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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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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. |
format | Online Article Text |
id | pubmed-9642874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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