Monash University (Australia)
  • Melbourne, Victoria, Australia
Recent publications
Background: Immigration detention is associated with detrimental mental health outcomes but little is known about the underlying psychological processes. Moral injury, the experience of transgression of moral beliefs, may play an important role. Objective: Our aim was to explore moral injury appraisals and associated mental health outcomes related to immigration detention on Nauru. Methods: In this retrospective study, we conducted in-depth interviews with 13 individuals who had sought refuge in Australia and, due to arriving by boat, had been transferred to immigration detention on Nauru. At the time of the study, they lived in Australia following medical transfer. We used reflexive thematic analysis to develop themes from the data. Results: Major themes included 1) how participants' home country experience and the expectation to get protection led them to seek safety in Australia; 2) how they experienced deprivation, lack of agency, violence, and dehumanization after arrival, with the Australian government seen as the driving force behind these experiences; and 3) how these experiences led to feeling irreparably damaged. The participant statement 'In my country they torture your body but in Australia they kill your mind.' conveyed these three key themes in our analysis. Conclusion: Our findings suggest that moral injury may be one of the processes by which mandatory immigration detention can cause harm. Although refugees returned to Australia from offshore detention may benefit from interventions that specifically target moral injury, collective steps are needed to diminish deterioration of refugee mental health. Our results highlight the potentially deleterious mental health impact of experiencing multiple subtle and substantial transgressions of one's moral frameworks. Policy makers should incorporate moral injury considerations to prevent eroding refugee mental health.
No previous research has examined age and sex differences in balance outcomes in individuals with chronic obstructive pulmonary disease (COPD) at risk of falls. A secondary analysis of baseline data from an ongoing trial of fall prevention in COPD was conducted. Age and sex differences were analyzed for the Berg Balance scale (BBS), Balance Evaluation System Test (BEST test) and Activities-specific Balance Confidence Scale (ABC). Overall, 223 individuals with COPD were included. Females had higher balance impairments than males [BBS: mean (SD) = 47 (8) vs. 49 (6) points; BEST test: 73 (16) vs. 80 (16) points], and a lower confidence to perform functional activities [ABC = 66 (21) vs. 77 (19)]. Compared to a younger age (50-65 years) group, age >65 years was moderately associated with poor balance control [BBS (r = - 0.37), BEST test (r = - 0.33)] and weakly with the ABC scale (r = - 0.13). After controlling for the effect of balance risk factors, age, baseline dyspnea index (BDI), and the 6-min walk test (6-MWT) explained 38% of the variability in the BBS; age, sex, BDI, and 6-MWT explained 40% of the variability in the BEST test; And BDI and the 6-MWT explained 44% of the variability in the ABC scale. This study highlights age and sex differences in balance outcomes among individuals with COPD at risk of falls. Recognition of these differences has implications for pulmonary rehabilitation and fall prevention in COPD, particularly among females and older adults.
The Large Hadron Collider beauty (LHCb) experiment at CERN is undergoing an upgrade in preparation for the Run 3 data collection period at the Large Hadron Collider (LHC). As part of this upgrade, the trigger is moving to a full software implementation operating at the LHC bunch crossing rate. We present an evaluation of a CPU-based and a GPU-based implementation of the first stage of the high-level trigger. After a detailed comparison, both options are found to be viable. This document summarizes the performance and implementation details of these options, the outcome of which has led to the choice of the GPU-based implementation as the baseline.
Spatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomics is presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.
