127 resultados para Environmental risk assessment


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Background: Appropriate disposition of emergency department (ED) patients with chest pain is dependent on clinical evaluation of risk. A number of chest pain risk stratification tools have been proposed. The aim of this study was to compare the predictive performance for major adverse cardiac events (MACE) using risk assessment tools from the National Heart Foundation of Australia (HFA), the Goldman risk score and the Thrombolysis in Myocardial Infarction risk score (TIMI RS). Methods: This prospective observational study evaluated ED patients aged ≥30 years with non-traumatic chest pain for which no definitive non-ischemic cause was found. Data collected included demographic and clinical information, investigation findings and occurrence of MACE by 30 days. The outcome of interest was the comparative predictive performance of the risk tools for MACE at 30 days, as analyzed by receiver operator curves (ROC). Results: Two hundred eighty-one patients were studied; the rate of MACE was 14.1%. Area under the curve (AUC) of the HFA, TIMI RS and Goldman tools for the endpoint of MACE was 0.54, 0.71 and 0.67, respectively, with the difference between the tools in predictive ability for MACE being highly significant [chi2 (3) = 67.21, N = 276, p < 0.0001]. Conclusion: The TIMI RS and Goldman tools performed better than the HFA in this undifferentiated ED chest pain population, but selection of cutoffs balancing sensitivity and specificity was problematic. There is an urgent need for validated risk stratification tools specific for the ED chest pain population.

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The contact lens industry has evolved and now provides many choices, including continuous wear, overnight orthokeratology, frequent-replacement lenses, daily-disposable lenses, and many alternatives in systems of care and maintenance. Epidemiologic studies to date have shown that how a lens is worn, particularly if worn overnight, can increase the risk of microbial keratitis. However, the risk of silicone hydrogel contact lenses worn on a continuous-wear basis has been evaluated only recently. This article summarizes the recent research data on extended-wear silicone hydrogel lenses and discusses the challenges of early evaluations of silicone hydrogel lens safety. Finally, the relevance of this information is discussed to practitioners and contact lens wearers making choices about the risks and benefits of different products and how they are used.

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The growing public concern about the complexity, cost and uncertain efficacy of the statuary environmental impact assessment process applying to large-scale projects in Queensland is reviewed. This is based on field data gathered over the past six years sat large-scale marina developments that access major environmental reserves along the coast. An ecological design proposal to broaden the process consisted with both government aspirations and regional ecological parameters - termed Regional Landscape Strategies - would allow the existing Environmental Impact Asessment to be modified alone potentially more practicable and effective lines.

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The trust and credibility gap between institutional regulators and the public is based on fundamental social and cultural differences related to power and authority. It is also associated with the 'distance' of a bureaucracies from those whom they serve. The nature of public concern about risk may be investigated by considering specific cognitive decision making 'rules' such as 'familiarity' of a hazard or 'voluntariness' of exposure. A more complete appreciation of the 'how' and 'why' of public response to danger from industrial hazards can be gained by appreciating these 'rules' within the broader context of mis-communication between 'elite' regulators and a highly diverse public. If the results of risk assessments are expressed in technical terms alone, it is unlikely that any real communication will occur. Further, if issues related to the 'remote' nature of much institutional decision making are not addressed, closure of the 'gap' may be difficult to bring about.

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One of the most important parts of any Bridge Management System (BMS) is the condition assessment and rating of bridges. This paper, introduces a procedure for condition assessment, based on criticality and vulnerability analysis. According to this procedure, new rating equations are developed. The inventory data is used to determine the contribution of different critical factors such as environmental effects, flood, earthquake, wind, and vehicle impacts. The criticality of the components to live load and vulnerability of the components to the above critical factors are identified. Based on the criticality and the vulnerability of the components and criticality of factors, and by using the new rating equations, the condition assessment and the rating of the railway bridges and their components at the network level will be conducted. This method for the first time incorporates structural analysis, available knowledge of risk assessment in structural engineering standards, and the experience of structural engineers in a practical way to enhance the reliability of the condition assessment and rating a network of bridges.

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Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

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Post-earthquake fire (PEF) is considered one of the most high risk and complicated problems affecting buildings in urban areas and can cause even more damage than the earthquake itself. However, most standards and codes ignore the implications of PEF and so buildings are not normally designed with PEF in mind. What is needed is for PEF factors to be routinely scrutinized and codified as part of the design process. A systematic application is presented as a means of mitigating the risk of PEF in urban buildings. This covers both existing buildings, in terms of retrofit solutions, and those yet to be designed, where a PEF factor is proposed. To ensure the mitigation strategy meets the defined criteria, a minimum time is defined – the safety guaranteed time target – where the safety of the inhabitants in a building is guaranteed.

