Prediction of chronic critical illness in a general intensive care unit
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Associação Médica Brasileira (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302013000300009 |
Resumo: | OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI. |
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Prediction of chronic critical illness in a general intensive care unitCritical illnessProlonged mechanical ventilationCost controlHospital mortalityOBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI.Associação Médica Brasileira2013-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302013000300009Revista da Associação Médica Brasileira v.59 n.3 2013reponame:Revista da Associação Médica Brasileira (Online)instname:Associação Médica Brasileira (AMB)instacron:AMB10.1016/j.ramb.2012.12.002info:eu-repo/semantics/openAccessLoss,Sérgio H.Marchese,Cláudia B.Boniatti,Márcio M.Wawrzeniak,Iuri C.Oliveira,Roselaine P.Nunes,Luciana N.Victorino,Josué A.eng2013-07-05T00:00:00Zoai:scielo:S0104-42302013000300009Revistahttps://ramb.amb.org.br/ultimas-edicoes/#https://old.scielo.br/oai/scielo-oai.php||ramb@amb.org.br1806-92820104-4230opendoar:2013-07-05T00:00Revista da Associação Médica Brasileira (Online) - Associação Médica Brasileira (AMB)false |
dc.title.none.fl_str_mv |
Prediction of chronic critical illness in a general intensive care unit |
title |
Prediction of chronic critical illness in a general intensive care unit |
spellingShingle |
Prediction of chronic critical illness in a general intensive care unit Loss,Sérgio H. Critical illness Prolonged mechanical ventilation Cost control Hospital mortality |
title_short |
Prediction of chronic critical illness in a general intensive care unit |
title_full |
Prediction of chronic critical illness in a general intensive care unit |
title_fullStr |
Prediction of chronic critical illness in a general intensive care unit |
title_full_unstemmed |
Prediction of chronic critical illness in a general intensive care unit |
title_sort |
Prediction of chronic critical illness in a general intensive care unit |
author |
Loss,Sérgio H. |
author_facet |
Loss,Sérgio H. Marchese,Cláudia B. Boniatti,Márcio M. Wawrzeniak,Iuri C. Oliveira,Roselaine P. Nunes,Luciana N. Victorino,Josué A. |
author_role |
author |
author2 |
Marchese,Cláudia B. Boniatti,Márcio M. Wawrzeniak,Iuri C. Oliveira,Roselaine P. Nunes,Luciana N. Victorino,Josué A. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Loss,Sérgio H. Marchese,Cláudia B. Boniatti,Márcio M. Wawrzeniak,Iuri C. Oliveira,Roselaine P. Nunes,Luciana N. Victorino,Josué A. |
dc.subject.por.fl_str_mv |
Critical illness Prolonged mechanical ventilation Cost control Hospital mortality |
topic |
Critical illness Prolonged mechanical ventilation Cost control Hospital mortality |
description |
OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-06-01 |
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=S0104-42302013000300009 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302013000300009 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.ramb.2012.12.002 |
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 |
Associação Médica Brasileira |
publisher.none.fl_str_mv |
Associação Médica Brasileira |
dc.source.none.fl_str_mv |
Revista da Associação Médica Brasileira v.59 n.3 2013 reponame:Revista da Associação Médica Brasileira (Online) instname:Associação Médica Brasileira (AMB) instacron:AMB |
instname_str |
Associação Médica Brasileira (AMB) |
instacron_str |
AMB |
institution |
AMB |
reponame_str |
Revista da Associação Médica Brasileira (Online) |
collection |
Revista da Associação Médica Brasileira (Online) |
repository.name.fl_str_mv |
Revista da Associação Médica Brasileira (Online) - Associação Médica Brasileira (AMB) |
repository.mail.fl_str_mv |
||ramb@amb.org.br |
_version_ |
1754212830730518528 |