Background Tonsillectomy, with or without adenoidectomy, is the leading reason for paediatric unplanned hospital readmission, some of which are potentially avoidable. Reducing unplanned hospital revisits would improve patient safety and decrease use of healthcare resources. This study aimed to describe the incidence, timing and risk factors for any surgery-related hospital revisits (both emergency presentation and readmission) following paediatric tonsillectomy and adenotonsillectomy in a large state-wide cohort. Methods We conducted a population-based cohort study using linked administrative datasets capturing all paediatric tonsillectomy and adenotonsillectomy surgeries performed between 2010 and 2015 in the state of Victoria, Australia. The primary outcome was presentation to the emergency department or hospital readmission within 30-day post-surgery. Results Between 2010 and 2015, 46,583 patients underwent 47,054 surgeries. There was a total of 4758 emergency department presentations (10.11% total surgeries) and 2750 readmissions (5.84% total surgeries). Haemorrhage was the most common reason for both revisit types, associated with 33.02% of ED presentations (3.34% total surgeries) and 67.93% of readmissions (3.97% total surgeries). Day 5 post-surgery was the median revisit time for both ED presentations (IQR 3–7) and readmission (IQR 3–8). Predictors of revisit included older age, public and metropolitan hospitals and peri-operative complications during surgery. Conclusions Haemorrhage was the most common reason for both emergency department presentation and hospital readmission. The higher risk of revisits associated with older children, surgeries performed in public and metropolitan hospitals, and in patients experiencing peri-operative complications, suggest the need for improved education of postoperative care for caregivers, and avoidance of inappropriate early discharge. Graphical Abstract
In this paper, we assess the role of investment in research and development (R&D) and economic policy uncertainty (EPU) in Sri Lanka’s economic growth experience. We do this by first determining which endogenous growth theories best explain the evolution of total factor productivity (TFP) in the country. Using historical time series data (1980–2018), we find that semi-endogenous growth theories best explain the evolution of TFP in Sri Lanka. This evidence suggests that R&D is critical to the country’s TFP expansion. We find that, through R&D, EPU has a crucial detrimental impact on TFP growth, although it is short-lived. Our findings are robust and have important implications for R&D investment and for moderating EPU.
While protein-truncating variants in RAD51C have been shown to predispose to triple-negative (TN) breast cancer (BC) and ovarian cancer, little is known about the pathogenicity of missense (MS) variants. The frequency of rare RAD51C MS variants was assessed in the BEACCON study of 5734 familial BC cases and 14,382 population controls, and findings were integrated with tumour sequencing data from 21 cases carrying a candidate variant. Collectively, a significant enrichment of rare MS variants was detected in cases (MAF < 0.001, OR 1.57, 95% CI 1.00–2.44, p = 0.05), particularly for variants with a REVEL score >0.5 (OR 3.95, 95% CI 1.40–12.01, p = 0.006). Sequencing of 21 tumours from 20 heterozygous and 1 homozygous carriers of nine candidate MS variants identified four cases with biallelic inactivation through loss of the wild-type allele, while six lost the variant allele and ten that remained heterozygous. Biallelic loss of the wild-type alleles corresponded strongly with ER- and TN breast tumours, high homologous recombination deficiency scores and mutational signature 3. Using this approach, the p.Gly264Ser variant, which was previously suspected to be pathogenic based on small case–control analyses and loss of activity in in vitro functional assays, was shown to be benign with similar prevalence in cases and controls and seven out of eight tumours showing no biallelic inactivation or characteristic mutational signature. Conversely, evaluation of case–control findings and tumour sequencing data identified p.Ile144Thr, p.Arg212His, p.Gln143Arg and p.Gly114Arg as variants warranting further investigation.
Clinical Trial Networks in which trialists work collaboratively enable multi-site, large-scale, high-quality clinical trials to be efficiently run. Although the benefits of Clinical Trial Networks are largely known, establishing a Clinical Trial Network can be complex. There are many factors for clinicians and researchers to consider, and there is currently a paucity of information on how to form a Clinical Trial Network. This article provides a suggested roadmap on how to establish a Clinical Trial Network. The Australian Clinical Trials Alliance (ACTA) is the peak body for Clinical Trial Networks, Coordinating Centres and Registries in Australia, and has produced several resources to support the effective and efficient running of clinical trials. This guide has come about through discussions with members of the ACTA Clinical Trial Network Sector Expansion Reference Group consisting of clinical trialists, clinicians, researchers, and consumers.
