearson's r, 0.96), demonstrating equivalence of test results. The 97.5% percentile reference values on the cobas u 701 analyzer were 5.3 cells/μL (RBC) and 6.2 cells/μL (WBC). The cobas 6500 system showed good sensitivity for small bacteria (>1 μm) and pathological casts, and the user interface, maintenance wizards, and system design were highly rated by operators.

CONCLUSIONS

The fully automated workflow, high precision, and high throughput of the cobas 6500 system have the potential to facilitate standardization of urine screening.

Performance of the cobas u 701 Analyzer in Urinary Tract Infection Screening

Background

Negative urine cultures to rule out urinary tract infections (UTI) generate a considerable laboratory workload; thus, a rapid screening test is desirable. We evaluated the performance of a new automated microscopy analyzer, cobas u 701 (Roche Diagnostics International, Rotkreuz, Switzerland) for the screening of UTI, and developed a rule-out strategy to reduce the number of samples requiring culture. We also assessed squamous epithelial cell (SEC) count as a predictor of culture contamination.

Methods

In total, 1,604 urine samples from outpatients were analyzed with cobas u 701 and culture. Bacterial (BAC) and white blood cell (WBC) counts were used for sample interpretation. To determine a useful cut-off point to predict negative cultures, we selected the highest sensitivity and specificity values obtained from ROC curves. Diagnostic accuracy by age and gender was evaluated.

Results

Urine culture showed growth of ≥10⁴ colony forming units (CFU)/mL in 256 samples (16.0%). The highest sensitivity (91.8%) and specificity (68.4%) were obtained for cut-off points of 119 BAC/µL and 22 WBC/µL. The combination of BAC and WBC improved the performance of the rule-out strategy with a low rate of false-negative results (1.5%) and a high negative predictive value (NPV, 97.3%). Fifty-seven percent of the samples would not have required culture. SEC count was a poor predictor of culture contamination.

Conclusions

cobas u 701 can substantially reduce the number of urine samples requiring culture, with a low false-negative rate and a high NPV.

The standardization of the report for urine cell counting-A converting factor for Sysmex UF-1000i

Background

Multicenter laboratory may apply both automated flow cytometer and microscopy for urinalysis. Automated flow cytometer such as Sysmex UF‐1000i evaluates particles with native urine without centrifugation and reports as “counts per μL.” Microscopic examination recommended as the reference method for urine sediment analysis reports results as “counts per HPF (or μL).” Moreover, some results from flow cytometer are needed to be checked visually under microscopy. Therefore, it is worth to establish the consistency of the results from these two methods.

Methods

Urine specimens from 412 patients were examined with Sysmex UF‐1000i and manual microscopy using FAST‐READ disposable counting chambers. White blood cell (WBC) and red blood cell (RBC) counting results from UF‐1000i after transferred with the converting factor (0.297) we estimated were compared with that from microscopic examination. Method comparison was performed using Passing‐Bablok analysis.

Results

After transferred with the converting factor (0.297), cell counting results from UF‐1000i showed a good correlation with that derived by the reference method (R² was 0.868 for RBCs (P < 0.001), 0.882 for WBCs (P < 0.001)). Passing‐Bablok analysis showed no systematic difference (intercept estimate, −1 [95%CI, −7 to 3] and slightly proportional (slope estimate, 1.2 [95%CI, 1.0 to 1.7]) bias between concentrations of cells measured by manual microscopy and Sysmex UF‐1000i using the converting factor.

Conclusion

The converting factor (0.297) helps to transfer “counts per μL (non‐centrifugal urine)” to “counts per μL (equal to centrifugal urine),” and to keep the urine particle analysis results of Sysmex UF‐1000i consistent with the results from the reference method.

Comparative Performance Analysis of Urised 3 and DIRUI FUS-200 Automated Urine Sediment Analyzers and Manual Microscopic Method

Objective:

Microscopic examination of urine sediment is necessary for evaluation of renal and urinary tract diseases. In this study, we evaluated and compared analytic and diagnostic performances of DIRUI FUS-200 and a new image-based automated urine sediment analyzer Urised 3.

