Results from the third Scottish National Prevalence Survey: is a population health approach now needed to prevent healthcare-associated infections?

Summary Background Healthcare associated infections (HAI) are a major public health concern and a significant cause of morbidity and mortality. A robust and current evidence base that is specific to local, national and Europe-wide settings is necessary to inform the development of strategies to reduce HAI and contain antimicrobial resistance (AMR). Aim To measure the prevalence of HAI and antimicrobial prescribing and identify key priority areas for interventions to reduce the burden of infection. Methods A national rolling PPS in National Health Service (NHS) acute, NHS non-acute, NHS paediatric and independent hospitals was carried out between September and November 2016 using the European Centre for Disease Prevention and Control protocol designed for the European PPS. Findings The prevalence of HAI was 4.6%, 2.7% and 3.2% in acute adults, paediatric and non-acute patient groups, respectively. The most common HAI types reported in adult patients were urinary tract infection and pneumonia. The prevalence of antimicrobial prescribing was 35.7%, 29.3% and 13.8% in acute adults, paediatric and non-acute patient groups, respectively. Respiratory, skin and soft tissue, gastrointestinal and urinary tract infections were the most common infections being treated at the time of survey. Conclusion HAI continues to be a public health concern in Scotland. UTI and pneumonia continue to place a significant burden on patients and on healthcare delivery, including those that develop in the community and require hospital admission. A broader population health approach which focuses on reducing the risk of infection upstream would reduce these infections in both community and hospital settings

Defect formation in superconducting rings: external fields and finite-size effects

Consistent with the predictions of Kibble and Zurek, scaling behaviour has been seen in the production of fluxoids during temperature quenches of superconducting rings. However, deviations from the canonical behaviour arise because of finite-size effects and stray external fields. Technical developments, including laser heating and the use of long Josephson tunnel junctions, have improved the quality of data that can be obtained. With new experiments in mind we perform large-scale 3D simulations of quenches of small, thin rings of various geometries with fully dynamical electromagnetic fields, at nonzero externally applied magnetic flux. We find that the outcomes are, in practice, indistinguishable from those of much simpler Gaussian analytical approximations in which the rings are treated as one-dimensional systems and the magnetic field fluctuation-free.Comment: 10 pages, 3 figures, presentation at QFS2012, to appear in JLT

An 8-Year, High-Resolution Reanalysis of Atmospheric CO2 Mixing Ratios Based on OCO-2 and GOSAT-ACOS Retrievals

The NASA GMAO (Global Modeling and Assimilation Office) reanalysis blends OCO-2 (Orbiting Carbon Observatory 2) and GOSAT-ACOS (Greenhouse Gases Observing Satellite-Atmospheric Carbon Observations from Space) retrievals (top) with GEOS (Goddard Earth Observing System) model predictions (bottom) to estimate the full 3D (three-dimensional) state of CO2 every 3 hours (middle). This poster describes monthly atmospheric growth rates derived from the reanalysis and an application to aircraft data with the potential to aid bias correction

Progress in Atmospheric Carbon Monitoring Using NASA's GEOS Model and Data from the OCO and GOSAT Missions

NASA's Global Modeling and Assimilation Office (GMAO) produces a variety of carbon products based the synthesis of satellite remote sensing data and outputs of the Goddard Earth Observing System (GEOS). This includes bottom-up surface fluxes due to fossil fuel emissions, biomass burning, terrestrial biospheric exchange, and ocean exchangeconstrained by measurements of nighttime lights, fire radiative power, normalized difference vegetation index, and ocean color. These fluxes are the basis of top-down estimates of carbon concentrations and fluxes. In particular, the GMAO system processes retrievals of column carbon dioxide (XCO2) from GOSAT and OCO-2 to produce a high-resolution, long-term global analysis of CO2 in three dimensions every 6 hours. Here, we discuss the potential applications of such products for satellite intercomparison and evaluation against independent, non-coincident data. We also highlight the ability to provide monthly global atmospheric growth rates inferred from the assimilated CO2 concentration product. Finally, we discuss the challenges facing such products including bias correction and the estimation and analysis of model transport errors

Using keystroke logging to understand writers’ processes on a reading-into-writing test

Background Integrated reading-into-writing tasks are increasingly used in large-scale language proficiency tests. Such tasks are said to possess higher authenticity as they reflect real-life writing conditions better than independent, writing-only tasks. However, to effectively define the reading-into-writing construct, more empirical evidence regarding how writers compose from sources both in real-life and under test conditions is urgently needed. Most previous process studies used think aloud or questionnaire to collect evidence. These methods rely on participants’ perceptions of their processes, as well as their ability to report them. Findings This paper reports on a small-scale experimental study to explore writers’ processes on a reading-into-writing test by employing keystroke logging. Two L2 postgraduates completed an argumentative essay on computer. Their text production processes were captured by a keystroke logging programme. Students were also interviewed to provide additional information. Keystroke logging like most computing tools provides a range of measures. The study examined the students’ reading-into-writing processes by analysing a selection of the keystroke logging measures in conjunction with students’ final texts and interview protocols. Conclusions The results suggest that the nature of the writers’ reading-into-writing processes might have a major influence on the writer’s final performance. Recommendations for future process studies are provided

Wheat potential yield trials 1980

80C34, 80TS9, 80BA4, 80WH8, 80KA7, 80N20, 80E41

Divergent confidence intervals among pre-specified analyses in the HiSTORIC stepped wedge trial:an exploratory post-hoc investigation

BACKGROUND: The high-sensitivity cardiac troponin on presentation to rule out myocardial infarction (HiSTORIC) study was a stepped-wedge cluster randomised trial with long before-and-after periods, involving seven hospitals across Scotland. Results were divergent for the binary safety endpoint (type 1 or type 4b myocardial infarction or cardiac death) across certain pre-specified analyses, which warranted further investigation. In particular, the calendar-matched analysis produced an odds ratio in the opposite direction to the primary logistic mixed-effects model analysis. METHODS: Several post-hoc statistical models were fitted to each of the co-primary outcomes of length of hospital stay and safety events, which included adjusting for exposure time, incorporating splines, and fitting a random time effect. We improved control of patient characteristics over time by adjusting for multiple additional covariates using different methods: direct inclusion, regression adjustment for propensity score, and weighting. A data augmentation approach was also conducted aiming to reduce the effect of sparse data bias. Finally, the raw data was examined. RESULTS: The new statistical models confirmed the results of the pre-specified trial analysis. In particular, the observed divergence between the calendar-matched and other analyses remained, even after performing the covariate adjustment methods, and after using data augmentation. Divergence was particularly acute for the safety endpoint, which had an event rate of 0.36% overall. Examining the raw data was particularly helpful to assess the sensitivity of the results to small changes in event rates and identify patterns in the data. CONCLUSIONS: Our experience reveals the importance of conducting multiple pre-specified sensitivity analyses and examining the raw data, particularly for stepped wedge trials with low event rates or with a small number of sites. Before-and-after analytical approaches that adjust for differences in patient populations but avoid direct modelling of the time trend should be considered in future stepped wedge trials with similar designs