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Research
Does machine learning have a role in the prediction of asthma in children?Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value.
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The PELICAN (Prematurity's Effect on the Lungs In Children and Adults Network) ERS Clinical Research Collaboration: understanding the impact of preterm birth on lung health throughout lifeAn estimated 15 million babies (∼11%) are born preterm each year (before 37 weeks of gestation), the rates of which are increasing worldwide. Enhanced perinatal care, including antenatal corticosteroids, postnatal surfactant and improved respiratory management, have markedly improved survival outcomes since the 1990s, particularly for babies born very preterm (<32 weeks gestation). However, long-term pulmonary sequelae are frequent in preterm survivors and ongoing clinical management is often required.
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Reduced forced vital capacity in Aboriginal Australians: Biology or missing evidence?This editorial article addresses chronic obstructive pulmonary disease and lung function testing in Aboriginal Australians.
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ERS technical standard on bronchial challenge testing: General considerations and performance of methacholine challenge testsThis international task force report updates general considerations for bronchial challenge testing and the performance of the methacholine challenge test.
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Age- and height-based prediction bias in spirometry reference equationsPrediction bias in spirometry reference equations can arise from combining equations for different age groups,...
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Characterisation of lung function trajectories and associated early-life predictors in an Australian birth cohort studyThere is growing evidence that lung function in early-life predicts later lung function. Adverse events over the lifespan might influence an individual’s lung function trajectory, resulting in poor respiratory health. The aim of this study is to identify early-life risk factors and their impact on lung function trajectories to prevent long-term lung impairments.
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Daytime sleepiness and emotional and behavioral disturbances in Prader-Willi syndromeIndividuals with Prader-Willi syndrome (PWS) often have excessive daytime sleepiness and emotional/behavioral disturbances. The objective of this study was to examine whether daytime sleepiness was associated with these emotional/behavioral problems, independent of nighttime sleep-disordered breathing, or the duration of sleep.
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Quality of life is poorly correlated to lung disease severity in school-aged children with cystic fibrosisThere is no data exclusively on the relationship between health-related quality-of-life (HRQOL) and lung disease severity in early school-aged children with cystic fibrosis (CF). Using data from the Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF) we assessed the relationships between HRQOL, lung function and structure.
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Methods used to evaluate the immediate effects of airway clearance techniques in adults with cystic fibrosis: A systematic review and meta-analysisThis review reports on methods used to evaluate airway clearance techniques (ACT) in adults with CF and examined data for evidence of any effect. Sixty-eight studies described ACT in adequate detail and were included in this review.
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The EU Child Cohort Network’s core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variablesThe Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables.