Experiences and insights from the collection of a novel multimedia EEG dataset

There is a growing interest in utilising novel signal sources such as EEG (Electroencephalography) in multimedia research. When using such signals, subtle limitations are often not readily apparent without significant domain expertise. Multimedia research outputs incorporating EEG signals can fail to be replicated when only minor modifications have been made to an experiment or seemingly unimportant (or unstated) details are changed. This can lead to overoptimistic or overpessimistic viewpoints on the potential real-world utility of these signals in multimedia research activities. This paper describes an EEG/MM dataset and presents a summary of distilled experiences and knowledge gained during the preparation (and utilisiation) of the dataset that supported a collaborative neural-image labelling benchmarking task. The goal of this task was to collaboratively identify machine learning approaches that would support the use of EEG signals in areas such as image labelling and multimedia modeling or retrieval. The contributions of this paper can be listed thus; a template experimental paradigm is proposed (along with datasets and a baseline system) upon which researchers can explore multimedia image labelling using a brain-computer interface, learnings regarding commonly encountered issues (and useful signals) when conducting research that utilises EEG in multimedia contexts are provided, and finally insights are shared on how an EEG dataset was used to support a collaborative neural-image labelling benchmarking task and the valuable experiences gained

A prospective observational study to assess the diagnostic accuracy of clinical decision rules for children presenting to emergency departments after head injuries (protocol): The Australasian Paediatric Head Injury Rules Study (APHIRST)

Background: Head injuries in children are responsible for a large number of emergency department visits. Failure to identify a clinically significant intracranial injury in a timely fashion may result in long term neurodisability and death. Whilst cranial computed tomography (CT) provides rapid and definitive identification of intracranial injuries, it is resource intensive and associated with radiation induced cancer. Evidence based head injury clinical decision rules have been derived to aid physicians in identifying patients at risk of having a clinically significant intracranial injury. Three rules have been identified as being of high quality and accuracy: the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) from Canada, the Children's Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) from the UK, and the prediction rule for the identification of children at very low risk of clinically important traumatic brain injury developed by the Pediatric Emergency Care Applied Research Network (PECARN) from the USA. This study aims to prospectively validate and compare the performance accuracy of these three clinical decision rules when applied outside the derivation setting.Methods/design: This study is a prospective observational study of children aged 0 to less than 18 years presenting to 10 emergency departments within the Paediatric Research in Emergency Departments International Collaborative (PREDICT) research network in Australia and New Zealand after head injuries of any severity. Predictor variables identified in CATCH, CHALICE and PECARN clinical decision rules will be collected. Patients will be managed as per the treating clinicians at the participating hospitals. All patients not undergoing cranial CT will receive a follow up call 14 to 90 days after the injury. Outcome data collected will include results of cranial CTs (if performed) and details of admission, intubation, neurosurgery and death. The performance accuracy of each of the rules will be assessed using rule specific outcomes and inclusion and exclusion criteria.Discussion: This study will allow the simultaneous comparative application and validation of three major paediatric head injury clinical decision rules outside their derivation setting.Trial registration: The study is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR)- ACTRN12614000463673 (registered 2 May 2014). © 2014 Babl et al.; licensee BioMed Central Ltd

Protocol for take-home naloxone In multicentre emergency (TIME) settings: Feasibility study

Background: Opioids, such as heroin, kill more people worldwide by overdose than any other type of drug, and death rates associated with opioid poisoning in the UK are at record levels (World Drug Report 2018 [Internet]. [cited 2019 Nov 19]. Available from: http://www.unodc.org/wdr2018/; Deaths related to drug poisoning in England and Wales - Office for National Statistics [Internet]. [cited 2019 Nov 19]. Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsrelatedtodrugpoisoninginenglandandwales/2018registrations). Naloxone is an opioid antagonist which can be distributed in 'kits' for administration by witnesses in an overdose emergency. This intervention is known as take-home naloxone (THN). We know that THN can save lives on an individual level, but there is currently limited evidence about the effectiveness of THN distribution on an aggregate level, in specialist drug service settings or in emergency service settings. Notably, we do not know whether THN kits reduce deaths from opioid overdose in at-risk populations, if there are unforeseen harms associated with THN distribution or if THN is cost-effective. In order to address this research gap, we aim to determine the feasibility of a fully powered cluster randomised controlled trial (RCT) of THN distribution in emergency settings. Methods: We will carry out a feasibility study for a RCT of THN distributed in emergency settings at four sites, clustered by Emergency Department (ED) and catchment area within its associated ambulance service. THN is a peer-administered intervention. At two intervention sites, emergency ambulance paramedics and ED clinical staff will distribute THN to adult patients who are at risk of opioid overdose. At two control sites, practice will carry on as usual. We will develop a method of identifying a population to include in an evaluation, comprising people at risk of fatal opioid overdose, who may potentially receive naloxone included in a THN kit. We will gather anonymised outcomes up to 1 year following a 12-month 'live' trial period for patients at risk of death from opioid poisoning. We expect approximately 100 patients at risk of opioid overdose to be in contact with each service during the 1-year recruitment period. Our outcomes will include deaths, emergency admissions, intensive care admissions, and ED attendances. We will collect numbers of eligible patients attended by participating in emergency ambulance paramedics and attending ED, THN kits issued, and NHS resource usage. We will determine whether to progress to a fully powered trial based on pre-specified progression criteria: sign-up of sites (n = 4), staff trained (≥ 50%), eligible participants identified (≥ 50%), THN provided to eligible participants (≥ 50%), people at risk of death from opioid overdose identified for inclusion in follow-up (≥ 75% of overdose deaths), outcomes retrieved for high-risk individuals (≥ 75%), and adverse event rate (< 10% difference between study arms). Discussion: This feasibility study is the first randomised, methodologically robust investigation of THN distribution in emergency settings. The study addresses an evidence gap related to the effectiveness of THN distribution in emergency settings. As this study is being carried out in emergency settings, obtaining informed consent on behalf of participants is not feasible. We therefore employ novel methods for identifying participants and capturing follow-up data, with effectiveness dependent on the quality of the available routine data