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Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach

BACKGROUND: To evaluate the ability of Weighted-Incidence Syndromic Combination Antibiograms (WISCA) to inform the selection of empirical antibiotic regimens for suspected paediatric community-acquired urinary tract infections. METHODS: Data were collected from outpatients (< 15 years) accessing...

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Autores principales: Barbieri, Elisa, Bottigliengo, Daniele, Tellini, Matteo, Minotti, Chiara, Marchiori, Mara, Cavicchioli, Paola, Gregori, Dario, Giaquinto, Carlo, Da Dalt, Liviana, Donà, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088309/
https://www.ncbi.nlm.nih.gov/pubmed/33933164
http://dx.doi.org/10.1186/s13756-021-00939-2
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author Barbieri, Elisa
Bottigliengo, Daniele
Tellini, Matteo
Minotti, Chiara
Marchiori, Mara
Cavicchioli, Paola
Gregori, Dario
Giaquinto, Carlo
Da Dalt, Liviana
Donà, Daniele
author_facet Barbieri, Elisa
Bottigliengo, Daniele
Tellini, Matteo
Minotti, Chiara
Marchiori, Mara
Cavicchioli, Paola
Gregori, Dario
Giaquinto, Carlo
Da Dalt, Liviana
Donà, Daniele
author_sort Barbieri, Elisa
collection PubMed
description BACKGROUND: To evaluate the ability of Weighted-Incidence Syndromic Combination Antibiograms (WISCA) to inform the selection of empirical antibiotic regimens for suspected paediatric community-acquired urinary tract infections. METHODS: Data were collected from outpatients (< 15 years) accessing the emergency rooms of Padua University-Hospital and Mestre Dell' Angelo-Hospital (Venice) between January 1st, 2016, and December 31st, 2018. WISCAs were developed by estimating the coverage of eight regimens using a Bayesian hierarchical model adjusted for age, sex, and previous antibiotic treatment or renal/urological comorbidities. RESULTS: 385 of 620 urine culture requests were included in the model analysis. The most frequently observed bacterium was E. coli (85% and 87%, Centre A and B). No centre effect on coverage estimates was found, and data were successfully pooled together. Coverage ranged from 77.8% (Co-trimoxazole) to 97.6% (Carbapenems). Complex cases and males had significantly lower odds of being covered by a regimen than non-complex cases and females (odds ratio (OR) 0.49 [95% HDI, 0.38–0.65], and OR: 0.73 [95% HDIs, 0.56–0.96] respectively). Children aged 3–5 years had lower odds of being covered by a regimen than other age groups, except for neonates. CONCLUSIONS: The developed WISCAs provide highly informative estimates on coverage patterns overcoming the limitation of combination antibiograms and expanding the framework of previous Bayesian WISCA algorithm. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13756-021-00939-2.
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spelling pubmed-80883092021-05-03 Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach Barbieri, Elisa Bottigliengo, Daniele Tellini, Matteo Minotti, Chiara Marchiori, Mara Cavicchioli, Paola Gregori, Dario Giaquinto, Carlo Da Dalt, Liviana Donà, Daniele Antimicrob Resist Infect Control Research BACKGROUND: To evaluate the ability of Weighted-Incidence Syndromic Combination Antibiograms (WISCA) to inform the selection of empirical antibiotic regimens for suspected paediatric community-acquired urinary tract infections. METHODS: Data were collected from outpatients (< 15 years) accessing the emergency rooms of Padua University-Hospital and Mestre Dell' Angelo-Hospital (Venice) between January 1st, 2016, and December 31st, 2018. WISCAs were developed by estimating the coverage of eight regimens using a Bayesian hierarchical model adjusted for age, sex, and previous antibiotic treatment or renal/urological comorbidities. RESULTS: 385 of 620 urine culture requests were included in the model analysis. The most frequently observed bacterium was E. coli (85% and 87%, Centre A and B). No centre effect on coverage estimates was found, and data were successfully pooled together. Coverage ranged from 77.8% (Co-trimoxazole) to 97.6% (Carbapenems). Complex cases and males had significantly lower odds of being covered by a regimen than non-complex cases and females (odds ratio (OR) 0.49 [95% HDI, 0.38–0.65], and OR: 0.73 [95% HDIs, 0.56–0.96] respectively). Children aged 3–5 years had lower odds of being covered by a regimen than other age groups, except for neonates. CONCLUSIONS: The developed WISCAs provide highly informative estimates on coverage patterns overcoming the limitation of combination antibiograms and expanding the framework of previous Bayesian WISCA algorithm. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13756-021-00939-2. BioMed Central 2021-05-01 /pmc/articles/PMC8088309/ /pubmed/33933164 http://dx.doi.org/10.1186/s13756-021-00939-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Barbieri, Elisa
Bottigliengo, Daniele
Tellini, Matteo
Minotti, Chiara
Marchiori, Mara
Cavicchioli, Paola
Gregori, Dario
Giaquinto, Carlo
Da Dalt, Liviana
Donà, Daniele
Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title_full Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title_fullStr Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title_full_unstemmed Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title_short Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach
title_sort development of a weighted-incidence syndromic combination antibiogram (wisca) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a bayesian approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088309/
https://www.ncbi.nlm.nih.gov/pubmed/33933164
http://dx.doi.org/10.1186/s13756-021-00939-2
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