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Alzheimers disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimers disease. Here, we investigate whether genetic risk for Alzheimers disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimers Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimers disease unfolds in a disease stage-dependent

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

The Child Behavior Checklist (CBCL 1.5–5 years) posttraumatic stress disorder (PTSD) subscale by Dehon & Scheeringa (2006) as a screener for PTSD in trauma-exposed young children has yielded inconsistent results so far. Therefore, the aim of this study was to create and examine the validity of alternative CBCL-PTSD subscales and compare them to the existing CBCL-PTSD subscale based on the DSM-5 PTSD diagnostic criteria for children 6 years and younger. Further, the CBCL-PTSD subscales were examined regarding their usefulness in screening for posttraumatic stress-related functional impairment. The sample comprised 116 trauma-exposed young children (M$_{age}$ = 3.42 years, SD$_{age}$ = 1.21 years, female = 49.1%). The psychometric properties of the existing CBCL-PTSD subscale as well as the alternative subscales based on expert rating (CBCL-PTSD-17) and based on variable importance (CBCL-PTSD-6) were evaluated by means of receiver operating characteristic curves, sensitivity, specificity, positive predictive values, and negative predictive values. Area under the curves for all three investigated CBCL-PTSD subscales were good to excellent for PTSD and functional impairment. Further, all three CBCL-PTSD subscales showed high sensitivity for PTSD and functional impairment. Considering the length and the performance of the three investigated subscales, the CBCL-PTSD-6 appears to be a promising and clinically useful CBCL-PTSD subscale as a screener for PTSD and functional impairment due to the easiest and most practicable application. For purposes of discriminant validation of the CBCL-PTSD-6, young children without a history of trauma should be compared to young children with trauma history.

To better understand the pathological and phenotypic heterogeneity of progressive supranuclear palsy and the links between the two, we applied a novel unsupervised machine learning algorithm (Subtype and Stage Inference) to the largest MRI data set to date of people with clinically diagnosed progressive supranuclear palsy (including progressive supranuclear palsy-Richardson and variant progressive supranuclear palsy syndromes). Our cohort is comprised of 426 progressive supranuclear palsy cases, of which 367 had at least one follow-up scan, and 290 controls. Of the progressive supranuclear palsy cases, 357 were clinically diagnosed with progressive supranuclear palsy-Richardson, 52 with a progressive supranuclear palsy-cortical variant (progressive supranuclear palsy-frontal, progressive supranuclear palsy-speech/language, or progressive supranuclear palsy-corticobasal), and 17 with a progressive supranuclear palsy-subcortical variant (progressive supranuclear palsy-parkinsonism or progressive supranuclear palsy-progressive gait freezing). Subtype and Stage Inference was applied to volumetric MRI features extracted from baseline structural (T1-weighted) MRI scans and then used to subtype and stage follow-up scans. The subtypes and stages at follow-up were used to validate the longitudinal consistency of subtype and stage assignments. We further compared the clinical phenotypes of each subtype to gain insight into the relationship between progressive supranuclear palsy pathology, atrophy patterns, and clinical presentation. The data supported two subtypes, each with a distinct progression of atrophy: a 'subcortical' subtype, in which early atrophy was most prominent in the brainstem, ventral diencephalon, superior cerebellar peduncles, and the dentate nucleus, and a 'cortical' subtype, in which there was early atrophy in the frontal lobes and the insula alongside brainstem atrophy. There was a strong association between clinical diagnosis and the Subtype and Stage In

Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue→Airway group; r = -0.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers

Clinical practice guidelines, such as those focusing on traumatic stress treatment, can play an important role in promoting inclusion and equity. Based on a review of 14 international trauma treatment guidance documents that explicitly mentioned children, we reflect on two areas in which these guidelines can become more inclusive and equitable; a) representation of children’s cultural background and b) children’s opportunity to have their voice heard. While a few guidelines mentioned that treatment should be tailored to children’s cultural needs, there was little guidance on how this could be done. Moreover, there still appears to be a strong white Western lens across all stages of producing and evaluating the international evidence base. The available documentation also suggested that no young people under the age of 18 had been consulted in the guideline development processes. To contribute to inclusion and equity, we suggest five elements for future national guideline development endeavours. Promoting research and guideline development with, by, and for currently under-represented communities should be a high priority for our field. Our national, regional and global professional associations are in an excellent position to (continue to) stimulate conversation and action in this domain.

