24 resultados para nucleation positions


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Dual-energy X-ray absorptiometry (DXA) is commonly used in the care of patients for diagnostic classification of osteoporosis, low bone mass (osteopenia), or normal bone density; assessment of fracture risk; and monitoring changes in bone density over time. The development of other technologies for the evaluation of skeletal health has been associated with uncertainties regarding their applications in clinical practice. Quantitative ultrasound (QUS), a technology for measuring properties of bone at peripheral skeletal sites, is more portable and less expensive than DXA, without the use of ionizing radiation. The proliferation of QUS devices that are technologically diverse, measuring and reporting variable bone parameters in different ways, examining different skeletal sites, and having differing levels of validating data for association with DXA-measured bone density and fracture risk, has created many challenges in applying QUS for use in clinical practice. The International Society for Clinical Densitometry (ISCD) 2007 Position Development Conference (PDC) addressed clinical applications of QUS for fracture risk assessment, diagnosis of osteoporosis, treatment initiation, monitoring of treatment, and quality assurance/quality control. The ISCD Official Positions on QUS resulting from this PDC, the rationale for their establishment, and recommendations for further study are presented here.

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The best indirect evidence that increased bone turnover contributes to fracture risk is the fact that most of the proven therapies for osteoporosis are inhibitors of bone turnover. The evidence base that we can use biochemical markers of bone turnover in the assessment of fracture risk is somewhat less convincing. This relates to natural variability in the markers, problems with the assays, disparity in the statistical analyses of relevant studies and the independence of their contribution to fracture risk. More research is clearly required to address these deficiencies before biochemical markers might contribute a useful independent risk factor for inclusion in FRAX(®).

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Risk factors for fracture can be purely skeletal, e.g., bone mass, microarchitecture or geometry, or a combination of bone and falls risk related factors such as age and functional status. The remit of this Task Force was to review the evidence and consider if falls should be incorporated into the FRAX® model or, alternatively, to provide guidance to assist clinicians in clinical decision-making for patients with a falls history. It is clear that falls are a risk factor for fracture. Fracture probability may be underestimated by FRAX® in individuals with a history of frequent falls. The substantial evidence that various interventions are effective in reducing falls risk was reviewed. Targeting falls risk reduction strategies towards frail older people at high risk for indoor falls is appropriate. This Task Force believes that further fracture reduction requires measures to reduce falls risk in addition to bone directed therapy. Clinicians should recognize that patients with frequent falls are at higher fracture risk than currently estimated by FRAX® and include this in decision-making. However, quantitative adjustment of the FRAX® estimated risk based on falls history is not currently possible. In the long term, incorporation of falls as a risk factor in the FRAX® model would be ideal.

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Recent studies have started to use media data to measure party positions and issue salience. The aim of this article is to compare and cross-validate this alternative approach with the more commonly used party manifestos, expert judgments and mass surveys. To this purpose, we present two methods to generate indicators of party positions and issue salience from media coverage: the core sentence approach and political claims analysis. Our cross-validation shows that with regard to party positions, indicators derived from the media converge with traditionally used measurements from party manifestos, mass surveys and expert judgments, but that salience indicators measure different underlying constructs. We conclude with a discussion of specific research questions for which media data offer potential advantages over more established methods.

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MOTIVATION: The analysis of molecular coevolution provides information on the potential functional and structural implication of positions along DNA sequences, and several methods are available to identify coevolving positions using probabilistic or combinatorial approaches. The specific nucleotide or amino acid profile associated with the coevolution process is, however, not estimated, but only known profiles, such as the Watson-Crick constraint, are usually considered a priori in current measures of coevolution. RESULTS: Here, we propose a new probabilistic model, Coev, to identify coevolving positions and their associated profile in DNA sequences while incorporating the underlying phylogenetic relationships. The process of coevolution is modeled by a 16 × 16 instantaneous rate matrix that includes rates of transition as well as a profile of coevolution. We used simulated, empirical and illustrative data to evaluate our model and to compare it with a model of 'independent' evolution using Akaike Information Criterion. We showed that the Coev model is able to discriminate between coevolving and non-coevolving positions and provides better specificity and specificity than other available approaches. We further demonstrate that the identification of the profile of coevolution can shed new light on the process of dependent substitution during lineage evolution.