Method:

A total of 440 urine samples, submitted to our laboratory, were evaluated by two automated urine sediment analyzers and a standardized manual microscopy. Precision, linearity and method comparison studies were performed according to CLSI guidelines.

Results:

Considering the red blood cell (RBC) and white blood cell (WBC) counts, strong correlations existed between FUS-200 and manual microscopy (r=0.993 vs 0.861), Urised 3 and manual microscopy (r=0.962 vs 0.818), FUS200 and Urised 3 (r=0.961 vs 0.961). Clinical non-concordance ranged from 7% to 14.16% among all methods.

Conclusions:

The concordance between the analyzers and manual microscopy for WBC was better than that of RBC. The concordance between the two analyzers was better for WBC and RBC, with respect to the manual microscopy. Although the Urised 3, FUS-200 and manual microscopy counts were in agreement; confirmation of the results of automated analyzers with manual microscopy is particularly helpful, for pathological samples with near cut-off values.

Progress in Automated Urinalysis

New technological advances have paved the way for significant progress in automated urinalysis. Quantitative reading of urinary test strips using reflectometry has become possible, while complementary metal oxide semiconductor (CMOS) technology has enhanced analytical sensitivity and shown promise in microalbuminuria testing. Microscopy-based urine particle analysis has greatly progressed over the past decades, enabling high throughput in clinical laboratories. Urinary flow cytometry is an alternative for automated microscopy, and more thorough analysis of flow cytometric data has enabled rapid differentiation of urinary microorganisms. Integration of dilution parameters (e.g., creatinine, specific gravity, and conductivity) in urine test strip readers and urine particle flow cytometers enables correction for urinary dilution, which improves result interpretation. Automated urinalysis can be used for urinary tract screening and for diagnosing and monitoring a broad variety of nephrological and urological conditions; newer applications show promising results for early detection of urothelial cancer. Concomitantly, the introduction of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has enabled fast identification of urinary pathogens. Automation and workflow simplification have led to mechanical integration of test strip readers and particle analysis in urinalysis. As the information obtained by urinalysis is complex, the introduction of expert systems may further reduce analytical errors and improve the quality of sediment and test strip analysis. With the introduction of laboratory-on-a-chip approaches and the use of microfluidics, new affordable applications for quantitative urinalysis and readout on cell phones may become available. In this review, we present the main recent developments in automated urinalysis and future perspectives.

Automated analysis for differentiating leukocytes in body fluids using the software "biological liquid application" on ADVIA2120/2120i hematology analyzer

INTRODUCTION

We evaluated the "Biological liquid application ADVIA2120" software for differentiating the percentage of polymorphonucleated (%PMN) and mononucleated cells (%MN) in ascitic, pleural, and peritoneal dialysis (PD) fluid.

METHODS

Biological fluid test results of 193 specimens obtained by automated methods (87 with and 106 without dedicated software) were compared with May-Grünwald-Giemsa (MGG) stained blood smears. Limit of detection (LoD) and quantitation (LoQ), repeatability, and inaccuracy were assessed.

RESULTS

Good agreement between the automated methods with dedicated software and the manual method for %PMN and %MN was obtained for leukocyte differentiation in ascitic and pleural fluids, while correlation with the manual method for PD fluid was poor, both with and without the dedicated software.

CONCLUSIONS

We demonstrated that the automated differentiation of leukocytes with dedicated software on the ADVIA2120 analyzer for body fluids is a good alternative to the microscopic reference method for peritoneal and pleural specimens, but not for PD fluids.

Evaluation of the new Sysmex UF-5000 fluorescence flow cytometry analyser for ruling out bacterial urinary tract infection and for prediction of Gram negative bacteria in urine cultures

BACKGROUND

We evaluated the new flow cytometer UF-5000 with a blue semiconductant laser as a screening tool for ruling out urine samples negative for UTI and its ability to predict Gram negatives in culture.