During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a wide variability of clinical CXR acquisitions. This variation is seen in the CXR projections used, image annotations added and in the inspiratory effort and degree of rotation of clinical images. The image analysis community has attempted to ease the burden on overstretched radiology departments during the pandemic by developing automated COVID-19 diagnostic algorithms, the input for which has been CXR imaging. Large publicly available CXR datasets have been leveraged to improve deep learning algorithms for COVID-19 diagnosis. Yet the variable quality of clinically-acquired CXRs within publicly available datasets could have a profound effect on algorithm performance. COVID-19 diagnosis may be inferred by an algorithm from non-anatomical features on an image such as image labels. These imaging shortcuts may be dataset-specific and limit the generalisability of AI systems. Understanding and correcting key potential biases in CXR images is therefore an essential first step prior to CXR image analysis. In this study, we propose a simple and effective step-wise approach to pre-processing a COVID-19 chest X-ray dataset to remove undesired biases. We perform ablation studies to show the impact of each individual step. The results suggest that using our proposed pipeline could increase accuracy of the baseline COVID-19 detection algorithm by up to 13%.

The Covid-19 pandemic has affected all levels of the UK theatre industry, particularly independent arts workers (IAWs) who are essential to the sector’s sustainability and survival. The repeated closures, restrictions, and changing safety guidelines caused by the global public health crisis had wide ranging impacts upon the, largely freelance, UK theatre workforce, affecting livelihoods, working practices, and support networks.

Background: Early empirical data shows that school-aged children, adolescents and adults are experiencing elevated levels of anxiety and depression during the COVID-19 pandemic. Currently, there is very little research on mental health outcomes for young children. Objectives: To describe the formation of a global collaboration entitled, ‘COVID-19 Unmasked’. The collaborating researchers aim to (1) describe and compare the COVID-19 related experiences within and across countries; (2) examine mental health outcomes for young children (1 to 5 years) and caregivers over a 12-month period during the COVID-19 pandemic; (3) explore the trajectories/time course of psychological outcomes of the children and parents over this period and (4) identify the risk and protective factors for different mental health trajectories. Data will be combined from all participating countries into one large open access cross-cultural dataset to facilitate further international collaborations and joint publications. Methods: COVID-19 Unmasked is an online prospective longitudinal cohort study. An international steering committee was formed with the aim of starting a global collaboration. Currently, partnerships have been formed with 9 countries (Australia, Cyprus, Greece, the Netherlands, Poland, Spain, Turkey, the UK, and the United States of America). Research partners have started to start data collection with caregivers of young children aged 1–5 years old at baseline, 3-months, 6-months, and 12-months. Caregivers are invited to complete an online survey about COVID-19 related exposure and experiences, child’s wellbeing, their own mental health, and parenting. Data analysis: Primary study outcomes will be child mental health as assessed by scales from the Patient-Reported Outcomes Measurement Information System–Early Childhood (PROMIS-EC) and caregiver mental health as assessed by the Depression Anxiety Stress Scale (DASS-21). The trajectories/time course of mental health difficulties a

Purpose: During our band 5 rotation through MSK outpatients, we became increasingly more aware of a cohort of patients who were not appropriate for referral into the existing exercise classes, as they did not have good enough balance to complete the class circuits. In circumstances where the patients were referred, they required 1:1 support throughout to ensure their safety.

Purpose: During our band 5 rotation through MSK outpatients, we became increasingly more aware of a cohort of patients who were not appropriate for referral into the existing exercise classes, as they did not have good enough balance to complete the class circuits. In circumstances where the patients were referred, they required 1:1 support throughout to ensure their safety.

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features using multidimensional data. Here, to classify MS subtypes based on pathological features, we apply unsupervised machine learning to brain MRI scans acquired in previously published studies. We use a training dataset from 6322 MS patients to define MRI-based subtypes and an independent cohort of 3068 patients for validation. Based on the earliest abnormalities, we define MS subtypes as cortex-led, normal-appearing white matter-led, and lesion-led. People with the lesion-led subtype have the highest risk of confirmed disability progression (CDP) and the highest relapse rate. People with the lesion-led MS subtype show positive treatment response in selected clinical trials. Our findings suggest that MRI-based subtypes predict MS disability progression and response to treatment and may be used to define groups of patients in interventional trials.

Alzheimer's disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These 'subtypes' were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.

Accurate prediction of progression in subjects at risk of Alzheimer's disease is crucial for enrolling the right subjects in clinical trials. However, a prospective comparison of state-of-the-art algorithms for predicting disease onset and progression is currently lacking. We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of patient-specific biomarkers. On a limited, cross-sectional subset of the data emulating clinical trials, performance of the best algorithms at predicting clinical diagnosis decreased only slightly (2 pe

Purpose: During our band 5 rotation through MSK outpatients, we became increasingly more aware of a cohort of patients who were not appropriate for referral into the existing exercise classes, as they did not have good enough balance to complete the class circuits. In circumstances where the patients were referred, they required 1:1 support throughout to ensure their safety.

