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dc.contributor.authorEsteban, Cristóbal
dc.contributor.authorArostegui Madariaga, Inmaculada ORCID
dc.contributor.authorGarcía Gutiérrez, Susana
dc.contributor.authorGonzález Hernández, Nerea
dc.contributor.authorLafuente Guerrero, Iratxe
dc.contributor.authorBaré Mañas, Marisa
dc.contributor.authorFernández de Larrea, Nerea
dc.contributor.authorRivas Ruiz, Francisco
dc.contributor.authorQuintana López, José María
dc.date.accessioned2019-04-09T14:42:25Z
dc.date.available2019-04-09T14:42:25Z
dc.date.issued2015-12-22
dc.identifier.citationRespiratory Research 16 : (2015) // Article ID 151es_ES
dc.identifier.issn1465-993X
dc.identifier.issn1465-9921
dc.identifier.urihttp://hdl.handle.net/10810/32389
dc.description.abstractBackground: Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD. Methods: We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50 %) and validation samples (50 %). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample. Results: Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0 % to 55 % in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95 % CI: 0.783, 0.888) and 0.794 (95 % CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95 % CI: 0.776, 0.859) and 0.770 (95 % CI: 0.716, 0.823) in the validation sample. Conclusions: We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care.es_ES
dc.description.sponsorshipThis work was supported in part by grants from the Fondo de Investigacion Sanitaria (PI 06\1010, PI06\1017, PI06\714, PI06\0326, PI06\0664); Department of Health of the Basque Government (2012111008), Department of Education, Language Policy and Culture of the Basque Government (IT620-13); the Research Committee of the Hospital Galdakao; and the thematic networks REDISSEC (Red de Investigacion en Servicios de Salud en Enfermedades Cronicas) - of the Instituto de Salud Carlos III.es_ES
dc.language.isoenges_ES
dc.publisherBiomed Centrales_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectCOPDes_ES
dc.subjectdecision treees_ES
dc.subjectshort-term mortalityes_ES
dc.subjectobstructive pulmonary-diseasees_ES
dc.subjectmyocardial-infarctiones_ES
dc.subjectstable COPDes_ES
dc.subjectpredictorses_ES
dc.subjectriskes_ES
dc.subjecthospitalizationes_ES
dc.subjectvalidationes_ES
dc.subjectregressiones_ES
dc.subjectdiagnosises_ES
dc.subjectclassificationes_ES
dc.titleA Decision Tree to Assess Short-Term Mortality After an Emergency Department Visit for an Exacerbation of COPD: a Cohort Studyes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2015 Esteban et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.es_ES
dc.relation.publisherversionhttps://respiratory-research.biomedcentral.com/articles/10.1186/s12931-015-0313-4es_ES
dc.identifier.doi10.1186/s12931-015-0313-4
dc.departamentoesMatemática Aplicada, Estadística e Investigación Operativaes_ES
dc.departamentoeuMatematika aplikatua eta estatistikaes_ES


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© 2015 Esteban et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as © 2015 Esteban et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.