975 resultados para literature-data integration
Resumo:
Ultrasound (US) has become a useful tool in the detection of early disease, differential diagnosis, guidance of treatment decisions and treatment monitoring of rheumatoid arthritis (RA). In 2008, the Swiss Sonography in Arthritis and Rheumatism (SONAR) group was established to promote the use of US in inflammatory arthritis in clinical practice. A scoring system was developed and taught to a large number of Swiss rheumatologists who already contributed to the Swiss Clinical Quality Management (SCQM) database, a national patient register. This paper intends to give a Swiss consensus about best clinical practice recommendations for the use of US in RA on the basis of the current literature knowledge and experience with the Swiss SONAR score. Literature research was performed to collect data on current evidence. The results were discussed among specialists of the Swiss university centres and private practice, following a structured procedure. Musculoskelatal US was found to be very helpful in establishing the diagnosis and monitoring the evolution of RA, and to be a reliable tool if used by experienced examiners. It influences treatment decisions such as continuing, intensifying or stepping down therapy. The definite modalities of integrating US into the diagnosis and monitoring of RA treatments will be defined within a few years. There are, however, strong arguments to use US findings as of today in daily clinical care. Some practical recommendations about the use of US in RA, focusing on the diagnosis and the use of the SONAR score, are proposed.
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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.
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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.
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In line with educational issues involved in emergent literacy practices in preschool, in particular those concerning comprehension processes, this paper focuses on picture-based narrative comprehension during an interactive reading session of a wordless picture book, involving a group of children aged three and their teacher. Children are asked to make inferences about the meaning and outcome of the story, a procedure which gradually elicits their responses on how events link together, thus enhancing their capacity to use prior and implicit knowledge to build the story meaning. Moreover, this study highlights the importance of interaction for developing comprehension. Data collected was analysed following didactic microgenesis, an analytical approach showing that knowledge built during interaction depends on the joint construction of a zone of common meaning by which teacher and children try to adjust to each other. In order to help the process of merging different meanings of the story built online, a text written by researchers, following the narrative structure of the story, was read by the teacher after the picture-based reading. This led us to examine through interactional analysis which semiotic cues were used during recall on the following day, as an additional measure of knowledge construction.
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Background and Purpose-The safety and efficacy of thrombolysis in cervical artery dissection (CAD) are controversial. The aim of this meta-analysis was to pool all individual patient data and provide a valid estimate of safety and outcome of thrombolysis in CAD.Methods-We performed a systematic literature search on intravenous and intra-arterial thrombolysis in CAD. We calculated the rates of pooled symptomatic intracranial hemorrhage and mortality and indirectly compared them with matched controls from the Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register. We applied multivariate regression models to identify predictors of excellent (modified Rankin Scale=0 to 1) and favorable (modified Rankin Scale=0 to 2) outcome.Results-We obtained individual patient data of 180 patients from 14 retrospective series and 22 case reports. Patients were predominantly female (68%), with a mean +/- SD age of 46 +/- 11 years. Most patients presented with severe stroke (median National Institutes of Health Stroke Scale score=16). Treatment was intravenous thrombolysis in 67% and intra-arterial thrombolysis in 33%. Median follow-up was 3 months. The pooled symptomatic intracranial hemorrhage rate was 3.1% (95% CI, 1.3 to 7.2). Overall mortality was 8.1% (95% CI, 4.9 to 13.2), and 41.0% (95% CI, 31.4 to 51.4) had an excellent outcome. Stroke severity was a strong predictor of outcome. Overlapping confidence intervals of end points indicated no relevant differences with matched controls from the Safe Implementation of Thrombolysis in Stroke-International Stroke Thrombolysis Register.Conclusions-Safety and outcome of thrombolysis in patients with CAD-related stroke appear similar to those for stroke from all causes. Based on our findings, thrombolysis should not be withheld in patients with CAD. (Stroke. 2011;42:2515-2520.)
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As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).
