Screening of urine samples by flow cytometry reduces the need for culture

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

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

A fully interpretable machine learning model for increasing the effectiveness of urine screening

OBJECTIVES

This article addresses the need for effective screening methods to identify negative urine samples before urine culture, reducing the workload, cost, and release time of results in the microbiology laboratory. We try to overcome the limitations of current solutions, which are either too simple, limiting effectiveness (1 or 2 parameters), or too complex, limiting interpretation, trust, and real-world implementation ("black box" machine learning models).

METHODS

The study analyzed 15,312 samples from 10,534 patients with clinical features and the Sysmex Uf-1000i automated analyzer data. Decision tree (DT) models with or without lookahead strategy were used, as they offer a transparent set of logical rules that can be easily understood by medical professionals and implemented into automated analyzers.

RESULTS

The best model achieved a sensitivity of 94.5% and classified negative samples based on age, bacteria, mucus, and 2 scattering parameters. The model reduced the workload by an additional 16% compared to the current procedure in the laboratory, with an estimated financial impact of €40,000/y considering 15,000 samples/y. Identified logical rules have a scientific rationale matched to existing knowledge in the literature.

CONCLUSIONS

Overall, this study provides an effective and interpretable screening method for urine culture in microbiology laboratories, using data from the Sysmex UF-1000i automated analyzer. Unlike other machine learning models, our model is interpretable, generating trust and enabling real-world implementation.

Customized cutoff limits for the sediMAX-2 automated analyzer reduce the number of urine culture tests

BACKGROUND

Urinary tract infections are highly prevalent in nosocomial and community settings. Their diagnosis, although costly and time-consuming, is crucial to avoid inappropriate treatments and/or clinical complications. In this context, automated analyzers have been developed and commercialized to screen and rule out negative urine samples. Adjustments of the manufacturers' suggested cutoff values might lead to substantial diagnostic and economic advantages.

METHODS

We retrospectively analyzed 776 urine samples from different individuals. 546 samples (training group) were used to optimize develop new cutoffs values. The remaining 230 samples (validation group) were used to validate the optimized cutoffs. All samples were subjected to urine culture, 17% resulted positive. Escherichia coli and Enterococcus faecalis were the two most frequently identified bacteria, 95 and 9 samples, respectively.

RESULTS

Two different cutoffs levels were obtained. Cutoff-A (bacteria>110 and/or white blood cells> 15 cell/µL), showed the same sensitivity of the manufacturers' suggested cutoff, yet leads to a large reduction of the samples to be cultured. Cutoff-B (bacteria>50 and/or white blood cells>20 cell/µL), showed an almost 100% sensitivity by subjecting only ~70% of the samples to urine culture.

CONCLUSION

Cutoff-A is a good compromise between sensitivity and specificity yet allowing economic advantages by reducing the number of urinary cultures. Cutoff-B relegates urinary tract infection misdiagnosis to a rare event without the need of culturing the entire batch of samples. We believe that clinical implementation of the proposed cutoffs will help other laboratories, using similar instrumentation, to reach their most convenient balance between sensitivity and economical needs.

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.

Convergence of flow cytometry and bacteriology. Current and future applications: a focus on food and clinical microbiology

Since its development in the 1960s, flow cytometry (FCM) was quickly revealed a powerful tool to analyse cell populations in medical studies, yet, for many years, was almost exclusively used to analyse eukaryotic cells. Instrument and methodological limitations to distinguish genuine bacterial signals from the background, among other limitations, have hampered FCM applications in bacteriology. In recent years, thanks to the continuous development of FCM instruments and methods with a higher discriminatory capacity to detect low-size particles, FCM has emerged as an appealing technique to advance the study of microbes, with important applications in research, clinical and industrial settings. The capacity to rapidly enumerate and classify individual bacterial cells based on viability facilitates the monitoring of bacterial presence in foodstuffs or clinical samples, reducing the time needed to detect contamination or infectious processes. Besides, FCM has stood out as a valuable tool to advance the study of complex microbial communities, or microbiomes, that are very relevant in the context of human health, as well as to understand the interaction of bacterial and host cells. This review highlights current developments in, and future applications of, FCM in bacteriology, with a focus on those related to food and clinical microbiology.

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

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

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.

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

BACKGROUND

Our study aims to evaluate the performance of the combination of Sysmex urine dry chemistry analyzer UC-3500 and urine particle analyzer UF-5000 in screening bacterial urinary tract infection (UTI).

METHODS

We analyzed 2000 urine specimens from patients with suspected UTI by using a urine dry chemistry analyzer (UC-3500) and a fully automated sediment analyzer (UF-5000). After being tested by the instrument, all specimens were sent to our clinical microbiology laboratory for culture. In addition, 600 urine specimens were selected to evaluate the accuracy of the six screening strategies established in this study.

RESULTS

The consistency of UF-5000 bacterial classification and bacterial culture was fair (Kappa = 0.339). The counts of WBC and BACT elevated with sequential group designs (P < 0.001). The cut-off value of WBC was 32.20/μL for males (AUC, 0.942, 95%CI, 0.930-0.955) and 39.15/μL for females (AUC, 0.931, 95%CI, 0.914-0.948). The sensitivity and specificity of WBC were relatively higher than those of BACT. Strategy④ and Strategy⑥ in all six strategies had a good negative predictive value (NPV) which was 98.73%.

