Bronchodilator Responsiveness in Different Ventilatory Patterns

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OT Ehondor
OG Ojeh-Oziegbe

Abstract

Background: Bronchodilator response varies across ventilatory impairments, influencing diagnosis and treatment decisions. While obstructive lung diseases like asthma and COPD often show reversibility, the response in restrictive and mixed impairments remains unclear. In resource-limited settings, spirometry with bronchodilator testing is a valuable tool for distinguishing these conditions. The objective of the study was to evaluate bronchodilator response in obstructive, restrictive, and mixed ventilatory impairments and its clinical implications.


Methods: This study analyzed spirometric parameters (FEV₁% and PEF%) before and after bronchodilator administration in individuals with different ventilatory patterns. Reversibility was assessed by comparing pre- and post-bronchodilator values, identifying significant changes within each impairment group.


Results: The obstructive group exhibited significant improvements in FEV₁% and PEF%, confirming bronchodilator reversibility in asthma and mild COPD. In contrast, restrictive and mixed impairments showed minimal or negative responses, suggesting limited therapeutic benefit. The restrictive group’s decline in PEF% and FEV₁% likely reflects parenchymal or chest wall limitations rather than reversible airway obstruction. The mixed pattern demonstrated the least response, highlighting its complex interplay between obstruction and restriction. Normal and obstructive groups had the highest reversibility, while restrictive cases showed the lowest.


Conclusion: Spirometry with bronchodilator testing is an effective, low-cost diagnostic tool for distinguishing ventilatory impairments, particularly in resource-limited settings. The findings reinforce the limited role of bronchodilators in restrictive lung diseases and emphasize the need for alternative treatment strategies. Future research should explore long-term bronchodilator responsiveness in restrictive and mixed impairments, incorporating biomarkers such as eosinophil counts or FeNO to improve personalized treatment approaches.


 

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ORIGINAL RESEARCH