392 resultados para Injury Prediction.


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BACKGROUND Measurement of the global burden of disease with disability-adjusted life-years (DALYs) requires disability weights that quantify health losses for all non-fatal consequences of disease and injury. There has been extensive debate about a range of conceptual and methodological issues concerning the definition and measurement of these weights. Our primary objective was a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach. METHODS We surveyed respondents in two ways: household surveys of adults aged 18 years or older (face-to-face interviews in Bangladesh, Indonesia, Peru, and Tanzania; telephone interviews in the USA) between Oct 28, 2009, and June 23, 2010; and an open-access web-based survey between July 26, 2010, and May 16, 2011. The surveys used paired comparison questions, in which respondents considered two hypothetical individuals with different, randomly selected health states and indicated which person they regarded as healthier. The web survey added questions about population health equivalence, which compared the overall health benefits of different life-saving or disease-prevention programmes. We analysed paired comparison responses with probit regression analysis on all 220 unique states in the study. We used results from the population health equivalence responses to anchor the results from the paired comparisons on the disability weight scale from 0 (implying no loss of health) to 1 (implying a health loss equivalent to death). Additionally, we compared new disability weights with those used in WHO's most recent update of the Global Burden of Disease Study for 2004. FINDINGS 13,902 individuals participated in household surveys and 16,328 in the web survey. Analysis of paired comparison responses indicated a high degree of consistency across surveys: correlations between individual survey results and results from analysis of the pooled dataset were 0·9 or higher in all surveys except in Bangladesh (r=0·75). Most of the 220 disability weights were located on the mild end of the severity scale, with 58 (26%) having weights below 0·05. Five (11%) states had weights below 0·01, such as mild anaemia, mild hearing or vision loss, and secondary infertility. The health states with the highest disability weights were acute schizophrenia (0·76) and severe multiple sclerosis (0·71). We identified a broad pattern of agreement between the old and new weights (r=0·70), particularly in the moderate-to-severe range. However, in the mild range below 0·2, many states had significantly lower weights in our study than previously. INTERPRETATION This study represents the most extensive empirical effort as yet to measure disability weights. By contrast with the popular hypothesis that disability assessments vary widely across samples with different cultural environments, we have reported strong evidence of highly consistent results.

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Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

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Exploring the ethical issues present in professional practice within the field of sport, exercise and performance psychology, this case study outlines challenges that may be encountered, ways to address issues should they arise, and the overall ethical considerations of supporting injury rehabilitation within a dance training context.

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Transfusion-related acute lung injury (TRALI) has been the leading cause of transfusion-related morbidity and mortality in the UK and the USA in recent years. A threshold mechanism of TRALI has been proposed in which both patient factors (type and/or severity of clinical insult) and blood product factors (strength and/or concentration of antibodies or biological response modifiers) interact to surpass a threshold for TRALI development (Bux et al. Br J Haematol; 2007; 136: 788-99). The risk of developing antibody-mediated TRALI has been minimised by the introduction of risk-reduction strategies such as limiting the use of plasma from female donors. In contrast, there are no strategies currently in place to mitigate the development of non-antibody mediated TRALI as the mechanisms remain largely undefined. Previous studies have implicated non-polar lipids such as arachidonic acid and various species of hydroxyeicosatetranoic acid (HETE) in the development of non-antibody mediated TRALI (Silliman et al. Transfusion; 2011; 51: 2549-54), however the contribution of these lipids to the development of an inflammatory response in TRALI is poorly understood.

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Chronic difficulties arising from mild brain injury (TBI) are difficult to predict because the processes underlying changes after TBI are poorly understood. In mild brain injury the extent of neuropsychiatric and cognitive symptoms correspond poorly to overt tissue loss (Barth 1983; Liu 2010). Cellular, immune and hormonal cascades occurring after injury and continuing during the healing process may impact uninjured brain regions sensitive to the effects of physiological and emotional stress, which receive projections from the injury site. Changes in these most basic properties due to injury or disease have profound implications for virtually every aspect of brain function through disruption of neurotransmitter, neuroendocrine and metabolic systems. In order to screen for changes in transmitter and metabolic activity, in this study we developed Single voxel proton Magnetic Resonance Spectroscopy (1H-MRS) for use in both injured and control animals. We first evaluated if 1H-MRS could be used to evaluate in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus in both control and injured animals after controlled cortical impact injury to the rat prefrontal cortex. We found that metabolite measurements for Myo-Inositol, Choline, creatine, Glutamate+Glutamine, and N-acetyl-acetate are attainable in deep brain structures in vivo in injured and controls rats. We next seek to evaluate longitudinally, in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus during the first month after controlled cortical impact injury to the rat prefrontal cortex. These ongoing studies will provide data on the changes in transmitters and metabolites over time in injured and non-injured subjects. These studies address some of the fundamental questions about how mild brain injury has such diverse effects on overall brain health and function.