CONCLUSION

UF-5000 bacterial classification cannot be used as a practical reference. 32.20/μL (male) and 39.15/μL (female) for WBC as well as 22.35/μL (male) and 127.25/μL (female) for BACT were used as cut-off values to effectively determine whether UTI occurs. WBC, BACT and LEU joint screening programs were suitable to rapidly and effectively exclude bacterial UTI.

Effecting the culture: Impact of changing urinalysis with reflex to culture criteria on culture rates and outcomes

OBJECTIVE

To evaluate the impact of changes to urinalysis with reflex to culture (UARC) reflex criteria on culture performance and clinical decision outcomes.

DESIGN

Retrospective study utilizing interrupted time series analysis from December 2018 to November 2020. Primary outcomes were measures of culture performance. Secondary outcomes were rates of antimicrobial prescription for suspected urinary tract infection (UTI) and catheter-associated urinary tract infection (CAUTI). We also assessed harmful events related to antimicrobial prescription for all causes and UTI, UTI symptoms, and sepsis.

SETTING

A 415-bed, academic, tertiary-care, medical center.

PATIENTS

Hospitalized adult patients with urine testing performed.

INTERVENTION

UARC reflex criteria were changed on October 22, 2019, from ≥5×109/L white blood cells (WBCs) or trace leukocyte esterase or positive nitrite units on urinalysis to only ≥15×109/L WBCs.

RESULTS

The study included 11,322 unique UARC tests. We detected a significant decrease in the rate of urine cultures performed from UARC after the intervention (32.5-8.7 cultures per 1,000 patient days; P < .001), with improved diagnostic efficacy (ie, culture positivity increased from 34.8% to 62.1%). CAUTI rates did not change. We detected a significant decrease in antimicrobial prescription rates (P = .05), this was primarily driven by preintervention changes. One case of sepsis occurred secondary to a missed UTI, and UTIs were rarely missed after the intervention.

CONCLUSIONS

Implementation of a stricter UARC reflex criterion was associated with a decrease in culture rates with improved diagnostic efficacy without significant adverse events. Continued education is needed to change antimicrobial prescribing practices.

Multiplex high-resolution melting assay for simultaneous detection of five key bacterial pathogens in urinary tract infections: A pilot study

The diagnosis of urinary tract infections (UTIs) is usually based on the results of urine culture, but it is time-consuming, labor-intensive and has a low sensitivity. The aim of this study was to develop multiplex high-resolution melting assay (MHRM) for the simultaneous detection of five common bacterial pathogens (Escherichia coli, Klebsiella pneumoniae, Staphylococcus saprophyticus, Enterococcus faecalis, and group B streptococci (GBS)) directly from urine samples. A total of 287 urine specimens were evaluated by HRM assay and the results were compared with the conventional culture method. Five different melt curves generated and differentiated five bacterial pathogens. The detection limit of the MHRM assay was 1.5 × 10³ CFU/ml for E. coli and K. pneumoniae and 1.5 × 10² CFU/ml for S. saprophyticus, E. faecalis and GBS. Compared to culture, the specificity of the MHRM assay ranged from 99.3 to 100%, and sensitivity 100% for all test pathogens. The MHRM assay developed in the current study might be functional tool for the diagnosis of UTIs and has the potential for direct detection of the organism in the clinical samples. Additionally, it creates results in less than 5 h, helping clinicians to start treatment with appropriate antimicrobial agents. This method could be a useful supplement to urine culture.

The diagnostic value of rapid urine test platform UF-5000 for suspected urinary tract infection at the emergency department

Background and objective

Urine culture is time consuming, which may take days to get the results and impede further timely treatment. Our objective is to evaluate whether the fast urinalysis and bacterial discrimination system called Sysmex UF-5000 may predict urinary tract infections (UTIs) (within minutes) compared with the clinical routine test in suspected UTI patients. In addition, we aimed to explore the accuracy of microbiologic information by UF-5000.

Materials and Methods

Consecutive patients who were admitted from the emergency department at Queen Mary Hospital (a tertiary hospital in Hong Kong) from June 2019 to February 2020 were enrolled in the present study. The dipstick test, manual microscopic test with culture, and Sysmex UF-5000 test were performed in the urine samples at admission.

Results

A total of 383 patients were finally included in the present study. UF-5000 urinalysis (area under the receiver operator characteristic curve, AUC=0.821, confidence interval, 95%CI: 0.767–0.874) outperformed the dipstick test (AUC=0.602, 95%CI: 0.550–0.654, P=1.32×10^-10) for predicting UTIs in patients without prior antibiotic treatment. A significant net benefit from UF-5000 was observed compared with the dipstick test (NRI=39.9%, 95%CI: 19.4–60.4, P=1.36 × 10^-4). The urine leukocyte tested by UF-5000 had similar performance (AUC) for predicting UTI compared with the manual microscopic test (P=0.27). In patients without a prior use of antibiotics, the concordance rates between UF-5000 and culture for predicting Gram-positive or -negative bacteriuria and a negative culture were 44.7% and 96.2%, respectively.

Conclusions

UF-5000 urinalysis had a significantly better predictive value than the dipstick urine test for predicting UTIs.

