Trial reportPloS one2018
The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.
Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture.BMC infectious diseases · 2025Article
- Development and validation of a parsimonious prediction model for positive urine cultures in outpatient visits.PLOS digital health · 2023Article
- Can the application of machine learning to electronic health records guide antibiotic prescribing decisions for suspected urinary tract infection in the Emergency Department?PLOS digital health · 2023Article
- Big Data in Laboratory Medicine-FAIR Quality for AI?Diagnostics (Basel, Switzerland) · 2022Review
- Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques.Diagnostics (Basel, Switzerland) · 2022Article
- Comparison of Urine Flow Cytometry on the UF-1000i System and Urine Culture of Urine Samples from Urological Patients.Urologia internationalis · 2022Article
- 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 · 2021Article
- Performance of yeast-like cell counting (YLCC) using the Sysmex UF-1000i for clinical candiduria screening.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019Article
- Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations.Disease markers · 2019Observational
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePatients 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.
methodsThis 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.
resultsRelevant 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.
conclusionsUrine 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.
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