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Abstract On-street parking is a commonly used form of parking facility as part of transportation infrastructure. However, the emergence of connected and autonomous vehicles (CAVs) is expected to significantly impact parking in the future. This study aims to investigate the impacts of on-street parking regulations for CAVs on the environment, safety and mobility in mixed traffic fleets. To achieve this goal, a calibrated and validated network model of the city of Leicester, UK, was selected to test the implementation of CAVs under various deployment scenarios. The results revealed that replacing on-street parking with driving lanes, cycle lanes, and public spaces can lead to better traffic performance. Specifically, there could be a 27–30% reduction in travel time, a 43–47% reduction in delays, more than 90% in emission reduction, and a 94% reduction in traffic crashes compared to the other tested measures. Conversely, replacing on-street parking with pick-up/drop-off stations may have a less significant impact due to increased stop-and-go events when vehicles pick-up and drop-off passengers, resulting in more interruptions in the flow and increased delays. The paper provides examples of interventions that can be implemented for on-street parking during a CCAM era, along with their expected impacts in order for regional decision-makers and local authorities to draw relative policies. By replacing on-street parking with more efficient traffic measures, cities can significantly improve mobility, reduce emissions, and enhance safety.

Despite advancements in road safety, Powered Two-Wheelers (PTWs) remain a vulnerable group with disproportionately high crash rates. This paper presents an in-depth analysis of PTW crashes in six European countries, with a case study of Loss of Control in Curves (LoCC), to address the gap between crash causation and prevention. By examining crash causation factors and their linkage to prevention strategies, the study illustrates various approaches for connecting causes and countermeasures. These approaches, which are applicable to different crash scenarios, include looking forward in the crash causation chains, looking backward, looking at only the last cause (critical events), or the first cause, or following a systemic approach. The research introduces a set of guidelines following the safe system approach, aiming to enhance the understanding of crash prevention among policymakers. The systemic approach to countermeasures, bridges the shortcomings of traditional crash causation studies that may exhibit bias or a narrow focus on “root causes”. The proposed approach emphasizes the need for a comprehensive view of crash scenarios (i.e., considering the entire crash causation chain or multiple causation chains) and ensuring that preventive measures address the full spectrum of the system. It also takes in to account external factors such as cost, benefits, and politics, leading to improved road safety outcomes. The study findings are significant for researchers, since it is a step forward in in-depth crash causation studies, as well as road practitioners and policymakers, in providing a strategic framework for more effective and efficient road safety interventions.

Orientation: Industrial Psychologists (IPs) could significantly benefit from integrating neuroscientific evidence into their practices, provided they critically engage with scholarly research rather than rely on unsupported assertions. Research purpose: The study aimed to assess the prevalence of neuroscientific misconceptions among IPs, student psychologists, and intern psychologists in South Africa as well as advocate for enhanced foundational knowledge in applied organisational neuroscience within industrial psychology. Motivation for the study: The emerging field of organisational neuroscience, which applies brain science to workplace behaviour, is particularly vulnerable to misconceptions that could hinder its development. Research approach/design and method: Using a cross-sectional survey, this research evaluated the knowledge of neuro misconceptions at one point in time within a convenience sample of (n = 98), consisting of registered student psychologists (n = 7; 7%), intern psychologists (n = 8; 10%), and IPs (n = 83; 85%). Main findings: Results indicated that this sample endorses many neuromyth conceptions. There was significant disparity in the endorsement of misconceptions between those with and without neuroscientific training, highlighting a knowledge gap. Practical/managerial implications: These findings underscore the necessity for improved education in applied organisational neuroscience among IOPs, suggesting integration into training and education programs. Contribution/value-add: This pioneering study in South Africa emphasises the role of general knowledge, specific training in applied organisational neuroscience, and critical thinking in psychological research as key to combating neuromyths, marking a meaningful contribution to the field.

To investigate differences in the safety behaviours of distracted and non-distracted pedestrians crossing roads, an unobtrusive observational study was conducted in Leicestershire, UK. Video recordings were taken of 1409 pedestrians crossing roads at controlled and uncontrolled crossing sites, both on a university campus and in urbanised town centre locations. On average, 42% of pedestrians were visibly distracted while crossing, and distracted pedestrians demonstrated significantly fewer safety behaviours than non-distracted pedestrians. They generally took longer to cross the road and made fewer looks towards the traffic environment, particularly at controlled crossings. Of all distraction activities, talking to another pedestrian had the most negative impact on safety behaviours. The findings highlight areas requiring further investigation, including distraction behaviours such as engaging with other pedestrians and supervising children. The results also identify that controlled crossings may benefit from targeted interventions to improve pedestrian safety.