Evaluation of Flow Cytometry for Cell Count and Detection of Bacteria in Biological Fluids

The analysis of biological fluids is crucial for the diagnosis and monitoring of diseases causing effusions and helps in the diagnosis of infectious diseases. The gold standard method for cell count in biological fluids is the manual method using counting chambers. The microbiological routine procedures consist of Direct Gram staining and culture on solid or liquid media. We evaluate the analytical performance of SYSMEX UF4000 (Sysmex, Kobe, Japan) and Sysmex XN10 (Sysmex, Kobe, Japan) in comparison with cytological and microbiological routine procedures. A total of 526 biological fluid samples were included in this study (42 ascitic, 31 pleural, 31 peritoneal, 125 cerebrospinal, 281 synovial, and 16 peritoneal dialysis fluids). All samples were analyzed by flow cytometry and subsequently processed following cytological and/or microbiological routine procedures. With regard to cell counts, UF4000 (Sysmex, Kobe, Japan) showed a performance that was at least equivalent to those of the reference methods and superior to those of XN10 (Sysmex, Kobe, Japan). Moreover, the bacterial count obtained with UF4000 (Sysmex, Kobe, Japan) was significantly higher among culture or Direct Gram stain positive samples. We established three optimal cutoff points to predict Direct Gram stain positive samples for peritoneal (465.0 bacteria/μL), synovial (1200.0 bacteria/μL), and cerebrospinal fluids (17.2 bacteria/μL) with maximum sensitivity and negative predictive values. Cell count and detection of bacteria by flow cytometry could be used upstream cytological and microbiological routine procedures to improve and accelerate the diagnosis of infection of biological fluid samples.

IMPORTANCE The analysis of biological fluids is crucial for the diagnosis and monitoring of diseases causing effusions and helps in the diagnosis of infectious diseases. The possibility of carrying out cytological and microbiological analyses of biological fluid samples on the same automated machine would simplify the sample circuit (addressing the sample in a single laboratory, 24/7). It would also minimize the quantity of sample required. The performance of cytological and microbiological analysis by the flow cytometer UF 4000 (Sysmex, Kobe, Japan) has never been evaluated yet. This study has shown that bacterial count by flow cytometry using UF4000 (Sysmex, Kobe, Japan) could be used upstream of microbiological routine procedures to improve and to accelerate the diagnosis of infection of biological fluid samples.

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.

Use of Sysmex UF-5000 flow cytometry in rapid diagnosis of urinary tract infection and the importance of validating carryover rates against bacterial count cut-off

Introduction

Urinary tract infections are common bacterial infections worldwide. Urine culture is the gold standard method to identify and quantify the presence or absence of bacteria in urine. Flow cytometry, which can differentiate and quantify multiple particles (including bacteria) in the urine, presents an alternative method for rapid screening to rule out bacteriuria.

Hypothesis

Adding flow cytometry to identify urine samples without bacteriuria could substantially reduce the number of urine samples that need to be cultured as well as the response time for negative results. However, the level of instrument rinsing between samples could affect sample-to-sample carryover rate, a concept given little attention in previous studies.

Aim

We aimed to evaluate urine flow cytometry as a rapid screening method to identify urine samples without significant bacterial growth, including analyses of cross-contamination and sample-to-sample carryover rate.

Methodology

We analysed 3919 urine samples by quantitative urine culture and flow cytometry screening (Sysmex UF-5000). Receiver operator characteristic (ROC) curve analyses were used to test method agreement to identify: (a) positive vs. negative culture and (b) mixed vs. pure culture. In addition, we performed carryover and cross-contamination studies.

Results

ROC curve analyses identified bacterial count (BACT ml⁻¹) and leucocyte count (WBC µl⁻¹) as possible predictors of bacterial growth in the total material and subpopulations, except pregnant women (n=451). This subgroup was excluded from further analyses, leaving a final 3468 urine samples. Area under the ROC curve was 0.94 (95 % CI 0.93–0.95) and 0.81 (95 % CI 0.79–0.82) for bacterial and leucocyte count, respectively. A bacterial count cut-off of 30 BACT ml⁻¹ resulted in 95.2 % sensitivity and 91.2 % negative predictive value, resulting in approximately 30 % of urine samples that could be reported as negative without culture. Use of high-level rinse modes was necessary to ensure carryover rates <0.05 %.

Conclusion

Flow cytometry is a suitable and rapid method to rule out urine samples without significant bacterial growth. Rinses between samples should be adjusted, depending on the cut-off used, to prevent sample-to-sample carryover, whereas cross-contamination can be eliminated by the use of separate urine aliquots for flow cytometry analysis and urine culturing respectively.

Influence of gender on the performance of urine dipstick and automated urinalysis in the diagnosis of urinary tract infections at the emergency department

BACKGROUND

Urinary tract infections (UTIs) are frequently encountered at the Emergency Department (ED). Given the anatomical differences between men and women, we aimed to clarify differences in the diagnostic performance of urinary parameters at the ED.

METHODS

A cohort study of adults presenting at the ED with fever and/or clinical suspected UTI. Performance of urine dipstick (UD) and automated urinalysis (UF-1000i) were analysed for the total study population and men and women separately. We focused on 1) UTI diagnosis and 2) positive urine culture (UC, ≥10⁵ CFU/ml) as outcome.

