Cindy Thamrin

Rationale: Strategies for asthma management need better tools to identify risk of exacerbations. In this prospective observational study, we investigated day-to-day variability of lung mechanics, measured using home telemonitored oscillometry, by examining relationships between current symptom control and future risk of exacerbation in asthma patients taking medium-/high-dose treatment, regardless of their level of asthma control. Methods: Participants underwent ≥24 weeks of telemonitoring during stable or stepped-down treatment, with once-daily self-recording of symptoms, and oscillometry (Resmon Pro Diary, Restech Srl, Milan, Italy). The 5-item Asthma Control Questionnaire and exacerbations were captured via weekly telephone calls. Mean inspiratory resistance and reactance at 5 Hz (R _insp and X _insp ), and their standard deviation and coefficient of variation over 7-day windows, were calculated; their associations with current symptom control were examined using linear mixed modelling, and their capacity to predict exacerbations in the following week was examined using logistic regression and receiver-operator characteristic (ROC) analysis, and conditional probability methods. Results: Data from 30 participants were analysed (19 female; mean± sd age 59±13 years, body mass index 30.1±6.6 kg·m ^-2 , percent predicted forced expiratory volume in 1 s 73.7±25.0), with mean monitoring adherence of 83.9±13.1%, and with 16 exacerbations recorded from 12 participants. Only X _insp was a significant predictor of current symptom control (p<0.001). Coefficient of variation of inspiratory resistance was the most accurate in predicting future exacerbations (area under the ROC curve (AUC)=0.664, p<0.001); accuracy was further enhanced using individual conditional probability (AUC=0.836, p<0.001). Conclusion: This proof-of-concept study shows that daily telemonitoring of oscillometry is useful for assessing current symptom control and future risk of exacerbations in asthma patients taking medium-/high-dose treatment.

Sensor errors that elevated values of N₂ concentration in commercial multiple-breath washout (MBW) devices resulted in errors in calculated parameters including S_cond and S_acin. We examined the mechanism of the change in values produced by these errors and explored the appropriateness of the calculation of S_cond and S_acin. This work serves to emphasize that the current algorithm in use is appropriate for the calculation of S_cond and S_acin.

Rationale: Poor adherence with asthma controller medication contributes to worse symptom control and increased exacerbation risk. Adherence is often expressed as the mean proportion of prescribed doses taken over a period of 6–12 months. New metrics may capture individual day-to-day variability patterns linked with distinct clinical outcomes. Objectives: To test the hypotheses that novel time- and dose-based adherence variability metrics offer independent value to mean adherence in identifying distinct adherence patterns that are associated with symptom control (Asthma Control Test [ACT] score) and exacerbation risk, using electronically recorded medication data from a 6-month cluster randomized trial examining the effect of inhaler reminders on adherence. Methods: Adherence metrics were calculated from the first 2 months (Months 0–2) of the study period. In addition to mean adherence (percentage prescribed puffs/day taken), we examined novel metrics, including time adherence area under the curve (T-AUC), reflecting cumulative gaps in adherence over time; entropy, reflecting disorder in the ways in which a patient changed their medication dose adherence from day to day; and standard deviation of the percentage prescribed puffs/day taken. Dominant metrics identified from factor analysis were included in hierarchical clustering analysis. We compared the resultant clusters in terms of outcomes over Months 2–6 and exacerbation risk over the entire study period. Results: Two factors explained >65% of the total variance in adherence, primarily driven by T-AUC and entropy. Two main patient clusters based on their adherence metrics were identified: cluster 1 (high time adherence, n = 75) had better T-AUC (i.e., fewer gaps between medication-taking days) than cluster 2 (low time adherence, n = 23). Though both clusters had similar symptom control at 2 months, cluster 1 showed less subsequent decline in ACT over Months 2–6 (median [interquartile range] change in ACT score: 1 [−1 to 4] vs. −2 [−3.75 to 0.75]; P = 0.012), and had better symptom control at 6 months (ACT score: 20 [17–23] vs. 17 [15–20]; P = 0.034). There were no significant differences between the clusters in terms of proportion of exacerbators or time to exacerbation. Conclusions: Novel metrics showed that low time adherence was associated with greater risk of decline in asthma symptom control. Adherence patterns may exhibit “memory” relevant to future clinical status, warranting validation in a larger dataset.