METHODS

Flow cytometry and microbiological analysis were performed on 2719 urine samples, sent to our microbiology laboratory with a request for urine culture.

RESULTS

UF-5000 showed a very good performance in the screening process. Carryover and cross-contamination was negligible. 797 samples were culture positive at a cut-off of ≥10⁵CFU/mL. ROC curve analysis for BACT count demonstrated AUC between 0.973, on 2714 samples, 0.959, on 1516 female samples, and 0.988 on 1198 male samples, respectively. At the cut-off of BACT ≥58/μL AND/OR YLC ≥150/μL, SE was 99.4%, SP 78.2%, PPV 65.4% and NPV 99.7%; false negatives were 0.6%, avoiding unnecessary cultures in 55.5% of specimens. "Gram Neg?" flag predicted Gram negatives in culture with a SE of 81.6% and SP of 93.3%.

CONCLUSION

The new Sysmex UF-5000 showed high diagnostic accuracy in UTI-screening with a very low rate of false negatives. The instrument is capable of predicting Gram negatives with a good SE and a high agreement with the culture, even if this performance needs further evaluation.

UriSed 3 and UX-2000 automated urine sediment analyzers vs manual microscopic method: A comparative performance analysis

BACKGROUND

Fully automated urine analyzers now play an important role in routine urinalysis in most laboratories. The recently introduced UriSed 3 has a new automated digital imaging urine sediment analyzer with a phase contrast feature. The aim of this study was to compare the performance of the UriSed 3 and UX-2000 automated urine sediment analyzers with each other and with the results of the manual microscopic method.

METHODS

Two hundred seventy-seven (277) samples of leftover fresh urine from our hospital's central laboratory were evaluated by two automated urine sediment analyzers-UriSed 3 and UX-2000. The results of urine sediment analysis were compared between the two automated analyzers and against the results of the manual microscopic method.

RESULTS

Both devices demonstrated excellent agreement for quantitative measurement of red blood cells and white blood cells. UX-2000 had a lower coefficient correlation and demonstrated slightly lower agreement for squamous epithelial cells. Regarding semiquantitative analysis, both machines demonstrated very good concordance, with all applicable rates within one grade difference of the other machine. UriSed 3 had higher sensitivity for small round cells, while UX-2000 showed greater sensitivity for detecting bacteria and hyaline casts. UriSed 3 demonstrated slightly better specificity, especially in the detection of hyaline and pathological casts.

CONCLUSIONS

Both instruments had nearly similar performance for red blood cells and white blood cells measurement. UriSed 3 was more reliable for measuring squamous epithelial cells and small round cells, while the UX-2000 was more accurate for detecting bacteria and hyaline casts.

The Accuracy of the Sysmex UF-1000i in Urine Bacterial Detection Compared With the Standard Urine Analysis and Culture

CONTEXT

- Urinary tract infections are characterized by the presence of microbial pathogens within the urinary tract. They represent one of the most common infections in hospitalized and clinic patients.

OBJECTIVES

- To model the parameters of the Sysmex UF-1000i to the gold standard, urine culture, and to compare the detection of dipstick leukocyte esterase and nitrates to urine cultures and UF-1000i results.

DESIGN

- Data were compared from urine samples collected in sterile containers for bacterial culture and microscopic analysis. One sample was used to inoculate a 5% sheep blood agar and MacConkey agar plate using a 0.001-mL calibrated loop. The second sample was analyzed by urinalysis-associated microscopy. The media plates were investigated for growth after 18 to 24 hours of aerobic incubation at 37°C. The second sample was analyzed for bacteria and leukocytes with the Sysmex UF-1000i according to the manufacturer's guidelines. Three definitions for culture results, sensitivity, and specificity at different cutoff values were calculated for the UF-1000i.

RESULTS

- The negative predictive value for any positive culture in the adult population included in the study was 95.5%, and the negative predictive value for positive cultures containing growth of 100 000 or more colony-forming units was 99.3% using the Sysmex UF-1000i.

