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The effect of azithromycin on structural lung disease in infants with cystic fibrosis (COMBAT CF): a phase 3, randomised, double-blind, placebo-controlled clinical trialStructural lung disease and neutrophil-dominated airway inflammation is present from 3 months of age in children diagnosed with cystic fibrosis after newborn screening. We hypothesised that azithromycin, given three times weekly to infants with cystic fibrosis from diagnosis until age 36 months, would reduce the extent of structural lung disease as captured on chest CT scans.
Research
Standardised treatment and monitoring protocol to assess safety and tolerability of bacteriophage therapy for adult and paediatric patients (STAMP study): protocol for an open-label, single-arm trialThere has been renewed interest in the therapeutic use of bacteriophages (phages); however, standardised therapeutic protocols are lacking, and there is a paucity of rigorous clinical trial data assessing efficacy.
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Pseudomonas aeruginosa Resistance to Bacteriophages and Its Prevention by Strategic Therapeutic Cocktail FormulationAntimicrobial resistance poses a significant threat to modern healthcare as it limits treatment options for bacterial infections, particularly impacting those with chronic conditions such as cystic fibrosis (CF). Viscous mucus accumulation in the lungs of individuals genetically predisposed to CF leads to recurrent bacterial infections, necessitating prolonged antimicrobial chemotherapy. Pseudomonas aeruginosa infections are the predominant driver of CF lung disease, and airway isolates are frequently resistant to multiple antimicrobials.
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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.
Research
Learning to make a difference for chILD: Value creation through network collaboration and team scienceAddressing the recognized challenges and inequalities in providing high quality healthcare for rare diseases such as children's interstitial lung disease (chILD) requires collaboration across institutional, geographical, discipline, and system boundaries. The Children's Interstitial Lung Disease Respiratory Network of Australia and New Zealand (chILDRANZ) is an example of a clinical network that brings together multidisciplinary health professionals for collaboration, peer learning, and advocacy with the goal of improving the diagnosis and management of this group of rare and ultra-rare conditions.