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Showing results for "lung disease preterm"

Aboriginal Community Research Assistant - Children's Lung Health

The Opportunity At The Kids Research Institute Australia, we are bringing together community, researchers, practitioners, policy makers and funders,

Research

Determinants of early-life lung function in African infants

To assess the determinants of early lung function in African infants.

Research

Metabolomics to predict asthma in children (MAP Study)

Childhood asthma begins as wheeze (a whistling sound produced by the airways during breathing) during pre­school age.

Research

ERS/ATS technical standard on interpretive strategies for routine lung function tests

Appropriate interpretation of pulmonary function tests (PFTs) involves the classification of observed values as within/outside the normal range based on a reference population of healthy individuals, integrating knowledge of physiological determinants of test results into functional classifications and integrating patterns with other clinical data to estimate prognosis.

Research

Bronchodilator responsiveness in children with asthma is not influenced by spacer device selection

Spacer device was not associated with clinically important differences in lung function following bronchodilator inhalation in children with asthma

Research

Expiratory flow limitation and breathing strategies in overweight adolescents during submaximal exercise

Young people who are overweight/obese are more likely to display expFL during submaximal exercise compared with children of healthy weight.

Research

Clinical investigation of respiratory system admittance in preschool children

We compared the ability of Ars, to standard oscillatory outcomes, to determine respiratory disease and differentiate responses to inhaled bronchial challenges.

Research

Exhaled breath temperature in healthy children is influenced by room temperature and lung volume

Exhaled breath temperature (EBT) has been proposed for the non-invasive assessment of airway inflammation

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.

Research

Air Trapping on Chest CT Is Associated with Worse Ventilation Distribution in Infants with Cystic Fibrosis

In school-aged children with cystic fibrosis (CF) structural lung damage assessed using chest CT is associated with abnormal ventilation distribution.