Abstract
Introduction: The goal of asthma management is to achieve optimal asthma control. Dysfuctional breathing patterns are common in asthma. However breathing patterns are primarly assessed indirectly via Nijmegen questionnaire (NQ).
Aim: To examine whether quantifiable components of breathing patterns are associated with levels of asthma control and NQ scores.
Methods: Structured Light Plethysmography was used to record breathing patterns for 5 minutes in adults with mild to severe asthma. Mean respiratiry rate (RR), inspiration time over expiration time (Ti/Te), ribcage displacement over abdominal displacement (RC/AB) and within-individiual variability (CoV%) were calculated. Asthma control was asessed using Asthma Control Questionnaire (ACQ) and dysfuctional breathing via NQ. Relationships between outcomes were sought.
Results: 122 adults with asthma (75 females) with mean age (SD) 44.75 years (15.98), mean BMI 25.74 kg/m2 (3.95) on GINA Step 3 to 4 (73%) or Step 2 treatment were recruited. 59 patients had ACQ<0.75 and 59 patients had NQ≥10. Binary multiple logistic regression showed poor prediction of ACQ(R2:0.09) when mean RR, Ti/Te and RC/AB were used whereas CoV% of these variables predicted poor asthma control (R2:0.45) with all predictors having significant odds ratios (p<0.01). The area under the ROC curve (AUC) of the model including CoV% of breathing components for predciting asthma control was 0.895 (95%CI:0.839-0.951). Similar results were found for predcitions of NQ with the AUC being 0.791 (95%CI:0.708-0.873).
Conclusion: High variability of quantified elements of breathing patterns can predict lower asthma control and presence of breathing pattern disorders.
Footnotes
Cite this article as: European Respiratory Journal 2019; 54: Suppl. 63, PA5038.
This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).
- Copyright ©the authors 2019