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Showing results for "lung disease preterm"
Research
The next generation of impact in cystic fibrosisLung damage in children with CF occurs much earlier than previously thought, and proving this is related to the decline that occurs later will create new paradigms for prevention and treatment.
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Factors influencing participation in home, school, and community settings by 6- to 9-year-old children born preterm: a qualitative descriptive studyThere is no published information on preterm children's activities and participation during middle childhood, a time when growth and development are characterised by increasing motor, reasoning, self-regulation, social and executive functioning skills. This study explored the health, activities and participation of children born very preterm during middle childhood (6-9 years) from the perspectives of their parents.
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Nasal airway epithelial repair after very preterm birthNasal epithelial cells from very preterm infants have a functional defect in their ability to repair beyond the first year of life, and failed repair may be associated with antenatal steroid exposure.
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Smoking during pregnancy, vitamin C supplementation, and infant respiratory healthThis article discusses the merits and potential shortcomings of a study reported previously showing that giving Vitamin C to women who smoked during...
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Expression of bronchodilator response using forced oscillation technique measurements: absolute versus relativeExpression of bronchodilator response using forced oscillation technique measurements: absolute versus relative
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End-inspiratory molar mass step correction for analysis of infant multiple breath washout testsWe aimed to evaluate the use of the EIMM-step method in a broad range of infants.
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Child health a focus in national research grantsThe Kids Research Institute Australia researchers have been awarded more than $8 million in prestigious project grants from the NHMRC.
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Technical standards for respiratory oscillometryThe aim of the task force was to provide technical recommendations regarding oscillometry measurement
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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.