Summary: Background: Methotrexate (MTX) is the gold-standard first-line disease-modifying anti-rheumatic drug for juvenile idiopathic arthritis (JIA), despite only being either effective or tolerated in half of children and young people (CYP). To facilitate stratified treatment of early JIA, novel methods in machine learning were used to i) identify clusters with distinct disease patterns following MTX initiation; ii) predict cluster membership; and iii) compare clusters to existing treatment response measures. Methods: Discovery and verification cohorts included CYP who first initiated MTX before January 2018 in one of four UK multicentre prospective cohorts of JIA within the CLUSTER consortium. JADAS components (active joint count, physician (PGA) and parental (PGE) global assessments, ESR) were recorded at MTX start and over the following year.Clusters of MTX ‘response’ were uncovered using multivariate group-based trajectory modelling separately in discovery and verification cohorts. Clusters were compared descriptively to ACR Pedi 30/90 scores, and multivariate logistic regression models predicted cluster-group assignment. Findings: The discovery cohorts included 657 CYP and verification cohorts 1241 CYP. Six clusters were identified: Fast improvers (11%), Slow Improvers (16%), Improve-Relapse (7%), Persistent Disease (44%), Persistent PGA (8%) and Persistent PGE (13%), the latter two characterised by improvement in all features except one. Factors associated with clusters included ethnicity, ILAR category, age, PGE, and ESR scores at MTX start, with predictive model area under the curve values of 0.65–0.71. Singular ACR Pedi 30/90 scores at 6 and 12 months could not capture speeds of improvement, relapsing courses or diverging disease patterns. Interpretation: Six distinct patterns following initiation of MTX have been identified using methods in artificial intelligence. These clusters demonstrate the limitations in traditional yes/no treatment response assessment (e.g., ACRPedi30) and can form the basis of a stratified medicine programme in early JIA. Funding: Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children's Charity, Olivia’s Vision, and the National Institute for Health Research.

There have been strong calls in the research literature for the adoption of system-based approaches to further reduce road casualties. However, person-based approaches remain at the forefront of both national and local-level decision-making around road safety in the UK. Focusing on person-based approaches inhibits learning across the system. Practical examples are needed to support adoption of system-based approaches and ensure safety learning is maximised within the industry.This study builds on previous work (Staton et al., 2022) mapping the control structure for the municipal area of Cambridgeshire, UK. It utilizes a system-based accident investigation method: Causal Analysis based on System Theory (CAST) (Leveson, 2019). The method is based on Rasmussen’s Risk Management Framework and is used to identify weaknesses in the control structure across the entire sociotechnical system. This supports understanding why the collision occurred and prevention of similar future events, rather than apportioning blame. In the study, CAST is used to investigate a random sample of ten fatal collisions that occurred in Cambridgeshire between 2018 and 2020. The investigations were conducted retrospectively using police forensic collision investigation files that had already concluded crown or coroner’s court proceedings.Across all ten collisions investigated, 21 different types of actor were identified across all levels of the system, each of whom played some role in at least one of the collisions. As a result, 49 specific recommendations are made concerning these actor’s roles in preventing future road deaths and serious injuries. In addition, 11 system-wide recommendations are made relating to communication and coordination; the safety information system; safety culture; design of the safety management system; changes and dynamics over time; and economic factors in the system environment.This study demonstrates that the CAST method is a viable tool for learning in the road safety industry and provides a taxonomy of system hazards, alongside the system control structure from Staton et al. (2022), to support any future analysis using this method. The use of CAST identifies the importance of controls within the road transport system and that currently, despite having one of the best road safety records in the world, the existing controls in place in the UK are insufficient to prevent serious injury and death occurring daily and are in danger of being eroded further through a political agenda of deregulation.This study reinforces that road safety requires system-based approaches and the strength of the CAST method in identifying system-wide recommendations which can be used in support of a Safe System approach to provide recommendations across the Safe System pillars.

