Cutoff values for bacteria and leukocytes for urine flow cytometer Sysmex UF-1000i in urinary tract infections

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.

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.

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

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

Usefulness of UF-5000 automatic screening system in UTI diagnosis

We have evaluated the Sysmex UF-5000 cytometer use in microbiology for the screening of negative urines, looking for cut-off points to detect bacteria and leukocytes. The number of processed urines was 3569, the highest to date in these studies. The best general cut-off point has been 100 bact/μl, giving an area under the ROC curve of 0.868, a sensitivity of 96%, a specificity of 50%, 1.17% of false negatives, and saving 40% of cultures. The PPV and NPV have been 35.5 and 95.4 respectively. The leukocyte count has not been useful. Finally, we have evaluated urine screening usefulness, concluding that in laboratories such as ours (284 urines/working day) or smaller, it is not cost-effective.

The diagnostic performances of the Atellica® 1500 automated urinalysis system for ruling out bacterial urinary tract infection

Urinary tract infection (UTI) is one of the most common diseases occurring in both hospitalized and community subjects. Urine culture is the gold standard test for the diagnosis of UTI, but approximately 80% are negative. The aim of this study was to evaluate the performance of the automated urinalysis system Atellica® 1500 (Siemens Healthineers, Erlangen, Germany) as screening tool for ruling out UTI. A total of 5,490 urine specimens from outpatients, that had simultaneous requests for urinalysis and urine culture, were evaluated. Of the 5,490 samples, 833 (15.2 %) resulted positive for urine culture. Among UTI-related parameters, bacterial count was considered the most apt to be diagnostic of subjects affected by UTI. Using a cutoff value for bacteria count equal to 180 elements/µL, Atellica® 1500 detected bacteriuria with diagnostic sensitivity (Se) of 88.1 %, diagnostic specificity (Sp) of 82.1 %, and negative predictive value (NPV) of 95.2 %. Comparing our results with the literature's data, we observed that our Se and NPV were lower, while our Sp was higher. Our data showed that the Atellica® 1500 system detected bacteria with satisfactory analytical performance, but the results obtained do not make it a reliable tool for excluding UTI with urinalysis.

Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine—A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques

Background: Urine flow cytometry (UFC) analyses urine samples and determines parameter counts. We aimed to predict different types of urine culture growth, including mixed growth indicating urine culture contamination. Methods: A retrospective cohort study (07/2017–09/2020) was performed on pairs of urine samples and urine cultures obtained from adult emergency department patients. The dataset was split into a training (75%) and validation set (25%). Statistical analysis was performed using a machine learning approach with extreme gradient boosting to predict urine culture growth types (i.e., negative, positive, and mixed) using UFC parameters obtained by UF-4000, sex, and age. Results: In total, 3835 urine samples were included. Detection of squamous epithelial cells, bacteria, and leukocytes by UFC were associated with the different types of culture growth. We achieved a prediction accuracy of 80% in the three-class approach. Of the n = 126 mixed cultures in the validation set, 11.1% were correctly predicted; positive and negative cultures were correctly predicted in 74.0% and 96.3%. Conclusions: Significant bacterial growth can be safely ruled out using UFC parameters. However, positive urine culture growth (rule in) or even mixed culture growth (suggesting contamination) cannot be adequately predicted using UFC parameters alone. Squamous epithelial cells are associated with mixed culture growth.

FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections

Due to the high prevalence of patients attending with urinary tract infection (UTI) symptoms, the use of flow-cytometry as a rapid screening tool to avoid unnecessary cultures is becoming a widely used system in clinical practice. However, the recommended cut-points applied in flow-cytometry systems differ substantially among authors, making it difficult to obtain reliable conclusions. Here, we present FlowUTI, a shiny web-application created to establish optimal cut-off values in flow-cytometry for different UTI markers, such as bacterial or leukocyte counts, in urine from patients with UTI symptoms. This application provides a user-friendly graphical interface to perform robust statistical analysis without a specific training. Two datasets are analyzed in this manuscript: one composed of 204 urine samples from neonates and infants (≤3 months old) attended in the emergency department with suspected UTI; and the second dataset including 1174 urines samples from an elderly population attended at the primary care level. The source code is available on GitHub (https://github.com/GuillermoMG-HUVR/Microbiology-applications/tree/FlowUTI/FlowUTI). The web application can be executed locally from the R console. Alternatively, it can be freely accessed at https://covidiario.shinyapps.io/flowuti/. FlowUTI provides an easy-to-use environment for evaluating the efficiency of the urinary screening process with flow-cytometry, reducing the computational burden associated with this kind of analysis.

Comparison of Urine Flow Cytometry on the UF-1000i System and Urine Culture of Urine Samples from Urological Patients

Introduction

The aims of this study were to evaluate urine flow cytometry (UFC) as a tool to screen urine samples of urological patients for bacteriuria and to compare UFC and dipstick analysis with urine culture in a patient cohort at a urological department of a university hospital.

Methods and Material

We screened 662 urine samples from urological patients (75.2% male; 80.7% inpatients; mean age 58 years). UFC results were compared to microbiological urine culture.

Results

The accuracy in using the UFC-based parameters for detecting cultural bacteriuria was 91.99% and 88.97% for ≥10⁵ colony-forming units (CFU)/mL and ≥10⁴ CFU/mL, respectively. UFC and leukocyte dipstick analysis measured leukocyturia similarly (Pearson correlation coefficient 0.87, p value <0.01%), but dipstick analysis scored less accurately on bacteriuria (accuracy 59.37% and 62.69%). UFC remained effective in subgroup analysis of patients of both sexes and with different urological conditions with its overall use only slightly impaired when assessing gross hematuria (NPV 84.62% for ≥10⁴ CFU/mL). UFC also reliably removed those urine samples below cutoffs with negative predictive values of 99.28% for ≥10⁵ CFU/mL and 95.86% for ≥10⁴ CFU/mL.