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OBJECTIVE: To determine if the results of resin-dentin microtensile bond strength (µTBS) is correlated with the outcome parameters of clinical studies on non-retentive Class V restorations. METHODS: Resin-dentin µTBS data were obtained from one test center; the in vitro tests were all performed by the same operator. The µTBS testing was performed 8h after bonding and after 6 months of storing the specimens in water. Pre-test failures (PTFs) of specimens were included in the analysis, attributing them a value of 1MPa. Prospective clinical studies on cervical restorations (Class V) with an observation period of at least 18 months were searched in the literature. The clinical outcome variables were retention loss, marginal discoloration and marginal integrity. Furthermore, an index was formulated to be better able to compare the laboratory and clinical results. Estimates of adhesive effects in a linear mixed model were used to summarize the clinical performance of each adhesive between 12 and 36 months. Spearman correlations between these clinical performances and the µTBS values were calculated subsequently. RESULTS: Thirty-six clinical studies with 15 adhesive/restorative systems for which µTBS data were also available were included in the statistical analysis. In general 3-step and 2-step etch-and-rinse systems showed higher bond strength values than the 2-step/3-step self-etching systems, which, however, produced higher values than the 1-step self-etching and the resin modified glass ionomer systems. Prolonged water storage of specimens resulted in a significant decrease of the mean bond strength values in 5 adhesive systems (Wilcoxon, p<0.05). There was a significant correlation between µTBS values both after 8h and 6 months of storage and marginal discoloration (r=0.54 and r=0.67, respectively). However, the same correlation was not found between µTBS values and the retention rate, clinical index or marginal integrity. SIGNIFICANCE: As µTBS data of adhesive systems, especially after water storage for 6 months, showed a good correlation with marginal discoloration in short-term clinical Class V restorations, longitudinal clinical trials should explore whether early marginal staining is predictive for future retention loss in non-carious cervical restorations.
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The Huqf Supergroup in Oman contains an exceptionally well-preserved and complete sedimentary record of the Middle to Late Neoproterozoic Era. Outcrops of the Huqf Supergroup in northern and central Oman are now well documented, but their correlation with a key succession in the Mirbat area of southern Oman, containing a sedimentary record of two Neoproterozoic glaciations, is poorly understood. Integration of lithostratigraphic, chemostratigraphic and new U-Pb detrital zircon data suggests that the Mirbat Group is best placed within the Cryogenian (c. 850-635 Ma) part of the Huqf Supergroup. The c. I km thick marine deposits of the Arkahawl and Marsham Formations of the Mirbat Group are thought to represent a stratigraphic interval between older Cryogenian and younger Cryogenian glaciations that is not preserved elsewhere in Oman. The bulk of detrital zircons in the Huqf Supergroup originate from Neoproterozoic parent rocks. However, older Mesoproterozoic, Palaeoproterozoic and even Archaean zircons can be recognized in the detrital population from the upper Mahara Group (Fiq Formation) and Nafun Group, suggesting the tapping of exotic sources, probably from the Arabian-Nubian Shield.
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In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.
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BACKGROUND: There is increasing interest in provision of essential surgical care as part of public health policy in low- and middle-income countries (LMIC). Relatively simple interventions have been shown to prevent death and disability. We reviewed the published literature to examine the cost-effectiveness of simple surgical interventions which could be made available at any district hospital, and compared these to standard public health interventions. METHODS: PubMed and EMBASE were searched using single and combinations of the search terms "disability adjusted life year" (DALY), "quality adjusted life year," "cost-effectiveness," and "surgery." Articles were included if they detailed the cost-effectiveness of a surgical intervention of relevance to a LMIC, which could be made available at any district hospital. Suitable articles with both cost and effectiveness data were identified and, where possible, data were extrapolated to enable comparison across studies. RESULTS: Twenty-seven articles met our inclusion criteria, representing 64 LMIC over 16 years of study. Interventions that were found to be cost-effective included cataract surgery (cost/DALY averted range US$5.06-$106.00), elective inguinal hernia repair (cost/DALY averted range US$12.88-$78.18), male circumcision (cost/DALY averted range US$7.38-$319.29), emergency cesarean section (cost/DALY averted range US$18-$3,462.00), and cleft lip and palate repair (cost/DALY averted range US$15.44-$96.04). A small district hospital with basic surgical services was also found to be highly cost-effective (cost/DALY averted 1 US$0.93), as were larger hospitals offering emergency and trauma surgery (cost/DALY averted US$32.78-$223.00). This compares favorably with other standard public health interventions, such as oral rehydration therapy (US$1,062.00), vitamin A supplementation (US$6.00-$12.00), breast feeding promotion (US$930.00), and highly active anti-retroviral therapy for HIV (US$922.00). CONCLUSIONS: Simple surgical interventions that are life-saving and disability-preventing should be considered as part of public health policy in LMIC. We recommend an investment in surgical care and its integration with other public health measures at the district hospital level, rather than investment in single disease strategies.
