Prehospital critical care is associated with increased survival in adult trauma patients in Scotland

Background Scotland has three prehospital critical care teams (PHCCTs) providing enhanced care support to a usually paramedic-delivered ambulance service. The effect of the PHCCTs on patient survival following trauma in Scotland is not currently known nationally. Methods National registry-based retrospective cohort study using 2011-2016 data from the Scottish Trauma Audit Group. 30-day mortality was compared between groups after multivariate analysis to account for confounding variables. Results Our data set comprised 17 157 patients, with a mean age of 54.7 years and 8206 (57.5%) of male gender. 2877 patients in the registry were excluded due to incomplete data on their level of prehospital care, leaving an eligible group of 14 280. 13 504 injured adults who received care from ambulance clinicians (paramedics or technicians) were compared with 776 whose care included input from a PHCCT. The median Injury Severity Score (ISS) across all eligible patients was 9; 3076 patients (21.5%) met the ISS>15 criterion for major trauma. Patients in the PHCCT cohort were statistically significantly (all p < 0.01) more likely to be male; be transported to a prospective Major Trauma Centre; have suffered major trauma; have suffered a severe head injury; be transported by air and be intubated prior to arrival in hospital. Following multivariate analysis, the OR for 30-day mortality for patients seen by a PHCCT was 0.56 (95% CI 0.36 to 0.86, p=0.01). Conclusion Prehospital care provided by a physician-led critical care team was associated with an increased chance of survival at 30 days when compared with care provided by ambulance clinicians

Static Socio-Ecological COVID-19 Vulnerability Index and Vaccine Hesitancy Index for England

Background: Population characteristics can be used to infer vulnerability of communities to COVID-19, or to the likelihood of high levels of vaccine hesitancy. Communities harder hit by the virus, or at risk of being so, stand to benefit from greater resource allocation than their population size alone would suggest. This study reports a simple but efficacious method of ranking small areas of England by relative characteristics that are linked with COVID-19 vulnerability and vaccine hesitancy. Methods: Publicly available data on a range of characteristics previously linked with either poor COVID-19 outcomes or vaccine hesitancy were collated for all Middle Super Output Areas of England (MSOA, n=6790, excluding Isles of Scilly), scaled and combined into two numeric indices. Multivariable linear regression was used to build a parsimonious model of vulnerability (static socio-ecological vulnerability index, SEVI) in 60% of MSOAs, and retained variables were used to construct two simple indices. Assuming a monotonic relationship between indices and outcomes, Spearman correlation coefficients were calculated between the SEVI and cumulative COVID-19 case rates at MSOA level in the remaining 40% of MSOAs over periods both during and out with national lockdowns. Similarly, a novel vaccine hesitancy index (VHI) was constructed using population characteristics aligned with factors identified by an Office for National Statistics (ONS) survey analysis. The relationship between the VHI and vaccine coverage in people aged 12+years (as of 2021-06-24) was determined using Spearman correlation. The indices were split into quintiles, and MSOAs within the highest vulnerability and vaccine hesitancy quintiles were mapped. Findings: The SEVI showed a moderate to strong relationship with case rates in the validation dataset across the whole study period, and for every intervening period studied except early in the pandemic when testing was highly selective. The SEVI was more strongly correlated with case rates than any of its domains (rs 0·59 95% CI 0.57-0.62) and outperformed an existing MSOA-level vulnerability index. The VHI was significantly negatively correlated with COVID-19 vaccine coverage in the validation data at the time of writing (rs -0·43 95% CI -0·46 to -0·41). London had the largest number and proportion of MSOAs in quintile 5 (most vulnerable/hesitant) of SEVI and VHI concurrently. Interpretation: The indices presented offer an efficacious way of identifying geographical disparities in COVID-19 risk, thus helping focus resources according to need. Funding: Funder: Integrated Covid Hub North East Award number: n/a Grant recipient: Fiona Matthew

First Operation of a Resistive Shell Liquid Argon Time Projection Chamber -- A new Approach to Electric-Field Shaping

We present a new technology for the shaping of the electric field in Time Projection Chambers (TPCs) using a carbon-loaded polyimide foil. This technology allows for the minimisation of passive material near the active volume of the TPC and thus is capable to reduce background events originating from radioactive decays or scattering on the material itself. Furthermore, the high and continuous electric resistivity of the foil limits the power dissipation per unit area and minimizes the risks of damages in the case of an electric field breakdown. Replacing the conventional field cage with a resistive plastic film structure called 'shell' decreases the number of components within the TPC and therefore reduces the potential points of failure when operating the detector. A prototype liquid argon (LAr) TPC with such a resistive shell and with a cathode made of the same material was successfully tested for long term operation with electric field values up to about 1.5 kV/cm. The experiment shows that it is feasible to successfully produce and shape the electric field in liquefied noble-gas detectors with this new technology.Comment: 13 page

Towards applying NMR relaxometry as a diagnostic tool for bone and soft tissue sarcomas : a pilot study

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 668119 (project “IDentIFY”). This work received support from the EURELAX COST Action CA15209, supported by COST (European Cooperation in Science and Technology). The authors would like to thank Professor David Lurie for his continuous support.Peer reviewedPublisher PD

Can vaccination roll-out be more equitable if population risk is taken into account?

Background COVID-19 vaccination in many countries, including England, has been prioritised primarily by age. However, people of the same age can have very different health statuses. Frailty is a commonly used metric of health and has been found to be more strongly associated with mortality than age among COVID-19 inpatients. Methods We compared the number of first vaccine doses administered across the 135 NHS Clinical Commissioning Groups (CCGs) of England to both the over 50 population and the estimated frail population in each area. Area-based frailty estimates were generated using the English Longitudinal Survey of Ageing (ELSA), a national survey of older people. We also compared the number of doses to the number of people with other risk factors associated with COVID- 19: Atrial fibrillation, chronic kidney disease, diabetes, learning disabilities, obesity and smoking status. Results We estimate that after 79 days of the vaccine program, across all Clinical Commissioning Group areas, the number of people who received a first vaccine per frail person ranged from 4.4 (95% CI 4.0-4.8) and 20.1 (95% CI 18.3-21.9). The prevalences of other risk factors were also poorly associated with the prevalence of vaccination across England. Conclusions Vaccination with age-based priority created area-based inequities in the number of doses administered relative to the number of people who are frail or have other risk factors associated with COVID-19. As frailty has previously been found to be more strongly associated with mortality than age for COVID-19 inpatients, an age-based priority system may increase the risk of mortality in some areas during the vaccine roll-out period. Authorities planning COVID-19 vaccination programmes should consider the disadvantages of an age-based priority system

Comparing and combining process-based crop models and statistical models with some implications for climate change

We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model