It has been a challenge for solving the motor imagery classification problem in the brain informatics area. Accuracy and efficiency are the major obstacles for motor imagery analysis in the past decades since the computational capability and algorithmic availability cannot satisfy complex brain signal analysis. In recent years, the rapid development of machine learning (ML) methods has empowered people to tackle the motor imagery classification problem with more efficient methods. Among various ML methods, the Graph neural networks (GNNs) method has shown its efficiency and accuracy in dealing with inter-related complex networks. The use of GNN provides new possibilities for feature extraction from brain structure connection. In this paper, we proposed a new model called MCGNet⁺, which improves the performance of our previous model MutualGraphNet. In this latest model, the mutual information of the input columns forms the initial adjacency matrix for the cosine similarity calculation between columns to generate a new adjacency matrix in each iteration. The dynamic adjacency matrix combined with the spatial temporal graph convolution network (ST-GCN) has better performance than the unchanged matrix model. The experimental results indicate that MCGNet⁺ is robust enough to learn the interpretable features and outperforms the current state-of-the-art methods.
Gravitational-wave detections are enabling measurements of the rate of coalescences of binaries composed of two compact objects—neutron stars and/or black holes. The coalescence rate of binaries containing neutron stars is further constrained by electromagnetic observations, including Galactic radio binary pulsars and short gamma-ray bursts. Meanwhile, increasingly sophisticated models of compact objects merging through a variety of evolutionary channels produce a range of theoretically predicted rates. Rapid improvements in instrument sensitivity, along with plans for new and improved surveys, make this an opportune time to summarise the existing observational and theoretical knowledge of compact-binary coalescence rates.
Doppler is the most commonly utilised vascular assessment tool by podiatrists in Australia and the United Kingdom. Doppler is a key component of many international guidelines for vascular assessment. Used alongside pressure measurements such as ankle and toe-brachial indices, Doppler assists podiatrists to diagnose, triage and subsequently manage patients with peripheral arterial disease. This commentary aims to clarify the importance, technique, and interpretation of continuous wave handheld Doppler in podiatry practice. This commentary presents discussion on the equipment and optimal test conditions for use of Doppler, and guidance on the technique required in podiatry clinical practice. Furthermore, there is a focus on interpretation of the output from Doppler including both audio and visual output. There is in depth discussion about identifying pathology and integration into the clinical management plan.
Corrosion costs an estimated 3–4% of GDP for most nations each year, leading to significant loss of assets. Research regarding automatic corrosion detection is ongoing, with recent progress leveraging advances in deep learning. Studies are hindered however, by the lack of a publicly available dataset. Thus, corrosion detection models use locally produced datasets suitable for the immediate conditions, but are unable to produce generalized models for corrosion detection. The corrosion detection model algorithms will output a considerable number of false positives and false negatives when challenged in the field. In this paper, we present a deep learning corrosion detector that performs pixel-level segmentation of corrosion. Moreover, three Bayesian variants are presented that provide uncertainty estimates depicting the confidence levels at each pixel, to better inform decision makers. Experiments were performed on a freshly collected dataset consisting of 225 images, discussed and validated herein.
Background: Sports-related concussion (SRC) is common in collision sport athletes. There is growing evidence that repetitive SRC can have serious neurological consequences, particularly when the repetitive injuries occur when the brain has yet to fully recover from the initial injury. Hence, there is a need to identify biomarkers that are capable of determining SRC recovery so that they can guide clinical decisions pertaining to return-to-play. Cerebral venous oxygen saturation (SvO2) and cerebral blood flow (CBF) can be measured using magnetic resonance imaging (MRI) and may provide insights into changing energy demands and recovery following SRC. Results: In this study we therefore investigated SvO2 and CBF in a cohort of concussed amateur Australian Football athletes (i.e., Australia's most participated collision sport). Male and female Australian footballers (n = 13) underwent MRI after being cleared to return to play following a mandatory 13-day recovery period and were compared to a group of control Australian footballers (n = 16) with no recent history of SRC (i.e., > 3 months since last SRC). Despite the concussed Australian footballers being cleared to return to play at the time of MRI, we found evidence of significantly increased susceptibility in the global white matter (p = 0.020) and a trend (F5,21 = 2.404, p = 0.071) for reduced relative CBF (relCBF) compared to the control group. Further, there was evidence of an interaction between sex and injury in straight sinus susceptibility values (F1,25 = 3.858, p = 0.061) which were decreased in female SRC athletes (p = 0.053). Of note, there were significant negative correlations between straight sinus susceptibility and relCBF suggesting impaired metabolic function after SRC. Conclusions: These findings support the use of quantitative susceptibility mapping (QSM) and relCBF as sensitive indicators of SRC, and raise further concerns related to SRC guidelines that allow for return-to-play in less than two weeks.
