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Showing results for "preterm birth lungs"

Cerebral palsy after assisted reproductive technology: a cohort study

To calculate the birth prevalence of CP after ART and compare the clinical outcomes of children with CP after ART or natural conception.

Enteral Vitamin A for Reducing Severity of Bronchopulmonary Dysplasia: A Randomized Trial

Evidence suggests that intramuscular vitamin A reduces the risk of bronchopulmonary dysplasia (BPD) in preterm infants. Our objective was to compare enteral water-soluble vitamin A with placebo supplementation to reduce the severity of BPD in extremely preterm infants.

Premmie twins defy the odds

When Samuel and James Considine were born in October 2003, perilously close to what the medical world describes as the limit of viability, each weighed just 700 grams and could fit into the palm of their father’s hand.

Major grant supports innovative infant lung health study

A ground-breaking global clinical trial to improve the lifelong lung health of children born extremely prematurely has been awarded a Medical Research Future Fund (MRFF) International Clinical Trials Collaborations Grant totalling almost $3 million.

Identifying pediatric lung disease: A comparison of forced oscillation technique outcomes

These findings suggest the utility of specific FOT outcomes is dependent on the respiratory disease being assessed

Stan & Jean Perron Awards supporting outstanding child health researchers

We are pleased to announce latest recipients of the Stan and Jean Perron Awards, that recognise the work of exceptional postgraduate students who are undertaking their research projects at The Kids Research Institute Australia.

Pregnancy outcomes of mothers with an alcohol-related diagnosis: A population-based cohort study for the period 1983-2007

Infants of mothers with an alcohol-related diagnosis [International Classification of Disease (ICD), 9th/10th revisions] recorded on WA health data sets...

Research Track Record

The discoveries that have set our research apart primarily relate to the factors early in life that cause life-long respiratory problems.

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.