179566 research outputs found
Sort by
Use of a point prevalence survey to measure antimicrobial use and antimicrobial resistance in equine veterinary hospitals
Get PDFBackground: Antimicrobial resistance (AMR) is increasingly recognised in equine medicine. Antimicrobial use (AMU) is a key driver of AMR. Objectives: To pilot a point prevalence survey (PPS), based on the Global-PPS used in human hospitals, to obtain data on antibiotic prescribing and AMR in equine hospitals and to identify targets for improvement in AMU. Study Design: Point prevalence survey. Methods: Eight equine hospitals located in Australia, Belgium, South Africa, the United Kingdom and the United States were recruited. Data on AMU were collected from all in-patients on antibiotic treatment at 08h00 on four selected study days throughout the study year (2022). Results: In total, 742 patients, 310 (41.8%) surgical and 432 (58.2%) nonsurgical cases, were evaluated and 58.7% (182/310) surgical and 25.9% (112/432) nonsurgical patients were on antibiotics. The most prescribed antibiotics were penicillin, gentamicin and trimethoprim sulfonamides. In 45.2% (215/476) of prescriptions, use was prophylactic. Therapeutic use was based on a biomarker in 48.8% (127/260) of treatments. A sample was submitted for culture in 56.9% (148/260) of therapeutic treatments. A positive culture result was reported from 49.3% (73/148) of samples, with an antibiogram available for 90.4% (66/73) of the positive cultures. An antibiotic use stop/review date was not recorded in 59.5% (283/476) of uses. Main Limitations: This PPS was a pilot study with a relatively small sample size and likely does not reflect AMU in all types of equine hospitals in all geographic locations. Conclusions and Clinical Relevance: The PPS identified multiple ways in which antibiotic prescribing could be improved. Targets identified for stewardship interventions included empiric use of European Medicines Agency Category A and B antibiotics, the high prevalence of prophylaxis and the lack of use of a stop/review date. The survey could be used as a repeatable tool to assess stewardship interventions in equine hospitals.</p
Small vessel disease contributions to acute delirium:a pilot feasibility MRI study
Get PDFBACKGROUND AND AIMS: Delirium carries an eight-fold risk of future dementia. Small vessel disease (SVD), best seen on magnetic resonance imaging (MRI), increases delirium risk, yet delirium is understudied in MRI research. We aimed to determine MRI feasibility, tolerability, image usability and prevalence of SVD lesions in delirium.METHODS: This case-control feasibility study performed MRI (3D T1/T2-weighted), fluid-attenuated inversion recovery, susceptibility-weighted and diffusion-weighted imaging (DWI) on 20 medical inpatients >65 years: 10 with delirium ≥3 weeks and 10 without delirium, matched for vascular risk, Clinical Frailty Scale (CFS) and cognition. We excluded acute stroke, agitation necessitating sedation, mobility assistance of >2 and MRI contraindications. We measured scan duration, tolerability, image usability, acute infarcts and SVD features. Six months later, we recorded CFS and cognitive diagnoses.RESULTS: Mean age was 83.5 years (delirium 78.7 vs non-delirium 88.4); 13/20 were female; 17/20 had premorbid cognitive decline/impairment or dementia. Acquisition took mean 26.8 min. MRI was well tolerated in 16/20 (7/10 in delirium arm; 9/10 in non-delirium arm). Also, 4/20 had early scan termination, but 20/20 had clinically interpretable images. We detected DWI-hyperintense lesions in 3/10 (30%) with delirium (2/10 small subcortical and 1/10 cortical) and in 3/10 (30%) without delirium (2/10 small subcortical; 1/10 cortical). Mean white matter hyperintensity Fazekas score was 6 in delirium versus 4.5 without.CONCLUSIONS: MRI is feasible, usable and tolerable in delirium, and we detected DWI-hyperintense lesions in one-third of all study participants, regardless of delirium status. This study indicates acute vascular contributions, including SVD, to both delirium- and non-delirium-related presentations, supporting the need for larger studies.</p
Artificial Intelligence-driven prediction of optimal technology-aided alternative operations in post-emergency contexts:A case study from an Emirati University
Get PDFDespite the challenges posed by the recent pandemic, educational institutions were prompted to explore alternative operation modes to enhance teaching, learning, and service delivery through technology. However, effective implementation of these technology-aided modes in post-emergency contexts necessitates evidence-based practices and contextual insights into stakeholders’ challenges, comfortability, and preferences. This study aims to support the efficient planning and execution of digital transformation within a university in the United Arab Emirates (UAE) by examining stakeholders’ comfortability, challenges, and preferences following the pandemic’s impact. The novelty of this research lies in its use of artificial intelligence, specifically fuzzy logic, to predict stakeholder preferences, complemented by comprehensive stakeholder-centric analysis and an in-depth examination of demographic influences on digital transformation preferences. Additionally, the study provides unique regional insights within the UAE context, addressing cultural, economic, and technological factors underrepresented in international literature. Utilizing a survey method, data were analyzed through descriptive statistics and AI-driven predictive analytics. Findings indicate that institutional support and familiarity with online platforms reduced stress during the transition to technology-aided modes, with a strong preference for hybrid flexible models influenced significantly by demographic factors. This study contributes by demonstrating the enhanced predictive capabilities of AI in understanding stakeholder needs, offering tailored digital transformation strategies, highlighting the importance of demographic considerations, and providing a practical roadmap for building a sustainable and resilient digital ecosystem. Furthermore, it informs educational policy and governance, ensuring that technology-aided operations are effectively planned and implemented to meet the evolving needs of the academic community in post-emergency settings