Conclusion

Counting bacteria with UFC is an accurate and rapid method to determine significant bacteriuria in urological patients and is superior to dipstick analysis or indirect surrogate parameters such as leukocyturia. When UFC is available, we recommend it to be used for the diagnosis of bacteriuria over findings obtained by dipstick analysis.

Preoperative bacteriuria positivity on urinalysis increases wound complications in primary total hip arthroplasty regardless of the urine culture result

BACKGROUND

Current evidence does not recommend screening urine culture and curing asymptomatic bacteriuria (ASB) before joint arthroplasty. The bacteriuria count on pre-operative urinalysis is a more common clinical parameter. We aimed to investigate whether the bacteriuria count on preoperative urinalysis can increase postoperative wound complications in primary total hip arthroplasty (THA).

METHODS

We conducted a retrospective study that included patients who underwent primary THA in our institution from 2012 to 2018. We obtained preoperative urinalysis results before THA during the same hospitalization and identified patients with abnormal urinalysis. Receiver operating characteristic (ROC) curves were first generated to evaluate the predicted value of leukocyte esterase (LE), nitrite, bacteriuria, and pyuria in the urinalysis for superficial wound infection. Then, all included patients were divided into two groups according to the preoperative urinalysis: a bacteriuria-positive group and a bacteriuria-negative group. The primary outcome was the superficial wound infection rate within 3 months postoperatively, and the secondary outcomes included wound leakage, prosthetic joint infection (PJI), pulmonary infection, urinary tract infection (UTI), readmission rate within 3 months postoperatively, and length of stay (LOS) during hospitalization. We utilized univariable analyses to compare the outcomes between the two groups. A multivariable logistic regression model was generated to explore the potential association between bacteriuria and the risk of superficial wound infection, wound leakage, and readmission rate controlling for baseline values.

RESULTS

A total of 963 patients were included in the study. One hundred sixty patients had abnormal urinalysis. The AUCs for LE, nitrite, bacteriuria, and pyuria were 0.507 (95% confidence interval (CI), 0.315 to 0.698), 0.551 (0.347 to 0.756), 0.675 (0.467 to 0.882), and 0.529 (0.331 to 0.728), respectively. Bacteriuria was diagnostically superior to LE, nitrite, and pyuria. Among the 963 patients, 95 had a positive bacteriuria on preoperative urinalysis, and only 9 (9.5%) had a positive urine culture. Compared with the bacteriuria-negative group, the bacteriuria-positive group had a higher superficial wound infection rate (4.2% vs. 0.6%, P = 0.008), higher wound leakage rate (11.6% vs. 4.5%, P = 0.007), higher readmission rate (5.3% vs. 1.3%, P = 0.015) within 3 months postoperatively and longer LOS (6.19 ± 2.89 days vs. 5.58 ± 2.14 days, P = 0.011). After adjustment, the bacteriuria-positive group had a significantly increased risk of superficial wound infection (OR = 7.587, 95%CI: 2.002 to 28.755, P = 0.003), wound leakage (OR = 3.044, 95%CI: 1.461 to 6.342, P = 0.003), and readmission (OR = 4.410, 95%CI: 1.485 to 13.097, P = 0.008).

CONCLUSION

Preoperative bacteriuria positivity on urinalysis significantly increased the risk of postoperative wound complications, readmission, and LOS in primary THA regardless of the result of the urine culture. Urinalysis is a fast and cost-acceptable test whose advantages have been underestimated.

LEVEL OF EVIDENCE

Level III, observational study.

Evaluation of the sysmex UF-5000 fluorescence flow cytometer as a screening platform for ruling out urinary tract infections in elderly patients presenting at the Emergency Department

In this study, we evaluated the performance of the flow cytometer-based Sysmex UF-5000 automated urine analyzer as a screening tool for ruling out urinary tract infections in elderly patients presenting at the emergency department. A total of 1119 unselected patient samples (including 544 samples from elderly patients) submitted for urine culture were included in this study. Samples were measured on UF-5000 and dipsticks and the results were compared with interpretation of culture results, which is the gold standard. We obtained a diagnostic sensitivity of 99% and specificity of 51% with a low rate of false negatives (0.2%) and a negative predictive value of 99% at 10⁸ colony forming bacteria/L (CFB/L). A bacterial count ≥ 50x10⁶/L or yeast like cells ≥ 25x10⁶/L was used as the cutoff value. At this cutoff value, 30% of the urine cultures would have been redundant. This resulted in 35% false positive samples, mainly due to particle contamination or nongrowing bacteria. In comparison, at best, the dipsticks have a diagnostic sensitivity of 89%, a specificity of 52% and a negative predictive value of 92% at 10⁸ CFB/L.

Rapid identification of uropathogens by combining Alfred 60 system with matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry technology

Rapid identification of uropathogens is needed to determine appropriate antimicrobial therapy. This study evaluated performance of the Alfred 60 system combined with matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) technology for rapid identification of uropathogens. The Alfred 60 system was used to screen urine cultures, followed by identifying the microbial pathogen in positive cultures using MALDI-TOF MS. The Alfred 60 detected positive cultures by measuring the turbidity of urine samples, which were transferred automatically to vials containing liquid medium and incubated for 3.5 h at 35 °C in the Alfred 60 system. Vials that showed growth were removed and centrifuged. The pellet was subjected to MALDI-TOF MS identification. In parallel, positive urine samples were inoculated onto agar plates for identification by conventional culture. The time required to detect positive urine cultures with Alfred 60 and identify the uropathogens with MALDI-TOF MS ranged from 15 min to 3.5 h. Among 146 positive urine samples tested, conventional cultures showed three culture groups: group 1 included 101 samples with growth of a single type of microorganism; group 2 included 34 samples with 2 types of microorganisms; and group 3 included 11 samples with ≥ 3 types of microorganisms. Direct identification by MALDI-TOF MS was concordant with 95% of the samples in group 1, 100% of the principal microorganism in group 2, but could not identify microorganisms in group 3. This combination of methods provides rapid, reliable microbial identification for most positive urine cultures.