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Early full-term pregnancy is one of the most effective natural protections against breast cancer. To investigate this effect, we have characterized the global gene expression and epigenetic profiles of multiple cell types from normal breast tissue of nulliparous and parous women and carriers of BRCA1 or BRCA2 mutations. We found significant differences in CD44+ progenitor cells, where the levels of many stem cell-related genes and pathways, including the cell-cycle regulator p27, are lower in parous women without BRCA1/BRCA2 mutations. We also noted a significant reduction in the frequency of CD44+p27+ cells in parous women and showed, using explant cultures, that parity-related signaling pathways play a role in regulating the number of p27+ cells and their proliferation. Our results suggest that pathways controlling p27+ mammary epithelial cells and the numbers of these cells relate to breast cancer risk and can be explored for cancer risk assessment and prevention.

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Bushfires are regular occurrences in the Australian landscape which can, under adverse weather conditions, give rise to losses of life, property, infrastructure, environmental and cultural values. Where property loss is involved, historical surveys of house losses have focussed on ember, radiant heat and flame contact as key bushfire attack mechanisms. Although often noted, little work has been done to quantify the impact of fire generated or fire enhanced wind and pyro-convective events on house loss and to improve construction practice within Australia. It is well known that strong winds are always associated with bushfire events. It is less well known, although increasingly shown through anecdotal evidence, that bushfires are not a passive companion of wind, but indeed they interact with winds and can together cause significant damages to exposed buildings and ecological structures. Previous studies have revealed the effects of wind, fire and structure interactions with the result of increased pressure coefficient distributions on the windward side of a building downstream of a fire front. This paper presents a further analysis of the result in relations to the relevant standards and fire weather conditions. A review of wind code and bushfire code was conducted. Based on the result of the current study, the authors believe it is necessary to consider wind as an attack mechanism in bushfire events. The results of the study will also have implications on bushfire emergency management, design of emergency shelters, perception of danger, emergency evacuation and on risk assessment.

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Effective response by government and individuals to the risk of land degradation requires an understanding of regional climate variations and the impacts of climate and management on condition and productivity of land and vegetation resources. Analysis of past land degradation and climate variability provides some understanding of vulnerability to current and future climate changes and the information needs for more sustainable management. We describe experience in providing climate risk assessment information for managing for the risk of land degradation in north-eastern Australian arid and semi-arid regions used for extensive grazing. However, we note that information based on historical climate variability, which has been relied on in the past, will now also have to factor in the influence of human-induced climate change. Examples illustrate trends in climate for Australia over the past decade and the impacts on indicators of resource condition. The analysis highlights the benefits of insights into past trends and variability in rainfall and other climate variables based on extended historic databases. This understanding in turn supports more reliable regional climate projections and decision support information for governments and land managers to better manage the risk of land degradation now and in the future.

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Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

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Objectives To estimate the burden of disease attributable to unsafe water, sanitation and hygiene (WSH) by age group for South Africa in 2000. Design World Health Organization comparative risk assessment methodology was used to estimate the disease burden attributable to an exposure by comparing the observed risk factor distribution with a theoretical lowest possible population distribution. A scenario-based approach was applied for estimating diarrhoeal disease burden from unsafe WSH. Six exposure scenarios were defined based on the type of water and sanitation infrastructure and environmental faecal-oral pathogen load. For ‘intestinal parasites’ and schistosomiasis, the burden was assumed to be 100% attributable to exposure to unsafe WSH. Setting South Africa. Outcome measures Disease burden from diarrhoeal diseases, intestinal parasites and schistosomiasis, measured by deaths and disability-adjusted life years (DALYs). Results 13 434 deaths were attributable to unsafe WSH accounting for 2.6% (95% uncertainty interval 2.4 - 2.7%) of all deaths in South Africa in 2000. The burden was especially high in children under 5 years, accounting for 9.3% of total deaths in this age group and 7.4% of burden of disease. Overall, the burden due to unsafe WSH was equivalent to 2.6% (95% uncertainty interval 2.5 - 2.7%) of the total disease burden for South Africa, ranking this risk factor seventh for the country. Conclusions Unsafe WSH remains an important risk factor for disease in South Africa, especially in children under 5. High priority needs to be given to the provision of safe and sustainable sanitation and water facilities and to promoting safe hygiene behaviours, particularly among children.