Faculty Collaboration Database

Assessing small airway disease in GLI versus NHANES III based spirometry using area under the expiratory flow-volume curve. BMJ Open Respir Res 2019;6(1):e000511

Date

12/06/2019

Pubmed ID

31803477

Pubmed Central ID

PMC6890381

DOI

10.1136/bmjresp-2019-000511

Scopus ID

2-s2.0-85075655595 (requires institutional sign-in at Scopus site)   5 Citations

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 (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.

Author List

Ioachimescu OC, Stoller JK

Author

Octavian C. Ioachimescu MD, PhD Vice Chair, Director, Professor in the Medicine department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Aged
Airway Obstruction
Area Under Curve
Asthma
Datasets as Topic
Female
Forced Expiratory Volume
Humans
Lung
Male
Middle Aged
Plethysmography, Whole Body
Predictive Value of Tests
Prevalence
Prognosis
Pulmonary Disease, Chronic Obstructive
Reference Values
Severity of Illness Index
Spirometry