New Spirometry Indices for Detecting Mild Airflow Obstruction

Surya P Bhatt; Nirav R Bhakta; Carla G Wilson; Christopher B Cooper; Igor Barjaktarevic; Sandeep Bodduluri; Young-Il Kim; Michael Eberlein; Prescott G Woodruff; Frank C Sciurba; Peter J Castaldi; MeiLan K Han; Mark T Dransfield; Arie Nakhmani

doi:10.1038/s41598-018-35930-2

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New Spirometry Indices for Detecting Mild Airflow Obstruction

Journal article

Open access

Peer reviewed

New Spirometry Indices for Detecting Mild Airflow Obstruction

Surya P Bhatt, Nirav R Bhakta, Carla G Wilson, Christopher B Cooper, Igor Barjaktarevic, Sandeep Bodduluri, Young-Il Kim, Michael Eberlein, Prescott G Woodruff, Frank C Sciurba, …

Scientific reports, Vol.8(1), 17484

11/30/2018

DOI: 10.1038/s41598-018-35930-2

PMCID: PMC6269456

PMID: 30504791

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https://doi.org/10.1038/s41598-018-35930-2View

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Abstract

The diagnosis of chronic obstructive pulmonary disease (COPD) relies on demonstration of airflow obstruction. Traditional spirometric indices miss a number of subjects with respiratory symptoms or structural lung disease on imaging. We hypothesized that utilizing all data points on the expiratory spirometry curves to assess their shape will improve detection of mild airflow obstruction and structural lung disease. We analyzed spirometry data of 8307 participants enrolled in the COPDGene study, and derived metrics of airflow obstruction based on the shape on the volume-time (Parameter D), and flow-volume curves (Transition Point and Transition Distance). We tested associations of these parameters with CT measures of lung disease, respiratory morbidity, and mortality using regression analyses. There were significant correlations between FEV /FVC with Parameter D (r = -0.83; p < 0.001), Transition Point (r = 0.69; p < 0.001), and Transition Distance (r = 0.50; p < 0.001). All metrics had significant associations with emphysema, small airway disease, dyspnea, and respiratory-quality of life (p < 0.001). The highest quartile for Parameter D was independently associated with all-cause mortality (adjusted HR 3.22,95% CI 2.42-4.27; p < 0.001) but a substantial number of participants in the highest quartile were categorized as GOLD 0 and 1 by traditional criteria (1.8% and 33.7%). Parameter D identified an additional 9.5% of participants with mild or non-recognized disease as abnormal with greater burden of structural lung disease compared with controls. The data points on the flow-volume and volume-time curves can be used to derive indices of airflow obstruction that identify additional subjects with disease who are deemed to be normal by traditional criteria.

Comorbidity

Severity of Illness Index

Pulmonary Disease, Chronic Obstructive - diagnosis

Prognosis

Humans

Middle Aged

Airway Obstruction - diagnosis

Airway Obstruction - physiopathology

Male

Tomography, X-Ray Computed

Pulmonary Disease, Chronic Obstructive - physiopathology

Forced Expiratory Volume

Vital Capacity

Image Processing, Computer-Assisted

Spirometry - methods

Female

Aged

Respiratory Function Tests

Odds Ratio

Details

Title: Subtitle: New Spirometry Indices for Detecting Mild Airflow Obstruction
Creators: Surya P Bhatt - UAB Lung Imaging Core, University of Alabama at Birmingham, Birmingham, AL, 35294, USA. sbhatt@uabmc.edu
Nirav R Bhakta - Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University California San Francisco, San Francisco, CA, 94143, USA
Carla G Wilson - Department of Biostatistics and Bioinformatics, National Jewish Health, Denver, CO, 80206, USA
Christopher B Cooper - Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University California Los Angeles, Los Angeles, CA, 90095, USA
Igor Barjaktarevic - Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University California Los Angeles, Los Angeles, CA, 90095, USA
Sandeep Bodduluri - UAB Lung Imaging Core, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
Young-Il Kim - Department of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
Michael Eberlein - Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa Hospital, Iowa City, IA, 52242, USA
Prescott G Woodruff - Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University California San Francisco, San Francisco, CA, 94143, USA
Frank C Sciurba - Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
Peter J Castaldi - Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
MeiLan K Han - Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, 48109, USA
Mark T Dransfield - UAB Lung Imaging Core, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
Arie Nakhmani - Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
Resource Type: Journal article
Publication Details: Scientific reports, Vol.8(1), 17484
DOI: 10.1038/s41598-018-35930-2
PMID: 30504791
PMCID: PMC6269456
NLM abbreviation: Sci Rep
ISSN: 2045-2322
eISSN: 2045-2322
Grant note: U01 HL089856 / NHLBI NIH HHS K24 HL140108 / NHLBI NIH HHS U01 HL089897 / NHLBI NIH HHS K23 HL133438 / NHLBI NIH HHS U01 HL128952 / NHLBI NIH HHS R01 HL089897 / NHLBI NIH HHS P30 DK054759 / NIDDK NIH HHS K24 HL137013 / NHLBI NIH HHS
Language: English
Date published: 11/30/2018
Academic Unit: Pulmonary, Critical Care, and Occupational Medicine; Internal Medicine
Record Identifier: 9984094372902771

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