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We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments. [ABSTRACT FROM AUTHOR]

Background Hybrid theatres facilitate higher quality angiography and simultaneous employment of open and endovascular techniques. We compared treatment approaches and radiation exposure following hybrid theatre introduction in January 2016. Methods 6-year retrospective review of all aortic interventions (January 2015 - March 2021) at a single tertiary vascular unit, from a prospective operative database. 'Pre-hybrid' cases in traditional theatres were compared to those in the 'post-hybrid' period (hybrid and traditional theatres). Results From 3885 vascular procedures, there were 184 aortic cases in the pre-hybrid period and 886 post-hybrid (hybrid theatre n=539, traditional theatres n=369). Proportionally, endovascular procedures increased from 61% (pre-hybrid) to 97% (new hybrid theatre) (p < 0.05). Of the cases in traditional theatres, post hybrid introduction; 94% (347) open and 6% (22) endovascular or combined. 212 (40%) of all endovascular cases in the hybrid setting were complex (TEVAR, FEVAR, BEVAR & ChEVAR/ChEVAS). The average FEVAR DAP vastly reduced following hybrid introduction (403 vs 233 (Gy cm²) (p<0.005)). Conclusion The ratio of interventions clearly define a drive towards aortic endovascular approaches. Hybrid theatres facilitate a wider range of techniques for aortic procedures and significantly reduces radiation dosing in complex FEVAR. [ABSTRACT FROM AUTHOR]

Abstract Background Asthma is a common chronic respiratory inflammatory disease that adversely affects patients’ quality of life (QoL) and overall well-being. When asthma is not adequately controlled, there is a higher risk of exacerbations and hospitalizations, thereby increasing the direct and indirect costs associated with the treatment and productivity loss. Overreliance on SABA and underutilization of ICS in the management of asthma can result in suboptimal treatment and poor asthma control. Patients who visit the emergency department are more likely to have poorly controlled asthma. Ensuring that these patients are provided with an evidence-based treatment plan during discharge can help reduce the risk of future exacerbations and consequently reduce the burden on the UAE healthcare system. Methods A joint task force comprising experts from the Emirates Society of Emergency Medicine (ESEM) and Emirates Thoracic Society (ETS) reviewed published evidence and updated guidelines in asthma management to optimize the post-discharge recommendations. Results The ESEM-ETS experts’ joint task force has developed a step-by-step plan for emergency department/hospital discharge, which is based on the GINA 2023 guideline recommendations and the medications available in the UAE. By adhering to this structured plan, emergency department physicians can play a crucial role in improving asthma care, long-term patient outcomes, and the utilization of healthcare resources. Conclusions Prioritizing patient education and ensuring patients are equipped with the best-suited asthma treatment plans prior to discharge can help ED physicians improve patient outcomes and reduce healthcare resource utilization in UAE hospitals.

Computer models of intense, laser-driven ion acceleration require expensive particle-in-cell simulations that may struggle to capture all the multi-scale, multi-dimensional physics involved at reasonable costs. Explored is an approach to ameliorate this deficiency using a multi-fidelity framework that can incorporate physical trends and phenomena at different levels. As the basis for this study, an ensemble of approximately 8000 1D simulations was generated to buttress separate ensembles of hundreds of higher fidelity 1D and 2D simulations. Using transfer learning with deep neural networks, one can reproduce the results of more complex physics at a much lower cost. The networks trained in this fashion can, in turn, act as surrogate models for the simulations themselves, allowing for quick and efficient exploration of the parameter space of interest. Standard figures-of-merit were used as benchmarks such as the hot electron temperature, peak ion energy, conversion efficiency, and so on. We can rapidly identify and explore under what conditions differing fidelities become an important effect and search for outliers in feature space. [ABSTRACT FROM AUTHOR]

Oral cavity structures receive abundant perfusion from the branches of the external carotid artery. Although hemorrhage is a common complication of oral cancer, bleeding from a cancerous mouth can be a devastating event in the emergency department. Lingual artery embolization is a minimally invasive interventional radiology procedure that has rarely been reported in the literature. This case involves a patient with tongue cancer who experienced massive oral bleeding leading to cardiac arrest. Fortunately, the patient was successfully resuscitated, and spontaneous circulation was restored. Diagnostic angiography confirmed the presence of pseudoaneurysm in the lingual artery. Ultimately, bleeding was definitively controlled through bilateral lingual artery embolization. This case underscores the critical importance of a multidisciplinary approach involving emergency physicians, otolaryngologists, and interventional radiologists in managing complex vascular lesions in the head and neck. Furthermore, it contributes to the growing body of evidence supporting the use of embolization techniques as a valuable tool in the management of vascular lesions in the head and neck region.

