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.

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

BMC Infectious Diseases ◽

10.1186/s12879-021-05893-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Christian Gehringer ◽

Axel Regeniter ◽

Katharina Rentsch ◽

Sarah Tschudin-Sutter ◽

Stefano Bassetti ◽

...

Keyword(s):

Flow Cytometry ◽

Bacterial Growth ◽

Predictive Value ◽

Urine Culture ◽

Test Strip ◽

Urine Flow ◽

Urine Samples ◽

Urine Test ◽

Cell Counts ◽

Urine Flow Cytometry

Abstract 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).

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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

Journal of Medical Microbiology ◽

10.1099/jmm.0.001472 ◽

2021 ◽

Vol 70 (12) ◽

Author(s):

Kjersti Haugum ◽

Maria Schei Haugan ◽

Jannicke Skage ◽

Mariann Tetik ◽

Aleksandra Jakovljev ◽

...

Keyword(s):

Flow Cytometry ◽

Bacterial Growth ◽

Roc Curve ◽

Urine Culture ◽

Bacterial Count ◽

Urine Flow ◽

Urine Samples ◽

Rapid Screening ◽

Cross Contamination ◽

Rule Out

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.

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

Disease Markers ◽

10.1155/2019/5853486 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Sabine K. Schuh ◽

Ruth Seidenberg ◽

Spyridon Arampatzis ◽

Alexander B. Leichtle ◽

Wolf E. Hautz ◽

...

Keyword(s):

Flow Cytometry ◽

Urinary Tract ◽

Bacterial Growth ◽

Clinical Presentation ◽

Urine Culture ◽

High Sensitivity ◽

Urine Flow ◽

Clinical Presentations ◽

Tract Infections ◽

Urine Flow Cytometry

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.

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