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Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms
Early identification of subjects running an increased risk of contracting COPD enables focus on individual preventive measures. The slope of the alveolar plateau of the single-breath nitrogen washout test (N(2)-slope) is a sensitive measure of small-airway dysfunction. However, its role remains unex...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Respiratory Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473809/ https://www.ncbi.nlm.nih.gov/pubmed/34589539 http://dx.doi.org/10.1183/23120541.00383-2021 |
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author | Olofson, Jan Bake, Björn Bergman, Bengt Vanfleteren, Lowie E.G.W. Svärdsudd, Kurt |
author_facet | Olofson, Jan Bake, Björn Bergman, Bengt Vanfleteren, Lowie E.G.W. Svärdsudd, Kurt |
author_sort | Olofson, Jan |
collection | PubMed |
description | Early identification of subjects running an increased risk of contracting COPD enables focus on individual preventive measures. The slope of the alveolar plateau of the single-breath nitrogen washout test (N(2)-slope) is a sensitive measure of small-airway dysfunction. However, its role remains unexplored in predicting hospital admission or death related to COPD, i.e. incident COPD events, in relation to the presence of various respiratory symptoms. A random population sample of 625 men, aged 50 (n=218) or 60 years (n=407), was followed for 38 years for incident COPD events. At baseline, a questionnaire on respiratory symptoms and smoking habits was collected, spirometry and the single-breath nitrogen test were performed, and the N(2)-slope was determined. Proportional hazard regression (Cox regression) analysis was used for the prediction model. The N(2)-slope improved the prediction of COPD events significantly beyond that of respiratory symptoms weighted all together and other covariates (hazard ratio 1.63, 95% CI 1.20–2.22; p<0.005), a prediction applicable to subjects without (p=0.001) and with (p<0.05) airway obstruction. Dyspnoea and wheezing were the most predictive symptoms. The combination of the N(2)-slope and number of respiratory symptoms notably resulted in an effective prediction of incident COPD events even in nonobstructive subjects, as evidenced by a predicted incidence of ∼70% and ∼90% for a very steep N(2)-slope combined with many respiratory symptoms in subject without and with airway obstruction, respectively. The alveolar N(2)-slope should be considered in the critical need for further research on early diagnosis of COPD. |
format | Online Article Text |
id | pubmed-8473809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | European Respiratory Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-84738092021-09-28 Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms Olofson, Jan Bake, Björn Bergman, Bengt Vanfleteren, Lowie E.G.W. Svärdsudd, Kurt ERJ Open Res Original Research Articles Early identification of subjects running an increased risk of contracting COPD enables focus on individual preventive measures. The slope of the alveolar plateau of the single-breath nitrogen washout test (N(2)-slope) is a sensitive measure of small-airway dysfunction. However, its role remains unexplored in predicting hospital admission or death related to COPD, i.e. incident COPD events, in relation to the presence of various respiratory symptoms. A random population sample of 625 men, aged 50 (n=218) or 60 years (n=407), was followed for 38 years for incident COPD events. At baseline, a questionnaire on respiratory symptoms and smoking habits was collected, spirometry and the single-breath nitrogen test were performed, and the N(2)-slope was determined. Proportional hazard regression (Cox regression) analysis was used for the prediction model. The N(2)-slope improved the prediction of COPD events significantly beyond that of respiratory symptoms weighted all together and other covariates (hazard ratio 1.63, 95% CI 1.20–2.22; p<0.005), a prediction applicable to subjects without (p=0.001) and with (p<0.05) airway obstruction. Dyspnoea and wheezing were the most predictive symptoms. The combination of the N(2)-slope and number of respiratory symptoms notably resulted in an effective prediction of incident COPD events even in nonobstructive subjects, as evidenced by a predicted incidence of ∼70% and ∼90% for a very steep N(2)-slope combined with many respiratory symptoms in subject without and with airway obstruction, respectively. The alveolar N(2)-slope should be considered in the critical need for further research on early diagnosis of COPD. European Respiratory Society 2021-09-27 /pmc/articles/PMC8473809/ /pubmed/34589539 http://dx.doi.org/10.1183/23120541.00383-2021 Text en Copyright ©The authors 2021 https://creativecommons.org/licenses/by-nc/4.0/This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions@ersnet.org (mailto:permissions@ersnet.org) |
spellingShingle | Original Research Articles Olofson, Jan Bake, Björn Bergman, Bengt Vanfleteren, Lowie E.G.W. Svärdsudd, Kurt Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title | Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title_full | Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title_fullStr | Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title_full_unstemmed | Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title_short | Prediction of COPD by the single-breath nitrogen test and various respiratory symptoms |
title_sort | prediction of copd by the single-breath nitrogen test and various respiratory symptoms |
topic | Original Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473809/ https://www.ncbi.nlm.nih.gov/pubmed/34589539 http://dx.doi.org/10.1183/23120541.00383-2021 |
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