A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients

Detalhes bibliográficos
Autor(a) principal: Tuon,Felipe F.
Data de Publicação: 2014
Outros Autores: Rocha,Jaime L., Leite,Talita M., Dias,Camila
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Infectious Diseases
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702014000400360
Resumo: BACKGROUND: Local epidemiological data are always helpful when choosing the best antibiotic regimen, but it is more complex than it seems as it may require the analysis of multiple combinations. The aim of this study was to demonstrate a simplified mathematical calculation to determine the most appropriate antibiotic combination in a scenario where monotherapy is doomed to failure. METHODS: The susceptibility pattern of 11 antibiotics from 216 positive blood cultures from January 2012 to January 2013 was analyzed based on local policy. The length of hospitalization before bacteremia and the unit (ward or intensive care unit) were the analyzed variables. Bacteremia was classified as early, intermediate or late. The antibiotics were combined according to the combination model presented herein. RESULTS: A total of 55 possible mathematical associations were found combining 2 by 2, 165 associations with 3 by 3 and 330 combinations with 4 by 4. In the intensive care unit, monotherapy never reached 80% of susceptibility. In the ward, only carbapenems covered more than 90% of early bacteremia. Only three drugs combined reached a susceptibility rate higher than 90% anywhere in the hospital. Several regimens using four drugs combined reached 100% of susceptibility. CONCLUSIONS: Association of three drugs is necessary for adequate coverage of empirical treatment of bacteremia in both the intensive care unit and the ward.
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spelling A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patientsMathematical modelInfectionAntibioticBacteremia BACKGROUND: Local epidemiological data are always helpful when choosing the best antibiotic regimen, but it is more complex than it seems as it may require the analysis of multiple combinations. The aim of this study was to demonstrate a simplified mathematical calculation to determine the most appropriate antibiotic combination in a scenario where monotherapy is doomed to failure. METHODS: The susceptibility pattern of 11 antibiotics from 216 positive blood cultures from January 2012 to January 2013 was analyzed based on local policy. The length of hospitalization before bacteremia and the unit (ward or intensive care unit) were the analyzed variables. Bacteremia was classified as early, intermediate or late. The antibiotics were combined according to the combination model presented herein. RESULTS: A total of 55 possible mathematical associations were found combining 2 by 2, 165 associations with 3 by 3 and 330 combinations with 4 by 4. In the intensive care unit, monotherapy never reached 80% of susceptibility. In the ward, only carbapenems covered more than 90% of early bacteremia. Only three drugs combined reached a susceptibility rate higher than 90% anywhere in the hospital. Several regimens using four drugs combined reached 100% of susceptibility. CONCLUSIONS: Association of three drugs is necessary for adequate coverage of empirical treatment of bacteremia in both the intensive care unit and the ward. Brazilian Society of Infectious Diseases2014-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702014000400360Brazilian Journal of Infectious Diseases v.18 n.4 2014reponame:Brazilian Journal of Infectious Diseasesinstname:Brazilian Society of Infectious Diseases (BSID)instacron:BSID10.1016/j.bjid.2013.11.006info:eu-repo/semantics/openAccessTuon,Felipe F.Rocha,Jaime L.Leite,Talita M.Dias,Camilaeng2016-01-29T00:00:00Zoai:scielo:S1413-86702014000400360Revistahttps://www.bjid.org.br/https://old.scielo.br/oai/scielo-oai.phpbjid@bjid.org.br||lgoldani@ufrgs.br1678-43911413-8670opendoar:2016-01-29T00:00Brazilian Journal of Infectious Diseases - Brazilian Society of Infectious Diseases (BSID)false
dc.title.none.fl_str_mv A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
title A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
spellingShingle A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
Tuon,Felipe F.
Mathematical model
Infection
Antibiotic
Bacteremia
title_short A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
title_full A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
title_fullStr A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
title_full_unstemmed A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
title_sort A simple mathematical model to determine the ideal empirical antibiotic therapy for bacteremic patients
author Tuon,Felipe F.
author_facet Tuon,Felipe F.
Rocha,Jaime L.
Leite,Talita M.
Dias,Camila
author_role author
author2 Rocha,Jaime L.
Leite,Talita M.
Dias,Camila
author2_role author
author
author
dc.contributor.author.fl_str_mv Tuon,Felipe F.
Rocha,Jaime L.
Leite,Talita M.
Dias,Camila
dc.subject.por.fl_str_mv Mathematical model
Infection
Antibiotic
Bacteremia
topic Mathematical model
Infection
Antibiotic
Bacteremia
description BACKGROUND: Local epidemiological data are always helpful when choosing the best antibiotic regimen, but it is more complex than it seems as it may require the analysis of multiple combinations. The aim of this study was to demonstrate a simplified mathematical calculation to determine the most appropriate antibiotic combination in a scenario where monotherapy is doomed to failure. METHODS: The susceptibility pattern of 11 antibiotics from 216 positive blood cultures from January 2012 to January 2013 was analyzed based on local policy. The length of hospitalization before bacteremia and the unit (ward or intensive care unit) were the analyzed variables. Bacteremia was classified as early, intermediate or late. The antibiotics were combined according to the combination model presented herein. RESULTS: A total of 55 possible mathematical associations were found combining 2 by 2, 165 associations with 3 by 3 and 330 combinations with 4 by 4. In the intensive care unit, monotherapy never reached 80% of susceptibility. In the ward, only carbapenems covered more than 90% of early bacteremia. Only three drugs combined reached a susceptibility rate higher than 90% anywhere in the hospital. Several regimens using four drugs combined reached 100% of susceptibility. CONCLUSIONS: Association of three drugs is necessary for adequate coverage of empirical treatment of bacteremia in both the intensive care unit and the ward.
publishDate 2014
dc.date.none.fl_str_mv 2014-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702014000400360
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702014000400360
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.bjid.2013.11.006
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Infectious Diseases
publisher.none.fl_str_mv Brazilian Society of Infectious Diseases
dc.source.none.fl_str_mv Brazilian Journal of Infectious Diseases v.18 n.4 2014
reponame:Brazilian Journal of Infectious Diseases
instname:Brazilian Society of Infectious Diseases (BSID)
instacron:BSID
instname_str Brazilian Society of Infectious Diseases (BSID)
instacron_str BSID
institution BSID
reponame_str Brazilian Journal of Infectious Diseases
collection Brazilian Journal of Infectious Diseases
repository.name.fl_str_mv Brazilian Journal of Infectious Diseases - Brazilian Society of Infectious Diseases (BSID)
repository.mail.fl_str_mv bjid@bjid.org.br||lgoldani@ufrgs.br
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