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The 2010 Position Development Conference addressed four questions related to the impact of previous fractures on 10-year fracture risk as calculated by FRAX(®). To address these questions, PubMed was searched on the keywords "fracture, epidemiology, osteoporosis." Titles of retrieved articles were reviewed for an indication that risk for future fracture was discussed. Abstracts of these articles were reviewed for an indication that one or more of the questions listed above was discussed. For those that did, the articles were reviewed in greater detail to extract the findings and to find additional past work and citing works that also bore on the questions. The official positions and the supporting literature review are presented here. FRAX(®) underestimates fracture probability in persons with a history of multiple fractures (good, A, W). FRAX(®) may underestimate fracture probability in individuals with prevalent severe vertebral fractures (good, A, W). While there is evidence that hip, vertebral, and humeral fractures appear to confer greater risk of subsequent fracture than fractures at other sites, quantification of this incremental risk in FRAX(®) is not possible (fair, B, W). FRAX(®) may underestimate fracture probability in individuals with a parental history of non-hip fragility fracture (fair, B, W). Limitations of the methodology include performance by a single reviewer, preliminary review of the literature being confined to titles, and secondary review being limited to abstracts. Limitations of the evidence base include publication bias, overrepresentation of persons of European descent in the published studies, and technical differences in the methods used to identify prevalent and incident fractures. Emerging topics for future research include fracture epidemiology in non-European populations and men, the impact of fractures in family members other than parents, and the genetic contribution to fracture risk.

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Tools to predict fracture risk are useful for selecting patients for pharmacological therapy in order to reduce fracture risk and redirect limited healthcare resources to those who are most likely to benefit. FRAX® is a World Health Organization fracture risk assessment algorithm for estimating the 10-year probability of hip fracture and major osteoporotic fracture. Effective application of FRAX® in clinical practice requires a thorough understanding of its limitations as well as its utility. For some patients, FRAX® may underestimate or overestimate fracture risk. In order to address some of the common issues encountered with the use of FRAX® for individual patients, the International Society for Clinical Densitometry (ISCD) and International Osteoporosis Foundation (IOF) assigned task forces to review the medical evidence and make recommendations for optimal use of FRAX® in clinical practice. Among the issues addressed were the use of bone mineral density (BMD) measurements at skeletal sites other than the femoral neck, the use of technologies other than dual-energy X-ray absorptiometry, the use of FRAX® without BMD input, the use of FRAX® to monitor treatment, and the addition of the rate of bone loss as a clinical risk factor for FRAX®. The evidence and recommendations were presented to a panel of experts at the Joint ISCD-IOF FRAX® Position Development Conference, resulting in the development of Joint ISCD-IOF Official Positions addressing FRAX®-related issues.

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Dual-energy X-ray absorptiometry (DXA) is the most widely used technical instrument for evaluating bone mineral content (BMC) and density (BMD) in patients of all ages. However, its use in pediatric patients, during growth and development, poses a much more complex problem in terms of both the technical aspects and the interpretation of the results. For the adults population, there is a well-defined term of reference: the peak value of BMD attained by young healthy subjects at the end of skeletal growth. During childhood and adolescence, the comparison can be made only with healthy subjects of the same age, sex and ethnicity, but the situation is compounded by the wide individual variation in the process of skeletal growth (pubertal development, hormone action, body size and bone size). The International Society for Clinical Densitometry (ISCD) organized a Pediatric Position Development Conference to discuss the specific problems of bone densitometry in growing subjects (9-19 years of age) and to provide essential recommendations for its clinical use.

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BACKGROUND: Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. RESULTS: We have developed a web-based platform that gives a user-friendly access to two phylogenetic-based methods implementing the Coev model: the evaluation of coevolving scores and the simulation of coevolving positions. We have also extended the capabilities of the Coev model to allow for the generalization of the alphabet used in the Markov model, which can now analyse both nucleotide and amino acid data sets. The simulation of coevolving positions is novel and builds upon the developments of the Coev model. It allows user to simulate pairs of dependent nucleotide or amino acid positions. CONCLUSIONS: The main focus of our paper is the new simulation method we present for coevolving positions. The implementation of this method is embedded within the web platform Coev-web that is freely accessible at http://coev.vital-it.ch/, and was tested in most modern web browsers.