Candiduria in hospitalized patients: an investigation with the Sysmex UF-1000i urine analyzer

Background

Candiduria is common in hospitalized patients. Its management is limited because of inadequate understanding. Previous epidemiological studies based on culture assay have been limited to small study populations. Therefore, data collected by automated systems from a large target population are necessary for more comprehensive understanding of candiduria in hospitalized patients.

Methods

To determine the performance of the Sysmex UF-1000i in detecting candiduria, a cross-sectional study was designed and conducted. A total of 203 yeast-like cell (YLC)-positive and 127 negative samples were randomly chosen and subjected to microbiologic analysis. The receiver operating characteristic curve (ROC) was used to evaluate the ability of YLC counts as measured by the Sysmex UF1000i to predict candiduria. Urinalysis data from 31,648 hospitalized patients were retrospectively investigated, and statistical analysis was applied to the data collected.

Results

Using a cutoff value of 84.6 YLCs/µL, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the yeast like cell (YLC) counts to predict candiduria were 61.7%, 84.1%, 88.6% and 66.3%, respectively. C. glabrata (33.6%) and C. tropicalis (31.4%) were more prevalent than C. albicans (24.3%) in the present study. Of the investigated hospitalized patients, 509 (1.61%) were considered candiduria-positive. Age, gender and basic condition were associated with candiduria in hospitalized patients. In the ICU setting, urinary catheterization appeared to be the only independent risk factor contributing to candiduria according to our investigation. Although antibiotic therapy has been reported to be a very important risk factor, we could not confirm its significance in ICU candiduria patients because of excessive antibiotic usage in our hospital.

Conclusions

The YLC measured by Sysmex UF-1000i is a practical and convenient tool for clinical candiduria screening prior to microbiologic culture. Candiduria is common in hospitalized patients, and its incidence varies according to age, gender and the wards where it is isolated. Candiduria had no direct connection with mortality but might be considered a marker of seriously ill patients who need particular attention in the clinic.

Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations

Background

Bacterium and leucocyte counts in urine can be measured by urine flow cytometry (UFC). They are used to predict significant bacterial growth in urine culture and to diagnose infections of the urinary tract. However, little information is available on appropriate UFC cut-off values for bacterium and leucocyte counts in specific clinical presentations.

Objective

To develop, validate, and evaluate adapted cut-off values that result in a high negative predictive value for significant bacterial growth in urine culture in common clinical presentation subgroups.

Methods

This is a single center, retrospective, observational study with data from patients of the emergency department of Bern University Hospital, Switzerland, with suspected infections of the urinary tract. The patients presented with different symptoms, and urine culture and urine flow cytometry were performed. For different clinical presentations, the patients were grouped by (i) age (>65 years), (ii) sex, (iii) clinical symptoms (e.g., fever or dysuria), and (iv) comorbidities such as diabetes and immunosuppression. For each group, cut-off values were developed, validated, and analyzed using different strategies, i.e., linear discriminant analysis (LDA) and Youden's index, and were compared with known cut-offs and cut-offs optimized for sensitivity.

Results

613 patients were included in the study. Significant bacterial growth in urine culture depended on clinical presentation and ranged from 32.3% in male patients to 61.5% in patients with urinary frequency. In all clinical presentations, the predictive accuracy of UFC leucocyte and UFC bacterium counts was good for significant bacterial growth in urine culture (AUC ≥ 0.88). The adapted LDA₉₅ equations did not exhibit consistently high sensitivity. However, the in-house cut-offs (test positive if UFC leucocytes > 17/μL or UFC bacteria > 125/μL) were highly sensitive (>90%). In female, younger, and dysuric patients, even higher cut-offs for UFC leucocytes (169/μL, 169/μL, and 205/μL) exhibited high sensitivity. Specificity was insufficient (<0.9) for all tested cut-offs.

Conclusions

For various clinical presentations, significant bacterial growth in urine culture can be excluded if flow cytometry measurements give a bacterial count of ≤125/μL or a leucocyte count of ≤17/μL. In female patients, dysuric patients, and patients younger than ≤65 years, the leucocyte cut-off can be increased to 170/μL.

Performance of yeast-like cell counting (YLCC) using the Sysmex UF-1000i for clinical candiduria screening

Candiduria is common in clinical practice. However, an effective and convenient assay to screen for candiduria is still needed. This study aimed to evaluate the performance of the Sysmex UF-1000i urine analyzer for yeast-like cell counting (YLCC) to screen for candiduria prior to urine culture. We retrospectively analyzed data from 5233 urine samples from 1813 patients, including 837 males and 976 females. Urine culture and urinalysis-obtained YLCC data were used to estimate the performance of YLCC in diagnosing candiduria. Different cutoff values were used to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The YLCC-positive rates differed according to the Candida colony-forming units (CFU) counts in the urine samples. A sharp drop in YLCC-positive rate (from 64.3 to 22.0%) was observed between the urine groups with 10⁴ CFUs and 10³ CFUs. A cutoff value of 0 YLCs/μL results in the highest Youden index (0.71) with 77.04% sensitivity and 93.68% specificity. In a group of 34 hospitalized candiduria patients with serial urinalysis data, 25 were YLCC-positive before urine culture. In conclusion, YLCC with the Sysmax UF-1000i could serve as an auxiliary technique to exclude culture-negative specimens prior to urine culture. Positive YLCC results could imply candiduria, especially when persistent YLCC-positive results were observed.

Comparing Two Automated Techniques for the Primary Screening-Out of Urine Culture

Urinary tract infection is the most common human infection with a high morbidity. In primary care and hospital services, conventional urine culture is a key part of infection diagnosis but results take at least 24 h. Therefore, a rapid and reliable screening method is still needed to discard negative samples as quickly as possible and to reduce the laboratory workload. In this aspect, this study aims to compare the diagnostic performance between Sysmex UF-1000i and FUS200 systems in comparison to urine culture as the gold standard. From March to June 2016, 1,220 urine samples collected at the clinical microbiology laboratory of the “Miguel Servet” hospital were studied in parallel with both analysers, and some technical features were evaluated to select the ideal equipment. The most balanced cut-off values taking into account bacteria or leukocyte counts were 138 bacteria/μL or 119.8 leukocyte/μL for the UF-1000i (95.3% SE and 70.4% SP), and 5.7 bacteria/μL or 4.3 leukocyte/μL for the FUS200 (95.8% SE and 44.4% SP). The reduction of cultured plates was 37.4% with the FUS200 and 58.3% with the UF-1000i. This study shows that both techniques improve the workflow in the laboratory, but the UF-1000i has the highest specificity at any sensitivity and the FUS200 needs a shorter processing time.