Alzheimer’s disease (AD) is characterized by the spread of tau pathology throughout the cerebral cortex. This spreading pattern was thought to be fairly consistent across individuals, although recent work has demonstrated substantial variability in the population with AD. Using tau-positron emission tomography scans from 1,612 individuals, we identified 4 distinct spatiotemporal trajectories of tau pathology, ranging in prevalence from 18 to 33%. We replicated previously described limbic-predominant and medial temporal lobe-sparing patterns, while also discovering posterior and lateral temporal patterns resembling atypical clinical variants of AD. These ‘subtypes’ were stable during longitudinal follow-up and were replicated in a separate sample using a different radiotracer. The subtypes presented with distinct demographic and cognitive profiles and differing longitudinal outcomes. Additionally, network diffusion models implied that pathology originates and spreads through distinct corticolimbic networks in the different subtypes. Together, our results suggest that variation in tau pathology is common and systematic, perhaps warranting a re-examination of the notion of ‘typical AD’ and a revisiting of tau pathological staging.

Purpose: During our band 5 rotation through MSK outpatients, we became increasingly more aware of a cohort of patients who were not appropriate for referral into the existing exercise classes, as they did not have good enough balance to complete the class circuits. In circumstances where the patients were referred, they required 1:1 support throughout to ensure their safety.

The Alzheimer’s Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge compares the performance of algorithms at predicting the future evolution of individuals at risk of Alzheimer’s disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. Participants are then required to make forecasts of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, Alzheimer’s Disease Assessment Scale Cognitive Subdomain (ADAS-Cog 13), and total volume of the ventricles – which are then compared with future measurements. Strong points of the challenge are that the test data did not exist at the time of forecasting (it was acquired afterwards), and that it focuses on the challenging problem of cohort selection for clinical trials by identifying fast progressors. The submission phase of TADPOLE was open until 15 November 2017; since then data has been acquired until April 2019 from 219 subjects with 223 clinical visits and 150 Magnetic Resonance Imaging (MRI) scans, which was used for the evaluation of the participants’ predictions. Thirty-three teams participated with a total of 92 submissions. No single submission was best at predicting all three outcomes. For diagnosis prediction, the best forecast (team Frog), which was based on gradient boosting, obtained a multiclass area under the receiver-operating curve (MAUC) of 0.931, while for ventricle prediction the best forecast (team EMC1), which was based on disease progression modelling and spline regression, obtained mean absolute error of 0.41% of total intracranial volume (ICV). For ADAS-Cog 13, no forecast was considerably better than the benchmark mixed effects model (BenchmarkME), provided to participants before the submission deadline. Further analysis can help understand which input features and algorithms are most suitable for Alzheimer’s disease prediction and for aiding patient stratification in cl

We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even when only limited, unimodal data is available, by transferring information from larger multimodal datasets from common neurodegenerative diseases. DKT is a joint-disease generative model of biomarker progressions, which exploits biomarker relationships that are shared across diseases. Our proposed method allows, for the first time, the estimation of plausible multimodal biomarker trajectories in Posterior Cortical Atrophy (PCA), a rare neurodegenerative disease where only unimodal MRI data is available. For this we train DKT on a combined dataset containing subjects with two distinct diseases and sizes of data available: (1) a larger, multimodal typical AD (tAD) dataset from the TADPOLE Challenge, and (2) a smaller unimodal Posterior Cortical Atrophy (PCA) dataset from the Dementia Research Centre (DRC), for which only a limited number of Magnetic Resonance Imaging (MRI) scans are available. Although validation is challenging due to lack of data in PCA, we validate DKT on synthetic data and two patient datasets (TADPOLE and PCA cohorts), showing it can estimate the ground truth parameters in the simulation and predict unseen biomarkers on the two patient datasets. While we demonstrated DKT on Alzheimer’s variants, we note DKT is generalisable to other forms of related neurodegenerative diseases. Source code for DKT is available online: https://github.com/mrazvan22/dkt., NIH (Grants NAC-P41EB015902 and U01-AG024904), DOD (Award W81XWH-12-2-0012)

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10-4) or temporal stage (p = 3.96 × 10-5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 × 10-4) or temporal stage (p = 3.96 × 10-5). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine.

