Recording and analysis of breathing patterns: a physiological marker in asthma management

This thesis explores the potential use of breathing patterns as a physiological marker in asthma management. The goal of asthma management is to achieve optimal asthma control, whose assessment currently involves the use of a combination of patient-related outcomes and established physiological markers. These asthma-related outcomes are also used to guide asthma treatment. To reduce patient burden and increase patient adherence, there is a need for supplemental markers that are minimally intrusive, do not rely on patients’ perception and, preferably, can be made outside specialist clinical centres. One such marker could be the breathing patterns, but little is known about their current role in asthma management. This research primarily aimed to explore the use of specific quantifiable breathing pattern components to predict asthma control, as well as their ability to respond to a physiotherapy breathing retraining programme. To meet these aims, three studies were conducted: a) an initial equipment validation study in healthy adults (n=50) to test the criterion-validity of Structured Light Plethysmography (SLP) prior to selecting a method for breathing pattern measurements in this research; b) a correlational study involving asthma patients (n=122) to establish if absolute measurements and/or within-individual variability of the examined breathing components could primarily predict asthma control and secondary be associated with other asthma-related outcomes used in asthma management; and c) a small responsiveness study involving asthma patients (n=6) to explore if breathing pattern components were affected by a physiotherapy breathing retraining programme. This research found that SLP is a valid and responsive technology to record breathing patterns in the sitting position, during resting breathing and immediately after exercise as compared to Respiratory Inductive Plethysmography. The within individual variability of the breathing components predicted asthma control, although their absolute measurements did not. Same results were found for the prediction of other asthma related outcomes, such as the presence of dysfunctional breathing. No firm conclusions could be drawn regarding their responsiveness to breathing retraining, but some consistent changes in the within-individual variability of breathing components were observed. Based on all findings, this research found that breathing pattern variability can be used as a supplemental physiological marker in asthma management