Urine Flow Cytometry in the Diagnosis of Urinary Tract Infection

OBJECTIVES

To determine the cut-off value of bacteria with urine flow cytometer in diagnosing urinary tract infection.

METHODS

From a total of 546 patients admitted to the hospital with urinary tract infection (UTI), two urine samples were obtained for each patient. Urine samples in sterile containers were divided into two; first for urine culture and second for simultaneous measurement with UF-1000i flow cytometry device. The presence of a single type of bacteria over 10³ CFU/mL in urine culture was accepted as UTI.

RESULTS

Of 546 patients, 210 (38.5%) were boys and 336 (61.5%) were girls. There was no growth in 489 (89.5%) of the urine specimens and 57 (10.4%) samples showed growth (>10³ CFU/ml). A threshold of 10 bacteria/μL in flow cytometry (sensitivity = 100%) showed the best compatibility with culture. Diagnostic values in terms of sensitivity (100%), specificity (43.5%), negative predictive value (100%) and positive predictive value (17.7%) were satisfactory.

CONCLUSIONS

The UF-1000i flow cytometer can give results quickly and exclude UTI using the determined number of cut-off bacteria at low cost. Thus, if Sysmex UF-1000i is used, quick and accurate results can be obtained and unnecessary laboratory tests can be prevented. Also, patient convenience can be increased.

High false positive rate of white blood cells in urine samples of pregnant women may be caused by epithelial cells being misclassified by the sysmex UF-1000i urine flow cytometer

Background

The UF‐1000i has been widely used in screening urinary sediments. However, the interference factor of the UF‐1000i in the screening urinary sediments of pregnant women has not been reported. The aim of the study was to demonstrate that epithelial cells (ECs) cause a high false positive rate of white blood cells (WBCs) by the UF‐1000i in pregnant women.

Methods

Urine samples were collected from 207 pregnant women. All samples were measured by the UF‐1000i and a microscopic method.

Results

The areas under the curve (AUC) for WBC and EC counts were 0.837 (95% CI, 0.773–0.901) and 0.844 (95% CI, 0.785–0.903), respectively. The positive rates of the WBC and EC were 73.43% and 37.20%, respectively, by the UF‐1000i, and they were 19.32% and 72.95% by the microscopic method. The positive predictive value, negative predictive value, false positive rates, and false negative rates by the UF‐1000i were for WBC 25.66%, 98.18%, 74.34%, and 1.82%, respectively, and for EC they were 96.1%, 40.77%, 3.9%, and 59.23%, respectively. The coefficient of correlation R value was 0.503 (P < 0.01) between WBC by UF‐1000i and EC by the microscopic method in WBC false positive samples.

Conclusions

EC could be an interference factor for the UF‐1000i in screening urinary WBC of pregnant women, and the high false positive rate for WBC may be caused by ECs being misclassified as WBCs by the UF‐1000i. © 2018 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals, Inc. on behalf of International Clinical Cytometry Society.

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.

Validation and Search of the Ideal Cut-Off of the Sysmex UF-1000i® Flow Cytometer for the Diagnosis of Urinary Tract Infection in a Tertiary Hospital in Spain

Urinary tract infections (UTI) are one of the most prevalent infections. A rapid and reliable screening method is useful to screen out negative samples. The objective of this study was to validate the Sysmex flow cytometer UF-1000i by evaluating its accuracy, linearity and carry-over; and define an optimal cut-off value to be used in routine practice in our hospital. For the validation of the UF-1000i cytometer, precision, linearity and carry-over were studied in samples with different counts of bacteria, leukocytes and erythrocytes. Between March and June 2016, urine samples were tested in the Clinical Microbiology Laboratory at University Miguel Servet Hospital, in Spain. Samples were analyzed with the Sysmex UF-1000i cytometer, and cultured. Growth of ≥10⁵ CFUs/mL was considered positive. The validation study reveals that the precision in all the variables is acceptable; that there is a good linearity in the dilutions performed, obtaining values almost identical to those theoretically expected; and for the carry-over has practically null values. A total of 1,220 urine specimens were included, of which 213 (17.4%) were culture positive. The optimal cut-off point of the bacteria–leukocyte combination was 138.8 bacteria or 119.8 leukocytes with an S and E of 95.3 and 70.4%, respectively. The UF-1000i cytometer is a valuable method to screen urine samples to effectively rule out UTI and, may contribute to the reduction of unnecessary urine cultures.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter

Objective

Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter.

Methods

This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated.

Results

Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared.

Conclusions

Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected.

Laboratory diagnosis of urinary tract infections: Towards a BILULU consensus guideline

Urinary tract infections (UTI) are very common throughout life and account for the majority of the workload in the clinical microbiology laboratory. Clear instructions for the interpretation of urine cultures by the laboratory technicians are indispensable to obtain standardized, reliable, and clinically useful results. In literature, there is often a lack of evidence-based practice in processing urinary samples in the laboratory. In this consensus document, the BILULU Study Group presents a practical approach for the implementation of existing guidelines for the culture of urine in the microbiology laboratory and offers answers for issues where no clear solution is available in the guidelines.