Background: Adoption of responsive trauma-informed practices by staff in hospital-based paediatric care may help mitigate downstream costs associated with treatment delivery due to reduced pain and distress for children and care providers, improved health-related quality of life and increased satisfaction with care. A web-based education intervention (termed Responsive CARE) was developed to build self-efficacy of staff in a paediatric medical setting. This protocol paper describes a feasibility study (including preliminary effectiveness) of the implementation of Responsive CARE in a tertiary, outpatient burn clinical setting. Methods: A pre-post, mixed methods design will be employed. Children and caregivers attending hospital for change of burn wound dressings or burn scar management during the 3-month control or 3-month intervention period will be eligible, with follow-up to 6-months post-baseline. All children and caregiver/s will receive "standard care"including burn interventions focused on wound healing, scar management, itch management (both pharmacological and non-pharmacological), counselling, age-appropriate procedural support and burn rehabilitation. Health professional participants will be those involved in the management of children with burns during the study period or their senior managers. Health professional participants who attend a weekly educational clinical meeting will be invited to complete the intervention during a 1-month time frame between the control and intervention period (or upon their commencement in burn outpatients during the intervention period) using an individualised log-in process. A purposive sample of caregivers and health professionals will be sought for participation in semi-structured interviews. Qualitative data will be analysed using Framework analysis. Feasibility will be evaluated via interviews, digital records of intervention usage and technical assistance logs. The primary outcome measure

Purpose: To thematically describe parent-clinician communication during a child's first burn dressing change following emergency department presentation. Design and methods: An observational study of parent-clinician communication during the first burn dressing change at a tertiary children's hospital. Verbal communication between those present at the dressing change for 87 families, was audio recorded. The recordings were transcribed verbatim and transcripts were analysed within NVivo11 qualitative data analysis software using qualitative content analysis. Findings: Three themes, underpinned by parent-clinician rapport-building, were identified. Firstly, knowledge sharing was demonstrated: Clinicians frequently informed the parent about the state of the child's wound, what the procedure will involve, and need for future treatment. Comparatively, parents informed the clinician about their child's temperament and coping since the accident. Secondly, child procedural distress management was discussed: Clinicians and parents had expectations about the likelihood of procedural distress, which was also related to communication about how to prevent and interpret procedural distress (i.e., pain/fear). Finally, parents communicated to clinicians about their own distress, worry and uncertainty, from the accident and wound care. Parents also communicated guilt and blame in relation to injury responsibility. Conclusions: This study provides a description of parent-clinician communication during paediatric burn wound care. Practical implications: The results can assist healthcare professionals to be prepared for a range of conversations with parents during potentially distressing paediatric medical procedures.

Bojidar A Rangelov,1 Alexandra L Young,1– 3 Joseph Jacob,1,4 Anthony P Cahn,5 Sarah Lee,6 Frederick J Wilson,5 David J Hawkes,1 John R Hurst4 1Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK; 2Department of Computer Science, University College London, London, UK; 3Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK; 4UCL Respiratory, University College London, London, UK; 5GlaxoSmithKline Research and Development, Stevenage, UK; 6Amallis Consulting LTD, London, UKCorrespondence: John R Hurst Email j.hurst@ucl.ac.ukAbstract: Exacerbations of chronic obstructive pulmonary disease (COPD) are currently diagnosed based on changes in respiratory symptoms. Characterizing the imaging manifestation of exacerbations could be useful for objective diagnosis of exacerbations in the clinic and clinical trials, as well as provide a mechanism for monitoring exacerbation treatment and recovery. In this systematic review, we employed a comprehensive search across three databases (Medline, EMBASE, Web of Science) to identify studies that performed imaging of the thorax at COPD exacerbation. We included 51 from a total of 5,047 articles which met all our inclusion criteria. We used an adapted version of the Modified Newcastle-Ottawa Quality Assessment Scale for cohort studies to assess the quality of the included studies. Conclusions were weighted towards higher-quality articles. We identified a total of 36 thoracic imaging features studied at exacerbation of COPD. Studies were generally heterogeneous in their measurements and focus. Nevertheless, considering studies which performed consecutive imaging at stable state and exacerbation, which scored highest for quality, we identified salient imaging biomarkers of exacerbations. An exacerbation is characterized by airway wall and airway calibre changes, hyperinflation, pul