RESULTS

In 360 of 917 cases (39.3%) UTI was established (men/women 35.1%/43.6%). Diagnostic accuracy of UD was around 10% lower in women compared to men. Median automated leucocyte and bacterial count were higher in women compared to men. Diagnostic performance by receiver operating analysis was 0.851 for leucocytes (men/women 0.879/0.817) and 0.850 for bacteria (men/women 0.898/0.791). At 90% sensitivity, cut-off values of leucocyte count (men 60/µL, women 43/µL), and bacterial count (men 75/µL, women 139/µL) showed performance differences in favour of men. In both men and women, diagnostic performance using specified cut-off values was not different between normal and non-normal bladder evacuation. UC was positive in 327 cases (men/women 149/178), as with UTI diagnosis, diagnostic values in men outperformed women.

CONCLUSIONS

Overall diagnostic accuracy of urinary parameters for diagnosing UTI is higher in men. The described differences in cut-off values for leukocyte and bacterial counts for diagnosing UTI necessitates gender-specific cut-off values, probably reflecting the influence of anatomical and urogenital differences.

Accuracy of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for direct bacterial identification from culture-positive urine samples

Background

Urinary tract infection (UTI) is one of the most frequent reasons for antimicrobial therapy. In typical clinical setting, 18–48 h is needed to identify pathogens by urine culture. A rapid method for pathogenic UTI diagnosis by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been developed in recent years.

Methods

This meta-analysis systematically evaluated the accuracy of MALDI-TOF MS for direct identification of bacteria from culture-positive urine samples. We queried the electronic database of Medline and Web of Science to obtain relevant articles.

Results

Nineteen articles involving 4,579 isolates were included after final selection in the meta-analysis. The random-effects pooled identification accuracy of MALDI-TOF MS was 0.82 with 95% confidence interval of 0.79 to 0.86 at the species level. For Gram-negative isolates, the correct identification performance of the species ranged from 0.54 to 0.98, with a cumulative rate of 0.87 (95% CI: 0.83 to 0.91). For Gram-positive isolates, the correct identification rate ranged from 0.32 to 0.80, with a cumulative rate of 0.59 (95% CI: 0.49 to 0.68).

Conclusions

MALDI-TOF MS provides a reliable direct identification of bacteria, particularly in cases of Gram-negative isolates, from clinical urine specimens. Nevertheless, the identification accuracy of this method is moderate for Gram-positive bacteria.

Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations

Background

Urinary tract infection (UTI) is diagnosed combining urinary symptoms with demonstration of urine culture growth above a given threshold. Our aim was to compare the diagnostic accuracy of Urine Flow Cytometry (UFC) with urine test strip in predicting bacterial growth and in identifying contaminated urine samples, and to derive an algorithm to identify relevant bacterial growth for clinical use.

Methods

Species identification and colony-forming unit (CFU/ml) quantification from bacterial cultures were matched to corresponding cellular (leucocytes/epithelial cells) and bacteria counts per μl. Results comprise samples analysed between 2013 and 2015 for which urine culture (reference standard) and UFC and urine test strip data (index tests, Sysmex UX-2000) were available.

Results

47,572 urine samples of 26,256 patients were analysed. Bacteria counts used to predict bacterial growth of ≥10⁵ CFU/ml showed an accuracy with an area under the receiver operating characteristic curve of > 93% compared to 82% using leukocyte counts. The relevant bacteriuria rule-out cut-off of 50 bacteria/μl reached a negative predictive value of 98, 91 and 89% and the rule-in cut-off of 250 bacteria/μl identified relevant bacteriuria with an overall positive predictive value of 67, 72 and 73% for microbiologically defined bacteriuria thresholds of 10⁵, 10⁴ or 10³ CFU/ml, respectively. Measured epithelial cell counts by UFC could not identify contaminated urine.

Conclusions

Prediction of a relevant bacterial growth by bacteria counts was most accurate and was a better predictor than leucocyte counts independently of the source of the urine and the medical specialty ordering the test (medical, surgical or others).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05893-3.

A performance comparison of the fully automated urine particle analyzer UF-5000 with UF-1000i and Gram staining in predicting bacterial growth patterns in women with uncomplicated urinary tract infections

Background

The aim of this study was to compare the performance of the new flow cytometer UF-5000 with the UF-1000i and Gram staining for determining bacterial patterns in urine samples.

Methods

Women who attended our clinic with symptoms suggestive of urinary tract infection were enrolled in the study. Mid-stream urine samples were collected for gram staining, urine analysis and urine cultures. Bacterial patterns were classified using the UF-1000i (none, cocci bacteria or rods/mixed growth), the UF-5000 (none, cocci, rods or mixed growth) and Gram staining.

Results

Among the 102 included samples, there were 10 g-positive cocci, 2 g-positive bacilli, 66 g-negative rods, and 24 mixed growth. The sensitivity/specificity of the UF-1000i was 81.8/91.1% for gram-negative rods and 23.5/96.9% for cocci/mixed. The sensitivity/specificity of the UF-5000 was 80.0/88.2% for gram negative rods and 70.0/86.5% for gram-positive cocci.

Conclusions

The UF-5000 demonstrated good sensitivity and specificity for Gram-negative bacilli and demonstrated an improved sensitivity for detecting Gram-positive cocci compared with the UF-1000i.

UriSed 3 PRO automated microscope in screening bacteriuria at region-wide laboratory organization

BACKGROUND AND AIMS

We assessed the possibility to rule out negative urine cultures by counting with UriSed 3 PRO (77 Elektronika, Hungary) at Helsinki and Uusimaa Hospital District.