Sysmex UF-1000i flow cytometer to screen urinary tract infections: the URISCAM multicentre study

The new Sysmex UF-1000i analyzer - which incorporates bacteria morphology distinction - allows to automatically screen samples to be cultured at microbiology laboratories. We have evaluated the feasibility and accuracy of Sysmex UF-1000i to screen urinary tract infections (UTIs). A total amount of 2468 urine samples from six Spanish hospitals were analysed. Demographic and clinical data such as age, gender, source and sample type, preserving conditions, cytometer parameters (bacteria, leucocytes and bacteria morphology) as well as urine culture results (gold standard) were recorded. After applying data mining techniques, the variables of age, bacteria count and rod morphology were defined as predictive variables of UTIs. By using the UF-1000i in combination with a predictive algorithm of three decision rules, we could identify 94·9 and 47·4% positive and negative urine samples, respectively, with a negative predictive value of 97 and only 1·17% diagnostic error. This error was reduced down to 0·4% when contaminated samples were excluded. Our results show that flow cytometry parameters together with age, by means of a predictive algorithm model, can be used to screen UTIs. Its implementation would avoid culturing 38% of urine samples, and therefore, would reduce time to diagnosis with a discrete false negative ratio.

SIGNIFICANCE AND IMPACT OF THE STUDY

Fluorescent flow cytometry performance has recently spread for urine screening. However, controversy about cytometer results can be drawn from medical literature. This study shows the diagnosis accuracy of Sysmex UF-1000i analyzer by means of a group of decision rules encompassing both demographic variables (age) and cytometer parameters (bacteria, leucocytes and bacteria morphology). After applying the predictive algorithm, the UF-1000i could optimally identify 95% urinary tract infections with high negative predictive value and low diagnostic error. Implementation of UF-1000i would avoid culturing almost 38% of urine samples, thus reducing time to diagnosis, unnecessary antibiotic treatments and consequently improving cost-effectiveness.

Multicenter Evaluation of an Image Analysis Device (APAS): Comparison Between Digital Image and Traditional Plate Reading Using Urine Cultures

BACKGROUND

The application of image analysis technologies for the interpretation of microbiological cultures is evolving rapidly. The primary aim of this study was to establish whether the image analysis system named Automated Plate Assessment System (APAS; LBT Innovations Ltd., Australia) could be applied to screen urine cultures. A secondary aim was to evaluate differences between traditional plate reading (TPR) and the reading of cultures from images, or digital plate reading (DPR).

METHODS

A total of 9,224 urine samples submitted for culture to three clinical laboratories, two in Australia and one in the USA, were included in the study. Cultures were prepared on sheep blood and MacConkey agar plates and read by panels of three microbiologists. The plates were then presented to APAS for image capture and analysis, and the images and results were stored for later review.

RESULTS

Image analysis of cultures using APAS produced a diagnostic sensitivity and specificity of 99.0% and 84.5%, respectively. Colonies were detected by APAS on 99.0% of blood agar plates with growth and on 99.5% of MacConkey agar plates. DPR agreed with TPR for colony enumeration on 92.1% of the plates, with a sensitivity of 90.8% and specificity of 92.8% for case designation. However, several differences in the classification of colony morphologies using DPR were identified.

CONCLUSIONS

APAS was shown to be a reliable screening system for urine cultures. The study also showed acceptable concordance between DPR and TPR for colony detection, enumeration, and case designation.

Emerging nanotechnology based strategies for diagnosis and therapeutics of urinary tract infections: A review

At present, various diagnostic and therapeutic approaches are available for urinary tract infections. But, still the quest for development of more rapid, accurate and reliable approach is an unending process. The pathogens, especially uropathogens are adapting to new environments and antibiotics day by day rapidly. Therefore, urinary tract infections are evolving as hectic and difficult to eradicate, increasing the economic burden to the society. The technological advances should be able to compete the adaptability characteristics of microorganisms to combat their growth in new environments and thereby preventing their infections. Nanotechnology is at present an extensively developing area of immense scientific interest since it has diverse potential applications in biomedical field. Nanotechnology may be combined with cellular therapy approaches to overcome the limitations caused by conventional therapeutics. Nanoantibiotics and drug delivery using nanotechnology are currently growing areas of research in biomedical field. Recently, various categories of antibacterial nanoparticles and nanocarriers for drug delivery have shown their potential in the treatment of infectious diseases. Nanoparticles, compared to conventional antibiotics, are more beneficial in terms of decreasing toxicity, prevailing over resistance and lessening costs. Nanoparticles present long term therapeutic effects since they are retained in body for relatively longer periods. This review focuses on recent advances in the field of nanotechnology, principally emphasizing diagnostics and therapeutics of urinary tract infections.

Automated Flow Cytometry: An Alternative to Urine Culture in a Routine Clinical Microbiology Laboratory?

The urine culture is the "gold standard" for the diagnosis of urinary tract infections (UTI) but constitutes a significant workload in the routine clinical laboratory. Due to the high percentage of negative results, there is a need for an efficient screening method, with a high negative predictive value (NPV) that could reduce the number of unnecessary culture tests. With the purpose of improving the efficiency of laboratory work, several methods for screening out the culture-negative samples have been developed, but none of them has shown adequate sensitivity (SE) and high NPV. Many authors show data about the efficacy of flow cytometry in the routine clinical laboratory. The aim of this article is to review and discuss the current literature on the feasibility of urine flow cytometry (UFC) and its utility as an alternative analytical technique in urinalysis.

Performance assessment of urine flow cytometry (UFC) to screen urines to reflex to culture in immunocompetent and immunosuppressed hosts

PURPOSE

Urine flow cytometry (UFC) is an automated method to quantify bacterial and white blood cell (WBC) counts. We aimed to determine whether a threshold for these parameters can be set to use UFC as a sensitive screen to predict which urine samples will subsequently grow in culture.

METHODOLOGY

Urines submitted to our microbiology laboratory at a tertiary care centre from 22 July 2015-17 February 2016 underwent UFC (Sysmex UF-1000i) analysis, regular urinalysis and urine culture. Positive urine cultures were defined as growth ≥104 c.f.u. ml-1 of organisms associated with urinary tract infections. The correlation of UFC bacterial and WBC counts with urine culture was assessed using receiver operating characteristics curves. The sensitivity (SN), specificity (SP), negative predictive values (NPVs), positive predictive values (PPVs) and false negative rate (FNR) were calculated at various thresholds in immunocompetent and immunosuppressed patients.