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed earl

Introduction: The psychological distress and risk of mental health problems for parents of children with critical injury is well-established. There has been little exploration, however, of parent experiences and psychosocial trajectories over time following child critical injury. To address this knowledge gap, a longitudinal qualitative study was conducted to explore parent experiences and support needs and identify parent psychosocial trajectories in the 12 months following child critical injury. Methods: Semi- structured in-depth interviews were conducted with 27 parents at three time points over a 12 month period: the immediate hospital period post-child injury, and 6 and 12 months following injury, resulting in a total of 81 interviews. Data were analysed using a longitudinal within and across-case thematic analysis of patterns emerging over time. Findings: Three parent trajectory patterns were identified: resilient trajectory where parents were temporarily disrupted by the child's injury and hospitalisation, but recovered their mental and emotional wellbeing quickly, which was maintained over time; recovering trajectory where parents were initially disrupted at the time of injury but their mental and emotional wellbeing fluctuated over time and had not been fully restored by 12 months; and distressed trajectory where parents experienced significant psychosocial disruption due to their child's injury and struggled to adapt and regain their wellbeing over time, remaining emotionally distressed about the circumstances and impacts of the injury on their child and family. Illustrative narratives that represent each trajectory are presented. Conclusions: This is the first qualitative study to report the psychosocial trajectories of parents of critically injured children. Clinical application of insights provided by these trajectories can assist clinicians to use targeted strategies to help strengthen parental adaptation and prevent adverse mental health outcomes, and

Introduction: The psychological distress and risk of mental health problems for parents of children with critical injury is well-established. There has been little exploration, however, of parent experiences and psychosocial trajectories over time following child critical injury. To address this knowledge gap, a longitudinal qualitative study was conducted to explore parent experiences and support needs and identify parent psychosocial trajectories in the 12 months following child critical injury. Methods: Semi- structured in-depth interviews were conducted with 27 parents at three time points over a 12 month period: the immediate hospital period post-child injury, and 6 and 12 months following injury, resulting in a total of 81 interviews. Data were analysed using a longitudinal within and across-case thematic analysis of patterns emerging over time. Findings: Three parent trajectory patterns were identified: resilient trajectory where parents were temporarily disrupted by the child's injury and hospitalisation, but recovered their mental and emotional wellbeing quickly, which was maintained over time; recovering trajectory where parents were initially disrupted at the time of injury but their mental and emotional wellbeing fluctuated over time and had not been fully restored by 12 months; and distressed trajectory where parents experienced significant psychosocial disruption due to their child's injury and struggled to adapt and regain their wellbeing over time, remaining emotionally distressed about the circumstances and impacts of the injury on their child and family. Illustrative narratives that represent each trajectory are presented. Conclusions: This is the first qualitative study to report the psychosocial trajectories of parents of critically injured children. Clinical application of insights provided by these trajectories can assist clinicians to use targeted strategies to help strengthen parental adaptation and prevent adverse mental health outcomes, and

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed earl

Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer’s disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer’s disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer’s disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer’s disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer’s disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer’s disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer’s disease showed early h

Introduction: The psychological distress and risk of mental health problems for parents of children with critical injury is well-established. There has been little exploration, however, of parent experiences and psychosocial trajectories over time following child critical injury. To address this knowledge gap, a longitudinal qualitative study was conducted to explore parent experiences and support needs and identify parent psychosocial trajectories in the 12 months following child critical injury. Methods: Semi- structured in-depth interviews were conducted with 27 parents at three time points over a 12 month period: the immediate hospital period post-child injury, and 6 and 12 months following injury, resulting in a total of 81 interviews. Data were analysed using a longitudinal within and across-case thematic analysis of patterns emerging over time. Findings: Three parent trajectory patterns were identified: resilient trajectory where parents were temporarily disrupted by the child's injury and hospitalisation, but recovered their mental and emotional wellbeing quickly, which was maintained over time; recovering trajectory where parents were initially disrupted at the time of injury but their mental and emotional wellbeing fluctuated over time and had not been fully restored by 12 months; and distressed trajectory where parents experienced significant psychosocial disruption due to their child's injury and struggled to adapt and regain their wellbeing over time, remaining emotionally distressed about the circumstances and impacts of the injury on their child and family. Illustrative narratives that represent each trajectory are presented. Conclusions: This is the first qualitative study to report the psychosocial trajectories of parents of critically injured children. Clinical application of insights provided by these trajectories can assist clinicians to use targeted strategies to help strengthen parental adaptation and prevent adverse mental health outcomes, and