Sex dimorphism in brain cell death after hypoxia-ischemia in newborn piglets
Get PDFBACKGROUND: Clinical data suggest that females might be more resistant to hypoxia than males, with male sex recognized as a risk factor for suffering life-long neurological sequelae. However, the impact of hypoxia-ischemia in certain brain regions and its association with genetic sex remains unclear.METHODS: Using the piglet model of neonatal brain injury, fifteen piglets (8 females and 7 males) were subjected to a global cerebral hypoxic-ischemic insult. After 48 h, total cell death and the number of necrotic, apoptotic and cleaved-caspase-3 positive cells was quantified in five brain regions.RESULTS: Male piglets exposed to hypoxia-ischemia were more vulnerable than females (total cell death p < 0.01), also showing a region-specific response to brain injury depending on sex, with males being more affected in both deep gray (caudate p < 0.01; THAL p < 0.0001) and white (p < 0.01) matter. Despite necrosis was the primary form of cell death for both sexes, the pattern of cell death differed: while male piglets showed more necrosis (p < 0.0001), apoptosis (p < 0.0001) and caspase-3 activation (p < 0.0001) were higher in females.CONCLUSION: Our results suggest that male piglets were globally and regionally more vulnerable than females after HI; further, both the pattern of cell death and the apoptotic molecular mechanisms were sexually dimorphic.IMPACT: Clinical data suggest that females might be more resistant to perinatal asphyxia than male newborns. The impact of hypoxia-ischemia in certain brain regions and the association of cell death patterns with sex remain unclear. Hypoxic-ischemic male piglets were more vulnerable than females, showing also increased regional vulnerability in both deep gray and white matter areas. Although necrosis was the primary form of cell death for both sexes, male piglets showed more necrosis, whereas apoptosis and caspase-3 activation were higher in females. Neonatal brain injury and therapeutic responses may be sex-dependent due to differences in cell death patterns and molecular mechanisms.</p
Protecting the Bunce Legacy: Lessons Learned From Safeguarding Long-term Ecological Survey Datasets in Great Britain
Get PDFRescued data helps to strengthen ecological understanding of biodiversity change. This paper presents experience from safeguarding long-term strategic ecological surveys established by the late Professor Robert Bunce and colleagues in the 1970s: the Great Britain Countryside Surveys, and various related and complementary surveys in the period 1969 to the mid-1990s, including woodland surveys, and regional surveys for Cumbria and Shetland. These surveys are valuable data sources - especially considering national and global ecological restoration targets to address the biodiversity crisis - providing evidence to explore and understand ecological changes in the British countryside over time. For these kinds of data to be useful, usable and used, it is essential they are accessible and well managed, but many important ecological data sets are at risk of loss. A decade of work to protect the Bunce surveys has resulted in a structured five-step approach that can benefit other data rescue and safeguarding initiatives as well as scientists planning new ecological monitoring projects. The steps involve identifying available resources, processing datasets, assembling metadata, producing outputs and publishing. Valuable lessons learnt in the process include: (1) the growing appreciation and relevance of historic ecological data; (2) the importance of adequate resourcing and recognition of data rescue activity; (3) the value of engaging with the originators; (4) the need to identify and understand potential users and uses of the data. The Bunce legacy of strategic ecological surveys in the UK is now protected and the data available for repeat survey and further analysis
Exploring nurse-led cardiopulmonary resuscitation in the emergency department:A scoping review
Get PDFAim of the Review: The aim is to map the existing evidence on nurse-led resuscitation and identify gaps to inform future research directions. This scoping review critically examines the role of nurse-led resuscitation in the emergency department (ED). The review identifies the integral role of nurses in resuscitation teams, evaluates nurses’ performance during resuscitation, and highlights the need for further research. Method: The review employed a comprehensive search strategy across multiple databases, including MEDLINE, CINAHL, PROSPERO, and EMBASE, along with sources of unpublished studies and grey literature such as ProQuest Theses, Grey Matters, Policy Commons, and Google Scholar. The search covered literature from 1993 to 2023. Results: The searches returned a total of 494 citations. A total of 8 full articles met the inclusion criteria for data extraction and synthesis. Three key themes emerged from the review: (1) the integral role of nurses in resuscitation teams, (2) nurses’ performance during resuscitation and (3) the need for future research. Conclusion: This scoping review underscores the potential of nurse-led resuscitation in emergency care settings. Nurses’ roles in resuscitation teams are integral, with performance comparable to that of physicians in multiple domains. However, the current evidence base is limited to literature reviews and simulated environments and highlights the necessity for further robust research. Future studies should explore interdisciplinary team dynamics, communication patterns, and the direct impact of nurse-led resuscitation on patient outcomes in real-world clinical settings.</p
