Nutrition and metabolism have been the topic of extensive scientific research in chronic obstructive pulmonary disease (COPD) but clinical awareness of the impact dietary habits, nutritional status and nutritional interventions may have on COPD incidence, progression and outcome is limited. A multidisciplinary Task Force was created by the European Respiratory Society to deliver a summary of the evidence and description of current practice in nutritional assessment and therapy in COPD, and to provide directions for future research. Task Force members conducted focused reviews of the literature on relevant topics, advised by a methodologist. It is well established that nutritional status, and in particular abnormal body composition, is an important independent determinant of COPD outcome. The Task Force identified different metabolic phenotypes of COPD as a basis for nutritional risk profile assessment that is useful in clinical trial design and patient counselling. Nutritional intervention is probably effective in undernourished patients and probably most when combined with an exercise programme. Providing evidence of costeffectiveness of nutritional intervention is required to support reimbursement and thus increase access to nutritional intervention. Overall, the evidence indicates that a well-balanced diet is beneficial to all COPD patients, not only for its potential pulmonary benefits, but also for its proven benefits in metabolic and cardiovascular risk. @ERSpublications Metabolism and nutrition: shifting paradigms in COPD management

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Chavannes, N. H. (2013). Integrated disease management interventions for patients with chronic obstructive pulmonary disease. Cochrane Database of Systematic Reviews, (10), [009437].

Background Smartphone-based contact tracing apps can contribute to reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased. Objective The primary objective of our study is to determine the potential uptake of a contact tracing app in the Dutch population, depending on the characteristics of the app. Methods A discrete choice experiment was conducted in a nationally representative sample of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate population average and individual-level preferences using a mixed logit model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into the sample as well as subgroup-specific contact tracing app adoption rates. Results The predicted app adoption rates ranged from 59.3% to 65.7% for the worst and best possible contact tracing app, respectively. The most realistic contact tracing app had a predicted adoption of 64.1%. The predicted adoption rates strongly varied by age group. For example, the adoption rates of the most realistic app ranged from 45.6% to 79.4% for people in the oldest and youngest age groups (ie, ≥75 years vs 15-34 years), respectively. Educational attainment, the presence of serious underlying health conditions, and the respondents’ stance on COVID-19 infection risks were also correlated with the predicted adoption rates but to a lesser extent. Conclusions A secure and privacy-respecting contact tracing app with the most realistic characteristics can obtain an adoption rate as high as 64% in the Netherlands. This exceeds the target uptake of 60% that has been formulated by the Dutch government. The main challenge will be to increase the uptake among older adults, who are least inclined to install and use a COVID-19 contact tracing app.