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Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve
  1. Octavian C Ioachimescu1,2 and
  2. James K Stoller3
  1. 1Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, School of Medicine, Emory University, Atlanta, Georgia, USA
  2. 2Section of Sleep Medicine, Atlanta VAMC, Atlanta, Georgia, USA
  3. 3Respiratory Institute, Cleveland Clinic, Cleveland, Ohio, USA
  1. Correspondence to Dr Octavian C Ioachimescu; oioac{at}yahoo.com

Abstract

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 (FEF50) 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 FEF50.

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 (FEF50 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 FEF50 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.

  • lung physiology
  • respiratory measurement
  • asthma
  • lung transplantation

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/.

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Footnotes

  • Contributors OCL: concept, data analysis and interpretation, article writing, submission. JKS: concept, interpretation, article writing.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The study received Institutional Review Board approvals (Cleveland Clinic IRB EX#0504 and EX#19–1129; Emory IRB #00049576).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement No data are available.