Data Hazards as An Ethical Toolkit for Neuroscience
Get PDFThe Data Hazards framework (Zelenka, Di Cara, & Contributors, 2024) is intended to encourage thinking about the ethical implications of data science projects. It takes the form of community-designed data hazard labels, similar to warning labels on chemicals, that can encourage reflection and discussion on what ethical risks are associated with a project and how they can be mitigated. In this article, we explain how the Data Hazards framework can apply to neuroscience. We demonstrate how the hazard labels can be applied to one of our own projects, on the computational modelling of postsynaptic mechanisms.</p
Accessible, realistic genome simulation with selection using stdpopsim
Get PDFSelection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to the stdpopsim framework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintains stdpopsim's core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by comparing methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.</p
Distinct Bone Metabolic Networks Identified in Phospho1-/- Mice Versus Wild Type Mice using [18F]FDG Total-Body PET
No full textIntroduction Total-body PET is a recent development in clinical imaging that produces large datasets involving multiple tissues, enabling the use of new analytical methods for multi-organ assessments, such as network analysis – a well-developed method in neuroimaging. The skeletal system provides a good model for applying network analysis to total-body PET, as bone serves many classical whole-body functions as well as being an endocrine regulator of metabolism. Previous reports have suggested an association between the expression of bone specific phosphatase, orphan 1 and disorders of altered energy metabolism such as obesity and diabetes. Here, we explore how lacking phosphatase, orphan 1 affects the skeletal metabolic networks of mice as a test approach for deploying network analysis in total-body PET. Methods We retrospectively analysed [18F]fluorodeoxyglucose total-body PET/CT images from six 13-week-old wild type mice, three 22-week-old wild type mice, and three 22-week-old Phospho1 −/− mice. Pearson correlation networks were created using the dynamic data from seven bone regions, with a Pearson threshold of r>0.6 (significant at p<0.005). Results The bone metabolic networks of 13-week-old wild type mice were found to robustly resist changes to the data from different PET measurements, increased noise, and shortened scan length. Key features were repeatedly observed, namely that all bones except the spine are highly inter-correlated, while the spine has minimal correlation to other bones. When networkanalysis was used to compare the three cohorts, the older wild type network had similar features to the young mouse, whereas the Phospho1−/− network had increased correlations across all bones. An all-cohort network separated the data into one part including only bones from the wild type mice (13 nodes) and one part only bones from the Phospho1 24 −/− mice (8 nodes, 95% separation purity). Within the wild type section, the same bone from each young and old mouse were correlated.Discussion We demonstrated network analysis is a promising method for studying whole-body PET, sensitive to dynamic details in the data without relying on assumptions or modelling. The proposed method could be applied to other total-body PET data – of healthy and diseased subjects, with different radiotracers, and more – to further elucidate tissue interactions at a systems level.<br/
Effect modification and interaction between ethnicity and socioeconomic factors in severe COVID-19:analyses of linked national data for Scotland
No full textOBJECTIVE: Minority ethnic groups disproportionately experienced adverse COVID-19 outcomes, partly a consequence of disproportionate exposure to socioeconomic disadvantage and high-risk occupations. We examined whether minority ethnic groups were also disproportionately vulnerable to the consequences of socioeconomic disadvantage and high-risk occupations in Scotland.DESIGN: We investigated effect modification and interaction between area deprivation, education and occupational risk and ethnicity (assessed as both a binary white vs non-white variable and a multi-category variable) in relation to severe COVID-19 (hospitalisation or death). We used electronic health records linked to the 2011 census and Cox proportional hazards models, adjusting for age, sex and health board. We were principally concerned with additive interactions as a measure of vulnerability, estimated as the relative excess risk due to interaction (RERI).RESULTS: Analyses considered 3 730 837 individuals aged ≥16 years (with narrower age ranges for analyses focused on education and occupation). Severe COVID-19 risk was typically higher for minority ethnic groups and disadvantaged socioeconomic groups, but additive interactions were not consistent. For example, non-white ethnicity and highest deprivation level experienced elevated risk ((HR=2.7, 95% CI: 2.4, 3.2) compared with the white least deprived group. Additive interaction was not present (RERI=-0.1, 95% CI: -0.4, 0.2), this risk being less than the sum of risks of white ethnicity/highest deprivation level (HR=2.4, 95% CI: 2.3, 2.5) and non-white ethnicity/lowest deprivation level (1.4, 95% CI: 1.2, 1.7). Similarly, non-white ethnicity/no degree education (HR=2.5, 95% CI: 2.2, 2.7; RERI=-0.1, 95% CI: -0.4, 0.2) and non-white ethnicity/high-risk occupation (RERI=0.3, 95% CI: -0.2, 0.8) did not experience greater than additive risk. No clear evidence of effect modification was identified when using the multicategory ethnicity variable or on the multiplicative scale either.CONCLUSION: We found no definitive evidence that minority ethnic groups were more vulnerable to the effect of social disadvantage on the risk of severe COVID-19.</p
Access Repository Dashboard
Do you manage Edinburgh Research Explorer? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!