RESULTS

A total of 15 046 urine specimens were submitted, of which 14 908 were analysable in the study. The average time to UFC result from receipt in the laboratory was 0.76 h (+/-1.04). The test performance at a set threshold of UFC bacteria ≥20 or WBC >5 was: SN=96.0 %, SP=39.2 %, PPV=47.0 %, NPV=94.5 % and FNR=4.0 %. This threshold eliminates 26 % of urine cultures. Immunosuppressed hosts had a lower sensitivity of 90.6 % and a higher FNR of 9.4 %.

CONCLUSIONS

UFC is a rapid and sensitive method to screen out urine samples that will subsequently be negative and to reflex urines to culture that will subsequently grow. UFC results are available within 1 h from receipt and enable the elimination of culture when the set threshold is not met.

Flow cytometric analysis of viable bacteria in urine samples of febrile patients at the emergency department

BACKGROUND

Fast and reliable diagnostics are important in febrile patients admitted to the emergency department. Current urine diagnostics are fast but moderately reliable or reliable but time consuming. Flow cytometry (FC) is a new promising technique in the diagnostics of complicated urinary tract infections by counting bacteria in urine samples. The aim of this study is to improve the FC method by counting only viable bacteria.

METHODS

Urine was obtained from 135 consecutive febrile patients at the emergency department. According to protocol regular diagnostic urine tests were performed. In addition, FC counting of viable and non-viable bacteria was executed after staining with thiazole orange and propidium iodide. All test results were compared to the results of urine culture (≥ 10⁵ colony forming units/mL).

RESULTS

At a cut-off value of 2.01 × 10⁵ viable bacteria/mL the sensitivity was 100% and specificity was 78.4% (AUC-value 0.955 on ROC-curve). Spearman correlation test exhibited a higher correlation for flow cytometric counting of only viable bacteria than counting of all bacteria (0.59 vs. 0.37). Using ROC-curves, the AUC-values for FC counting of all bacteria, only viable bacteria and Gram staining were respectively 0.935, 0.955, and 0.968 (P > 0.05).

CONCLUSION

FC counting of only viable bacteria can predict quickly and reliably positive and negative urine cultures in febrile patients admitted to the emergency department. It can help to improve the speed and accuracy of the diagnostic procedure at the emergency department. © 2017 Clinical Cytometry Society.

Evaluation of the Cobas u 701 microscopy analyser compared with urine culture in screening for urinary tract infection

Purpose. A new automated Cobas u 701 microscopy analyser for urine sediment examination was introduced. The aim of this study was to evaluate the analyser in comparison with urine culture in screening for urinary tract infection (UTI).Methodology. A total of 852 urine specimens submitted for culture were included in this study. Urine sediment examination was performed using the Cobas u 701 microscopy analyser. The results of the bacteria (BAC) and yeast (YEA) analyses were compared with the results from urine culture as a method for UTI screening. In addition, we compared the BAC results with white blood cells (WBCs) and leukocyte and nitrite measurement in the Cobas u 601 system.Results. Of the 852 urine specimens, 16.1 % (N=137) were positive by urine culture, yielding 130 bacteria from 124 specimens and 14 yeasts from 14 specimens. The Cobas u 701 microscopy analyser provided no result for 52 specimens because of their high turbidity. The sensitivity, specificity, positive predictive value and negative predictive value were 85.8, 69.4, 33.1 and 96.5 %, respectively. For YEA, these figures were 100, 91.9, 15.8 and 100 %, respectively. The areas under the curve for BAC and WBCs were 0.827 [95 % confidence interval (CI) 0.799, 0.852] and 0.727 (95 % CI 0.695, 0.757), respectively. The sensitivity of the leukocyte and nitrite was 63.5 and 54.6 %, respectively.Conclusion. The Cobas u 701 microscopy analyser showed good diagnostic performance. It can be used for rapid screening for UTI and can reduce the number of cultures required.

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.

A new concept and a comprehensive evaluation of SYSMEX UF-1000i flow cytometer to identify culture-negative urine specimens in patients with UTI

Urinary tract infections (UTIs) are among the most common bacterial infections in men and urine culture is gold standard for diagnosis. Considering the high prevalence of culture-negative specimens, any method that identifies such specimens is of interest. The aim was to evaluate a new screening concept for flow cytometry analysis (FCA). The outcomes were evaluated against urine culture, uropathogen species and three conventional screening methods. A prospective, consecutive study examined 1,312 urine specimens, collected during January and February 2012. The specimens were analyzed using the Sysmex UF1000i FCA. Based on the FCA data culture negative specimens were identified in a new model by use of linear discriminant analysis (FCA-LDA). In total 1,312 patients were included. In- and outpatients represented 19.6% and 79.4%, respectively; 68.3% of the specimens originated from women. Of the 610 culture-positive specimens, Escherichia coli represented 64%, enterococci 8% and Klebsiella spp. 7%. Screening with FCA-LDA at 95% sensitivity identified 42% (552/1312) as culture negative specimens when UTI was defined according to European guidelines. The proposed screening method was either superior or similar in comparison to the three conventional screening methods. In conclusion, the proposed/suggested and new FCA-LDA screening method was superior or similar to three conventional screening methods. We recommend the proposed screening method to be used in clinic to exclude culture negative specimens, to reduce workload, costs and the turnaround time. In addition, the FCA data may add information that enhance handling and support diagnosis of patients with suspected UTI pending urine culture.

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.

Analysis of the costs for the laboratory of flow cytometry screening of urine samples before culture

Urine culture samples comprise a large proportion of the workload in clinical microbiology laboratories, and most of the urine samples show no growth or insignificant growth. A flow cytometry-based analyzer (Sysmex Corporation, Japan) has been used to screen out negative urine samples prior to culture in the Päijät-Häme district. We applied decision analytic modelling to analyze, from a laboratory perspective, the economic feasibility of the screening method as compared to culture only (conventional method) for diagnosis of urinary tract infection. Our model suggests that the least costly analytical strategy is the conventional method. The incremental cost of screening is €0.29/sample. Although laboratory costs are higher, considerable savings on workload can be achieved. Furthermore, screening has numerous benefits on the treatment process of a patient that well warrant the use of the screening method. We conclude that the incremental cost of screening the samples is worth the expense.