Background: The non-vitamin K antagonist oral anticoagulants (NOACs) have become the mainstay anticoagulation therapy for patients requiring oral anticoagulants (OACs) in the Gulf Council Cooperation (GCC) countries. The frequency of NOAC-associated major bleeding is expected to increase in the Emergency Department (ED). Nonetheless, we still lack local guidelines and recommendations for bleeding management in the region. The present Delphi-based consensus aims to establish a standardized and evidence-based clinical care pathway for managing NOAC-associated major bleeding in the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE). Methods: We adopted a three-step modified Delphi method to develop evidence-based recommendations through two voting rounds and an advisory meeting between the two rounds. A panel of 11 experts from the KSA and UAE participated in the consensus development. Results: Twenty-eight statements reached the consensus level. These statements addressed key aspects of managing major bleeding events associated with NOACs, including the increased use of NOAC in clinical practice, clinical care pathways, and treatment options. Conclusion: The present Delphi consensus provides evidence-based recommendations and protocols for the management of NOAC-associated bleeding in the region. Patients with major NOAC-induced bleeding should be referred to a well-equipped ED with standardized management protocols. A multidisciplinary approach is recommended for establishing the association between NOAC use and major bleeding. Treating physicians should have prompt access to specific reversal agents to optimize patient outcomes. Real-world evidence and national guidelines are needed to aid all stakeholders involved in NOAC-induced bleeding management.

Objective: Emergency abdominal surgery has poorer outcomes and higher mortality rates, compared with elective surgery. Serious morbidity or mortality occurs in up to 40% of patients. No information is available with regard to the outcome of patients undergoing emergency abdominal surgery in rural Australia., Methods: Patients undergoing emergency abdominal surgery in a 110-bed rural surgical centre in South Australia over a 5 year period (January 2010-December 2014) were included in the study. Patient data were retrieved using the hospital database and review of patient records., Results: A total of 4396 general surgical emergency admissions was recorded. Emergency admissions without intervention, endoscopic intervention only, appendectomy, cholecystectomy or urological or gynaecological diagnoses were excluded from mortality analysis. The remaining 237 patients underwent major abdominal emergency surgery for bowel obstruction (benign and malignant: n = 143, 60%), injury/inflammation/perforation/peritonitis (n = 85, 36%) or haemorrhage/ischaemia (n = 9, 3.8%). Thirty- (n = 9) and 90- (n = 12) day mortality rates were 3.8% and 5.1%, respectively., Conclusion: Emergency abdominal surgery can be safely provided in non-metropolitan Australian centres, with a low 30-day mortality rate of 3.8% and a 90-day mortality rate of 5.1%. This compares well with results published by other national and international investigators., (© 2018 National Rural Health Alliance Ltd.)

Building highly nonlinear and nonparametric models is central to several state-of-the-art machine learning systems. Kernel methods form an important class of techniques that induce a reproducing kernel Hilbert space (RKHS) for inferring non-linear models through the construction of similarity functions from data. These methods are particularly preferred in cases where the training data sizes are limited and when prior knowledge of the data similarities is available. Despite their usefulness, they are limited by the computational complexity and their inability to support end-to-end learning with a task-specific objective. On the other hand, deep neural networks have become the de facto solution for end-to-end inference in several learning paradigms. In this paper, we explore the idea of using deep architectures to perform kernel machine optimization, for both computational efficiency and end-to-end inferencing. To this end, we develop the deep kernel machine optimization framework, that creates an ensemble of dense embeddings using Nyström kernel approximations and utilizes deep learning to generate task-specific representations through the fusion of the embeddings. Intuitively, the filters of the network are trained to fuse information from an ensemble of linear subspaces in the RKHS. Furthermore, we introduce the kernel dropout regularization to enable improved training convergence. Finally, we extend this framework to the multiple kernel case, by coupling a global fusion layer with pretrained deep kernel machines for each of the constituent kernels. Using case studies with limited training data, and lack of explicit feature sources, we demonstrate the effectiveness of our framework over conventional model inferencing techniques.

Objective: To explore the risk factors for ward and paediatric assessment unit (PAU) admissions from the emergency department (ED)., Design: Prospective observational study., Setting and Patients: Febrile children attending a large tertiary care ED during the winter of 2014-2015., Main Outcome Measures: Ward and PAU admissions, National Institute for Health and Care Excellence (NICE) guidelines classification, reattendance to the ED within 28 days and antibiotic use., Results: A total of 1097 children attending the children's ED with fever were analysed. Risk factors for PAU admission were tachycardia (RR=1.1, 95% CI (1 to 1.1)), ill-appearance (RR=2.2, 95% CI (1.2 to 4.2)), abnormal chest findings (RR=2.1, 95% CI (1.2 to 4.3)), categorised as NICE amber (RR 1.7 95% CI (1.2 to 2.5)). There was a 30% discordance between NICE categorisation at triage and statistical internal validation. Predictors of ward admission were a systemic (RR=6.9, 95% CI (2.4 to 19.8)) or gastrointestinal illness (RR=3.8, 95% (1.4 to 10.4)) and categorised as NICE Red (RR=5.9, 95% CI (2.2 to 15.3)). Only 51 children had probable bacterial pneumonia (4.6%), 52 children had a proven urinary tract infection (4.2%), with just 2 (0.2%) positive blood cultures out of 485 (44%) children who received an antibiotic. 15% of all children reattended by 28 days and were more likely to have been categorised as Amber and had investigations on initial visit., Conclusions: Risk factors for PAU and ward admissions are different in this setting with high reattendance rates and very low proportion of confirmed/probable serious bacterial infections. Future studies need to focus on reducing avoidable admissions and antibiotic treatment., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)