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Pedestrian crashes are one of the major road safety problems in developing countries representing about 40% of total fatal crashes in low income countries. Despite the fact that many pedestrian crashes in these countries occur at unsignalized intersections such as roundabouts, studies focussing on this issue are limited—thus representing a critical research gap. The objective of this study is to develop safety performance functions for pedestrian crashes at modern roundabouts to identify significant roadway geometric, traffic and land use characteristics related to pedestrian safety. To establish the relationship between pedestrian crashes and various causal factors, detailed data including various forms of exposure, geometric and traffic characteristics, and spatial factors such as proximity to schools and proximity to drinking establishments were collected from a sample of 22 modern roundabouts in Addis Ababa, Ethiopia, representing about 56% of such roundabouts in Addis Ababa. To account for spatial correlation resulting from multiple observations at a roundabout, both the random effect Poisson (REP) and random effect Negative Binomial (RENB) regression models were estimated and compared. Model goodness of fit statistics reveal a marginally superior fit of the REP model compared to the RENB model of pedestrian crashes at roundabouts. Pedestrian crossing volume and the product of traffic volumes along major and minor road had significant and positive associations with pedestrian crashes at roundabouts. The presence of a public transport (bus/taxi) terminal beside a roundabout is associated with increased pedestrian crashes. While the maximum gradient of an approach road is negatively associated with pedestrian safety, the provision of a raised median along an approach appears to increase pedestrian safety at roundabouts. Remedial measures are identified for combating pedestrian safety problems at roundabouts in the context of a developing country.

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Objective This study highlights the serious consequences of ignoring reverse causality bias in studies on compensation-related factors and health outcomes and demonstrates a technique for resolving this problem of observational data. Study Design and Setting Data from an English longitudinal study on factors, including claims for compensation, associated with recovery from neck pain (whiplash) after rear-end collisions are used to demonstrate the potential for reverse causality bias. Although it is commonly believed that claiming compensation leads to worse recovery, it is also possible that poor recovery may lead to compensation claims—a point that is seldom considered and never addressed empirically. This pedagogical study compares the association between compensation claiming and recovery when reverse causality bias is ignored and when it is addressed, controlling for the same observable factors. Results When reverse causality is ignored, claimants appear to have a worse recovery than nonclaimants; however, when reverse causality bias is addressed, claiming compensation appears to have a beneficial effect on recovery, ceteris paribus. Conclusion To avert biased policy and judicial decisions that might inadvertently disadvantage people with compensable injuries, there is an urgent need for researchers to address reverse causality bias in studies on compensation-related factors and health.

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Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

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Changing environments pose a serious problem to current robotic systems aiming at long term operation under varying seasons or local weather conditions. This paper is built on our previous work where we propose to learn to predict the changes in an environment. Our key insight is that the occurring scene changes are in part systematic, repeatable and therefore predictable. The goal of our work is to support existing approaches to place recognition by learning how the visual appearance of an environment changes over time and by using this learned knowledge to predict its appearance under different environmental conditions. We describe the general idea of appearance change prediction (ACP) and investigate properties of our novel implementation based on vocabularies of superpixels (SP-ACP). Our previous work showed that the proposed approach significantly improves the performance of SeqSLAM and BRIEF-Gist for place recognition on a subset of the Nordland dataset under extremely different environmental conditions in summer and winter. This paper deepens the understanding of the proposed SP-ACP system and evaluates the influence of its parameters. We present the results of a large-scale experiment on the complete 10 h Nordland dataset and appearance change predictions between different combinations of seasons.