CONCLUSIONS

- Sysmex UF-1000i showed 98% sensitivity and 93.7% specificity with a 95.5% negative predictive value. Thus, a negative screen with the UF-1000i using defined thresholds for white blood cell counts and bacteria was likely to be a true negative, decreasing the need for presumptive antibiotics.

Performance evaluation of the new fully automated urine particle analyser UF-5000 compared to the reference method of the Fuchs-Rosenthal chamber

BACKGROUND

UF-5000 is the new fully automated urine particle analyser. We validated its performance.

METHODS

736 urines were analysed and results were compared by two pathologists on uncentrifuged samples, using Fuchs-Rosenthal chamber.

RESULTS

AUC of ROC curve ranged between 0.86 and 0.99. Sensitivity was >0.90 for all the elements and similar for RBC and yeasts. Specificity ranged between 0.74 and 0.89 for total cast, epithelial/non-squamous/renal-tubular cells and RBC. For all the other parameters specificity was >0.90. Comparison with Fuchs-Rosenthal chamber was very good for all the parameters; r ranged between 0.52 and 0.99 except for pathological cast because of the lack of the pathological samples in medium and higher ranges. Linearity performance (R²) was 1.00, 1.00 and 0.99 respectively for RBC, WBC and epithelial cells (EC). No carry-over was observed. The within-run imprecision was 25.42%,13.81%,1.36% for RBC; 37.50%,10.16%,1.41% for WBC and 35.25%, 17.85%,6.30% for EC at low, near the cut off level and high concentrations, respectively. The between-run imprecision was 6.90%,1.60% for RBC, 4.10%,1.90% for WBC and 7.60%,7.30% for EC, using low and high positive quality controls, respectively.

CONCLUSION

UF-5000 is an analyser of great interest to detect urine particle related to pathological process of kidney and urinary tract.

Performance Evaluation and Comparison of the Fully Automated Urinalysis Analyzers UX-2000 and Cobas 6500

OBJECTIVE

To evaluate and compare the performances of the automated urinalysis devices UX-2000 and Cobas 6500.

METHOD

A total of 258 urine specimens were collected from the routine specimen workload. We analyzed all specimens on both automated instruments and recorded the turnaround time from each method. Physical, chemical, and sedimentary urine components were compared between the automated and the manual method for each analyzer.

RESULTS

The correlation of urine physical/chemical properties between the 2 instruments was excellent. The Cobas 6500 instrument demonstrated a higher level of agreement for red blood cells (Cobas 6500:R= 0.94; UX-2000:R= 0.78) and white blood cells (Cobas 6500:R= 0.95; UX-2000:R= 0.85). The UX-2000 demonstrated higher sensitivity for small round cells, hyaline casts, pathological casts, and bacteria. The median turnaround time was 1.5 minutes and 8.5 minutes for the Cobas 6500 and UX-2000, respectively.

CONCLUSIONS

The 2 devices showed similar performance in technical evaluation; they each reduce workload and increase time saving. However, manual examination by technicians is recommended for pathological specimens.

Validation and verification of automated urine particle analysers

There is often uncertainty on how validation and verification of newly introduced tests should be conducted, and there is a real risk of verification becoming a meaningless ritual, rather than a useful exercise. This article reviews the literature and makes recommendations regarding the validation and verification of automated urine particles analysers. A generic practical approach to verification is also recommended. For many analysers, the accuracy of white blood cells, epithelial cells and bacterial counts is corroborated by a number of independent evaluations; thus, any verification laboratory work could be significantly scaled down. Conversely, in the scenario that automated urine microscopy is used as a screening test to reduce the number of urines cultured, the extremely variable performance reported in the literature requires a full-scale verification to define the optimal cut-off values that give a sensitivity of >98% with the local settings and circumstances. With some analysers, the risk of carry-over also needs to be assessed, as part of the verification process, and exclusion criteria (urines requiring culture regardless of the microscopy results) need to be well defined, as there are patients or specimen types for which the performance of microscopy as a screening test may not be adequate.

