Comparison of automated devices UX-2000 and SediMAX/AutionMax for urine samples screening: A multicenter Spanish study

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).

Laboratory Tests, Bacterial Resistance, and Treatment Options in Adult Patients Hospitalized with a Suspected Urinary Tract Infection

Patients treated for systemic urinary tract infections commonly have nonspecific presentations, and the specificity of the results of the urinalysis and urine cultures is low. In the following narrative review, we will describe the widespread misuse of urine testing, and consider how to limit testing, the disutility of urine cultures, and the use of antibiotics in hospitalized adult patients. Automated dipstick testing is more precise and sensitive than the microscopic urinalysis which will result in false negative test results if ordered to confirm a positive dipstick test result. There is evidence that canceling urine cultures if the dipstick is negative (negative leukocyte esterase, and nitrite) is safe and helps prevent the overuse of urine cultures. Because of the side effects of introducing a urine catheter, for patients who cannot provide a urine sample, empiric antibiotic treatment should be considered as an alternative to culturing the urine if a trial of withholding antibiotic therapy is not an option. Treatment options that will decrease both narrower and wider spectrum antibiotic use include a period of watching and waiting before antibiotic therapy and empiric treatment with antibiotics that have resistance rates > 10%. Further studies are warranted to show the option that maximizes patient comfort and safety.

Prediction of the bacterial shape in urinary tract infections with the Sysmex UF-1000i analyser: technical note

Background

The aim of our study was to explore the utility of the Sysmex UF-1000i analyzer as a rapid screening tool for urinary tract infections (UTI) and its ability to predict bacterial shape in order to help physicians choose the appropriate empiric treatment.

Materials and methods

This is a retrospective study, including 1023 urine cytobacteriological examinations. Urines were processed according to the recommendations of the medical microbiology reference system (REMIC). Using the Sysmex Uf-1000i analyzer, the authors evaluated bacteria forward scatter (B_FSC) and fluorescent light scatter (B_FLH) in a preliminary discrimination step for UTI caused by bacilli or cocci bacteria.

Results

The authors got 1023 positive samples. Comparing baccili and cocci bacteria, the authors observed a statistically significant difference for B_FSC but not for B_FLH. The values of B_FLH are very close for the four categories of microorganisms compared (bacilli, cocci, bacilli-cocci association, and yeasts). For these same categories, tests show different values for the B_FSC. A separate analysis of the B_FSC values for bacilli shows that their distribution is relatively homogeneous and exhibits a peak between 20 and 30 ch.

Conclusion

Dimensional parameters of bacteria generated by UF-1000i could be a rapid and useful tool for predicting the bacterial shape causing UTI.

Pitfalls in the diagnosis of hematuria

Detection of hemoglobin (Hb) and red blood cells in urine (hematuria) is characterized by a large number of pitfalls. Clinicians and laboratory specialists must be aware of these pitfalls since they often lead to medical overconsumption or incorrect diagnosis. Pre-analytical issues (use of vacuum tubes or urine tubes containing preservatives) can affect test results. In routine clinical laboratories, hematuria can be assayed using either chemical (test strips) or particle-counting techniques. In cases of doubtful results, Munchausen syndrome or adulteration of the urine specimen should be excluded. Pigmenturia (caused by the presence of dyes, urinary metabolites such as porphyrins and homogentisic acid, and certain drugs in the urine) can be easily confused with hematuria. The peroxidase activity (test strip) can be positively affected by the presence of non-Hb peroxidases (e.g. myoglobin, semen peroxidases, bacterial, and vegetable peroxidases). Urinary pH, haptoglobin concentration, and urine osmolality may affect specific peroxidase activity. The implementation of expert systems may be helpful in detecting preanalytical and analytical errors in the assessment of hematuria. Correcting for dilution using osmolality, density, or conductivity may be useful for heavily concentrated or diluted urine samples.

Performance evaluation of Hipee S2 point-of-care testing urine dipstick analyser: a cross-sectional study

OBJECTIVE

With advances in mobile technology, smartphone-based point-of-care testing (POCT) urinalysis hold great potential for disease screening and health management for clinicians and individual users. The purpose of this study is to evaluate the analytical performance of Hipee S2 POCT urine dipstick analyser.

DESIGN

A multicentre, hospital-based, cross-sectional study.

SETTING

Analytical performance of the POCT analyser was conducted at a clinical laboratory, and method comparison was performed at three clinical laboratories in China.

PARTICIPANTS

Urine samples were collected from 1603 outpatients and inpatients at three hospitals, and 5 health check-up population at one of the hospitals.

OUTCOME MEASURES

All tests were performed by clinical laboratory technicians. Precision, drift, carry-over, interference and method comparison of Hipee S2 were evaluated. Diagnostic accuracy of semiquantitative albumin-to-creatinine ratio (ACR) for albuminuria was carried out using quantitative ACR as the standard.

