The study aimed to examine whether respiratory timing parameters and/ or individual TA movements could predict and classify levels of asthma control. The within-subject variability of breathing pattern components, such as RR, Ti/Te and RCampe/ABampe, was found to predict asthma control, but their absolute mean values did not. Based on these findings, the within-subject variability of breathing pattern components is suggested as a better indicator of asthma control than their mean values when measured in a single occasion. This may be because the within-subject variability can efficiently reflect changes in the natural behaviour of tidal breathing occurred in relation to asthma control. The importance of measuring the natural behaviour of breathing patterns has been previously highlighted as this reflects better the adaptability of the respiratory system occurred during symptomatic periods of asthma [19].
On the other hand, the limited variance we found in the absolute mean values of Ti/Te and RCampe/ABampe may have biased the asthma control prediction. Although the RR was found to be a significant predictor of asthma control, there was a lack of a linear relationship between mean RR and asthma control. For example, increased RR were not always associated with uncontrolled asthma. Lack of asthma control prediction using mean values of the examined breathing pattern components may be attributed to the presence of study’s confounders previously reported in other cross-sectional observational study designs [20, 21]. Examples of such confounders could be a postural effect, the patients’ asthma complexity, the underlying patients’ anxiety levels, and an effect of rescue medication usage prior to breathing pattern measurements. Some of these, such as posture and emotions, have been clearly suggested to affect absolute mean values of breathing pattern measurements [20,21,22], but the impact of asthma complexity and medication usage on breathing patterns is not clear yet.
Respiratory rate can be affected by different factors, and so there was no clear separation between the well-controlled and controlled groups for this parameter in our study. Asthma patients frequently have co-existing anxiety which can have an impact on the RR [23]. There is also a relationship between asthma and obesity [24], and it is well known that BMI can have an impact on asthma control and timing components of breathing patterns [25]. Although levels of anxiety were not assessed in our study, our study’s individuals with raised RR and well-controlled asthma were obese (BMI > 30 kg/m2). The normal RR found in individuals of the uncontrolled asthma group is unexplained, but could be due to the effect of rescue medication on RR. The participants were asked to state whether they had taken any type of asthma medication prior to breathing pattern measurements. No attempt was made to control the participants’ use of medication, they were just advised to take their medications as normal. It was established that all individuals had taken their controller medication as prescribed, but that patients with normal RR and uncontrolled asthma had additionally used rescue medication before attending the recording session. However, the impact of either short-acting or long-acting asthma medication on quantifiable breathing pattern components (both absolute or variability measurements) has not yet been established.
In addition, Raoufy et al. [15] have previously reported that the within-subject variability of Vt and breath cycle duration can differentiate patients with well-controlled asthma from those with uncontrolled asthma. Our findings are in agreement with Raoufy et al.’s work despite methodological differences, such as the method used to determine asthma control (National Asthma Education and Prevention program vs ACQ7-item), the breathing pattern recording time (60 min vs 5 min), the recording posture (supine vs sitting) and the equipment used to monitor breathing patterns (SLP vs RIP) at rest.
The optimal time for recording variability within breathing pattern parameters is not known in the literature. We measured within-subject variability over 5 min and found this was sufficient for making significant predictions of asthma control using respiratory rate, proportionality of respiratory phases, and TA motion. To the best of authors’ knowledge, the study presented here also provides for a first time specific cut-off points for the within-subject variability of the breathing pattern components, which differentiated well-controlled from uncontrolled asthma. However, more research is required to confirm the accuracy of our results in the future.
In addition, the different posture selected in our study compared to Raoufy et al. [15] did not seem to have an impact on the ability of within-subject variability of the breathing pattern components to predict asthma control. However, more research involving different postures, such as supine or standing, is required to check maintenance of the identified association between asthma control and within-subject variability of breathing pattern components.
Some limitations underlie this research. We did not include patients with partially controlled asthma (ACQ7-item score between 0.75 and 1.50) so that ACQ7-item score could be used as a binary outcome within the recruited sample. A causal or coincidental relationship between within-subject variability and asthma control could not be determined from our findings due to the selected study design. It is not known whether uncontrolled asthma preceded the increased within-subject variability of the breathing pattern components, or vice versa. However, we speculate that increased within-subject variability in the presence of uncontrolled asthma is likely to be the result of several changes of the respiratory system as previously proposed in the literature [26]. For example, dysfunctional breathing has been characterised as a change in the biomechanical and physiological components of breathing, resulting in intermittent or chronic respiratory symptoms, which can worsen asthma progress [26]. In any way, a future prospective cohort study is required to examine the exact nature of the relationship between the changes in quantifiable breathing pattern components and asthma control.