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Ratio of Maximal Inspiratory to Expiratory Flow Aids in the Separation of COPD from Asthma

Research output: Contribution to journalArticlepeer-review

Abstract

Patients who have chronic obstructive pulmonary disease (COPD) and bronchial asthma (BA) share symptoms such as, dyspnoea, cough and wheeze. Differentiating these diseases in the ambulatory setting can be challenging especially in older adult smokers who are being treated with a variety of medications. The objective of this study was to test the value of adding a maximal inspiratory manoeuvre to basic spirometry to differentiate COPD and BA. One hundred forty-three COPD patients and 142 BA patients had measurements of maximal inspiratory and expiratory flow during routine spirometry. Parameters from these tests were used to assess diagnostic accuracy using receiver-operating characteristic (ROC) analyses followed by logistic regression. The association of two independent parameters were analyzed using linear regression analyses. Results show that forced expiratory volume in one second/forced vital capacity (FEV1/FVC%) <62.4 was the best independent predictor to diagnose COPD. The combination of FEV1/FVC% <62.4 and the ratio of peak inspiratory flow/maximal expiratory flow at 50% FVC (PIF/MEF50) >3.06 significantly predicted COPD. Post-test probability for prediction of COPD was 82.0% when patients had both parameters. When asthmatic patients with a smoking history were compared with COPD patients, FEV1/FVC% <63.4 and PIF/MEF50 >3.29 were both independent predictors of COPD. The post-test probability for COPD was 94.4% when patients had both parameters. The association between FEV1/FVC% and PIF/MEF50 was significantly different between COPD and BA. In conclusion, the addition of the maximal inspiratory effort to routine pulmonary function measurements provides a simple test to help differentiate COPD and BA.

Original languageEnglish
Pages (from-to)230-239
Number of pages10
JournalCOPD: Journal of Chronic Obstructive Pulmonary Disease
Volume17
Issue number3
DOIs
Publication statusPublished - 03-05-2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Pulmonary and Respiratory Medicine

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