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Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve

BACKGROUND: Spirometry interpretation is influenced by the predictive equations defining lower limit of normal (LLN), while ‘distal’ expiratory flows such as forced expiratory flow at 50% FVC (FEF(50)) are important functional parameters for diagnosing small airway disease (SAD). Area under expirato...

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Autores principales: Ioachimescu, Octavian C, Stoller, James K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890381/
https://www.ncbi.nlm.nih.gov/pubmed/31803477
http://dx.doi.org/10.1136/bmjresp-2019-000511
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author Ioachimescu, Octavian C
Stoller, James K
author_facet Ioachimescu, Octavian C
Stoller, James K
author_sort Ioachimescu, Octavian C
collection PubMed
description BACKGROUND: Spirometry interpretation is influenced by the predictive equations defining lower limit of normal (LLN), while ‘distal’ expiratory flows such as forced expiratory flow at 50% FVC (FEF(50)) are important functional parameters for diagnosing small airway disease (SAD). Area under expiratory flow-volume curve (AEX) or its approximations have been proposed as supplemental spirometric assessment tools. We compare here the performance of AEX in differentiating between normal, obstruction, restriction, mixed defects and SAD, as defined by Global Lung Initiative (GLI) or National Health and Nutrition Examination Survey (NHANES) III reference values, and using various predictive equations for FEF(50). METHODS: We analysed 15 308 spirometry-lung volume tests. Using GLI versus NHANES III LLNs, and diagnosing SAD by the eight most common equation sets for forced expiratory flow at 50% of vital capacity lower limits of normal (FEF(50 LLN)), we assessed the degree of diagnostic concordance and the ability of AEX to differentiate between various definition-dependent patterns. RESULTS: Concordance rates between NHANES III and GLI-based classifications were 93.7%, 78.6%, 86.8%, 88.0%, 93.8% and 98.8% in those without, with mild, moderate, moderately severe, severe and very severe obstruction, respectively (agreement coefficient 0.81 (0.80–0.82)). The prevalence of SAD was 0.6%–6.9% of the cohort, depending on the definition used. The AEX differentiated well between normal, obstruction, restriction, mixed pattern and SAD, as defined by most equations. CONCLUSIONS: If the SAD diagnosis is established by using mean FEF(50 LLN) or a set number of predictive equations, AEX is able to differentiate well between various spirometric patterns. Using the most common predictive equations (NHANES III and GLI), the diagnostic concordance for functional type and obstruction severity is high.
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spelling pubmed-68903812019-12-04 Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve Ioachimescu, Octavian C Stoller, James K BMJ Open Respir Res Respiratory Physiology BACKGROUND: Spirometry interpretation is influenced by the predictive equations defining lower limit of normal (LLN), while ‘distal’ expiratory flows such as forced expiratory flow at 50% FVC (FEF(50)) are important functional parameters for diagnosing small airway disease (SAD). Area under expiratory flow-volume curve (AEX) or its approximations have been proposed as supplemental spirometric assessment tools. We compare here the performance of AEX in differentiating between normal, obstruction, restriction, mixed defects and SAD, as defined by Global Lung Initiative (GLI) or National Health and Nutrition Examination Survey (NHANES) III reference values, and using various predictive equations for FEF(50). METHODS: We analysed 15 308 spirometry-lung volume tests. Using GLI versus NHANES III LLNs, and diagnosing SAD by the eight most common equation sets for forced expiratory flow at 50% of vital capacity lower limits of normal (FEF(50 LLN)), we assessed the degree of diagnostic concordance and the ability of AEX to differentiate between various definition-dependent patterns. RESULTS: Concordance rates between NHANES III and GLI-based classifications were 93.7%, 78.6%, 86.8%, 88.0%, 93.8% and 98.8% in those without, with mild, moderate, moderately severe, severe and very severe obstruction, respectively (agreement coefficient 0.81 (0.80–0.82)). The prevalence of SAD was 0.6%–6.9% of the cohort, depending on the definition used. The AEX differentiated well between normal, obstruction, restriction, mixed pattern and SAD, as defined by most equations. CONCLUSIONS: If the SAD diagnosis is established by using mean FEF(50 LLN) or a set number of predictive equations, AEX is able to differentiate well between various spirometric patterns. Using the most common predictive equations (NHANES III and GLI), the diagnostic concordance for functional type and obstruction severity is high. BMJ Publishing Group 2019-11-24 /pmc/articles/PMC6890381/ /pubmed/31803477 http://dx.doi.org/10.1136/bmjresp-2019-000511 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Respiratory Physiology
Ioachimescu, Octavian C
Stoller, James K
Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title_full Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title_fullStr Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title_full_unstemmed Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title_short Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
title_sort assessing small airway disease in gli versus nhanes iii based spirometry using area under the expiratory flow-volume curve
topic Respiratory Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890381/
https://www.ncbi.nlm.nih.gov/pubmed/31803477
http://dx.doi.org/10.1136/bmjresp-2019-000511
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