BackgroundCOVID-19 data have been generated across the United Kingdom as a by-product of clinical care and public health provision, as well as numerous bespoke and repurposed research endeavors. Analysis of these data has underpinned the United Kingdom’s response to the pandemic, and informed public health policies and clinical guidelines. However, these data are held by different organizations, and this fragmented landscape has presented challenges for public health agencies and researchers as they struggle to find relevant data to access and interrogate the data they need to inform the pandemic response at pace. ObjectiveWe aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR). MethodsA federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners’ pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers’ secure environments, and to support federated cohort discovery queries and meta-analysis. ResultsA total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom. ConclusionsCO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures.

Abstract Background Fragmentation and habitat loss can restrict species movement and reduce connectivity, negatively impacting biodiversity. Characterising the overall connectivity of an area can inform better management of human modified landscapes. Contemporary connectivity modelling methods seldom incorporate fine-scale movement patterns associated with movement between fine-scaled structural connectivity elements such as scattered trees, roadside corridors and small patches of habitat. This study aims to characterise connectivity within the Karuah-Myall catchments, a typical woodland ecosystem that is fragmented by agriculture, using least-cost path analysis and a graph-theoretic approach; it focuses on how fine-scaled vegetation such as scattered trees support connectivity. We mapped scattered (and paddock) trees within this agricultural landscape where the main human modified land use was pasture. We modelled connectivity for a general representative woodland species using an interpatch dispersal distance and gap crossing threshold, and resistance from different land cover types. The gap crossing distance threshold was used to model movement between fine-scaled vegetation features. We compared the least-cost paths modelled with and without scattered trees. Results Our results show that by excluding scattered trees, least-cost paths across the cleared pasture landscape did not reflect the types of movement patterns typically observed from field studies, such as those associated with a foray-search strategy used by small and medium mammals and birds. The modelling also shows that the Karuah-Myall catchments are well connected and provide value to biodiversity beyond the catchment borders, by connecting coastal vegetation to the Great Eastern Ranges national wildlife corridor initiative. Conclusion Connectivity models that exclude fine-scale landscape features such as scattered trees and small, linear patches risk misrepresenting connectivity patterns. Models of regional-scale connectivity can be influenced by the presence or absence of even the smallest features, such as scattered trees.

Abstract Group B Streptococcus (GBS) remains the most common Gram‐positive bacterium causing neonatal meningitis and GBS meningitis continues to be an important cause of mortality and morbidity. In this study, we showed that GBS penetration into the brain occurred initially in the meningeal and cortex capillaries, and exploits a defined host cell signaling network comprised of S1P2, EGFR, and CysLT1. GBS exploitation of such network in penetration of the blood–brain barrier was demonstrated by targeting S1P2, EGFR, and CysLT1 using pharmacological inhibition, gene knockout and knockdown cells, and gene knockout animals, as well as interrogation of the network (up‐ and downstream of each other). More importantly, counteracting such targets as a therapeutic adjunct to antibiotic therapy was beneficial in improving the outcome of animals with GBS meningitis. These findings indicate that investigating GBS penetration of the blood–brain barrier provides a novel approach for therapeutic development of GBS meningitis.

Background Population-level information on dispensed medication provides insight on the distribution of treated morbidities, particularly if linked to other population-scale data at an individual-level. Objective To evaluate the impact of COVID-19 on dispensing patterns of medications. Methods Retrospective observational study using population-scale, individual-level dispensing records in Wales, UK. Total dispensed drug items for the population between 1st January 2016 and 31st December 2019 (3-years, pre-COVID-19) were compared to 2020 with follow up until 27th July 2021 (COVID-19 period). We compared trends across all years and British National Formulary (BNF) chapters and highlighted the trends in three major chapters for 2019-21: 1-Cardiovascular system (CVD); 2-Central Nervous System (CNS); 3-Immunological & Vaccine. We developed an interactive dashboard to enable monitoring of changes as the pandemic evolves. Result Amongst all BNF chapters, 73,410,543 items were dispensed in 2020 compared to 74,121,180 items in 2019 demonstrating -0.96% relative decrease in 2020. Comparison of monthly patterns showed average difference (D) of -59,220 and average Relative Change (RC) of -0.74% between the number of dispensed items in 2020 and 2019. Maximum RC was observed in March 2020 (D= +1,224,909 and RC= +20.62%), followed by second peak in June 2020 (D= +257,920, RC= +4.50%). A third peak was observed in September 2020 (D= +264,138, RC= +4.35%). Large increases in March 2020 were observed for CVD and CNS medications across all age groups. The Immunological and Vaccine products dropped to very low levels across all age groups and all months (including the March dispensing peak). Conclusions Reconfiguration of routine clinical services during COVID-19 led to substantial changes in community pharmacy drug dispensing. This change may contribute to a long-term burden of COVID-19, raising the importance of a comprehensive and timely monitoring of changes for evaluation of the potential impact on clinical care and outcomes.

