Will recording of lung function fluctuation open the door to internet-guided treatment of asthma?

What long-term changes in lung function can tell us about asthma control

Asthma severity is typically classified according to lung function, but asthma control in relation to lung function is often harder to define. In this paper, we will review how lung function measured at rest, as well as over time, relates to asthma control. We will explore not only conventional lung function as measured by spirometry, such as peak expiratory flow and forced expiratory volume in 1 s, but also more sophisticated measurements of peripheral airway function related to respiratory system impedance and ventilation heterogeneity. In particular, we will review the emerging area of assessing the fluctuation of lung function over time and how it may correlate to both past and future asthma control.

Detection of exacerbations in asthma based on electronic diary data: results from the 1-year prospective BIOAIR study

BACKGROUND

Objective measures are required that may be used as a proxy for exacerbations in asthma. The aim was to determine the sensitivity and specificity of electronic diary data to detect severe exacerbations (SEs) of asthma. A secondary aim was to identify phenotypic variables associated with a higher risk of exacerbation.

METHODS

In the BIOAIR study, 169 patients with asthma (93 severe (SA); 76 mild to moderate (MA)) recorded lung function, symptoms and medication use in electronic diaries for 1 year. Data were analysed using receiver-operator characteristics curves and related to physician-diagnosed exacerbations. Medical history and baseline clinical data were used to assess risk of exacerbation.

RESULTS

Of 122 physician-diagnosed exacerbations, 104 occurred in the SA group (1.1 per patient/year), 18 in the MA group (0.2 per patient/year) and 63 were severe using American Thoracic Society/European Respiratory Society criteria. During exacerbations, peak expiratory flow (PEF) and forced expiratory volume in 1 s significantly decreased, whereas day and night symptoms significantly increased. An algorithm combining a 20% decrease in PEF or a 20% increase in day symptoms on 2 consecutive days was able to detect SEs with 65% sensitivity and 95% specificity. The strongest risk factors for SEs were low Asthma Control Questionnaire score, sputum eosinophils ≥ 3%, body mass index >25 and low quality of life (St George's Respiratory Questionnaire), with ORs between 3.61 and 2.22 (p<0.05).

CONCLUSIONS

Regular electronic monitoring of PEF and asthma symptoms provides an acceptable sensitivity and specificity for the detection of SEs and may be suitable for personal internet-based monitoring of asthma control.