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...
- Autores:
-
Viloria Silva, Amelec Jesus
Campo Urbina, Myrna
Gómez Rodríguez, Lucila
Parody Muñoz, Alexander
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/1317
- Acceso en línea:
- https://hdl.handle.net/11323/1317
https://repositorio.cuc.edu.co/
- Palabra clave:
- Bacterial drug resistance
Escherichia coli
Imipenem and Meropenem
Linear regression model
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
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|
dc.title.eng.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 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.fl_str_mv |
Viloria Silva, Amelec Jesus Campo Urbina, Myrna Gómez Rodríguez, Lucila Parody Muñoz, Alexander |
dc.contributor.author.spa.fl_str_mv |
Viloria Silva, Amelec Jesus Campo Urbina, Myrna Gómez Rodríguez, Lucila Parody Muñoz, Alexander |
dc.subject.eng.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.issued.none.fl_str_mv |
2016 |
dc.date.accessioned.none.fl_str_mv |
2018-11-19T19:17:59Z |
dc.date.available.none.fl_str_mv |
2018-11-19T19:17:59Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
acceptedVersion |
dc.identifier.issn.spa.fl_str_mv |
09746846 |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/1317 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
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.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.spa.fl_str_mv |
Atribución – No comercial – Compartir igual |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
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.publisher.spa.fl_str_mv |
Indian Journal of Science and Technology |
institution |
Corporación Universidad de la Costa |
bitstream.url.fl_str_mv |
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Viloria Silva, Amelec JesusCampo Urbina, MyrnaGómez Rodríguez, LucilaParody Muñoz, Alexander2018-11-19T19:17:59Z2018-11-19T19:17:59Z201609746846https://hdl.handle.net/11323/1317Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/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%).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-4359-90e4-915cdc430463-600engIndian Journal of Science and TechnologyAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Bacterial drug resistanceEscherichia coliImipenem and MeropenemLinear regression modelPredicting of behavior of escherichia coli resistance to Imipenem and Meropenem, using a simple mathematical model regressionArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALPredicting of Behavior of Escherichia Coli Resistance.pdfPredicting of Behavior of Escherichia Coli Resistance.pdfapplication/pdf236907https://repositorio.cuc.edu.co/bitstreams/cab25b9a-d92c-4f37-83c8-4e7492a7c22c/download694c1f593d99236afb50a6925e9ad640MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/93601d1c-d72f-411d-857d-610173ae4c45/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILPredicting of Behavior of Escherichia Coli Resistance.pdf.jpgPredicting of Behavior of Escherichia Coli Resistance.pdf.jpgimage/jpeg68793https://repositorio.cuc.edu.co/bitstreams/d929f567-73c7-4b92-8e72-e12460b13cc7/download5aeb9e26dd3a4ce28ae2d7691dc18587MD54TEXTPredicting of Behavior of Escherichia Coli Resistance.pdf.txtPredicting of Behavior of Escherichia Coli Resistance.pdf.txttext/plain16190https://repositorio.cuc.edu.co/bitstreams/4982bf9b-3a3e-43e4-8bbd-706dde496e96/download5cf05f260f104c7aee902999ee54c073MD5511323/1317oai:repositorio.cuc.edu.co:11323/13172024-09-17 14:09:36.129open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |