Predicting parameters of airway dynamics generated from inspiratory and expiratory plethysmographic airway loops, differentiating subtypes of chronic obstructive diseases

Abstract

BackgroundThe plethysmographic shift volume–flow loop (sRaw-loop) measured during tidal breathing allows the determination of several lung function parameters such as the effective specific airway resistance (sReff), calculated from the ratio of the integral of the resistive aerodynamic specific work of breathing (sWOB) and the integral of the corresponding flow–volume loop. However, computing the inspiratory and expiratory areas of the sRaw-loop separately permits the determination of further parameters of airway dynamics. Therefore, we aimed to define the discriminating diagnostic power of the inspiratory and expiratory sWOB (sWOBin, sWOBex), as well as of the inspiratory and expiratory sReff(sReffINand sReffEX), for discriminating different functional phenotypes of chronic obstructive lung diseases.MethodsReference equations were obtained from measurement of different databases, incorporating 194 healthy subjects (35 children and 159 adults), and applied to a collective of 294 patients with chronic lung diseases (16 children with asthma, aged 6–16 years, and 278 adults, aged 17–92 years). For all measurements, the same type of plethysmograph was used (Jaeger Würzburg, Germany).ResultsBy multilinear modelling, reference equations of sWOBin, sWOBex, sReffINand sReffEXwere derived. Apart from anthropometric indices, additional parameters such as tidal volume (VT), the respiratory drive (P0.1), measured by means of a mouth occlusion pressure measurement 100 ms after inspiration and the mean inspiratory flow (VT/TI) were found to be informative. The statistical approach to define reference equations for parameters of airway dynamics reveals the interrelationship between covariants of the actual breathing pattern and the control of breathing.ConclusionsWe discovered that sWOBin, sWOBex, sReffINand sReffEXare new discriminating target parameters, that differentiate much better between chronic obstructive diseases and their subtypes, especially between chronic obstructive pulmonary disease (COPD) and asthma–COPD overlap (ACO), thus strengthening the concept of precision medicine.