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Objective To validate the accuracy and safety of the Canadian Syncope Risk Score (CSRS) for patients presenting with syncope. Methods Single centre prospective observational study in Brisbane, Australia. Adults presenting to the ED with syncope within the last 24 h were recruited after applying exclusion criteria. Study was conducted over 1 year, from March 2018 to March 2019. Thirty‐day serious adverse events (SAE) were reported based on the original derivation study and standardised outcome reporting for syncope. Individual patient CSRS was calculated and correlated with 30‐day SAE and disposition status from ED. Results Two hundred and eighty‐three patients were recruited to the study. Average age was 55.6 years (SD 22.7 years), 37.1% being male with a 39.9% admission rate. Thirty‐day SAE occurred in seven patients (2.5%) and no recorded deaths. The CSRS performed with a sensitivity of 71.4% (95% confidence interval [CI] 30.3–94.9%), specificity 72.8% (95% CI 67.1–77.9%) for a threshold score of 1 or higher. Conclusion Syncope patients in our study were predominantly very low to low risk (72%). The prevalence of 30‐day SAE was low, majority occurring following hospital discharge. Sensitivity estimates for CSRS was lower than the derivation study but lacked robustness with wide CIs because of a small sample size and number of events observed. However, the CSRS did not miss any clinically relevant outcomes in low risk patients making it potentially useful in aiding their disposition. Larger validation studies in Australia are encouraged to further test the diagnostic accuracy of the CSRS.

Objective This study aims to determine whether redeploying junior doctors to assist at triage represents good value for money and a good use of finite staffing resources. Methods We undertook a cost-minimisation analysis to produce new evidence, from an economic perspective, about the costs associated with reallocating junior doctors in the emergency department. We built a decision-analytic model, using a mix of prospectively collected data, routinely collected administrative databases and hospital costings to furnish the model. To measure the impact of uncertainty on the model’s inputs and outputs, probabilistic sensitivity analysis was undertaken, using Monte Carlo simulation. Results The mean costs for usual care were $27,035 (95% CI $27,016 to $27,054), while the mean costs for the new model of care were $25,474, (95% CI $25,453 to $25,494). As a result, the mean difference was -$1,561 (95% CI -$1,533 to -$1,588), with the new model of care being a less costly approach to managing staffing allocations, in comparison to the usual approach. Conclusion Our study shows that redeploying a junior doctor from the fast-track area of the department to assist at triage provides a modest reduction in cost. Our findings give decision-makers who seek to maximise benefit from their finite budget, support to reallocate personnel within the ED.

Background: Syncope is a common problem but can have any of a broad range of underlying causes. Initial evaluation of the patient in the emergency department often does not identify a specific cause, and the cornerstone of management is reliable risk stratification with clinical decision rules. Objectives: The primary objective is to validate the utility and safety of the Canadian Syncope Risk Score (CSRS) as a clinical decision rule when assessing patients who present with syncope to Australian emergency departments. Our secondary objective is to evaluate the economic benefits of diverting patients with syncope at low risk of serious adverse events from admission to hospital. Methods and analysis: Prospective, observational study. Patients aged 18 years or more who present to the emergency department (ED) after syncope in the preceding 24 hours and have returned to their baseline state will be enrolled. Patients will be contacted by telephone to determine whether they have experienced any adverse events within 30 days of their initial presentation to the ED. The CSRS will be applied retrospectively to determine the relationship between whether patients were admitted to hospital or discharged home and the reporting of serious adverse events for each CSRS risk level. We will also undertake a cost-effectiveness analysis from the health care perspective. Ethics approval: Prince Charles Hospital Human Research Ethics Committee (reference, HREC/17/QPCH/48). Dissemination of results: Outcomes will be disseminated by Queensland Health and the funding body via social media, presented at local and national emergency medicine conferences, and published in international emergency medicine and health economics journals. Clinical trials registration: Not applicable.

Nurse Practitioners (NPs) receive core clinical training at master’s level, with their employer providing the opportunity to upskill in clinical and procedural competencies. It is increasingly recognised that this generic education requires supplementary training for operating effectively within a specific clinical environment. In this paper we describe a pilot program designed to train Australian NP Candidates to work effectively within the Emergency Department Fast Track model of care. The training program consisted of a 12-month period: four hours in-house training per week over two semesters, running concurrently with the NP candidate’s University semesters, and 3 months’ clinical practice to consolidate. The training team defined milestones for Semesters one and two, and developed a case review form to assess application of the candidate’s knowledge in new clinical situations, as well as check for gaps in understanding. A clinical skills guide was developed for the candidate to work toward, and a comprehensive assessment was carried out at two time points in the training program. Feedback was obtained from the mentors and the candidate at the end point of the training program, and has been used to refine the program for 2017. This in-house training program provided specialised, evidence-based training for the emergency department environment, resulting in development of the nurse practitioner candidate as a high functioning team member.