Levels of albuminuria and risk of developing macroalbuminuria in type 2 diabetes: historical cohort study

Although increased urinary albumin excretion may increase the risk of adverse renal outcomes in patients with diabetes, it remains unclear whether microalbuminuria is associated with a higher incidence of macroalbuminuria in the absence of non-diabetic kidney events that frequently develop during the long-term course of type 2 diabetes. This historical cohort study included patients with type 2 diabetes, spot urine albumin:creatinine ratio (ACR) <300 mg/gCr and normal serum creatinine concentrations treated between August 1988 and April 2015. Patients with any evidence suggesting non-diabetic kidney diseases at baseline were excluded. Over a median follow-up of 50 months, 70 of the 1760 included patients developed macroalbuminuria. Twenty-one of these patients were diagnosed with non-diabetic renal events. The five-year cumulative incidence of macroalbuminuria in patients with ACRs of 0–7.5 mg/gCr, 7.5–30 mg/gCr, 30–150 mg/gCr, and 150–300 mg/gCr were 0%, 0.53%, 3.5%, and 36.0%, respectively, with significant differences between each pair of ACR categories. In type 2 diabetes, higher urinary ACR, even within a level of normoalbuminuria, was associated with a greater incidence of macroalbuminuria when non-diabetic renal events were excluded. These results conflict with findings suggesting that microalbuminuria is a poor indicator for the progression of diabetic nephropathy.

Comparison of the Automated cobas u 701 Urine Microscopy and UF-1000i Flow Cytometry Systems and Manual Microscopy in the Examination of Urine Sediments

BACKGROUND

The cobas u 701, a new automated image-based urine sediment analyzer, was introduced recently. In this study, we compared its performance with that of UF-1000i flow cytometry and manual microscopy in the examination of urine sediments.

METHODS

Precision, linearity, and carry-over were determined for the two urine sediment analyzers. For a comparison of the method, 300 urine samples were examined by the automated analyzers and by manual microscopy using a KOVA chamber.

RESULTS

Within-run coefficients of variation (CVs) for the control materials were 7.0-8.8% and 1.7-5.7% for the cobas u 701 and UF-1000i systems, respectively. Between-run CVs were 8.5-9.8% and 2.7-5.4%, respectively. Both instruments showed good linearity and negligible carry-over. For red blood cells (RBC), white blood cells (WBC), and epithelial cells (EPI), the overall concordance rates within one grade of difference among the three methods were good (78.6-86.0%, 88.7-93.8%, and 81.3-90.7%, respectively). The concordance rate for casts was poor (66.5-68.9%).

CONCLUSION

Compared with manual microscopy, the two automated sediment analyzers tested in this study showed satisfactory analytical performances for RBC, WBC, and EPI. However, for other urine sediment particles confirmation by visual microscopy is still required.

Diagnostic accuracy of urinary prostate protein glycosylation profiling in prostatitis diagnosis

INTRODUCTION

Although prostatitis is a common male urinary tract infection, clinical diagnosis of prostatitis is difficult. The developmental mechanism of prostatitis is not yet unraveled which led to the elaboration of various biomarkers. As changes in asparagine-linked-(N-)-glycosylation were observed between healthy volunteers (HV), patients with benign prostate hyperplasia and prostate cancer patients, a difference could exist in biochemical parameters and urinary N-glycosylation between HV and prostatitis patients. We therefore investigated if prostatic protein glycosylation could improve the diagnosis of prostatitis.

MATERIALS AND METHODS

Differences in serum and urine biochemical markers and in total urine N-glycosylation profile of prostatic proteins were determined between HV (N=66) and prostatitis patients (N=36). Additionally, diagnostic accuracy of significant biochemical markers and changes in N-glycosylation was assessed.

RESULTS

Urinary white blood cell (WBC) count enabled discrimination of HV from prostatitis patients (P<0.001). Urinary bacteria count allowed for discriminating prostatitis patients from HV (P<0.001). Total amount of biantennary structures (urinary 2A/MA marker) was significantly lower in prostatitis patients compared to HV (P<0.001). Combining the urinary 2A/MA marker and urinary WBC count resulted in an AUC of 0.79, 95% confidence interval (CI)=(0.70-0.89) which was significantly better than urinary WBC count (AUC=0.70, 95% CI=[0.59-0.82], P=0.042) as isolated test.