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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.
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BACKGROUND: Meta-analyses are particularly vulnerable to the effects of publication bias. Despite methodologists' best efforts to locate all evidence for a given topic the most comprehensive searches are likely to miss unpublished studies and studies that are published in the gray literature only. If the results of the missing studies differ systematically from the published ones, a meta-analysis will be biased with an inaccurate assessment of the intervention's effects.As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:â-ª To assess the impact of studies that are not published or published in the gray literature on pooled effect estimates in meta-analyses (quantitative measure).â-ª To assess whether the inclusion of unpublished studies or studies published in the gray literature leads to different conclusions in meta-analyses (qualitative measure). METHODS/DESIGN: Inclusion criteria: Methodological research projects of a cohort of meta-analyses which compare the effect of the inclusion or exclusion of unpublished studies or studies published in the gray literature.Literature search: To identify relevant research projects we will conduct electronic searches in Medline, Embase and The Cochrane Library; check reference lists; and contact experts.Outcomes: 1) The extent to which the effect estimate in a meta-analyses changes with the inclusion or exclusion of studies that were not published or published in the gray literature; and 2) the extent to which the inclusion of unpublished studies impacts the meta-analyses' conclusions.Data collection: Information will be collected on the area of health care; the number of meta-analyses included in the methodological research project; the number of studies included in the meta-analyses; the number of study participants; the number and type of unpublished studies; studies published in the gray literature and published studies; the sources used to retrieve studies that are unpublished, published in the gray literature, or commercially published; and the validity of the methodological research project.Data synthesis: Data synthesis will involve descriptive and statistical summaries of the findings of the included methodological research projects. DISCUSSION: Results are expected to be publicly available in the middle of 2013.
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1. Few examples of habitat-modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo-absences. 2. In this study we tested a new approach to generating pseudo-absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum. This method of generating pseudo-absences was compared with two others: (i) use of a GLM with pseudo-absences generated totally at random, and (ii) use of an ENFA only. 3. The influence of two different spatial resolutions (i.e. grain) was also assessed for tackling the dilemma of quality (grain) vs. quantity (number of occurrences). Each combination of the three above-mentioned methods with the two grains generated a distinct HS map. 4. Four evaluation measures were used for comparing these HS maps: total deviance explained, best kappa, Gini coefficient and minimal predicted area (MPA). The last is a new evaluation criterion proposed in this study. 5. Results showed that (i) GLM models using ENFA-weighted pseudo-absence provide better results, except for the MPA value, and that (ii) quality (spatial resolution and locational accuracy) of the data appears to be more important than quantity (number of occurrences). Furthermore, the proposed MPA value is suggested as a useful measure of model evaluation when used to complement classical statistical measures. 6. Synthesis and applications. We suggest that the use of ENFA-weighted pseudo-absence is a possible way to enhance the quality of GLM-based potential distribution maps and that data quality (i.e. spatial resolution) prevails over quantity (i.e. number of data). Increased accuracy of potential distribution maps could help to define better suitable areas for species protection and reintroduction.
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We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.
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This report presents the results of a literature review conducted to evaluate differences in seat belt use by race. A literature review was conducted to evaluate overall seat belt use, racial differences in seat belt use, overall child restraint use, racial differences in child restraint use, and information about seat belt and child restraint use specific to Iowa. A number of national studies and regional studies were found and are presented. Mixed results were found as to whether racial differences exist in both seat belt use and child restraint use. However, in the course of the literature review, several items that are of interest to safety in Iowa have emerged, although little data specific to Iowa was encountered. First, national seat belt use appears to be lower among African-Americans than for Caucasians or Hispanics. Second, national crash rates among Hispanics appear to be higher than those for Caucasians, particularly when population and lower vehicle miles traveled (VMT) are considered. One issue that should be considered throughout this literature review is that the Hispanic population may be higher than reported due to large numbers of undocumented persons who do not appear in population estimates, driver’s license, or other databases.