The European respiratory journal : official journal of the European Society for Clinical Respiratory Physiology
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Airway obstruction and parenchymal destruction underlie phenotype and severity in chronic obstructive pulmonary disease (COPD). We aimed to predict, by clinical and pulmonary function data, the predominant type and severity of pathological changes quantitatively assessed by computed tomography (CT). Airway wall thickness (AWT-Pi10) and percentage of lung area with X-ray attenuation values <-950 HU (%LAA-950) were measured in 100 (learning set) out of 473 COPD outpatients undergoing clinical and functional evaluation. ⋯ A model based on forced expiratory volume in 1 s/vital capacity, functional residual capacity and purulent sputum predicted CT2 (r = 0.77; p<0.01). Classification of patients in the testing set obtained by model-predicted CT1 and CT2 reflected, according to correlations with clinical and functional variables, both COPD phenotype and severity. Multivariate models based on pulmonary function variables and sputum purulence classify patients according to overall severity and predominant phenotype of COPD as assessed quantitatively by CT.
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We analysed a cohort of patients with normotensive pulmonary embolism (PE) in order to assess whether combining echocardiography and biomarkers with the pulmonary embolism severity index (PESI) improves the risk stratification in comparison to the PESI alone. The PESI was calculated in normotensive patients with PE who also underwent echocardiography and assays of cardiac troponin I and brain natriuretic peptide. 30-day adverse outcome was defined as death, recurrent PE or shock. 529 patients were included, 25 (4.7%, 95% CI 3.2-6.9%) had at least one outcome event. ⋯ In multivariate analysis, the PESI (class III-IV versus I-II, OR 3.1, 95% CI 1.2-8.3; class V versus I-II, OR 5.5, 95% CI 1.5-25.5 and echocardiography (right ventricular/left ventricular ratio, OR (for an increase of 0.1) 1.3, 95% CI 1.1-1.5) were independent predictors of an adverse outcome. In patients with normotensive PE, biomarkers and echocardiography provided additional prognostic information to the PESI.
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Clinical trials for the treatment of cystic fibrosis (CF) lung disease are important to test and optimise new therapeutic interventions. To evaluate the effect of these interventions, sensitive and accurate outcome measures are needed. The most commonly used endpoints are spirometric variables such as the forced expiratory volume in 1 s and respiratory tract exacerbations. ⋯ A large body of evidence has been produced to validate the use of chest CT as a primary endpoint to study CF lung disease. However, before chest CT can be used in clinical trials, it has to be recognised as a validated surrogate endpoint by regulatory agencies. The aim of this review is to summarise what is currently known about the use of chest CT as surrogate endpoint in clinical trials in CF.
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Due to climate change and other factors, air pollution patterns are changing in several urbanised areas of the world, with a significant effect on respiratory health both independently and synergistically with weather conditions; climate scenarios show Europe as one of the most vulnerable regions. European studies on heatwave episodes have consistently shown a synergistic effect of air pollution and high temperatures, while the potential weather-air pollution interaction during wildfires and dust storms is unknown. ⋯ The underlying mechanisms of all these interactions are not well known; the health consequences vary from decreases in lung function to allergic diseases, new onset of diseases, exacerbation of chronic respiratory diseases, and premature death. These multidimensional climate-pollution-allergen effects need to be taken into account in estimating both climate and air pollution-related respiratory effects, in order to set up adequate policy and public health actions to face both the current and future climate and pollution challenges.
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The aim of this study was to determine the prevalence, characteristics and outcomes of patients with unclassifiable interstitial lung disease (ILD) and to develop a simple method of predicting disease behaviour. Unclassifiable ILD patients were identified from an ongoing longitudinal cohort. Unclassifiable ILD was diagnosed after a multidisciplinary review did not secure a specific ILD diagnosis. ⋯ Unclassifiable ILD had longer survival rates when compared to IPF on adjusted analysis (hazard ratio 0.62, p = 0.04) and similar survival compared to non-IPF ILDs (hazard ratio 1.54, p = 0.12). Independent predictors of survival in unclassifiable ILD included diffusion capacity of the lung for carbon monoxide (p = 0.001) and a radiological fibrosis score (p = 0.02). Unclassifiable ILD represents approximately 10% of ILD cases and has a heterogeneous clinical course, which can be predicted using clinical and radiological variables.