St Vincent's Hospital

It is widely acknowledged that trauma is related to auditory hallucinations in psychotic disorders. Yet, this relationship has not been well explored in hallucinations across other sensory modalities. The current study investigated whether hallucination modality groups (auditory, visual, olfactory, tactile, multisensory) were significantly related to physical, sexual, or emotional trauma. The age at which the trauma was experienced (16 or below, 17 and above) was also considered. Multivariate linear models, analysis of variance, and regression analyses for sixty-six participants with a psychotic disorder sought to determine whether trauma was related to hallucinations. Specifically, we used a modified version of the Life-Stressor Checklist Revised and the Multimodal Hallucinations Schedule (MHS) to identify whether the number of trauma items endorsed, or severity of trauma, at different developmental stages were significantly associated with the severity of lifetime hallucinations across different modalities, and the number of hallucination modalities experienced. We found that the severity of visual hallucinations was significantly associated with a history of sexual trauma. Notably, we revealed that experiencing sexual trauma in both childhood and adulthood was related to an increased self-reported severity of the trauma, and possibly the severity of visual hallucinations. These preliminary findings suggest that type of trauma may be uniquely related to specific hallucination modality and severity. Further, it is important to consider adulthood traumas as well as those occurring in childhood. These results have implications for clinical assessment and intervention.

ABSTRACTNecrotising fasciitis (NF) is a rapidly progressing, life‐threatening infection with mortality rates that are exceedingly high. Despite the notably high risks of developing NF in patients with diabetes mellitus (DM), factors associated with mortality in this population are poorly understood. Therefore, to determine at‐risk patients and to improve overall clinical outcomes via hastening management, the objective of this systematic review is to determine what factors are associated with mortality for diabetic patients with NF. This systematic review followed the PRISMA guidelines. Patient data pertaining to outcomes and surgical management were extracted, and mortality rates were evaluated. Studies were assessed for quality using the Alberta Heritage Foundation for Medical Research (AHFMR) and Risk of Bias tool. A total of 25 studies were reviewed, covering 7879 patients with NF and DM with a 23.5% mortality rate. The most prevalent comorbidities among those who died included chronic kidney disease (15.95%), hypertension (9.42%) and obesity (9.02%). While limbs were the most common location for the disease, NF in the trunk and groin regions showed the highest mortality rates at 62.07%. Among those who died, common complications were acute renal failure (13.41%), pulmonary issues (20.41%) and septicaemia (12.80%). Mortality rates by surgical management were fasciotomy (42.9%), surgical debridement (40.68%) and amputation (9.09%). Mortality was comparable between patients with NF and DM (23.54%) and those with NF alone (23.61%). Although DM may not independently increase mortality, it can worsen outcomes when combined with other comorbidities, indicating a need for clearer clinical guidance.

• Though Gen AI is increasingly being explored in various fields, including healthcare, there is little to no research into health professional perspectives. • Generally, there is a support for the use of Gen AI in healthcare for both clinical use and administrative offloading, however, there are still concerns with regards to data privacy and technical errors. • Organisational support and the provision of guidelines and guardrails remain the crucial priority for health professional use of Gen AI technologies in the workplace. Generative Artificial Intelligence (Gen AI) has become an increasingly prevalent conversation in healthcare over the past few years. Though there have been research projects and articles exploring the administrative and clinical uses of such technologies, there has been little exploration of health professional perspectives, hopes and concerns. This study sought to explore perspectives and examine the barriers and enablers of Gen AI in healthcare. Australian health professionals participated in a mixed-methods study. A survey (n=31) explored the Six Dimensions of Healthcare Quality Framework, capturing quantitative (Likert-scale responses) and qualitative (free-text) data. Semi-structured interviews (n=10) explored participant perceptions of Gen AI. Quantitative data was analysed using descriptive statistics. Qualitative data was thematically analysed. Most survey respondents (74.14%) reported having used Gen AI to support their work, but only a few (25.81%) reported organisational supports for use of these technologies. Analysis of the qualitative data aligned with the survey responses. Five themes were generated through thematic analysis, aligning with health professional’s perceived use of Gen AI chatbots, benefits, risks, as well as drivers of safe use and opportunities for the future. Health professionals see potential for using Gen AI to support their work, with enthusiasm about the potential of Gen AI to reduce workloads, particularly in offloading administrative tasks. There is also awareness that Gen AI chatbots pose risks both at the individual level such as limited capability in using these technologies and at the organisational level such as lack of training to support in upskilling, and systemic concerns around policy gaps. Generative Artificial Intelligence (Gen AI) is increasingly topical in all aspects of life, and the health sector is no exception. Though there have research projects focusing on Gen AI in healthcare, there has been little exploration of health professional views and concerns. This study spoke to health professionals and found that though there is a lot of interest in potential applications of Gen AI in healthcare, particularly in administrative offloading and clinical support, the benefits don’t yet outweigh the risks. Software developers must work alongside health professionals in developing a substantially beneficial program to support the safe use of Gen AI in healthcare as well as be well supported on an organisational level. There is also opportunities to develop education to build health professionals capacity to use GenAI safely and effectively, and for health service organisations to develop guidance and policies to clearly articulate what safe use looks like.