Introduction: The psychological distress and risk of mental health problems for parents of children with critical injury is well-established. There has been little exploration, however, of parent experiences and psychosocial trajectories over time following child critical injury. To address this knowledge gap, a longitudinal qualitative study was conducted to explore parent experiences and support needs and identify parent psychosocial trajectories in the 12 months following child critical injury. Methods: Semi- structured in-depth interviews were conducted with 27 parents at three time points over a 12 month period: the immediate hospital period post-child injury, and 6 and 12 months following injury, resulting in a total of 81 interviews. Data were analysed using a longitudinal within and across-case thematic analysis of patterns emerging over time. Findings: Three parent trajectory patterns were identified: resilient trajectory where parents were temporarily disrupted by the child's injury and hospitalisation, but recovered their mental and emotional wellbeing quickly, which was maintained over time; recovering trajectory where parents were initially disrupted at the time of injury but their mental and emotional wellbeing fluctuated over time and had not been fully restored by 12 months; and distressed trajectory where parents experienced significant psychosocial disruption due to their child's injury and struggled to adapt and regain their wellbeing over time, remaining emotionally distressed about the circumstances and impacts of the injury on their child and family. Illustrative narratives that represent each trajectory are presented. Conclusions: This is the first qualitative study to report the psychosocial trajectories of parents of critically injured children. Clinical application of insights provided by these trajectories can assist clinicians to use targeted strategies to help strengthen parental adaptation and prevent adverse mental health outcomes, and

Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from short-term longitudinal data sets. DIVE clusters vertex-wise biomarker measurements on the cortical surface that have similar temporal dynamics across a patient population, and concurrently estimates an average trajectory of vertex measurements in each cluster. DIVE uniquely outputs a parcellation of the cortex into areas with common progression patterns, leading to a new signature for individual diseases. DIVE further estimates the disease stage and progression speed for every visit of every subject, potentially enhancing stratification for clinical trials or management. On simulated data, DIVE can recover ground truth clusters and their underlying trajectory, provided the average trajectories are sufficiently different between clusters. We demonstrate DIVE on data from two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Dementia Research Centre (DRC), UK, containing patients with Posterior Cortical Atrophy (PCA) as well as typical Alzheimer's disease (tAD). DIVE finds similar spatial patterns of atrophy for tAD subjects in the two independent datasets (ADNI and DRC), and further reveals distinct patterns of pathology in different diseases (tAD vs PCA) and for distinct types of biomarker data: cortical thickness from Magnetic Resonance Imaging (MRI) vs amyloid load from Positron Emission Tomography (PET). Finally, DIVE can be used to estimate a fine-grained spatial distribution of pathology in the brain using any kind of voxelwise or vertexwise measures including Jacobian compression maps, fractional anisotropy (FA) maps from diffusion imaging or other PET measures. DIVE source code is available online: https://github.com/mrazvan22/dive, Comment: 24 pages, 5 figures, 2 tables, 1 algorithm

We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even when only limited, unimodal data is available, by transferring information from larger multimodal datasets from common neurodegenerative diseases. DKT is a joint-disease generative model of biomarker progressions, which exploits biomarker relationships that are shared across diseases. Our proposed method allows, for the first time, the estimation of plausible, multimodal biomarker trajectories in Posterior Cortical Atrophy (PCA), a rare neurodegenerative disease where only unimodal MRI data is available. For this we train DKT on a combined dataset containing subjects with two distinct diseases and sizes of data available: 1) a larger, multimodal typical AD (tAD) dataset from the TADPOLE Challenge, and 2) a smaller unimodal Posterior Cortical Atrophy (PCA) dataset from the Dementia Research Centre (DRC), for which only a limited number of Magnetic Resonance Imaging (MRI) scans are available. Although validation is challenging due to lack of data in PCA, we validate DKT on synthetic data and two patient datasets (TADPOLE and PCA cohorts), showing it can estimate the ground truth parameters in the simulation and predict unseen biomarkers on the two patient datasets. While we demonstrated DKT on Alzheimer's variants, we note DKT is generalisable to other forms of related neurodegenerative diseases. Source code for DKT is available online: https://github.com/mrazvan22/dkt., Comment: accepted at MICCAI 2019, 13 pages, 5 figures, 2 tables

BACKGROUND Accidental injury represents the most common type of traumatic event experienced by children under the age of 6 years. Around 10-30 % of young injured children will go on to develop post-traumatic stress disorder (PTSD) and other co-morbid conditions. Parents of injured children are also at risk of PTSD, and this is associated with short- and long-term consequences for their children's physical and psychological recovery. Despite the significance of this problem, to date, the mental health needs of injured young children have been neglected. One reason for this is due to the uncertainty and considerable debate around how to best provide early psychological intervention to traumatised children and adults. To address these gaps, researchers and psychologists in Australia and Switzerland have developed the Coping with Accident Reactions (CARE) programme, which is a two-session early intervention designed to prevent persistent PTSD reactions in young injured children screened as 'at risk'. Two separate international studies are being conducted to evaluate the effectiveness and feasibility of this programme. METHODS/DESIGN The study design for the two proposed studies will employ a randomised controlled trial design and children (aged 1-6 years) who are screened as at risk for PTSD 1 week after an unintentional injury, and their parents will be randomised to either (1) CARE intervention or (2) treatment as usual. Assessment will be completed at baseline (2 weeks) and 3 and 6 months post-injury. DISCUSSION This international collaboration provides an excellent opportunity to test the benefit of screening and providing early intervention to young children in two different countries and settings. It is expected that outcomes from this research will lead to significant original contributions to the scientific evidence base and clinical treatment and recovery of very young injured children. TRIAL REGISTRATION The Australian study was registered with the Australian

