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Primary aim was to review severe acute respiratory infections (SARI) hospitalisations caused by respiratory syncytial virus (RSV) in children aged < 2 years in paediatric hospitals in Australia. Secondary aims included RSV subtyping, assessing RSV seasonality and contributing to the World Health Organisation's RSV surveillance programme.
Antimicrobial stewardship (AMS) is crucial for optimizing antimicrobial use and restraining emergence of antimicrobial resistance. The overall increase in reported antibiotic allergies in children can pose a significant barrier to AMS, but its impact on clinical AMS care in children has not been addressed.
Melissa Penny PhD, PD, BSc (Hons) Professor Fiona Stanley Chair in Child Health Research melissa.penny@thekids.org.au Professor Fiona Stanley Chair
Assessing obstructive sleep apnoea in children involves various methodologies, including sleep studies, nocturnal oximetry, and clinical evaluations. Previous literature has extensively discussed these traditional methods.
Personal protective equipment is essential to protect healthcare workers when exposed to aerosol-generating procedures in patients with airborne respiratory pathogens.
Promoting wellbeing for youth is a global health priority and young people with chronic conditions demonstrate disproportionately low wellbeing compared to their peers. However, wellbeing is variably defined, and little is understood as to what wellbeing means for this population. The aim of this study was to develop a conceptualisation of wellbeing that is rooted in the perspectives of young people with chronic conditions.
Although most people born this century will be educated in African schools, these schools often lack basic infrastructure, such as electricity and/or lighting. In the face of a rapidly growing school-age population in Africa, the electrification of educational facilities is not just an infrastructural challenge but also a pivotal investment in the continent’s future workforce.
Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
o map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa. We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.
Nick Gottardo MBChB FRACP PhD Head of Paediatric and Adolescent Oncology and Haematology, Perth Children’s Hospital; Co-head, Brain Tumour Research