Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression

Objectives: To determine the trend of bacterial resistance of Escherichia coli to Imipenem (IPM) and Meropenem (MEM), by means of a linear regression model, taking the information collected in the bulletins of bacterial resistance generated by the GREBO group of Bogotá between 2010 and 2014. Methods...

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Authors: Viloria Silva, Amelec Jesus, Campo Urbina, Myrna, Gómez Rodríguez, Lucila, Parody Muñoz, Alexander
Format: article
Status:Versión aceptada para publicación
Publication Date:2016
Country:Colombia
Institution:Corporación Universidad de la Costa
Repository:Repositorio REDICUC
Language:English
OAI Identifier:oai:repositorio.cuc.edu.co:11323/1317
Online Access:https://hdl.handle.net/11323/1317
https://repositorio.cuc.edu.co/
Access Level:Open access
Keyword:Bacterial drug resistance
Escherichia coli
Imipenem and Meropenem
Linear regression model
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spelling Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regressionViloria Silva, Amelec JesusCampo Urbina, MyrnaGómez Rodríguez, LucilaParody Muñoz, AlexanderBacterial drug resistanceEscherichia coliImipenem and MeropenemLinear regression modelObjectives: To determine the trend of bacterial resistance of Escherichia coli to Imipenem (IPM) and Meropenem (MEM), by means of a linear regression model, taking the information collected in the bulletins of bacterial resistance generated by the GREBO group of Bogotá between 2010 and 2014. Methods/Statistical Analysis: From the information published in newsletters GREBO group between 2010 and 2014, the behavior of E. coli bacterial resistance to antibiotics was analyzed. From this information simple linear regression models using the statistical software Statgraphics XVI were generated. Findings: The generated mathematical models to predict the evolution of antibiotic resistance as a function of time and that were significant are: Resistance IPM * Year = 0.00000208772 (p value 0.0020; adjusted R2 = 92.86%); Resistance MEM = 0.00000149115 * Year (p value 0.0026; adjusted R2 = 91.84%). Application/Improvements: There is a relationship between the values of resistance and over the years, with variable time sufficient to explain the behavior of the resistance of E. coli variable. In 2015 IPM resistance is estimated that this in 0.42% (CI 0.02% - 0.8%) and MEM 0.3% (CI 0.17% - 0.42%).Viloria Silva, Amelec Jesus-1be008bb-6eeb-4db4-bc0b-68bb6cb663e2-600Campo Urbina, Myrna-54f5cedd-7a38-4d60-a7df-0fe0780b7841-600Gómez Rodríguez, Lucila-96f477ee-c3db-4c48-82f9-5f94b19cda8e-600Parody Muñoz, Alexander-729969a6-104c-4359-90e4-915cdc430463-600Indian Journal of Science and Technology2018-11-19T19:17:59Z2018-11-19T19:17:59Z2016Artículo de revistahttp://purl.org/coar/resource_type/c_6501Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/version/c_ab4af688f83e57aaapplication/pdf09746846https://hdl.handle.net/11323/1317Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/engAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2reponame:Repositorio REDICUCinstname:Corporación Universidad de la Costainstacron:Corporación Universidad de la Costa2024-09-17T19:09:36Z
dc.title.none.fl_str_mv Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
title Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
spellingShingle Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
Viloria Silva, Amelec Jesus
Bacterial drug resistance
Escherichia coli
Imipenem and Meropenem
Linear regression model
title_short Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
title_full Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
title_fullStr Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
title_full_unstemmed Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
title_sort Predicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regression
dc.creator.none.fl_str_mv Viloria Silva, Amelec Jesus
Campo Urbina, Myrna
Gómez Rodríguez, Lucila
Parody Muñoz, Alexander
author Viloria Silva, Amelec Jesus
author_facet Viloria Silva, Amelec Jesus
Campo Urbina, Myrna
Gómez Rodríguez, Lucila
Parody Muñoz, Alexander
author_role author
author2 Campo Urbina, Myrna
Gómez Rodríguez, Lucila
Parody Muñoz, Alexander
author2_role author
author
author
dc.subject.none.fl_str_mv Bacterial drug resistance
Escherichia coli
Imipenem and Meropenem
Linear regression model
topic Bacterial drug resistance
Escherichia coli
Imipenem and Meropenem
Linear regression model
description Objectives: To determine the trend of bacterial resistance of Escherichia coli to Imipenem (IPM) and Meropenem (MEM), by means of a linear regression model, taking the information collected in the bulletins of bacterial resistance generated by the GREBO group of Bogotá between 2010 and 2014. Methods/Statistical Analysis: From the information published in newsletters GREBO group between 2010 and 2014, the behavior of E. coli bacterial resistance to antibiotics was analyzed. From this information simple linear regression models using the statistical software Statgraphics XVI were generated. Findings: The generated mathematical models to predict the evolution of antibiotic resistance as a function of time and that were significant are: Resistance IPM * Year = 0.00000208772 (p value 0.0020; adjusted R2 = 92.86%); Resistance MEM = 0.00000149115 * Year (p value 0.0026; adjusted R2 = 91.84%). Application/Improvements: There is a relationship between the values of resistance and over the years, with variable time sufficient to explain the behavior of the resistance of E. coli variable. In 2015 IPM resistance is estimated that this in 0.42% (CI 0.02% - 0.8%) and MEM 0.3% (CI 0.17% - 0.42%).
publishDate 2016
dc.date.none.fl_str_mv 2016
2018-11-19T19:17:59Z
2018-11-19T19:17:59Z
dc.type.none.fl_str_mv Artículo de revista
http://purl.org/coar/resource_type/c_6501
Text
info:eu-repo/semantics/article
http://purl.org/redcol/resource_type/ART
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/version/c_ab4af688f83e57aa
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv 09746846
https://hdl.handle.net/11323/1317
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
https://repositorio.cuc.edu.co/
identifier_str_mv 09746846
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/1317
https://repositorio.cuc.edu.co/
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv Atribución – No comercial – Compartir igual
info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Atribución – No comercial – Compartir igual
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Indian Journal of Science and Technology
publisher.none.fl_str_mv Indian Journal of Science and Technology
dc.source.none.fl_str_mv reponame:Repositorio REDICUC
instname:Corporación Universidad de la Costa
instacron:Corporación Universidad de la Costa
instname_str Corporación Universidad de la Costa
instacron_str Corporación Universidad de la Costa
institution Corporación Universidad de la Costa
reponame_str Repositorio REDICUC
collection Repositorio REDICUC
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