No randomized controlled trial has investigated the efficacy of hypnosis for reducing pain and improving wound-healing in children with burns. This randomized controlled trial aimed to investigate whether hypnosis decreases pain, anxiety, and stress and accelerates wound-healing in children undergoing burn wound procedures. Children (4-16 years) with acute burns presenting for their first dressing change were randomly assigned to a Hypnosis Group who received hypnosis plus standard care or a Standard Care Group who received standard pharmacological and nonpharmacological intervention. Repeated measures of pain intensity, anxiety, stress, and wound-healing were taken at dressing changes until ≥95% wound re-epithelialization. Data for 62 children were analyzed on an intent-to-treat basis using Generalized Estimating Equations (n = 35 Standard Care Group; n = 27 Hypnosis Group). An effect on the primary outcomes of pain and wound healing was not supported {self-reported pain intensity largest Mean Difference [MD] = -0.85 (95% confidence interval [CI]: -1.91 to 0.22), P = 0.12; MD for re-epithelialization = -0.46 [95% CI: -4.27 to 3.35], P = 0.81}. Some support was found for an effect on the secondary outcomes of preprocedural anxiety (MD = -0.80 [95% CI: -1.50 to -0.10], P = 0.03 before the second dressing change) and heart rate as a measure of stress (MD = -15.20 [-27.20 to -3.20], P = 0.01 and MD = -15.39 [-28.25 to -2.53], P = 0.02 before and after the third dressing change). Hypnosis may be effective for decreasing preprocedural anxiety and heart rate in children undergoing repeated pediatric wound care procedures but not for reducing pain intensity or accelerating wound healing.

Delirium is a common and serious neuropsychiatric complication in critically ill patients of all ages. In the context of critical illness, delirium may emerge as a result of a cascade of underlying pathophysiologic mechanisms and signals organ failure of the brain. Awareness of the clinical importance of delirium in adults is growing as emerging research demonstrates that delirium represents a serious medical problem with significant sequelae. However, our understanding of delirium in children lags significantly behind the adult literature. In particular, our knowledge of how to assess delirium is complicated by challenges in recognizing symptoms of delirium in pediatric patients especially in critical and intensive care settings, and our understanding of its impact on acute and long-term functioning remains in its infancy. This paper focuses on (a) the challenges associated with assessing delirium in critically ill children, (b) the current literature on the outcomes of delirium including morbidity following discharge from PICU, and care-giver well-being, and (c) the importance of assessment in determining impact of delirium on outcome. Current evidence suggests that delirium is a diagnostic challenge for clinicians and may play a detrimental role in a child’s recovery after discharge from the pediatric intensive care unit (PICU). Recommendations are proposed for how our knowledge and assessment of delirium in children could be improved.

Background: Burns and the associated wound care procedures can be extremely painful and anxiety-provoking for children. Burn injured children and adolescents are therefore at greater risk of experiencing a range of psychological reactions, in particular posttraumatic stress disorder, which can persist for months to years after the injury. Non-pharmacological intervention is critical for comprehensive pain and anxiety management and is used alongside pharmacological analgesia and anxiolysis. However, effective non-pharmacological pain and anxiety management during pediatric burn procedures is an area still needing improvement. Medical hypnosis has received support as a technique for effectively decreasing pain and anxiety levels in adults undergoing burn wound care and in children during a variety of painful medical procedures (e.g., bone marrow aspirations, lumbar punctures, voiding cystourethrograms, and post-surgical pain). Pain reduction during burn wound care procedures is linked with improved wound healing rates. To date, no randomized controlled trials have investigated the use of medical hypnosis in pediatric burn populations. Therefore this study aims to determine if medical hypnosis decreases pain, anxiety, and biological stress markers during wound care procedures; improves wound healing times; and decreases rates of traumatic stress reactions in pediatric burn patients. Methods/Design: This is a single-center, superiority, parallel-group, prospective randomized controlled trial. Children (4 to 16 years, inclusive) with acute burn injuries presenting for their first dressing application or change are randomly assigned to either the (1) intervention group (medical hypnosis) or (2) control group (standard care). A minimum of 33 participants are recruited for each treatment group. Repeated measures of pain, anxiety, stress, and wound healing are taken at every dressing change until ≥95 % wound re-epithelialization. Further data collection assess

