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Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method

Bibliographic Details
Main Author: Jacinto, Tiago
Publication Date: 2018
Other Authors: Amaral, Rita, Malinovschi, Andrei, Janson, Christer, Fonseca, João, Alving, Kjell
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.22/13932
Summary: Absolute values are used in the interpretation of the fraction of exhaled nitric oxide (FeNO), but it has been suggested that equations to calculate reference values may be a practical and clinically useful approach. We hypothesize that the application of the Lambda-Mu-Sigma (LMS) method may improve FeNO reference equations and their interpretation. Our aims were to develop FeNO reference equations with the LMS method and to describe the difference between this method and the absolute fixed cut-offs of the current recommendations. We utilized the United States National Health and Nutrition Examination Surveys 2007-2012 and included healthy individuals with no respiratory diseases and blood eosinophils <300/mm3 ( n = 8,340). Natural log-transformed FeNO was modeled using the LMS method, imbedded in the generalized additive models for location, scale, and shape models. A set of FeNO reference equations was developed. The explanatory variables were sex, age, height, smoking habits, and race/ethnicity. A significant proportion of individuals with normal FeNO given by the equations were classified as having intermediate levels by the current recommendations. Further lower predicted FeNO compared with previous linear models was seen. In conclusion, we suggest a novel model for the prediction of reference FeNO values that can contribute to the interpretation of FeNO in clinical practice. This approach should be further validated in large samples with an objective measurement of atopy and a medical diagnosis of asthma and rhinitis. NEW & NOTEWORTHY Novel reference equations and fraction of exhaled nitric oxide (FeNO)-predicted values to improve interpretation of FeNO in clinical practice are presented. These may increase the accuracy of ruling out airway inflammation in patients with asthma or suspected asthma.
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spelling Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma methodAsthmaExhaled nitric oxideAbsolute values are used in the interpretation of the fraction of exhaled nitric oxide (FeNO), but it has been suggested that equations to calculate reference values may be a practical and clinically useful approach. We hypothesize that the application of the Lambda-Mu-Sigma (LMS) method may improve FeNO reference equations and their interpretation. Our aims were to develop FeNO reference equations with the LMS method and to describe the difference between this method and the absolute fixed cut-offs of the current recommendations. We utilized the United States National Health and Nutrition Examination Surveys 2007-2012 and included healthy individuals with no respiratory diseases and blood eosinophils <300/mm3 ( n = 8,340). Natural log-transformed FeNO was modeled using the LMS method, imbedded in the generalized additive models for location, scale, and shape models. A set of FeNO reference equations was developed. The explanatory variables were sex, age, height, smoking habits, and race/ethnicity. A significant proportion of individuals with normal FeNO given by the equations were classified as having intermediate levels by the current recommendations. Further lower predicted FeNO compared with previous linear models was seen. In conclusion, we suggest a novel model for the prediction of reference FeNO values that can contribute to the interpretation of FeNO in clinical practice. This approach should be further validated in large samples with an objective measurement of atopy and a medical diagnosis of asthma and rhinitis. NEW & NOTEWORTHY Novel reference equations and fraction of exhaled nitric oxide (FeNO)-predicted values to improve interpretation of FeNO in clinical practice are presented. These may increase the accuracy of ruling out airway inflammation in patients with asthma or suspected asthma.American Physiological SocietyREPOSITÓRIO P.PORTOJacinto, TiagoAmaral, RitaMalinovschi, AndreiJanson, ChristerFonseca, JoãoAlving, Kjell2019-12-12T01:30:26Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/13932eng10.1152/japplphysiol.00093.2018info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-07T10:06:12Zoai:recipp.ipp.pt:10400.22/13932Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:32:21.008718Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
title Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
spellingShingle Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
Jacinto, Tiago
Asthma
Exhaled nitric oxide
title_short Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
title_full Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
title_fullStr Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
title_full_unstemmed Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
title_sort Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method
author Jacinto, Tiago
author_facet Jacinto, Tiago
Amaral, Rita
Malinovschi, Andrei
Janson, Christer
Fonseca, João
Alving, Kjell
author_role author
author2 Amaral, Rita
Malinovschi, Andrei
Janson, Christer
Fonseca, João
Alving, Kjell
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Jacinto, Tiago
Amaral, Rita
Malinovschi, Andrei
Janson, Christer
Fonseca, João
Alving, Kjell
dc.subject.por.fl_str_mv Asthma
Exhaled nitric oxide
topic Asthma
Exhaled nitric oxide
description Absolute values are used in the interpretation of the fraction of exhaled nitric oxide (FeNO), but it has been suggested that equations to calculate reference values may be a practical and clinically useful approach. We hypothesize that the application of the Lambda-Mu-Sigma (LMS) method may improve FeNO reference equations and their interpretation. Our aims were to develop FeNO reference equations with the LMS method and to describe the difference between this method and the absolute fixed cut-offs of the current recommendations. We utilized the United States National Health and Nutrition Examination Surveys 2007-2012 and included healthy individuals with no respiratory diseases and blood eosinophils <300/mm3 ( n = 8,340). Natural log-transformed FeNO was modeled using the LMS method, imbedded in the generalized additive models for location, scale, and shape models. A set of FeNO reference equations was developed. The explanatory variables were sex, age, height, smoking habits, and race/ethnicity. A significant proportion of individuals with normal FeNO given by the equations were classified as having intermediate levels by the current recommendations. Further lower predicted FeNO compared with previous linear models was seen. In conclusion, we suggest a novel model for the prediction of reference FeNO values that can contribute to the interpretation of FeNO in clinical practice. This approach should be further validated in large samples with an objective measurement of atopy and a medical diagnosis of asthma and rhinitis. NEW & NOTEWORTHY Novel reference equations and fraction of exhaled nitric oxide (FeNO)-predicted values to improve interpretation of FeNO in clinical practice are presented. These may increase the accuracy of ruling out airway inflammation in patients with asthma or suspected asthma.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2019-12-12T01:30:26Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/13932
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1152/japplphysiol.00093.2018
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv American Physiological Society
publisher.none.fl_str_mv American Physiological Society
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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