Electrospun triboelectric nanogenerators (TENGs) are exemplar devices for small scale electromechanical conversion towards powering small electronics and bespoke sensing applications. TENGs function via contact electrification (CE) between two dissimilar surfaces. Electrospinning enhances electromechanical conversion in TENGs by creating deformable, porous, mats with many contact sites for CE to occur. Within an electrospun mat, fibre alignment is widely recognized to influence charge generation, however, the role of the relative orientation between aligned fibre mats assembled into a TENG device remains unexplored. Here, we report a systematic study of orientation-dependent triboelectric output using electrospun polyacrylonitrile (PAN) nanofibres. Same-material contact electrification was used such that fibre-mat orientation change was decoupled from other CE effects, including chemical heterogeneities and dielectric constant variation. Systematic rotation of two aligned fibre mats revealed a direct dependence of output on relative orientation, with the highest response at parallel alignment (0 0 ) and the lowest at orthogonal alignment (90 0 ) imparting an electrical performance enhancement of up to 55%. A device made from optimized relative fibre orientation exhibited a V OC of 419 V, I SC of 407 nA, and a power density of 2.35 W m -2 , which is approximately 150% of output enhancement compared to similar devices. • The effect of the relative orientation between electrospun mats in TENGs was assessed. • Chemically identical materials enabled deconvolution of orientation from other factors • 50% enhancement in TENG performance was obtained when the relative fibre orientation varied from 90 0 to 0 0 • A same-material, orientation controlled, TENG imparted a maximum V OC of 419 V, an I SC of 407 nA, and a power density of 2.35 W m -2 .

Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease estimated to affect approximately 30% of children and 10%-15% of adults in Australia. Of those with this condition, one in five is estimated to have moderate-to-severe disease. Treatment guidelines for patients with moderate-to-severe AD recommend adding or switching to a targeted systemic medication if the disease is not well controlled with topical treatment. Without access to these medications, healthcare providers are limited in their ability to effectively treat moderate-to-severe AD. Availability of these guideline-recommended targeted systemic agents varies across the globe because of differences in both approval and reimbursement decisions. Patients in Australia should have funded or subsidised access to these highly effective, well-tolerated medications for moderate-to-severe AD. To highlight the importance of this, and to better understand potential barriers to such access in Australia, we conducted a narrative review of health technology assessment processes and the availability of funded/subsidised targeted systemic therapies for moderate-to-severe AD in patients aged ≥ 12 years in Australia and in countries with comparable healthcare systems, such as the United Kingdom, Canada, New Zealand and France. To provide context for this, we summarised current international guideline-recommended treatment for moderate-to-severe AD and considered healthcare resource utilisation in moderate-to-severe AD, both in Australia and internationally. In Australia, patients only have access to a limited selection of medicines launched globally. This suggests that national healthcare systems should consider updating health technology assessment procedures to better align with the current targeted high-cost therapeutics environment.