In 2014, Swedish oat milk producer Oatly was sued by the dairy lobby LRF Mjölk for their use of marketing slogans such as “It’s like milk, but made for humans” which the dairy lobby claimed painted cow’s milk negatively. Dubbed the “milk wars”, the dispute sparked an intense debate over the political and environmental impacts of dairy production up until and beyond the court’s decision in November 2015. Although Oatly lost the lawsuit, the company’s sales skyrocketed and a passionate supporter base was revealed. These supporters wrote opinion articles, started Twitter campaigns and created fan pages on social media in defence of Oatly. This widespread reaction illustrates a shifting, unconventional kind of political engagement through commodity activism, facilitated by digital media. This is an individual political engagement that evolves from the growing global concerns over the environmental impact of food production and consumption, and yet is inextricably linked with commodity culture, raising questions over the validity of this kind of political engagement for both individual and collective action. Recent research has begun to examine commodity activism as a way of doing politics within brand culture, aligning individual purchasing habits with political and social change. These analyses largely focus on the US context and little research has been dedicated to the emerging consumer demand for sustainable food products as a form of political engagement in the Swedish context. Existing research has also tended to focus on consumption as political engagement as an isolated practice, therefore this thesis analyses dynamic, multi-site political engagement across both online and offline spaces. Through in-depth interviews with both Oatly consumers and employees, this thesis explores political engagement that is located within a corporate environment. It addresses the multiple spaces where this engagement occurs to analyse the complexity of online and offline commodity

In 2014, Swedish oat milk producer Oatly was sued by the dairy lobby LRF Mjölk for their use of marketing slogans such as “It’s like milk, but made for humans” which the dairy lobby claimed painted cow’s milk negatively. Dubbed the “milk wars”, the dispute sparked an intense debate over the political and environmental impacts of dairy production up until and beyond the court’s decision in November 2015. Although Oatly lost the lawsuit, the company’s sales skyrocketed and a passionate supporter base was revealed. These supporters wrote opinion articles, started Twitter campaigns and created fan pages on social media in defence of Oatly. This widespread reaction illustrates a shifting, unconventional kind of political engagement through commodity activism, facilitated by digital media. This is an individual political engagement that evolves from the growing global concerns over the environmental impact of food production and consumption, and yet is inextricably linked with commodity culture, raising questions over the validity of this kind of political engagement for both individual and collective action. Recent research has begun to examine commodity activism as a way of doing politics within brand culture, aligning individual purchasing habits with political and social change. These analyses largely focus on the US context and little research has been dedicated to the emerging consumer demand for sustainable food products as a form of political engagement in the Swedish context. Existing research has also tended to focus on consumption as political engagement as an isolated practice, therefore this thesis analyses dynamic, multi-site political engagement across both online and offline spaces. Through in-depth interviews with both Oatly consumers and employees, this thesis explores political engagement that is located within a corporate environment. It addresses the multiple spaces where this engagement occurs to analyse the complexity of online and offline commodity

Jan Heath, Karen Grimmer-Somers, Steve Milanese, Susan Hillier, Ellena King, Kylie Johnston, Kylie Wall, Olivia Thorpe, Alexandra Young, Saravana KumarSchool of Health Sciences, University of South Australia, Adelaide, SA, AustraliaBackground: Excellence in Research for Australia (ERA) rankings are given to academic journals in which Australian academics publish. This provides a metric on which Australian institutions and disciplines are ranked for international competitiveness. This paper explores the issues surrounding the ERA rankings of allied health journals in Australia.Methods: We conducted a broad search to establish a representative list of general allied health and discipline-specific journals for common allied health disciplines. We identified the ERA rankings and impact factors for each journal and tested the congruence between these metrics within the disciplines.Results: Few allied health journals have high ERA rankings (A*/A), and there is variability in the impact factors assigned to journals within the same ERA rank. There is a small group of allied health researchers worldwide, and this group is even smaller when divided by discipline. Current publication metrics may not adequately assess the impact of research, which is largely aimed at clinicians to improve clinical practice. Moreover, many journals are produced by underfunded professional associations, and readership is often constrained by small numbers of clinicians in specific allied health disciplines who are association members.Conclusion: Allied health must have a stronger united voice in the next round of ERA rankings. The clinical impact of allied health journals also needs to be better understood and promoted as a research metric.Keywords: allied health, research impact, publication metrics