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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...

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Autores principales: Martín-Gutiérrez, Guillermo, Martín-Pérez, Carlos, Toledo, Héctor, Sánchez-Cantalejo, Emilio, Lepe, José Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9642874/
https://www.ncbi.nlm.nih.gov/pubmed/36346782
http://dx.doi.org/10.1371/journal.pone.0277340
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author Martín-Gutiérrez, Guillermo
Martín-Pérez, Carlos
Toledo, Héctor
Sánchez-Cantalejo, Emilio
Lepe, José Antonio
author_facet Martín-Gutiérrez, Guillermo
Martín-Pérez, Carlos
Toledo, Héctor
Sánchez-Cantalejo, Emilio
Lepe, José Antonio
author_sort Martín-Gutiérrez, Guillermo
collection PubMed
description 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.
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spelling pubmed-96428742022-11-15 FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections Martín-Gutiérrez, Guillermo Martín-Pérez, Carlos Toledo, Héctor Sánchez-Cantalejo, Emilio Lepe, José Antonio PLoS One Research Article 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. Public Library of Science 2022-11-08 /pmc/articles/PMC9642874/ /pubmed/36346782 http://dx.doi.org/10.1371/journal.pone.0277340 Text en © 2022 Martín-Gutiérrez et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Martín-Gutiérrez, Guillermo
Martín-Pérez, Carlos
Toledo, Héctor
Sánchez-Cantalejo, Emilio
Lepe, José Antonio
FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title_full FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title_fullStr FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title_full_unstemmed FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title_short FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
title_sort flowuti: an interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9642874/
https://www.ncbi.nlm.nih.gov/pubmed/36346782
http://dx.doi.org/10.1371/journal.pone.0277340
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