To determine whether quantitative computed tomography (qCT)-derived metrics of pulmonary vascular volume distribution could distinguish chronic obstructive pulmonary disease (COPD) subjects with associated pulmonary hypertension (PH) from those without and to characterize associations of these measurements with clinical and physiological characteristics and outcomes. We collected retrospective CT, pulmonary hemodynamic, clinical, and outcomes data from subjects with COPD and right-heart catheterization-confirmed PH (PH-COPD) and control subjects with COPD but without PH. We measured the volumes of pulmonary vessels < 5 and >10 mm in cross-sectional area as a percentage of total pulmonary vascular volume (qCT-derived volume of pulmonary vessels < 5 mm in cross-sectional area as a volume fraction of total pulmonary blood volume [BV5%] and qCT-derived volume of pulmonary vessels > 10 mm in cross-sectional area [BV10] as a volume fraction of total pulmonary blood volume [BV10%], respectively) using Functional Respiratory Imaging (FRI), an automated qCT platform, and compared them between PH and control arms and between subjects with mild-moderate PH and those with severe disease.
View Article and Find Full Text PDFBackground: Severe eosinophilic asthma (SEA) is characterised by elevated blood/sputum eosinophil counts and airway inflammation, which can lead to mucus plug-mediated airway obstruction, increased exacerbation frequency, declines in lung function, and death. Benralizumab targets the alpha-subunit of the interleukin-5 receptor found on eosinophils, leading to rapid and near complete eosinophil depletion. This is expected to result in reduced eosinophilic inflammation, reduced mucus plugging and improved airway patency and airflow distribution.
View Article and Find Full Text PDFAnnual average PM and NO were associated with airway inflammation as measured by FeNO in schoolchildren, adding new evidence that long-term exposure affects FeNO beyond the well-documented short-term effects.
View Article and Find Full Text PDFFractional exhaled nitric oxide ( ), a marker of allergic airway inflammation, is used in respiratory research and asthma clinical care; however, its trajectory with increasing age during childhood has not been well characterised. We examined longitudinally during a period of important somatic growth to describe trajectories across childhood and adolescence in healthy participants and evaluate clinical factors as potential determinants of trajectories. was collected at six visits over 8 years in a population-based cohort of 1791 schoolchildren without asthma (median age at entry 8.
View Article and Find Full Text PDFExhaled nitric oxide (FeNO) is an established respiratory biomarker with clinical applications in the diagnosis and management of asthma. Because FeNO depends strongly on the flow (exhalation) rate, early protocols specified that measurements should be taken when subjects exhaled at a fixed rate of 50 ml/s. Subsequently, multiple flow (or "extended") protocols were introduced which measure FeNO across a range of fixed flow rates, allowing estimation of parameters including C NO and C NO which partition the physiological sources of NO into proximal airway wall tissue and distal alveolar regions (respectively).
View Article and Find Full Text PDFThe fractional concentration of nitric oxide in exhaled breath (fe) is a biomarker of airway inflammation with applications in clinical asthma management and environmental epidemiology. fe concentration depends on the expiratory flow rate. Standard fe is assessed at 50 mL/sec, but "extended NO analysis" uses fe measured at multiple different flow rates to estimate parameters quantifying proximal and distal sources of NO in the lower respiratory tract.
View Article and Find Full Text PDFStat Appl Genet Mol Biol
August 2015
Recent results in Markov chain Monte Carlo (MCMC) show that a chain based on an unbiased estimator of the likelihood can have a stationary distribution identical to that of a chain based on exact likelihood calculations. In this paper we develop such an estimator for elliptically contoured distributions, a large family of distributions that includes and generalizes the multivariate normal. We then show how this estimator, combined with pseudorandom realizations of an elliptically contoured distribution, can be used to run MCMC in a way that replicates the stationary distribution of a likelihood based chain, but does not require explicit likelihood calculations.
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