Adjuvant immunotherapy improved patient outcomes in two trials in completely resected non-small cell lung cancer (NSCLC), but with conflicting primary end point results. The Canadian Cancer Trials Group BR.31 trial evaluated adjuvant durvalumab in completely resected early-stage NSCLC. Following resection of stage IB (≥4 cm) to IIIA NSCLC (American Joint Committee on Cancer 7th Edition) and optional adjuvant chemotherapy, patients were randomly assigned 2:1 to durvalumab 20 mg/kg or placebo 20 mg/kg once every 4 weeks for 12 cycles. Random assignment was stratified by stage, extent of nodal dissection, tumor cell (TC) PD-L1 expression, adjuvant chemotherapy use, and center. The primary end point was investigator-assessed disease-free survival (DFS). Secondary outcomes included overall survival (OS), adverse events, and quality of life. The primary analysis was in the subgroup with cancers that had a PD-L1 TC expression ≥25%, no common activating EGFR mutations (EGFR-), and no ALK gene rearrangements (ALK-). Secondary analyses in hierarchical order included DFS in the subgroup whose tumors were EGFR-/ALK- with PD-L1 TC ≥1%, followed by all patients whose tumors were EGFR-/ALK-, followed by OS in the same primary and secondary subgroups in the same hierarchical order. Of 1,415 patients randomly assigned, 1,219 (86%) had EGFR-/ALK- tumors: 815 randomly assigned to durvalumab and 404 to placebo. With a median follow-up of 60 months, there were no differences in DFS between patients assigned durvalumab (316) versus placebo (161) in the primary population (stratified hazard ratio [HR], 0.93 [95% CI, 0.71 to 1.25]; P = .64) or in the secondary populations. Grade 3 to 4 adverse events were higher in durvalumab-treated patients (D = 26% v P = 20%). Adjuvant durvalumab following complete resection was not associated with improvement in DFS compared with placebo in EGFR-/ALK- NSCLC, regardless of PD-L1 status.

BackgroundMobile stroke units (MSUs) accelerate prehospital acute stroke care and improve outcomes. Both onboard and telemedicine neurologist models of care are used but have not been directly compared.MethodsMSU-TELEMED was a randomized, open-label, blinded-endpoint trial comparing onboard neurologist care to a telemedicine care model for people presenting to an MSU with suspected stroke. MSU care was prospectively randomized by day to onboard versus telemedicine care. The primary outcome was a hierarchical composite outcome using a win-odds approach that prioritized: (1) safety, (2) scene-to-treatment-decision time, and (3) percentage of the total case time the neurologist spent in direct care (higher values denote better resource use). Every participant in each group was compared to those in the other, resulting in a “win/tie/loss” distribution for telemedicine compared to onboard.ResultsA total of 275 participants were assigned to telemedicine (n=135) or onboard (n=140) neurologist care groups. The primary outcome of win/tie/loss distribution favored the telemedicine model (76%/4%/20%) with an adjusted win odds of 3.5 (95% confidence interval [CI], 2.4–5.1). Safety events were similar (13% telemedicine vs. 12% onboard, risk ratio 0.9; 95% CI, 0.5–1.8). Median scene-to-treatment-decision time was 19 minutes in the telemedicine group and 13 minutes in the onboard group (adjusted difference in median time 4 minutes; 95% CI, 1.9–5.9). The median percentage of the neurologist’s time directly involved in patient care was 100% in the telemedicine group and 33% in the onboard group (adjusted difference in median percentage 63 percentage points; 95% CI, 53–74).ConclusionsCompared to an onboard model, an MSU telemedicine model of care was superior based on a composite hierarchical outcome of safety, scene-to-treatment-decision time, and percentage of the neurologist’s time spent in direct care. (Funded by the Sylvia and Charles Viertel Charitable Foundation and the Medical Research Future Fund “Golden Hour”; ClinicalTrials.gov number, NCT05991310.)