2,574 research outputs found
Multiple source direction of arrival estimation using subspace pseudointensity vectors
The recently proposed subspace pseudointensity method for direction of
arrival estimation is applied in the context of Tasks 1 and 2 of the LOCATA
Challenge using the Eigenmike recordings. Specific implementation details are
described and results reported for the development dataset, for which the
ground truth source directions are available. For both single and multiple
source scenarios, the average absolute error angle is about 9 degrees.Comment: In Proceedings of the LOCATA Challenge Workshop - a satellite event
of IWAENC 2018 (arXiv:1811.08482
Cardioverting acute atrial fibrillation and the risk of thromboembolism: not all patients are created equal
Current guidelines support the well-established clinical practice that patients who present with atrial fibrillation (AF) of less than 48Â hours duration should be considered for cardioversion, even in the absence of pre-existing anticoagulation. However, with increasing evidence that short runs of AF confer significant risk of stroke, on what evidence is this 48-hour rule based and is it time to adopt a new approach? We review existing evidence and suggest a novel approach to risk stratification in this setting. Overall, the risk of thromboembolism associated with acute cardioversion of patients with AF that is estimated to be of <48Â hours duration is low. However, this risk varies widely depending on patient characteristics. From existing evidence, we show that using the CHA2DS2-VASc score may allow better selection of appropriate patients in order to prevent exposing specific patient groups to an unacceptably high risk of a potentially devastating complication
The Scottish school leavers cohort: linkage of education data to routinely collected records for mortality, hospital discharge and offspring birth characteristics
Purpose: The Scottish school leavers cohort provides population-wide prospective follow-up of local authority secondary school leavers in Scotland through linkage of comprehensive education data with hospital and mortality records. It considers educational attainment as a proxy for socioeconomic position in young adulthood and enables the study of associations and causal relationships between educational attainment and health outcomes in young adulthood.
Participants: Education data for 284 621 individuals who left a local authority secondary school during 2006/2007–2010/2011 were linked with birth, death and hospital records, including general/acute and mental health inpatient and day case records. Individuals were followed up from date of school leaving until September 2012. Age range during follow-up was 15 years to 24 years.
Findings: to date Education data included all formal school qualifications attained by date of school leaving; sociodemographic information; indicators of student needs, educational or non-educational support received and special school unit attendance; attendance, absence and exclusions over time and school leaver destination. Area-based measures of school and home deprivation were provided. Health data included dates of admission/discharge from hospital; principal/secondary diagnoses; maternal-related, birth-related and baby-related variables and, where relevant, date and cause of death. This paper presents crude rates for all-cause and cause-specific deaths and general/acute and psychiatric hospital admissions as well as birth outcomes for children of female cohort members.
Future plans: This study is the first in Scotland to link education and health data for the population of local authority secondary school leavers and provides access to a large, representative cohort with the ability to study rare health outcomes. There is the potential to study health outcomes over the life course through linkage with future hospital and death records for cohort members. The cohort may also be expanded by adding data from future school leavers. There is scope for linkage to the Prescribing Information System and the Scottish Primary Care Information Resource
A comparison of the Scottish index of multiple deprivation (SIMD) 2004 with the 2009 + 1 SIMD: does choice of measure affect the interpretation of inequality in mortality?
Background
There is a growing international literature assessing inequalities in health and mortality by area based measures. However, there are few works comparing measures available to inform research design. The analysis here seeks to begin to address this issue by assessing whether there are important differences in the relationship between deprivation and inequalities in mortality when measures that have been constructed at different time points are compared.
Methods
We contrast whether the interpretation of inequalities in all-cause mortality between the years 2008-10 changes in Scotland if we apply the earliest (2004) and the 2009 + 1 releases of the Scottish Index of Multiple Deprivation (SIMD) to make this comparison. The 2004 release is based on data from 2001/2 and the 2009 + 1 release is based on data from 2008/9. The slope index of inequality (SII) and 1:10 ratio are used to summarise inequalities standardised by age/sex using population and mortality records.
Results
The 1:10 ratio suggests some differences in the magnitude of inequalities measured using SIMD at different time points. However, the SII shows much closer correspondence.