MATERIALS AND METHODS

Bacteria counting of the UriSed 3 PRO automated microscope was verified with reference phase contrast microscopy against growth in culture. After acceptance into routine, results of bacteria and leukocyte counting from 56 426 specimens with eight UriSed 3 PRO instruments were compared against results from parallel samples cultured on chromogenic agar. Laboratory data including preanalytical details were accessed through the regional database of the Helsinki and Uusimaa Hospital District.

RESULTS

A combined sensitivity of 87-92% and a negative predictive value of 90-96% with a specificity of 54-50% was reached, depending on criteria. Preanalytical data (incubation time in bladder) combined with the way of urine collection would improve these figures if reliable.

CONCLUSIONS

Complex patient populations, regional logistics and data interfases, and economics related to increased costs of additional particle counts against costs of screening cultures of all samples, did not support adaptation of a screening process of urine cultures. This conclusion was made locally, and may not be valid elsewhere.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry combined with UF-5000i urine flow cytometry to directly identify pathogens in clinical urine specimens within 1 hour

Background

Urinary tract infection (UTI) is one of the most common hospital-associated infectious. The traditional laboratory diagnosis method for UTI requires at least 24 hours, and it cannot provide the etiology basis for the clinic in time. The aim of our study is to develop a new method for pathogenic diagnosis of UTI by combining matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and UF-5000i from urine samples directly within 1 hour.

Methods

A total of 1,503 urine samples were collected from patients suggesting symptoms of UTI from August 2018 to January 2019. Each of these samples was divided into three aliquots. The first aliquot was used for conventional cleaning mid-stream urine culture; the second one for UF-5000i analysis to screen out the bacterial counts, which were more than 1×10⁵ bacteria/mL. The third one was processed to bacterial purification and directly identified by the MALDI-TOF MS.

Results

In our study, 296 of 1,503 urine specimens were screened out by UF-5000i (bacterial pellets counts ≥10⁵/mL). Compared the conventional culture-dependent method, the results of our methods were consistent in 249 of 263 (94.7%) cases, and they were both single-microorganism. Among 249 credible results, species-level identification (score ≥2.0) was contained 233 (233/249. 93.6%), 16 (16/249, 6.4%) samples scored between 1.7 and 1.99, and 14 (14/249, 5.6%) samples scored <1.7 or no peaks found. When there were 2 different kinds of bacteria in the urine, the result of MALDI-TOF MS was unreliable.

Conclusions

MALDI-TOF MS combined with UF-5000i to identify the pathogenic bacteria in urine directly is a novel and reliable method and saves at least 23 hours relative to the current routine conventional method. Thus its rapid and accurate detection may provide the basis of etiology for clinical diagnosis of UTIs efficiently.

Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections

BACKGROUND

A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the number of query samples to be cultured and enabling diagnostic services to concentrate on those in which there are true microbial infections, a significant improvement in efficiency of the service is possible.

METHODOLOGY

Screening process for urine samples prior to culture was modelled in a single clinical microbiology laboratory covering three hospitals and community services across Bristol and Bath, UK. Retrospective analysis of all urine microscopy, culture, and sensitivity reports over one year was used to compare two methods of classification: a heuristic model using a combination of white blood cell count and bacterial count, and a machine learning approach testing three algorithms (Random Forest, Neural Network, Extreme Gradient Boosting) whilst factoring in independent variables including demographics, historical urine culture results, and clinical details provided with the specimen.

RESULTS

A total of 212,554 urine reports were analysed. Initial findings demonstrated the potential for using machine learning algorithms, which outperformed the heuristic model in terms of relative workload reduction achieved at a classification sensitivity > 95%. Upon further analysis of classification sensitivity of subpopulations, we concluded that samples from pregnant patients and children (age 11 or younger) require independent evaluation. First the removal of pregnant patients and children from the classification process was investigated but this diminished the workload reduction achieved. The optimal solution was found to be three Extreme Gradient Boosting algorithms, trained independently for the classification of pregnant patients, children, and then all other patients. When combined, this system granted a relative workload reduction of 41% and a sensitivity of 95% for each of the stratified patient groups.

CONCLUSION

Based on the considerable time and cost savings achieved, without compromising the diagnostic performance, the heuristic model was successfully implemented in routine clinical practice in the diagnostic laboratory at Severn Pathology, Bristol. Our work shows the potential application of supervised machine learning models in improving service efficiency at a time when demand often surpasses resources of public healthcare providers.

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

Background

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

Methods

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

Results

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

Conclusions

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

Evaluation of flow cytometry for the detection of bacteria in biological fluids

OBJECTIVES

Conventional microbiological procedures for the isolation of bacteria from biological fluids consist of culture on solid media and enrichment broth. However, these methods can delay the microbiological identification for up to 4 days. The aim of this study was to evaluate the analytical performance of Sysmex UF500i (Sysmex, Kobe, Japan) as a screening method for the detection of bacteria in different biological fluids in comparison with direct Gram staining and the conventional culture on solid media and enrichment broth.

METHODS

A total of 479 biological fluid samples were included in the study (180 ascitic, 131 amniotic, 56 synovial, 40 cerebrospinal, 36 pleural, 24 peritoneal, 9 bile and 3 pericardial fluids). All samples were processed by conventional culture methods and analyzed by flow cytometry. Direct Gram staining was performed in 339 samples. The amount of growth on culture was recorded for positive samples.