IntroductionShort chain fatty acids (SCFA) are gut microbiota-derived metabolites that contribute to the gut-brain axis and may impact stroke outcomes following gut dysbiosis. We evaluated plasma SCFA concentrations against stroke severity parameters and identified SCFA-associated protein networks.MethodsThe Blood and Clot Thrombectomy Registry and Collaboration (BACTRAC), a continuously enrolling tissue bank, was used to obtain stroke samples. Arterial blood distal and proximal to the thrombus was obtained from Acute Ischemic Stroke (AIS) Patients (n=53) during thrombectomy. Patient demographics, stroke presentation and outcome parameters were reported. The SCFAs were isolated from proximal plasma via chemical derivatization UHPLC coupled tandem mass spectrometry using electrospray ionization and multiple reaction monitoring. Proteomic levels for 184 cardioembolic and inflammatory proteins was quantified from systemic and intracranial plasma by Olink. Arterial blood from cerebrovascular patients undergoing elective neurointerventional procedures was used as controls.ResultsAcetate positively correlated with time from last known normal (LKN) and was significantly lower in stroke patients compared to control. Isobutyrate, Butyrate and 2-Methylbutyrate negatively correlated with %ΔNIHSS. Isobutyrate and 2-Methylbutyrate positively correlated with NIHSS discharge. SCFA concentrations were not associated with NIHSS admission, infarct volume, or edema volume. Multiple SCFAs positively associated with systemic and pro-inflammatory cytokines, most notably IL-6, TNF-α, VCAM1, IL-17, and MCP-1.ConclusionsPlasma SCFA concentrations taken at time of stroke are not associated with stroke severity at presentation. However, higher levels of SCFAs at the time of stroke are associated with increased markers of inflammation, less recovery from admission to discharge, and worse symptom burden at discharge.

We introduce for the first time a new product line able to make high accuracy measurements of a number of water chemistry parameters in situ: i.e., submerged in the environment including in the deep sea (to 6,000 m). This product is based on the developments of in situ lab on chip technology at the National Oceanography Centre (NOC), and the University of Southampton and is produced under license by Clearwater Sensors Ltd., a start-up and industrial partner in bringing this technology to global availability and further developing its potential. The technology has already been deployed by the NOC, and with their partners worldwide over 200 times including to depths of ∼4,800 m, in turbid estuaries and rivers, and for up to a year in seasonally ice-covered regions of the arctic. The technology is capable of making accurate determinations of chemical and biological parameters that require reagents and which produce an electrical, absorbance, fluorescence, or luminescence signal. As such it is suitable for a wide range of environmental measurements. Whilst further parameters are in development across this partnership, Nitrate, Nitrite, Phosphate, Silicate, Iron, and pH sensors are currently available commercially. Theses sensors use microfluidics and optics combined in an optofluidic chip with electromechanical valves and pumps mounted upon it to mix water samples with reagents and measure the optical response. An overview of the sensors and the underlying components and technologies is given together with examples of deployments and integrations with observing platforms such as gliders, autonomous underwater vehicles and moorings.

Rationale Clinical trials are the gold standard for testing interventions. COVID-19 has further raised their public profile and emphasised the need to deliver better, faster, more efficient trials for patient benefit. Considerable overlap exists between data required for trials and data already collected routinely in electronic healthcare records (EHRs). Opportunities exist to use these in innovative ways to decrease duplication of effort and speed trial recruitment, conduct and follow-up.Approach The National Institute of Health Research (NIHR), Health Data Research UK and Clinical Practice Research Datalink co-organised a national workshop to accelerate the agenda for ‘data-enabled clinical trials’. Showcasing successful examples and imagining future possibilities, the plenary talks, panel discussions, group discussions and case studies covered: design/feasibility; recruitment; conduct/follow-up; collecting benefits/harms; and analysis/interpretation.Reflection Some notable studies have successfully accessed and used EHR to identify potential recruits, support randomised trials, deliver interventions and supplement/replace trial-specific follow-up. Some outcome measures are already reliably collected; others, like safety, need detailed work to meet regulatory reporting requirements. There is a clear need for system interoperability and a ‘route map’ to identify and access the necessary datasets. Researchers running regulatory-facing trials must carefully consider how data quality and integrity would be assessed. An experience-sharing forum could stimulate wider adoption of EHR-based methods in trial design and execution.Discussion EHR offer opportunities to better plan clinical trials, assess patients and capture data more efficiently, reducing research waste and increasing focus on each trial’s specific challenges. The short-term emphasis should be on facilitating patient recruitment and for postmarketing authorisation trials where research-relevant outcome measures are readily collectable. Sharing of case studies is encouraged. The workshop directly informed NIHR’s funding call for ambitious data-enabled trials at scale. There is the opportunity for the UK to build upon existing data science capabilities to identify, recruit and monitor patients in trials at scale.