Conclusions
Overall the findings show that substantive conclusions in relation to inequalities in all-cause mortality are little changed by the updated measure. This information is beneficial to researchers as the most recent measures are not always available. This adds to the body of literature showing stability in inequalities in health and mortality by geographical deprivation over time.</p
The impact on health of employment and welfare transitions for those receiving out-of-work disability benefits in the UK
Employment status has a dynamic relationship with health and disability. There has been a striking increase in the working age population receiving out-of-work disability benefits in many countries, including the UK. In response, recent UK welfare reforms have tightened eligibility criteria and introduced new conditions for benefit receipt linked to participation in return-to-work activities. Positive and negative impacts have been suggested but there is a lack of high quality evidence of the health impact when those receiving disability benefits move towards labour market participation. Using four waves of the UK’s Understanding Society panel survey (2009–2013) three different types of employment and welfare transition were analysed in order to identify their impact on health. A difference-in-difference approach was used to compare change between treatment and control groups in mental and physical health using the SF-12. To strengthen causal inference, sensitivity checks for common trends used pre-baseline data and propensity score matching. Transitions from disability benefits to employment (n = 124) were associated on average with an improvement in the SF12 mental health score of 5.94 points (95% CI = 3.52–8.36), and an improvement in the physical health score of 2.83 points (95% CI = 0.85–4.81) compared with those remaining on disability benefits (n = 1545). Transitions to unemployed status (n = 153) were associated with a significant improvement in mental health (3.14, 95% CI = 1.17–5.11) but not physical health. No health differences were detected for those who moved on to the new out-of-work disability benefit. It remains rare for disability benefit recipients to return to the labour market, but our results indicate that for those that do, such transitions may improve health, particularly mental health. Understanding the mechanisms behind this relationship will be important for informing policies to ensure both work and welfare are ‘good for health’ for this group
The image ray transform for structural feature detection
The use of analogies to physical phenomena is an exciting paradigm in computer vision that allows unorthodox approaches to feature extraction, creating new techniques with unique properties. A technique known as the "image ray transform" has been developed based upon an analogy to the propagation of light as rays. The transform analogises an image to a set of glass blocks with refractive index linked to pixel properties and then casts a large number of rays through the image. The course of these rays is accumulated into an output image. The technique can successfully extract tubular and circular features and we show successful circle detection, ear biometrics and retinal vessel extraction. The transform has also been extended through the use of multiple rays arranged as a beam to increase robustness to noise, and we show quantitative results for fully automatic ear recognition, achieving 95.2% rank one recognition across 63 subjects
Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland
It has been well documented that air pollution adversely affects health, and epidemiological pollutionhealth
studies utilise pollution data from automatic monitors. However, these automatic monitors are
small in number and hence spatially sparse, which does not allow an accurate representation of the spatial
variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide
(NO2) diffusion tubes are also used to measure concentrations, and due to their lower cost compared
to automatic monitors are much more prevalent. However, even combining both data sets still does not
provide sufficient spatial coverage of NO2 for epidemiological studies, and modelled concentrations on a
regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling
approach to using all three sources of NO2 data to make fine scale spatial predictions for use in
epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO2
concentrations from both automatic monitors and diffusion tubes against modelled NO2 concentrations
from an atmospheric dispersion model in order to predict fine scale NO2 concentrations across our West
Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of
NO2 compared to using the automatic monitors alone, and we use it to predict NO2 concentrations across
West Central Scotland in 2006
Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia
Objective: To explore patterns of health service use in the lead-up to, and following, admission for a ‘preventable’ hospitalisation.
Setting: 266 950 participants in the 45 and Up Study, New South Wales (NSW) Australia
Methods: Linked data on hospital admissions, general practitioner (GP) visits and other health events were used to create visual representations of health service use. For each participant, health events were plotted against time, with different events juxtaposed using different markers and panels of data. Various visualisations were explored by patient characteristics, and compared with a cohort of non-admitted participants matched on sociodemographic and health characteristics. Health events were displayed over calendar year and in the 90 days surrounding first preventable hospitalisation.
Results: The visualisations revealed patterns of clustering of GP consultations in the lead-up to, and following, preventable hospitalisation, with 14% of patients having a consultation on the day of admission and 27% in the prior week. There was a clustering of deaths and other hospitalisations following discharge, particularly for patients with a long length of stay, suggesting patients may have been in a state of health deterioration. Specialist consultations were primarily clustered during the period of hospitalisation. Rates of all health events were higher in patients admitted for a preventable hospitalisation than the matched non-admitted cohort.
Conclusions: We did not find evidence of limited use of primary care services in the lead-up to a preventable hospitalisation, rather people with preventable hospitalisations tended to have high levels of engagement with multiple elements of the healthcare system. As such, preventable hospitalisations might be better used as a tool for identifying sicker patients for managed care programmes. Visualising longitudinal health data was found to be a powerful strategy for uncovering patterns of health service use, and such visualisations have potential to be more widely adopted in health services research
How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging
The long-term impact of air pollution on human health can be estimated from small-area ecological studies in which the health outcome is regressed against air pollution concentrations and other covariates, such as socio-economic deprivation. Socio-economic deprivation is multi-factorial and difficult to measure, and includes aspects of income, education, and housing as well as others. However, these variables are potentially highly correlated, meaning one can either create an overall deprivation index, or use the individual characteristics, which can result in a variety of pollution-health effects. Other aspects of model choice may affect the pollution-health estimate, such as the estimation of pollution, and spatial autocorrelation model. Therefore, we propose a Bayesian model averaging approach to combine the results from multiple statistical models to produce a more robust representation of the overall pollution-health effect. We investigate the relationship between nitrogen dioxide concentrations and cardio-respiratory mortality in West Central Scotland between 2006 and 2012
Carstairs Scores for Scottish Postcode Sectors, Datazones and Output Areas from the 2011 Census
Carstairs deprivation scores, originally created in 1981, provide a measure of material deprivation. Four census variables (male unemployment, no car ownership, overcrowding and low social class) were used in the creation of the score. As near as possible the same four variables have been used to update Carstairs scores decennially, despite changes to the definition of some of the variables over time. Researchers at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow have now updated Carstairs scores for 2011 for Scottish postcode sectors and for the first time datazones and output areas
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