Evaluation of the appropriate time period between sampling and analyzing for automated urinalysis

Introduction

Preanalytical specifications for urinalysis must be strictly adhered to avoid false interpretations. Aim of the present study is to examine whether the preanalytical factor ‘time point of analysis’ significantly influences stability of urine samples for urine particle and dipstick analysis.

Materials and methods

In 321 pathological spontaneous urine samples, urine dipstick (Urisys™2400, Combur-10-Test™strips, Roche Diagnostics, Mannheim, Germany) and particle analysis (UF-1000 i™, Sysmex, Norderstedt, Germany) were performed within 90 min, 120 min and 240 min after urine collection.

Results

For urine particle analysis, a significant increase in conductivity (120 vs. 90 min: P < 0.001, 240 vs. 90 min: P < 0.001) and a significant decrease in WBC (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), RBC (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), casts (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001) and epithelial cells (120 vs. 90 min P = 0.610, 240 vs. 90 min P = 0.041) were found. There were no significant changes for bacteria. Regarding urine dipstick analysis, misclassification rates between measurements were significant for pH (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), leukocytes (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), nitrite (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), protein (120 vs. 90 min P < 0.001, 240 vs. 90 min P<0.001), ketone (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), blood (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001), specific gravity (120 vs. 90 min P < 0.001, 240 vs. 90 min P < 0.001) and urobilinogen (120 vs. 90 min, P = 0.031). Misclassification rates were not significant for glucose and bilirubin.

Conclusion

Most parameters critically depend on the time window between sampling and analysis. Our study stresses the importance of adherence to early time points in urinalysis (within 90 min).

Performance of the Sysmex UF-1000i urine analyser in the rapid diagnosis of urinary tract infections in hospitalized patients

BACKGROUND

Urinary tract infections (UTIs) are the second most frequently encountered nosocomial infectious diseases, and they greatly increase the cost of medical care and prolong the duration of hospital stays.

AIM

We aimed to evaluate the performance of the Sysmex UF-1000i analyser for the rapid prediction of UTIs in hospitalized patients with or without indwelling catheters at a comprehensive teaching hospital that encounters complex disease types.

METHODS

Urine specimens (n = 1016) were cultured and examined for WBC, RBC, bacteria (BACT) and yeast-like cell (YLC) count using the Sysmex UF-1000i. The results were compared with the urine culture results. Receiver operating characteristic curve analysis was applied to determine BACT and YLC cutoff values for bacterial and fungal UTIs independently. The diagnostic ability of the UF-1000i was also compared for patients with and without indwelling catheters.

FINDINGS

A cutoff value of 38.7/μL was acceptable for ruling out bacterial UTIs. In this setting, we achieved a sensitivity of 90%, a negative predictive value of 94.5%, a false negative rate of 2.85% (29 cases), and avoided culturing in 52% of the samples. The BACT count presented a larger area under the curve for patients with indwelling catheters than for those without (0.939 vs. 0.861); however, no significant difference in the diagnostic ability of the two curves was found.

CONCLUSION

The Sysmex UF-1000i analyser could be a reliable method for excluding bacterial UTIs in hospitalized patients with or without urinary catheters and could help clinicians determine whether antibiotic therapy is necessary.

Evaluation of an Image Analysis Device (APAS) for Screening Urine Cultures

While advancements have been made in some areas of pathology with diagnostic materials being screened using image analysis technologies, the reporting of cultures from agar plates remains a manual process. We compared the results for 2,163 urine cultures read by a reference panel of microbiologists, by the routine laboratory process, and by an automated plate reading system, APAS (LBT Innovations Ltd., South Australia). APAS detected colonies with a sensitivity of 99.1% and a specificity of 99.3% on blood agar, while on MacConkey agar, the colony detection sensitivity was 99.4% with a specificity of 99.3%. The device's ability to enumerate growth had an accuracy of 89.2%, and the morphological identification of colonies showed a high level of performance for the colony types typical of Escherichia coli and other enteric bacilli. On blood agar, lactose-fermenting colonies were morphologically identified with a sensitivity of 98.9%, while on MacConkey agar they were identified with a sensitivity of 99.2%. In this first clinical evaluation, APAS demonstrated high performance in the detection, enumeration, and colony classification of isolates compared with that for conventional plate-reading methods. The device found all cases reported by the laboratory and detected the most commonly encountered organisms found in urinary tract infections.

Direct Identification of Urinary Tract Pathogens from Urine Samples, Combining Urine Screening Methods and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Early diagnosis of urinary tract infections (UTIs) is essential to avoid inadequate or unnecessary empirical antibiotic therapy. Microbiological confirmation takes 24 to 48 h. The use of screening methods, such as cytometry and automated microscopic analysis of urine sediment, allows the rapid prediction of negative samples. In addition, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a widely established technique in clinical microbiology laboratories used to identify microorganisms. We evaluated the ability of MALDI-TOF MS to identify microorganisms from direct urine samples and the predictive value of automated analyzers for the identification of microorganisms in urine by MALDI-TOF MS. A total of 451 urine samples from patients with suspected UTIs were first analyzed using the Sysmex UF-1000iflow cytometer, an automatic sediment analyzer with microscopy (SediMax), culture, and then processed by MALDI-TOF MS with a simple triple-centrifuged procedure to obtain a pellet that was washed and centrifuged and finally applied directly to the MALDI-TOF MS plate. The organisms in 336 samples were correctly identified, mainly those with Gram-negative bacteria (86.10%). No microorganisms were misidentified, and noCandidaspp. were correctly identified. Regarding the data from autoanalyzers, the best bacteriuria cutoffs were 1,000 and 200 U/μl for UF-1000iand SediMax, respectively. It was concluded that the combination of a urine screening method and MALDI-TOF MS provided a reliable identification from urine samples, especially in those containing Gram-negative bacteria.