Introduction: The multiple breath nitrogen washout (MBNW) test provides important clinical information in obstructive airways diseases. Recently, a significant cross-sensitivity error in the O₂and CO₂sensors of a widely used commercial MBNW device (Exhalyzer D, Eco Medics AG, Duernten, Switzerland) was detected, which leads to overestimation of N₂concentrations. Significant errors in functional residual capacity (FRC) and lung clearance index (LCI) have been reported in infants and children. This study investigated the impact in adults, and on additional important indices reflecting conductive (S_cond) and acinar (S_acin) ventilation heterogeneity, in health and disease.Methods: Existing MBNW measurements of 27 healthy volunteers, 20 participants with asthma and 16 smokers were reanalysed using SPIROWARE V 3.3.1, which incorporates an error correction algorithm. Uncorrected and corrected indices were compared using paired t-tests and Bland–Altman plots.Results: Correction of the sensor error significantly lowered FRC (mean difference 9%) and LCI (8–10%) across all three groups.S_condwas higher following correction (11%, 14% and 36% in health, asthma and smokers, respectively) with significant proportional bias.S_acinwas significantly lower following correction in the asthma and smoker groups, but the effect was small (2–5%) and with no proportional bias.Discussion: The O₂and CO₂cross-sensitivity sensor error significantly overestimated FRC and LCI in adults, consistent with data in infants and children. There was a high degree of underestimation ofS_condbut minimal impact onS_acin. The presence of significant proportional bias indicates that previous studies will require reanalysis to confirm previous findings and to allow comparability with future studies.

Recently, “Technical standards for respiratory oscillometry” was published, which reviewed the physiological basis of oscillometric measures and detailed the technical factors related to equipment and test performance, quality assurance and reporting of results. Here we present a review of the clinical significance and applications of oscillometry. We briefly review the physiological principles of oscillometry and the basics of oscillometry interpretation, and then describe what is currently known about oscillometry in its role as a sensitive measure of airway resistance, bronchodilator responsiveness and bronchial challenge testing, and response to medical therapy, particularly in asthma and COPD. The technique may have unique advantages in situations where spirometry and other lung function tests are not suitable, such as in infants, neuromuscular disease, sleep apnoea and critical care. Other potential applications include detection of bronchiolitis obliterans, vocal cord dysfunction and the effects of environmental exposures. However, despite great promise as a useful clinical tool, we identify a number of areas in which more evidence of clinical utility is needed before oscillometry becomes routinely used for diagnosing or monitoring respiratory disease.

There is strong evidence to support the addition of respiratory oscillometry to standard lung function testing. The key parameters are sensitive in identifying the presence and severity of airways disease [1], and clinically meaningful cut-offs have been established to identify bronchodilator response [2] and bronchial hyperresponsiveness [3–6] independent of spirometry. While clinical uptake is increasing with the availability of commercial devices, oscillometry is yet to be widely adopted as a standard test. This has been in part due to a lack of standardisation in equipment specifications and inconsistent terminology, but also human-related factors such as measurement protocols and objective quality control. The recently published international technical standards [7] have partly addressed most of these issues, and the development of global reference equations is currently in progress. Nevertheless, there remains a strong need to develop standard methods to optimise measurement quality and operator competency.

Multiple-breath nitrogen washout (MBNW) is an emerging clinical test for assessing ventilation heterogeneity [1], often characteristically increased in asthma. MBNW indices both indicate and predict response to asthma treatment [2–4], and therefore may be an important tool for guiding treatment decisions [2]. Two established breathing protocols are currently in use: 1-L tidal volume (V_T) controlled breathing (CB) [5, 6] and unrestricted free breathing (FB) [7]. The CB protocol requires targeted V_T and respiratory rate, whereas the FB protocol encourages relaxed tidal breathing, making it more suitable for paediatrics [8]. Two recently published studies in healthy adults showed that indices of conductive and acinar ventilation heterogeneity (S_cond and S_acin, respectively) and, to a lesser extent, lung clearance index (LCI), were not comparable between breathing protocols [9, 10]. Importantly, differences between the protocols were dependent on the magnitude of ventilation heterogeneity. Thus, the assumption is that these effects would be amplified in disease, where ventilation heterogeneity is greater and clinical utility is most relevant. However, this has not been confirmed to date. We hypothesised that people with asthma, where ventilation heterogeneity is greater, would exhibit greater differences between the two protocols than the differences seen in healthy adults.