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Pneumo-BNA: Using Bayesian network models to facilitate a microbiological diagnosis in childhood pneumonia: development of a clinical decision support toolChristopher Peter Tom Blyth Richmond Snelling MBBS (Hons) DCH FRACP FRCPA PhD MBBS MRCP(UK) FRACP BMBS DTMH GDipClinEpid PhD FRACP Centre Head,
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Development of a pharmaceutical science systematic review process using a semi-automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care settingOur objective was to establish and test a machine learning-based screening process that would be applicable to systematic reviews in pharmaceutical sciences. We used the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) model, a broad search strategy, and a machine learning tool (Research Screener) to identify relevant references related to y-site compatibility of 95 intravenous drugs used in neonatal intensive care settings.
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A Systematic Framework for Prioritizing Burden of Disease Data Required for Vaccine Development and Implementation: The Case for Group A Streptococcal DiseasesVaccine development and implementation decisions need to be guided by accurate and robust burden of disease data. We developed an innovative systematic framework outlining the properties of such data that are needed to advance vaccine development and evaluation, and prioritize research and surveillance activities.
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Surveillance for severe influenza and COVID-19 in patients admitted to sentinel Australian hospitals in 2020: the Influenza Complications Alert Network (FluCAN)Influenza is a common cause of acute respiratory infection, and is a major cause of morbidity and mortality. Coronavirus disease 2019 (COVID-19) is an acute respiratory infection that emerged as a pandemic worldwide before the start of the 2020 Australian influenza season.
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Examining the entire delayed respiratory syncytial virus season in Western AustraliaAn interseasonal resurgence of respiratory syncytial virus (RSV) was observed in Western Australia at the end of 2020. Our previous report describing this resurgence compared the 2019 and 2020 calendar years, capturing only part of the 2020/21 season.
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Coronavax: preparing community and government for COVID-19 vaccination: a research protocol for a mixed methods social research projectAhead of the implementation of a COVID-19 vaccination programme, the interdisciplinary Coronavax research team developed a multicomponent mixed methods project to support successful roll-out of the COVID-19 vaccine in Western Australia. This project seeks to analyse community attitudes about COVID-19 vaccination, vaccine access and information needs. We also study how government incorporates research findings into the vaccination programme.
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Rare cause of scalp swelling in an infantChristopher Blyth MBBS (Hons) DCH FRACP FRCPA PhD Centre Head, Wesfarmers Centre of Vaccines and Infectious Diseases; Co-Head, Infectious Diseases
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Re-examining Hepatitis B Postexposure Prophylaxis Following Pediatric Community-acquired Needle-stick Injury in an Era of a National Immunization RegistryLong-term hepatitis B immunity has been demonstrated following the completion of the primary vaccination series in childhood. Some guidelines recommend a hepatitis B surface antibody (anti-HBs) directed approach following community-acquired needle-stick injury (CANSI) to inform hepatitis B postexposure prophylaxis (PEP) management.
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Lack of effectiveness of 13-valent pneumococcal conjugate vaccination against pneumococcal carriage density in Papua New Guinean infantsPapua New Guinea (PNG) introduced the 13-valent pneumococcal conjugate vaccine (PCV13) in 2014, with administration at 1, 2, and 3 months of age. PCV13 has reduced or eliminated carriage of vaccine types in populations with low pneumococcal carriage prevalence, carriage density and serotype diversity.
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Novel method to select meaningful outcomes for evaluation in clinical trialsA standardised framework for selecting outcomes for evaluation in trials has been proposed by the Core Outcome Measures in Effectiveness Trials working group. However, this method does not specify how to ensure that the outcomes that are selected are causally related to the disease and the health intervention being studied. Causal network diagrams may help researchers identify outcomes that are both clinically meaningful and likely to be causally dependent on the intervention, and endpoints that are, in turn, causally dependent on those outcomes.