RESULTS

Bacterial and white blood cell count by flow cytometry was significantly higher among culture positive samples and samples with a positive direct Gram stain compared to culture negative samples. Bacterial count directly correlated with the amount of growth on culture (Kruskall-Wallis H χ2(3) = 11.577, p = 0.009). The best specificity (95%) for bacterial count to predict culture positivity was achieved applying a cut-off value of 240 bacteria/μL.

CONCLUSIONS

Bacterial and white blood cell counts obtained with flow cytometry correlate with culture results in biological fluids. Bacterial count can be used as a complementary method along with the direct Gram stain to promptly detect positive samples and perform other diagnostic techniques in order to accelerate the bacterial detection and identification.

Rapid time-resolved luminescence based screening of bacteria in urine with luminescence modulating biosensing phages

Urinary tract infections (UTIs) are a common problem worldwide. The most prevalent causative pathogen of UTI is Escherichia coli, focus of this study. The current golden standard for detecting UTI is bacterial culture, creating a major workload for hospital laboratories - cost-effective and rapid mass screening of patient samples is needed. Here we present an alternative approach to screen patient samples with a single-step assay utilising time-resolved luminescence and luminescence modulating biosensing phages. Filamentous phage M13 was biopanned for binding luminescence quenching metal (copper) and further E. coli. The screening assay luminescence modulation was further enhanced by selecting right chemical environment for the functioning phage clones. Semi-specific interaction between phage, target bacteria and metal was detected by modulation in the signal of a weakly chelating, easily quenchable lanthanide complex. In the presence of the target pathogen, the phages collected quenching metal from solution to the bacterial surface changing the quenching effect on the lanthanide label and thus modulating the signal. Our method was compared with the bacterial culture data obtained from 70 patient samples. The developed proof-of-principle screening assay showed sensitivity and a specificity at the 90% mark when compared to culture method although some samples had high turbidity and even blood. The detection limit of E. coli was in the range of 1000-10 000 colony forming units/mL. Untreated urine sample was screened and time-resolved luminescence signal result was achieved within 10 min in a single incubation step.

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.

[Economic evaluation of the Alfred 60/AST device implantation for bacterial growth detection with automatic sewing machine]

OBJECTIVE

It is becoming increasingly necessary to automatize screening of urine samples to culture at Microbiology laboratories. Our objective was to estimate the budget threshold from which the Alfred 60/AST device would be profitable for our hospital.

METHODS

Cost minimization study by decision trees, carried out in a General Hospital. The cost of traditional urine culture and urine processing using Alfred-60/AST were compared. Traditional processing involves the culture of all urine specimens received onto blood and MacConkey agar, and identification of every microorganism isolated by Vitek-2 system. The autoanalyzer would only inoculate the positive urines onto a chromogenic media, directly identifying the Escherichia coli isolates.

RESULTS

The variables with the greatest economic impact in the model were the probability of obtaining a positive culture, the prevalence of E. coli in the urine cultures and the cost per sample using Alfred-60/AST. The multivariate sensitivity analysis showed that the model was solid. The bivariate sensitivity analysis showed that the model is suceptible to cost modification, mainly of the automatic device. At a threshold value of 1.40 euros/determination, the automatic processing would decrease the annual costs in 2,879 euros.

CONCLUSIONS

The introduction of the Alfred-60/AST device in our laboratory at 1.40 euros/determination would reduce urine processing workload, saving time and costs.

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.

A multicentre study investigating parameters which influence direct bacterial identification from urine

Rapid diagnosis is one of the best ways to improve patient management and prognosis as well as to combat the development of bacterial resistance. The aim of this study was to study parameters that impact the achievement of reliable identification using a combination of flow cytometry and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS).The study was carried out in nine hospitals in Spain and included 1,050 urine samples with bacterial counts of 5x10⁶ bacteria/ml. MALDI-ToF-MS-based identification was performed according to a previously described protocol. Valid identification by direct MALDI-ToF-MS was obtained in 72.8% of samples, in 80.3% of samples found to be positive by culture, 32.2% of contaminated samples, and 19.7% of negative samples. Among the positives samples with a valid identification the concordance at the species level was 97.2%. The parameters related to success of direct identification were: high bacterial count, the presence of Escherichia coli as a pathogen and rod-bacteria morphology provided by flow cytometry. The parameters related to failure were a high epithelial cell (EC) count, a high white blood cell (WBC) count and urine samples obtained from in-patients. In summary, this multicentre study confirms previously published data on the usefulness and accuracy of direct MALDI-ToF-MS-based identification of bacteria from urine samples. It seems important to evaluate not only the bacterial count, but also other parameters, such as EC and WBC counts, bacterial species and morphology, and the health care setting, to decide whether the sample is suitable for direct identification.

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.