The effectiveness of BD Vacutainer® Plus Urinalysis Preservative Tubes in preservation of urine for chemical strip analysis and particle counting

INTRODUCTION

The aim of this study was to evaluate the stability of urine collected in preservative tubes for chemistry strip analyses and particle counting to determine whether the transport of urine samples with all of their constituents is possible.

MATERIALS AND METHODS

275 pathologic urine specimens were included. Each urine sample was evaluated after 4, 8, 12, 24, and 48 hours of storage in BD Vacutainer(®) Plus Urinalysis Preservative (BD UAP) tubes and compared with refrigeration at 4 °C. All analyses were peformed on H-800 and FUS-200 automatic modular urine analyzers (Dirui Industry, Changchun, China). The kappa coefficients (κ), false positive (FP) and false negative (FN) rates were evaluated. κ > 0.8 was accepted as good agreement.

RESULTS

Haemoglobin (Hb), leucocyte esterase (LE), and protein (Pro) analyses should be performed within 4 hours, whereas glucose (Glc) was stable until the end of 48 hours in both storage conditions. Nitrite (Nit) was well preserved in BD UAP tubes for 24 hours but was stable only up to 8 hours at 4 °C. Bilirubin (Bil) had very high FN rates even at 4 hours in both conditions. The particle counting showed high FN rates for white blood cells (WBC) and red blood cells (RBC), whereas squamous epithelial cells (EC) were stable up to 8 hours in both conditions.

CONCLUSIONS

Preanalytical requirements for both urine chemical strip analyses and particle counting in a unique sample were not met in either condition. Thus, the transfer of urine samples for centralization of urinalysis is not yet feasible.

A new approach to determine the susceptibility of bacteria to antibiotics directly from positive blood culture bottles in two hours

The rapid identification and antibiotic susceptibility test of bacteria causing bloodstream infections are given a very high priority by clinical laboratories. In an effort to reduce the time required for performing antibiotic susceptibility test (AST), we have developed a new method to be applied from positive blood culture bottles. The design of method was performed using blood culture bottles prepared artificially with five strains which have a known susceptibility. An aliquot of the blood culture was subcultured in the presence of specific antibiotics and bacterial counts were monitored using the Sysmex UF-1000i flow cytometer at different times up to 180min. Receiver operating curve (ROC) analysis allowed us to find out the cut-off point for differentiating between sensitive and resistant strains to the tested antibiotic. This procedure was then validated against standard commercial methods on a total of 100 positive blood culture bottles from patients. First, bacterial identification was performed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) directly from positive blood culture bottles as we have previously reported. Secondly, antibiotic susceptibility test was performed in the same way that was carried out in artificially prepared blood culture bottles. Our results indicate that antibiotic susceptibility test can be determined as early as 120min since a blood culture bottle is flagged as positive. The essential agreement between our susceptibility test and commercial methods (E-test, MicroScan and Vitek) was 99%. In summary, we conclude that reliable results on bacterial identification and antibiotic susceptibility test performed directly from positive blood culture bottles can be obtained within 3h.

Evaluation and optimization of the Sysmex UF1000i system for the screening of urinary tract infection in primary health care elderly patients

OBJECTIVE

Urinary tract infections (UTIs) are a common problem in the elderly population. Urine culture is still considered the "gold standard" to diagnose infection in this population. However, urine cultures are laborious and costly, and most samples will yield no growth.

METHODS

An evaluation was made of the Sysmex UF-1000i flow cytometer as a screening tool for UTI in an elderly population older than 65 years who lived in the community, using 346 urine samples submitted for culture.

RESULTS

The Receiver Operating Characteristic (ROC) analysis showed a significant difference (P<0.01) between 0.98 bacteria area under the curve value and 0.82 of white blood cells (WBC). The combination of both counts for screening did not show any improvement in specificity or sensitivity. According to our data, the use of a single cut-off point of 200bacteria/μL is suggested, in which the sensitivity and specificity were 99.11% and 91.59%, respectively, with a NPV of 99.49%. Moreover, this cut-off value could avoid 60.24% of the samples to be cultured, with a minimal false negative results rate of 0.87%.

CONCLUSIONS

The stratification of age groups stratification helps in selecting a more adjusted Sysmex UF1000i cut-off limit, leading to an improvement in the screening parameters that would imply a better management of these infections, as well as a high reduction in the workload and cost savings.

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.

Detection of significant bacteriuria by use of the iQ200 automated urine microscope

In the microbiology laboratory, there is an augmented need for rapid screening methods for the detection of bacteria in urine samples, since about two-thirds of these samples will not yield any bacteria or will yield insignificant growth when cultured. Thus, a reliable screening method can free up laboratory resources and can speed up the reporting of a negative urine result. In this study, we have evaluated the detection of leukocytes, bacteria, and a new sediment indicator, the "all small particles" (ASP), by an automated instrument, the iQ200 urine analyzer, to detect negative urine samples that can be excluded from culture. A coupled automated strip reader (iChem Velocity), enabling the detection of nitrite and leukocyte esterase, was tested in parallel. In total, 963 urine samples were processed through both conventional urine culture and the iQ200/iChem Velocity workstation. Using the data, a multivariate regression model was established, and the predicted specificity and the possible reduction in urine cultures were calculated for the indicators and their respective combinations (leukocytes plus bacteria plus ASP and leukocyte esterase plus nitrite). Among all options, diagnostic performance was best using the whole microscopic content of the sample (leukocytes plus bacteria plus ASP). By using a cutoff value of ≥ 10(4) CFU/ml for defining a positive culture, a given sensitivity of 95% resulted in a specificity of 61% and a reduction in urine cultures of 35%. By considering the indicators alone, specificity and the culture savings were both much less satisfactory. The regression model was also used to determine possible cutoff values for running the instrument as part of daily routine. By using a graphical representation of all combinations possible, we derived cutoff values for leukocyte, bacterial, and ASP count, which should enable the iQ200 microscope to screen out approximately one-third of the urine samples, significantly reducing the workload in the microbiology laboratory.

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.