CONCLUSIONS

We have demonstrated the diagnostic value of urinary N-glycosylation profiling, which shows great potential as biomarker for prostatitis. Further research is required to unravel the developmental course of prostatic inflammation.

Automated urinalysis and urine dipstick in the emergency evaluation of young febrile children

OBJECTIVE

The performance of automated flow cytometric urinalysis is not well described in pediatric urinary tract infection. We sought to determine the diagnostic performance of automated cell counts and emergency department point-of-care (POC) dipstick urinalyses in the evaluation of young febrile children.

METHODS

We prospectively identified a convenience sample of febrile pediatric emergency department patients <48 months of age who underwent urethral catheterization to obtain POC and automated urinalyses and urine culture. Receiver operating characteristic analyses were performed and diagnostic indices were calculated for POC dipstick and automated cell counts at different cutpoints.

RESULTS

Of 342 eligible children, 42 (12%) had urinary bacterial growth ≥ 50000/mL. The areas under the receiver operating characteristic curves were: automated white blood cell count, 0.97; automated bacterial count, 0.998; POC leukocyte esterase, 0.94; and POC nitrite, 0.76. Sensitivities and specificities were 86% and 98% for automated leukocyte counts ≥ 100/μL and 98% and 98% for bacterial counts ≥ 250/μL. POC urine dipstick with ≥ 1+ leukocyte esterase or positive nitrite had a sensitivity of 95% and a specificity of 98%. Combinations of white blood cell and bacterial counts did not outperform bacterial counts alone.

CONCLUSIONS

Automated leukocyte and bacterial counts performed well in the diagnosis of urinary tract infection in these febrile pediatric patients, but POC dipstick may be an acceptable alternative in clinical settings that require rapid decision-making.

Usefulness of quantifying leukocytes in first-voided urine to predict positivity for Chlamydia trachomatis in asymptomatic men at high risk for chlamydial infection

Chlamydia trachomatis causes acute non-gonococcal urethritis, but some infected men are asymptomatic. We examined leukocytes in uncentrifuged first-voided urine (FVU) from asymptomatic men at high risk for chlamydial infection by automated urine particle analyzers to assess whether the quantification of urinary leukocytes could predict chlamydial infection in these men. We enrolled 209 asymptomatic men, whose female sexual partners had been diagnosed as having a genital chlamydial infection. Their FVU specimens were examined for quantification of leukocytes with automated urine particle analyzers and tested for Neisseria gonorrhoeae, C. trachomatis, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma parvum, and Ureaplasma urealyticum by nucleotide acid amplification tests. Eleven men positive for N. gonorrhoeae or M. genitalium were excluded from further analysis. In the remaining 198 men, 84 positive for C. trachomatis (42.4%) had 1.8-1666.9 white blood cells (WBCs)/μl (median, 43.3 WBCs/μl) in their FVU, whereas 114 negative for C. trachomatis had 0.1-1378 WBCs/μl (median, 4.8 WBCs/μl). A receiver operating characteristic (ROC) curve was constructed to examine the sensitivity and specificity of leukocytes counts for predicting chlamydial infection. A cut-off point of leukocyte counts of 12.5 WBCs/μl was determined from the ROC curve, resulting in a sensitivity of 86.9% and specificity of 88.6% for predicting chlamydial infection. Leukocyte quantification in FVU by automated urine particle analyzers showed good performance in predicting the positivity and negativity for chlamydial infection in asymptomatic men. This test could potentially develop into a relevant tool for preselecting asymptomatic men prior to C. trachomatis screening.

Isomorphic red blood cells using automated urine flow cytometry is a reliable method in diagnosis of bladder cancer

BACKGROUND

We aimed to identify patients with a chief complaint of hematuria who could safely avoid unnecessary radiation and instrumentation in the diagnosis of bladder cancer (BC), using automated urine flow cytometry to detect isomorphic red blood cells (RBCs) in urine.