RESULTS

The precision for each parameter, assessed by control materials, was acceptable. No sample carry-over or drift was observed. Ascorbate solution with 1 g/L had an inhibitory effect for the haemoglobin test. Agreement for specific gravity (SG) varied between moderate to substantial (κ values 0.496-0.687), for pH was moderate (κ values 0.423-0.569) and for other parameters varied between substantial to excellent (κ values 0.669-0.991), on comparing the Hipee S2 with laboratory analysers. The semiquantitative microalbumin and creatinine were highly correlated with the quantitative results. The sensitivity of semiquantitative ACR to detect albuminuria was 87.2%-90.7%, specificity was 70.7%-78.4%, negative predictive value was 85.3%-87.9% and positive predictive value was 73.9%-83%.

CONCLUSIONS

Hipee S2 POCT urine analyser showed acceptable analytical performance as a semiquantitative method. It serves as a convenient alternate device for clinicians and individual users for urinalysis and health management. In addition, the POCT semiquantitative ACR would be useful in screening for albuminuria.

Improved efficiency of urine cell image segmentation using droplet microfluidics technology

Recent advances in the recognition of biological samples using machine vision have made this technology increasingly important in research and detection. Image segmentation is an important step in this process. This study focuses on how to reduce the interference factors such as the overlap between different types (or within the same type) of urine cells according to microfluidics and improve the machine vision segmentation accuracy for cell images. In this study, we demonstrate that the platform can realize this hypothesis using urine cell image segmentation as an example application. We first discuss the reported urine cell droplet microfluidic chip system, which can realize the test conditions in which urine cells are encapsulated in the droplet and isolated from salt crystallization and/or bacteria and other urine-formed elements. Then, based on the analysis conditions set in the aforementioned experiment, the proportions of red blood cells, white blood cells, and squamous epithelial cells covered by various formed elements in the total urine cells in the same urine sample are measured. We simultaneously analyze the percentage of urine cells covered by salt crystallization and the incidence of overlapping between urine cells. Finally, the Otsu algorithm is used to segment the urine cell images encapsulated by the droplet and the urine cell images not encapsulated by the droplet, and the Dice, Jaccard, precision, and recall values are calculated. The results suggest that the method of encapsulating single cells based on droplets can improve the image segmentation effect without optimizing the algorithm.

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.

Increased effectiveness of urinalysis testing via the integration of automated instrumentation, the lean management approach, and autoverification

Background

In 2014, the Department of Clinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand developed and implemented a new process that uses fully automated instrumentation, the lean management approach, and autoverification to improve the productivity and efficiency of the urinalysis workflow process. The aim of this study was to evaluate analytical turnaround time compared with our old urinalysis workflow process and our new urinalysis workflow process that was launched in 2014.

Methods

This study was performed at the Central Laboratory of our center during June 2017 using data collected from the July 2012 (old process) and July 2014 (new process) study periods. We used our laboratory information system to compute and analyze turnaround time of urinalysis tests, and those results were compared between processes.

Results

The 90th percentile turnaround time in overall data was dramatically decreased from approximately 60 minutes in 2012 to <50 minutes in 2014. The mean during both 6:00 am to 9:00 am and 9:00 am to 12:00 pm was approximately 42 minutes in 2012; however, that duration was reduced to approximately 30 minutes for both of those time periods in 2014. Specimens within 60 minutes in both intervals increase from approximately 80% to more than 90%.

Conclusion

The results of this study revealed our new urinalysis workflow process that incorporates fully automated instrumentation, the lean management approach, and autoverification to be effective for significantly increasing productivity as measured by analytical turnaround time and removing 1 staff to another section.

Evaluation of the analytical performances of Cobas 6500 and Sysmex UN series automated urinalysis systems with manual microscopic particle counting

Introduction

Automated urinalysis systems are valuable tools in clinical laboratories, especially those with a high work load. The objective of this study was to compare the analytical performance of Sysmex UN series urine analyser, which may become a new one in our laboratory, with the Cobas 6500 automated urine analyser, which is used in our laboratory for a long time. For comparisons, manual microscopical examination was accepted as reference method.

Materials and methods

A total of 470 urine samples were tested in the two automated urinalysis systems, and urine sediment testing with manual microscopy was applied to a 100 pathological samples of the total 470. The diagnostic performance of the two automated urine analysers was compared with each other and manual microscopy.

Results

Differences were determined between automated and manual microscopy in some pathological samples. The resultant regression equations were as follows. Comparison of Cobas U701 with Sysmex UF-5000: y = - 0.57 (- 0.85 to - 0.29) + 0.95 (0.92 to 0.99) x for RBC, and y = - 0.11 (- 0.54 to 0.29) + 0.89 (0.84 to 0.98) x for WBC; comparison of Cobas U701 with manual microscopy: y = - 0.45 (- 0.85 to 0.21) + 1.00 (0.92 to 1.07) x for WBC; and comparison of Sysmex UF-5000 with manual microscopy: y = - 0.74 (- 1.09 to - 0.57) + 0.87 (0.85 to 0.91) x for WBC.

Conclusions

We can conclude that the new Sysmex UN series urine analyser can be safely used in our laboratory. Although the results showed good to moderate concordance, the microscopy results of the automated platforms should be confirmed by manual microscopy, particularly in pathological samples.

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.

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.

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.