Reliance on the hemodynamic response as a surrogate marker of neural activity imposes an intrinsic limit on the spatial specificity of functional MRI. An alternative approach based on diffusion-weighted functional MRI (DfMRI) has been reported as a contrast less reliant on hemodynamic effects, however current evidence suggests that both hemodynamic and unique neural sources contribute to the diffusion signal. Here we compare activation patterns obtained with the standard blood oxygenation level-dependent (BOLD) contrast to DfMRI in order to gain a deeper understanding of how the BOLD proportion contributes to the observable diffusion signal. Both individual and group-level activation patterns obtained with DfMRI and BOLD to a visual field stimulation paradigm were analyzed. At the individual level, the DfMRI contrast showed a strong, positive relationship between the volumes of cortex activated in response to quadrant- and hemi-field visual stimulation. This was not observed in the corresponding BOLD experiment. Overall, the DfMRI response indicated less between-subject variability, with random effects analyses demonstrating higher statistical values at the peak voxel for DfMRI. Furthermore, the spatial extent of the activation was more restricted to the primary visual region for DfMRI than BOLD. However, the diffusion signal was sensitive to the hemodynamic response in a manner dependent on experimental manipulation. It was also limited by its low signal-to-noise ratio (SNR), demonstrating lower sensitivity than BOLD. Together these findings both support DfMRI as a contrast that bears a closer spatial relationship to the underlying neural activity than BOLD, and raise important caveats regarding its utilization. Models explaining the DfMRI signal change need to consider the dynamic vascular contributions that may vary with neural activity.

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.

Introduction Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Methods Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. Results At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. Conclusions DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

Background Miscommunication in the healthcare sector can be life-threatening. The rising number of migrant patients and foreign-trained staff means that communication errors between a healthcare practitioner and patient when one or both are speaking a second language are increasingly likely. However, there is limited research that addresses this issue systematically. This protocol outlines a hospital-based study examining interactions between healthcare practitioners and their patients who either share or do not share a first language. Of particular interest are the nature and efficacy of communication in language-discordant conversations, and the degree to which risk is communicated. Our aim is to understand language barriers and miscommunication that may occur in healthcare settings between patients and healthcare practitioners, especially where at least one of the speakers is using a second (weaker) language. Methods/Design Eighty individual interactions between patients and practitioners who speak either English or Chinese (Mandarin or Cantonese) as their first language will be video recorded in a range of in- and out-patient departments at three hospitals in the Metro South area of Brisbane, Australia. All participants will complete a language background questionnaire. Patients will also complete a short survey rating the effectiveness of the interaction. Recordings will be transcribed and submitted to both quantitative and qualitative analyses to determine elements of the language used that might be particularly problematic and the extent to which language concordance and discordance impacts on the quality of the patient-practitioner consultation. Discussion Understanding the role that language plays in creating barriers to healthcare is critical for healthcare systems that are experiencing an increasing range of culturally and linguistically diverse populations both amongst patients and practitioners. The

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

In this paper we provide normative data along multiple cognitive and affective variable dimensions for a set of 110 sounds, including living and manmade stimuli. Environmental sounds are being increasingly utilized as stimuli in the cognitive, neuropsychological and neuroimaging fields, yet there is no comprehensive set of normative information for these type of stimuli available for use across these experimental domains. Experiment 1 collected data from 162 participants in an on-line questionnaire, which included measures of identification and categorization as well as cognitive and affective variables. A subsequent experiment collected response times to these sounds. Sounds were normalized to the same length (1 second) in order to maximize usage across multiple paradigms and experimental fields. These sounds can be freely downloaded for use, and all response data have also been made available in order that researchers can choose one or many of the cognitive and affective dimensions along which they would like to control their stimuli. Our hope is that the availability of such information will assist researchers in the fields of cognitive and clinical psychology and the neuroimaging community in choosing well-controlled environmental sound stimuli, and allow comparison across multiple studies.