Rapid Screening of Urinary Tract Infection and Discrimination of Gram-Positive and Gram-Negative Bacteria by Automated Flow Cytometric Analysis Using Sysmex UF-5000

Rapid screening of urinary tract infection is important to determine antibiotic treatment and reduce unnecessary urine culture. We evaluated the performance of the new flow cytometry-based UF-5000 automated urine analyzer (Sysmex, Kobe, Japan). A total of 1,430 urine samples from 1,226 patients were analyzed and compared to urine cultures to which a Previ Isola (bioMérieux, Marcy l'Etoile, France) system was applied. In total, 878 of 1,430 urine cultures (61.4%) produced ≥10³ CFU/ml bacterial growth (309 with Gram-negative [GN] bacteria, 517 with Gram-positive [GP] bacteria, and 52 mixed cultures), with 336 samples (23.5%) presenting ≥10⁵ CFU/ml bacterial growth. The ≥10⁵ CFU/ml bacterial growth was detected by a ≥71 bacteria/μl UF-5000 bacterial count with 95% sensitivity and 84% specificity. Using a cutoff of <15 bacteria/μl to determine whether or not to culture, 50.9% of samples were below the cutoff, 94.8 and 99.5% of which presented <10⁴ and <10⁵ CFU/ml of bacterial growth, respectively. The bacterial discrimination performance of the UF-5000 for GN bacteria was superior to that for GP bacteria, and in ≥10⁵ CFU/ml monobacterial samples, the sensitivity and specificity for reporting GN bacteria were 91.7 and 90.0%, respectively. In summary, UF-5000 demonstrated potential utility for the rapid screening of negative bacterial cultures. However, this utility is dependent on the patient population; cutoff optimizations must be performed for specific populations. In addition, UF-5000 presented improved performance in characterizing GP and GN bacteria, although the concurrence rates were not high enough to replace routine cultures.

The Usefulness of Chromogenic Media for Qualitative and Semi-Quantitative Diagnostic of Urinary Tract Infections

The aim of this study was to evaluate the usefulness of chromogenic media for isolation of bacteria from urine and direct identification of UTI pathogens. A total of 100 urine specimens were inoculated on blood agar and MacConkey agar as a reference method and on the following media to be tested: chromID^® CPS^® Elite (CPSE, bioMérieux), CHROMagar™ Orientation (BioMaxima), BD CHROMagar Orientation Medium (ORI, Becton Dickinson), CHROMagar™ Orientation (ORIE, Graso) and Brillance UTI Clarity Agar (UTI C, Oxoid). After a 24-hour incubation period, 47 Gram-positive cocci and 62 Gram-negative rods were observed. The specificity and sensitivity of all chromogenic media was 97.3% and 93.5% respectively for qualitative diagnostic; and 81.9% and 81.3% respectively for semi-quantitative diagnostic. The mean PPV and NPV of the chromogenic media were 98.7% and 87.7% for qualitative UTI diagnostic, and 90.9% and 71.9% respectively for semi-quantitative diagnostic.

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.

[URISCAM project: Multicenter evaluation of the UF-Series cytometer in the urinary tract infections screening]

OBJECTIVE

Urine culture, the gold standard to confirm the presence of urinary tract infection (UTI), is the most requested assay in the microbiology department. Our objective was to determine the diagnostic yield of the UF-Series cytometer as a screening method for UTI.

METHODS

All the urine samples sent to the six Microbiology Laboratories participating in a period of 5 working days were analyzed. We collected demographic variables, apart from those variables related to urine samples: source and sample type (midstream, catheterized or nephrostomy urines), collection with/without boric acid, cytometer parameters (leukocyturia, bacteriuria, bacteria morphology and epithelial cells) and urine culture results. ROC curves were plotted to determine predictive capacity of the cytometer.

RESULTS

A sample of 2,468 patients with average age of 53 years were processed (ratio women:men 2:1). Urine culture detected 23% of positive urine samples. The predictor variables of UTI were: morphology of bacilli, bacteriuria ≥21 bacteria/µL, age ≥65 years, samples collected in the emergency service and hospitalization and preserving conditions. With 21 bacteria/µL as a cut-off point, we obtained a sensitivity of 93.3% and 94.5% negative predictive value, then reducing the samples to be cultured by 28.9% with 1.6% false negatives.

CONCLUSIONS

We consider that the UF-Series is a valid and accurate tool for the detection of UTI. Therefore, it could be used as screening method in the clinical practice prior to the urine culture, reducing culture requirement by approximately 30%, with a low false negative rate.

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.

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 of the dipstick screening test as a predictor of negative urine culture

Objective

To investigate whether the urine dipstick screening test can be used to predict urine culture results.

Methods

A retrospective study conducted between January and December 2014 based on data from 8,587 patients with a medical order for urine dipstick test, urine sediment analysis and urine culture. Sensitivity, specificity, positive and negative predictive values were determined and ROC curve analysis was performed.

Results

The percentage of positive cultures was 17.5%. Nitrite had 28% sensitivity and 99% specificity, with positive and negative predictive values of 89% and 87%, respectively. Leukocyte esterase had 79% sensitivity and 84% specificity, with positive and negative predictive values of 51% and 95%, respectively. The combination of positive nitrite or positive leukocyte esterase tests had 85% sensitivity and 84% specificity, with positive and negative predictive values of 53% and 96%, respectively. Positive urinary sediment (more than ten leukocytes per microliter) had 92% sensitivity and 71% specificity, with positive and negative predictive values of 40% and 98%, respectively. The combination of nitrite positive test and positive urinary sediment had 82% sensitivity and 99% specificity, with positive and negative predictive values of 91% and 98%, respectively. The combination of nitrite or leukocyte esterase positive tests and positive urinary sediment had the highest sensitivity (94%) and specificity (84%), with positive and negative predictive values of 58% and 99%, respectively. Based on ROC curve analysis, the best indicator of positive urine culture was the combination of positives leukocyte esterase or nitrite tests and positive urinary sediment, followed by positives leukocyte and nitrite tests, positive urinary sediment alone, positive leukocyte esterase test alone, positive nitrite test alone and finally association of positives nitrite and urinary sediment (AUC: 0.845, 0.844, 0.817, 0.814, 0.635 and 0.626, respectively).