Many countries around the world are creating COVID-19 trial datasets and databases of COVID-19-related data such as test results that cover entire populations. It is our strong recommendation, and sincere hope, that these data assets will be brought together through record linkage so that their scientific value and impact for society can be amplified. We call on trialists, data stewards and research funders to work together so that prospective linkage of trial data to medical databases becomes the norm, starting with COVID-19 trials.

Objective To evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK. Design and Outcome measures We evaluated evidence of six domains characterising a new field of science: • defining central scientific challenges, • demonstrating how the central challenges might be solved, • creating novel interactions among groups of scientists, • training new types of experts, • re-organising universities, • demonstrating impacts in society. We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools. Setting Four UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018. Results 1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens. Conclusion The Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.

The overuse of antimicrobials in primary care can be linked to an increased risk of antimicrobial-resistant bacteria for individual patients. Although there are promising signs of the benefits associated with Antimicrobial Stewardship Programs (ASPs) in hospitals and long-term care settings, there is limited knowledge in primary care settings and how to implement ASPs in these settings is unclear. In this context, a qualitative study was undertaken to explore the perceptions of primary care prescribers of the usefulness, feasibility, and experiences associated with the implementation of a pilot community-focused ASP intervention in three primary care clinics. Qualitative interviews were conducted with primary care clinicians, including local ASP champions, prescribers, and other primary health care team members, while they participated in an ASP initiative within one of three primary care clinics. An iterative conventional content analyses approach was used to analyze the transcribed interviews. Themes emerged around the key enablers and barriers associated with ASP implementation. Study findings point to key insights relevant to the scalability of community ASP activities with primary care providers.

Abstract Introduction The current safety situation for Powered Two Wheelers (PTW) within the EU is alarming. According to EU statistics, PTW riders account for 17% of all fatal road injuries in the region and twice as many fatalities per hundred thousand registered vehicles compared with occupants of cars. In recent years, too little attention has been given to Vulnerable Road Users (VRUs), including PTW users, in the development of Intelligent Transport Systems (ITS). Therefore, ITS should be developed that consider PTW riders an integral part of traffic; we focus on three systems that we believe have the potential to improve safety among PTW riders, namely Intersection Safety (INS), the Powered Two Wheeler oncoming vehicle information system (PTW2V), and the Vulnerable road user Beacon System (VBS). The present study aims to estimate quantitatively the safety impacts of the selected ITS for PTW riders in the EU-28, once the systems are fully adopted and meet selected future scenarios for 2020 and 2030. Method An ex-ante method suggested by Kulmala (Accident Analysis and Prevention 42:1359–1369, 2010) was further developed and applied to assess the safety impacts of ITS specifically designed for VRUs. As suggested by the method, the analysis started by determining the impact mechanisms through which the selected ITS systems affect the safety of PTW riders. Results According to the main results, all the systems we studied have a positive impact on PTW rider safety by preventing fatalities and injuries. The greatest effects, based on 2012 accident data and full penetration, could be attained by implementing PTW2V (283 fewer yearly fatalities) and INS (261 fewer yearly fatalities). The weakest effect was found with VBS (216 fewer yearly fatalities). Forecasts for 2030, also based on estimated accident trends and penetration rates, confirm an expected edge for INS and PTW2V in terms of safety.