METHODS

We acquired urine samples from 134 patients over the age of 35 years with a chief complaint of hematuria and a positive urine occult blood test or microhematuria. The data were analyzed using the UF-1000i (®) (Sysmex Co., Ltd., Kobe, Japan) automated urine flow cytometer to determine RBC morphology, which was classified as isomorphic or dysmorphic. The patients were divided into two groups (BC versus non-BC) for statistical analysis. Multivariate logistic regression analysis was used to determine the predictive value of flow cytometry versus urine cytology, the bladder tumor antigen test, occult blood in urine test, and microhematuria test.

RESULTS

BC was confirmed in 26 of 134 patients (19.4 %). The area under the curve for RBC count using the automated urine flow cytometer was 0.94, representing the highest reference value obtained in this study. Isomorphic RBCs were detected in all patients in the BC group. On multivariate logistic regression analysis, only isomorphic RBC morphology was significantly predictive for BC (p < 0.001). Analytical parameters such as sensitivity, specificity, positive predictive value, and negative predictive value of isomorphic RBCs in urine were 100.0, 91.7, 74.3, and 100.0 %, respectively.

CONCLUSION

Detection of urinary isomorphic RBCs using automated urine flow cytometry is a reliable method in the diagnosis of BC with hematuria.

Sysmex UF-1000i performance for screening yeasts in urine

We tested the capacity of the Sysmex UF-1000i system to detect yeasts in urine by screening a total of 22 132 urine samples received for culture in our microbiology laboratory during 1 year. We also analyzed different dilutions of previously filtered urine inoculated with a strain of Candida albicans. With clinical samples, a single cut-off point of 50 yeast-like cells (YLCs)/μL detected candiduria ≥10 000 colony forming units (CFU)/mL and >100 000 CFU/mL with a sensitivity of 87.3%/95.4%, a specificity of 97%, a negative predictive value of 95.9%, and a positive predictive value of 9.3%/5.7%. With the simulated samples, a linear relationship was observed between the dilution factor and the number of cells detected by UF-1000i. This instrument appears to be able to reliably rule out candiduria of a magnitude of at least 10 000 CFU/mL and facilitate urine sample screening, thereby providing fast results. The Sysmex UF1000i system can be adapted for candiduria screening by the use of an appropriate YLCs/μL cut-off point that takes account of the prevalence of candiduria in the population.

Direct identification of bacteria causing urinary tract infections by combining matrix-assisted laser desorption ionization-time of flight mass spectrometry with UF-1000i urine flow cytometry

Rapid identification of bacterial pathogens from clinical specimens is essential to establish an adequate empirical antibiotic therapy to treat urinary tract infections (UTIs). We used matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) combined with UF-1000i urine flow cytometry of urine specimens to quickly and accurately identify bacteria causing UTIs. We divided each urine sample into three aliquots for conventional identification, UF-1000i, and MALDI-TOF MS, respectively. We compared the results of the conventional method with those of MALDI-TOF MS combined with UF-1000i, and discrepancies were resolved by 16S rRNA gene sequencing. We analyzed 1456 urine samples from patients with UTI symptoms, and 932 (64.0%) were negative using each of the three testing methods. The combined method used UF-1000i to eliminate negative specimens and then MALDI-TOF MS to identify the remaining positive samples. The combined method was consistent with the conventional method in 1373 of 1456 cases (94.3%), and gave the correct result in 1381 of 1456 cases (94.8%). Therefore, the combined method described here can directly provide a rapid, accurate, definitive bacterial identification for the vast majority of urine samples, though the MALDI-TOF MS software analysis capabilities should be improved, with regard to mixed bacterial infection.

Rapid discrimination of Gram-positive and Gram-negative bacteria in liquid samples by using NaOH-sodium dodecyl sulfate solution and flow cytometry

Background

For precise diagnosis of urinary tract infections (UTI), and selection of the appropriate prescriptions for their treatment, we explored a simple and rapid method of discriminating gram-positive and gram-negative bacteria in liquid samples.