Conclusion

A negative urine culture can be predicted by negative dipstick test results. Therefore, this test may be a reliable predictor of negative urine culture.

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.

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.

Performance of urinalysis tests and their ability in predicting results of urine cultures: a comparison between automated test strip analyser and flow cytometry in various subpopulations and types of samples

Aims

Results of urinalysis are available earlier than urine culture results. If urinalysis can predict results of culture, early decision can be made on treatment and whether urine samples should be cultured. This study sought to compare the performance of urinalysis tests by automated test strip analyser (nitrite and leucocyte esterase) with flow cytometry (bacteria and white cell count) in different subpopulations and types of samples.

Methods

Consecutive urine samples (n=2351) from a population with a median age of 45 years, 37.2% men, were tested. Sensitivity, specificity, positive predictive value and negative predictive value (NPV) of the tests were calculated using contingency tables. The gold standard was positive urine culture with cut-off >105 CFU/mL.

Results

14% of the cultures were positive (95.6% monomicrobial, 74.7% Enterobacteriaceae). Overall, nitrite test was the most specific (98.7%) but the least sensitive (43.2%). Bacteria count was the most sensitive (91.7%) and highly specific (87.5%). In infants <24 months, the sensitivity of bacteria count was reduced (86.1%), but specificity was high (95.9%). The specificity of nitrite was reduced in urine from the in-and-out procedure (81.9%). The sensitivity of bacteria count was reduced in bag specimens urine (83.3%) and in urine from indwelling catheter (84.7%). All tests showed a high NPV. The NPV of the combined flow cytometry tests was higher than those of automated test strip analyser (99.1% vs 97.4%).

Conclusions

Overall, the performance of urinalysis is excellent. Flow cytometry tests performed better than automated test strip analyser in ruling out urine to be cultured.

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.

Accuracy of Automated Flow Cytometry-Based Leukocyte Counts To Rule Out Urinary Tract Infection in Febrile Children: a Prospective Cross-Sectional Study

Automated flow cytometry of urine remains an incompletely validated method to rule out urinary tract infection (UTI) in children. This cross-sectional analytical study was performed to compare the predictive values of flow cytometry and a dipstick test as initial diagnostic tests for UTI in febrile children and prospectively included 1,106 children (1,247 episodes). Urine culture was used as the gold standard test for diagnosing UTI. The performance of screening tests to diagnose UTI were established using receiver operating characteristic (ROC) analysis. Among these 1,247 febrile episodes, 221 UTIs were diagnosed (17.7% [95% confidence interval {CI}, 15.6 to 19.8%]). The area under the ROC curve for flow cytometry white blood cell (WBC) counts (0.99 [95% CI, 0.98 to 0.99]) was significantly superior to that for red blood cell (0.74 [95% CI, 0.70 to 0.78]) and bacterial counts (0.89 [95% CI, 0.87 to 0.92]) (P < 0.001). Urinary WBC counts also had a significantly higher area under the ROC curve than that of the leukocyte esterase (LE) dipstick (0.92 [95% CI, 0.90 to 0.94]), nitrite dipstick (0.83 [95% CI, 0.80 to 0.87]), or the combination of positive LE and/or nitrite dipstick (0.91 [95% CI, 0.89 to 0.93]) test (P < 0.001). The presence of ≥35 WBC/μl of urine was the best cutoff point, yielding both a high sensitivity (99.5% [95% CI, 99 to 100%]) and an acceptable specificity (80.6% [95% CI, 78 to 83%]). Using this cutoff point would have reduced the number of samples sent to the laboratory for culture by 67%. In conclusion, the determination of urinary WBC counts by flow cytometry provides optimal performance as an initial diagnostic test for UTI in febrile children.

Screening of presumptive urinary tract infections by the automated urine sediment analyser sediMAX

BACKGROUND

Urinary tract infections (UTI) are among the most common bacterial infections and urine samples represent a large proportion of the specimens processed in clinical microbiology laboratories, up to 80% of which, however, yield negative results. Automated microscopy is widely used for urine sediment analysis and has recently been evaluated in a few studies for bacteriological screening of urine samples, achieving high levels of performance.

METHODS

We present a study in which urine samples from both inpatients and outpatients, with either clean-catch or indwelling catheter urine samples, were screened for UTI by urine culture, as the reference method, and the automated urine analyser sediMAX, for the detection of bacteria, leukocytes and yeasts.

RESULTS

In total, 3443 urine samples were evaluated. When a single algorithm was adopted for sediMAX to screen the total patient population, 96.4% sensitivity, 75.4% specificity, 57.8% positive predictive value, and 98.4% negative predictive value were found. However, for male outpatients and all patients with indwelling catheter other algorithms were necessary to improve performances. Altogether, with sediMAX false negative rate was 2.4% and false positive rate was 27.6%. In addition, 54% of the investigated samples could have avoided urine culture.

CONCLUSIONS

After the identification of specific algorithms for different patient subgroups, the automated urine analyser sediMAX can be reliably employed in the screening of UTI.