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COPD classification models and mortality prediction capacity
OBJECTIVE: Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. PATIENTS AND METHODS: A total of 543 patients with COPD (FEV(1) <80% and FEV(1)/FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclus...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410748/ https://www.ncbi.nlm.nih.gov/pubmed/30880950 http://dx.doi.org/10.2147/COPD.S184695 |
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author | Aramburu, Amaia Arostegui, Inmaculada Moraza, Javier Barrio, Irantzu Aburto, Myriam García-Loizaga, Amaia Uranga, Ane Zabala, Txomin Quintana, José María Esteban, Cristóbal |
author_facet | Aramburu, Amaia Arostegui, Inmaculada Moraza, Javier Barrio, Irantzu Aburto, Myriam García-Loizaga, Amaia Uranga, Ane Zabala, Txomin Quintana, José María Esteban, Cristóbal |
author_sort | Aramburu, Amaia |
collection | PubMed |
description | OBJECTIVE: Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. PATIENTS AND METHODS: A total of 543 patients with COPD (FEV(1) <80% and FEV(1)/FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index. RESULTS: Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV(1)% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLD(ABCD), GOLD(2017) and cluster analysis for predicting mortality, cluster system was found to be superior compared with GOLD(2017) (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001). CONCLUSION: Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortality. |
format | Online Article Text |
id | pubmed-6410748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64107482019-03-16 COPD classification models and mortality prediction capacity Aramburu, Amaia Arostegui, Inmaculada Moraza, Javier Barrio, Irantzu Aburto, Myriam García-Loizaga, Amaia Uranga, Ane Zabala, Txomin Quintana, José María Esteban, Cristóbal Int J Chron Obstruct Pulmon Dis Original Research OBJECTIVE: Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. PATIENTS AND METHODS: A total of 543 patients with COPD (FEV(1) <80% and FEV(1)/FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index. RESULTS: Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV(1)% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLD(ABCD), GOLD(2017) and cluster analysis for predicting mortality, cluster system was found to be superior compared with GOLD(2017) (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001). CONCLUSION: Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortality. Dove Medical Press 2019-03-07 /pmc/articles/PMC6410748/ /pubmed/30880950 http://dx.doi.org/10.2147/COPD.S184695 Text en © 2019 Aramburu et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Aramburu, Amaia Arostegui, Inmaculada Moraza, Javier Barrio, Irantzu Aburto, Myriam García-Loizaga, Amaia Uranga, Ane Zabala, Txomin Quintana, José María Esteban, Cristóbal COPD classification models and mortality prediction capacity |
title | COPD classification models and mortality prediction capacity |
title_full | COPD classification models and mortality prediction capacity |
title_fullStr | COPD classification models and mortality prediction capacity |
title_full_unstemmed | COPD classification models and mortality prediction capacity |
title_short | COPD classification models and mortality prediction capacity |
title_sort | copd classification models and mortality prediction capacity |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410748/ https://www.ncbi.nlm.nih.gov/pubmed/30880950 http://dx.doi.org/10.2147/COPD.S184695 |
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