This paper presents research into the area of public transport and accessibility, addressing the support of practitioners in achieving socially inclusive solutions to the mobility issues of diverse populations. For decades, social policy has been underpinned by a stereotyping of populations into simplified sub groups: old, young, disabled, etc. and thus solutions often fail to properly address the richness of human variability. These shortcomings are often ‘managed’ through the ability for people to adapt, however, this is not a sustainable way in which to build a socially inclusive transport infrastructure. A software design tool called HADRIAN is presented. This tool provides a means to evaluate designs for their physical inclusiveness through the use of a virtual user group. This virtual user group is the embodiment of over 100 people that can be used to assess an existing or proposed design and to gain an understanding of what may be done to improve its accommodation. A case study exploring the use of the tool is described together with work in exploring the correlation of the individuals within the HADRIAN system with data on the UK population as a whole and how the inclusion or exclusion of individuals with specific characteristics can be used to inform a more representative view of the inclusiveness of a design.

The microencapsulation of three model drugs; metronidazole, paracetamol and sulphapyridine into Poly (dl-Lactide-Co-Glycolide) (PLGA) scaffolds were probed using X-ray Powder Diffraction (XRPD). Changes in the diffraction patterns of the PLGA scaffolds after encapsulation was suggestive of a chemical interaction between the pure drugs and the scaffolds and not a physical intermixture.

Introduction New non-vitamin K Target Specific Oral Anticoagulants (TSOACs) have a favourable risk-benefit profile and debatable cost effectiveness. Large numbers and data from multiple countries in a European study are required to investigate safety issue of TSOACs in subgroups, e.g. people with an intracranial haemorrhage. Objectives and Approach We developed an approach to rapidly replicate data and analyses to support cross-country distributed research within the UK/EU using Electronic Health Records (EHRs). This project was conceptualised and initialled by linking relevant datasets held in multiple data warehouses, in Scotland with the Scottish National Data Safe Haven, and in Wales through the Secure Anonymised Information Linkage (SAIL) databank. Analysts in Edinburgh and Swansea had remote access to each other’s datasets and worked collaboratively to harmonise variables and analysis scripts. . A common R code script has been produced to harmonise individual data as well as the outputs from the study. Results The study screened data on 8M people to develop a cohort that included pseudonymised information of 4,153 individuals in Scotland and 2,676 individuals in Wales, 6,829 individuals in total. Standardised risk analyses were completed in both settings with ongoing work in combining the analyses. In Wales, 39.5% of the patients in the cohort had been admitted to hospitals due to serious vascular events or died caused by these events, after intracranial haemorrhage. Incident rates for male and female are 0.63 and 0.7 respectively. Within the cohort, 0.5% were prescribed with TSOACs and 3% with Warfarin (included as reference). The project is also in the process of including other European jurisdictions. Conclusion/Implications The adopted approach was the simplest, yet most efficient and cost-effective method to ensure consistency in analysis and coherence with currently available governance systems of both safe havens. It can also be considered as an initialisation of developing infrastructure to support research using EHRs across the UK and EU.

Clinical Presentation: A 59 year old male presented with a 1 day history of non-exertional chest pain that was pleuritic in nature and aggravated by lying flat. His chest pain symptoms were preceded by a one week history of “flu-like” symptoms. Physical exam demonstrated a blood pressure of 114/55 mmHg, heart rate of 75 bpm, and a normal oxygen saturation on room air. Cardiac examination revealed a biphasic pericardial rub vs. to-and-fro murmur. EKG demonstrated diffused ST-elevation and PR depression consistent with acute pericarditis. Laboratory findings revealed a normal WBC of 11.2×109/L and hsTnT of 78 ng/L. Imaging Findings: A point of care ultrasound (POCUS) assessment demonstrated mild aortic insufficiency with a dilated ascending aorta with no pericardial effusion or wall motion abnormalities. An expedited transthoracic echocardiography (TTE) confirmed a bicuspid aortic valve with moderate aortic insufficiency. The aortic root and ascending aorta were dilated at 50 and 52 mm, respectively. There was evidence of an aortic dissection flap prolapsing across the left ventricular outflow tract. A dissection flap was also visualized within the abdominal aorta consistent with a Type 1 aortic dissection. Computed tomography of the aorta confirmed the Type 1 aortic dissection and the patient underwent an urgent valve-sparing aortic root replacement procedure. Discussion Points: Despite a typical clinical presentation for acute pericarditis, any unexpected physical exam or laboratory findings should lead to a POCUS assessment. This case demonstrates a rare presentation of aortic dissection which could have been easily missed without a POCUS assessment. Here we propose an algorithm for a POCUS examination in setting of pleuritic chest pain consistent with pericarditis.