Background The collection of patient-reported outcome measures (PROMs) following arthroplasty is common. PROMs data collection programs seek to maximise completeness in order to minimise selection bias and optimise representativeness of the sample attained. We aimed to determine if patient factors influence variation in PROMs program completeness between-hospitals. Methods Using data from a national arthroplasty registry PROMs program, we tested for associations between patient characteristics (age, sex, body mass index [BMI] and American Society of Anaesthesiologists [ASA] class) and both potential completeness (registration completeness: the proportion of arthroplasty patients that were registered in the PROMs electronic system) and actual completeness (response completeness: the proportion of arthroplasty patients who provided PROMs data) using linear regression. Results When using all elective primary total hip, knee or shoulder arthroplasty procedures (N = 31,801) from 43 hospitals as the denominator, overall registration completeness was 52%, varying from 5 to 87% between hospitals. Overall pre-operative response completeness was 46%, varying from 5 to 82% between hospitals. There were no significant associations between hospital-level registration completeness or response completeness and age, sex, BMI or ASA score. Conclusion Completeness rates of a PROMs program in arthroplasty varied widely between hospitals but in the absence of a relationship between measured patient factors and completeness rates, the observed variation likely relates to local site factors such as access to patients, local resources and clinician engagement with the program. Efforts to improve the rates of completeness of arthroplasty PROMs programs at individual hospitals may not improve the representativeness of the sample.
End stage renal disease (ESRD) is an independent risk factor for the development of hip fractures and is associated with a higher mortality and complication rates. As these patients significantly skew healthcare financing in a bundled care payment (BCP) program, a risk stratified approach to BCPs could be done to take into account the difference in resources required. Introduction: End stage renal disease (ESRD) is an independent risk factor for the development of hip fractures and is associated with a higher mortality and complication rate. Hip fracture patients with ESRD may significantly skew healthcare financing in a bundled care payment (BCP) program. Materials and methods: ESRD patients undergoing hip fracture surgery from June 2007 to June 2012 within a tertiary hospital in Singapore were identified and matched to two other controls without ESRD based on secondary features of sex, age, fracture type, and surgery performed. Data was collected for American Society of Anesthesiologist (ASA) score, duration of surgery (DOS), length of stay (LOS), 30-day and 1-year mortality, and the presence of 10 other comorbidities: diabetes mellitus (DM), hypertension (HTN), hyperlipidemia (HLD), ischemic heart disease (IHD), arrhythmia (ARR), cerebrovascular disease (CVA), dementia (DEM), asthma (ASTH), peripheral vascular disease (PVD), and anemia (ANE) from electronic medical records. Costs were retrieved from the gross acute hospitalization bill. Results: Forty-one ESRD patients were successfully matched with 82 controls. Patients with ESRD had higher ASA scores (3 vs 2, p = 0.0001), had 75% higher LOS (21 vs 12 days, p < 0.0001), were associated with 67% higher healthcare expenditure (median $20542 vs $12236, p < 0.0001), and 1-year mortality (OR: 19.6, p < 0.0001). ESRD patients had an average of 4.1 comorbidities per patient compared to 1.84 in the control group. Conclusion: ESRD is an outsized factor on the outcome of hip fracture patients who have markedly higher and more variable healthcare utilization.
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34,338 members
Pathmanathan Rajadurai
  • School of Medicine and Health Sciences, Sunway
Farhad Fatehi
  • School of Psychological Sciences
Girdhar Singh Deora
  • Monash Institute of Pharmaceutical Sciences
Sheikh M Alif
  • Department of Epidemiology and Preventive Medicine
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3168, Melbourne, Victoria, Australia
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Professor Margaret Gardner AO
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http://monash.edu.au/
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