Methodology/Principal Findings

We employed the NaOH-sodium dodecyl sulfate (SDS) solution conventionally used for plasmid extraction from Escherichia coli and the automated urine particle analyzer UF-1000i (Sysmex Corporation) for our novel method. The NaOH-SDS solution was used to determine differences in the cell wall structures between gram-positive and gram-negative bacteria, since the tolerance to such chemicals reflects the thickness and structural differences of bacterial cell walls. The UF-1000i instrument was used as a quantitative bacterial counter. We found that gram-negative bacteria, including E. coli, in liquid culture could easily be lysed by direct addition of equal volumes of NaOH-SDS solution. In contrast, Enterococcus faecalis, which is a gram-positive bacterium, could not be completely lysed by the solution. We then optimized the reaction time of the NaOH-SDS treatment at room temperature by using 3 gram-positive and 4 gram-negative bacterial strains and determined that the optimum reaction time was 5 min. Finally, in order to evaluate the generalizability of this method, we treated 8 gram-positive strains and 8 gram-negative strains, or 4 gram-positive and 4 gram-negative strains incubated in voluntary urine from healthy volunteers in the same way and demonstrated that all the gram-positive bacteria were discriminated quantitatively from gram negative bacteria using this method.

Conclusions/Significance

Using our new method, we could easily discriminate gram-positive and gram-negative bacteria in liquid culture media within 10 min. This simple and rapid method may be useful for determining the treatment course of patients with UTIs, especially for those without a prior history of UTIs. The method may be easily applied in order to obtain additional information for clinical prescriptions from bacteriuria.

Cessation of dipstick urinalysis reflex testing and physician ordering behavior

The purpose of our study was to determine the effect of the elimination of laboratory-initiated reflex testing on physician ordering behavior. In 1999, we stopped laboratory-initiated reflex testing and did microscopic analysis only on physician request. The number of urinalysis dipstick tests, microscopic analysis tests, and urine cultures done during 6-month periods for the next 10 years was extracted from our laboratory information system that includes data from the middle of 1999. The number of physician complaints was also recorded. Before the intervention, we did 106,000 urine analysis tests per 6-month period, with 19,006 microscopic examinations (17.9%) that decreased to less than 0.2% after the change in policy. During the 10-year period, physician requests for microscopic urinalysis decreased gradually to around 50 in any 6-month period.

Screening for urinary tract infection with the Sysmex UF-1000i urine flow cytometer

The diagnosis of urinary tract infection (UTI) by urine culture is time-consuming and can produce up to 60 to 80% negative results. Fast screening methods that can reduce the necessity for urine cultures will have a large impact on overall turnaround time and laboratory economics. We have evaluated the detection of bacteria and leukocytes by a new urine analyzer, the UF-1000i, to identify negative urine samples that can be excluded from urine culture. In total, 1,577 urine samples were analyzed and compared to urine culture. Urine culture showed growth of ≥10(3) CFU/ml in 939 samples (60%). Receiver operating characteristics (ROC) curves and ROC decision plots were been prepared at three different gold standard definitions of a negative urine culture: no growth, growth of bacteria at <10(4) CFU/ml, and growth of bacteria at <10(5) CFU/ml. Also, the reduction in urine cultures and the percentage of false negatives were calculated. At the most stringent gold standard definition of no growth, a chosen sensitivity of 95% resulted in a cutoff value of 26 bacteria/μl, a specificity of 43% and a reduction in urine cultures of only 20%, of which 14% were false negatives. However, at a gold standard definition of <10(5) CFU/ml and a sensitivity of 95%, the UF-1000i cutoff value was 230 bacteria/μl, the specificity was 80%, and the reduction in urine cultures was 52%, of which 0.3% were false negatives. The applicability of the UF-1000i to screen for negative urine samples strongly depends on population characteristics and the definition of a negative urine culture. In our setting, however, the low workload savings and the high percentage of false-negative results do not warrant the UF-1000i to be used as a screening analyzer.