Hulme K.M.,University of Sydney |
Salome C.M.,University of Sydney |
Salome C.M.,Woolcock Institute of Medical Research Sydney |
Salome C.M.,Cooperative Research Center for Asthma |
And 15 more authors.
Respiratory Physiology and Neurobiology | Year: 2013
It is unclear whether the failure to reverse bronchoconstriction with deep inspiration (DI) in asthma is due to reduced maximal dilatation of the DI. We compared the effect of different DI volumes on maximal dilatation and reversal of bronchoconstriction in nine asthmatics and ten non-asthmatics.During bronchoconstriction, subjects took DI to 40%, 70% and 100% inspiratory capacity, on separate days. Maximal dilatation was measured as respiratory system resistance (Rrs) at end-inspiration and residual dilatation as Rrs at end-expiration, both expressed as percent of Rrs at end-tidal expiration prior to DI.DI volume was positively associated with maximal dilatation in non-asthmatics (ANOVA p= 0.055) and asthmatics (p= 0.023). DI volume was positively associated with residual dilatation in non-asthmatics (p= 0.004) but not in asthmatics (p= 0.53). The degree of maximal dilatation independently predicted residual dilatation in non-asthmatics but not asthmatics.These findings suggest that the failure to reverse bronchoconstriction with DI in asthma is not due to reduced maximal dilatation, but rather due to increased airway narrowing during expiration. © 2013 Elsevier B.V.
PubMed | Woolcock Institute of Medical Research Sydney
Type: Journal Article | Journal: Thorax | Year: 2011
In the last few years, there has been considerable debate on the use of threshold criteria for the diagnosis of obstructive lung disease based on FEV(1) and FEV(1)/FVC ratio. It has been argued that a fixed ratio and fixed percentage criterion result in misclassification. The author argues that this critique is based on a false presumption about the validity of reference equations as a criterion for normality. The flaw lies in the methods used to derive reference equations, which involve arbitrary and circular criteria for exclusion of some members of the population, use potentially non-representative reference populations and include predictive variables that are really risk factors for disease or for adverse outcomes of disease. The author argues for a new interpretative approach for the use of lung function data in clinical practice based on prognostic equations analogous to the Framingham cardiovascular risk factor equations. These interpretative equations should be based on data from cohort studies and randomised controlled trials, rather than cross-sectional studies, and if properly formulated, will prove to be valuable aids to clinical decision making.