Literature DB >> 16381616

A proposed curvilinearity index for quantifying airflow obstruction.

Chang-Jiang Zheng1, Alexander B Adams, Michael P McGrail, John J Marini, Ian A Greaves.   

Abstract

BACKGROUND: Though forced expiratory volume in the first second (FEV(1)) is the primary indicator of airway obstruction, curvilinearity in the expiratory flow-volume curve is used to support the quantitative assessment of obstruction via FEV(1). Currently there is no available index to quantify a pathological contour of curvilinearity. STUDY
PURPOSE: We propose a "curvature" index (k(max)) and compare FEV(1) values to the index with a sequential sample of spirometry data.
METHODS: The hyperbolic function b(0)Q + b(1)Q V + b(2)V = 1 (in which Q = flow rate, V = volume, and b(0), b(1), and b(2) are estimated from the patient's flow-volume data) is fit to a fixed segment of the descending phase of the expiratory flow-volume curve. A previously developed biomechanical interpretation of this relationship associates the coefficient b(1) with the rate of airway-resistance-increase as exhaled volume increases. A global curvature index k(max)=b(1)/2(b(0)b(2)+b(1)) is defined to quantify the curvilinearity phenomenon. We used statistics software to determine the k(max) of spirometry data from 67 sequential patients, and to determine the relationship of k(max) to FEV(1).
RESULTS: Individual k(max) estimates appeared to correspond well with the degree of curvilinearity observed and were related in an exponential manner to FEV(1).
CONCLUSIONS: We defined a curvature index to quantify the curvilinearity phenomenon observed in the expiratory limb of flow-volume loops from patients with obstructive lung disease. This index uses data from a major segment of the flow-volume curve, and our preliminary data indicate an exponential relationship with FEV(1). This new index allows the putative association between curvilinearity and obstructive lung disease to be examined quantitatively in clinical practice and future studies.

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Mesh:

Year:  2006        PMID: 16381616

Source DB:  PubMed          Journal:  Respir Care        ISSN: 0020-1324            Impact factor:   2.258


  8 in total

1.  Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease.

Authors:  Sandeep Bodduluri; Arie Nakhmani; Joseph M Reinhardt; Carla G Wilson; Merry-Lynn McDonald; Ramaraju Rudraraju; Byron C Jaeger; Nirav R Bhakta; Peter J Castaldi; Frank C Sciurba; Chengcui Zhang; Purushotham V Bangalore; Surya P Bhatt
Journal:  JCI Insight       Date:  2020-07-09

2.  Baseline spirometry parameters as predictors of airway hyperreactivity in adults with suspected asthma.

Authors:  Michael Peled; David Ovadya; Jennifer Cohn; Michael J Segel; Amir Onn; Lior Seluk; Teet Pullerits
Journal:  BMC Pulm Med       Date:  2021-05-06       Impact factor: 3.317

Review 3.  Spirometric indices of early airflow impairment in individuals at risk of developing COPD: Spirometry beyond FEV1/FVC.

Authors:  Daniel Hoesterey; Nilakash Das; Wim Janssens; Russell G Buhr; Fernando J Martinez; Christopher B Cooper; Donald P Tashkin; Igor Barjaktarevic
Journal:  Respir Med       Date:  2019-08-09       Impact factor: 3.415

Review 4.  Diagnosis and early detection of COPD using spirometry.

Authors:  David P Johns; Julia A E Walters; E Haydn Walters
Journal:  J Thorac Dis       Date:  2014-11       Impact factor: 2.895

5.  Subjective and Objective Assessments of Flow-Volume Curve Configuration in Children and Young Adults.

Authors:  Daniel J Weiner; Erick Forno; Leanna Sullivan; Gabriel A Weiner; Geoffrey Kurland
Journal:  Ann Am Thorac Soc       Date:  2016-07

6.  New Spirometry Indices for Detecting Mild Airflow Obstruction.

Authors:  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
Journal:  Sci Rep       Date:  2018-11-30       Impact factor: 4.379

7.  Improved spirometric detection of small airway narrowing: concavity in the expiratory flow-volume curve in people aged over 40 years.

Authors:  David P Johns; Aruneema Das; Brett G Toelle; Michael J Abramson; Guy B Marks; Richard Wood-Baker; E Haydn Walters
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2017-12-13

8.  A Novel Approach to the Identification of Compromised Pulmonary Systems in Smokers by Exploiting Tidal Breathing Patterns.

Authors:  Raj Rakshit; Anwesha Khasnobish; Arijit Chowdhury; Arijit Sinharay; Arpan Pal; Tapas Chakravarty
Journal:  Sensors (Basel)       Date:  2018-04-25       Impact factor: 3.576

  8 in total

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