998 resultados para POSTERIOR ANALYSIS
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Background Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. Findings We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world's men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women. Interpretation If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia.
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Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those required for climate models, such spatial modelling can be difficult. Also, computer models often require land cover proportions at sites larger than the original map scale as inputs, and it is the uncertainty in these proportions that this article discusses. This paper describes a Monte Carlo sampling scheme that generates realisations of land cover proportions from the posterior distribution as implied by a Bayesian analysis that combines spatial information in the land cover map and its associated confusion matrix. The technique is computationally simple and has been applied previously to the Land Cover Map 2000 for the region of England and Wales. This article demonstrates the ability of the technique to scale up to large (global) satellite derived land cover maps and reports its application to the GlobCover 2009 data product. The results show that, in general, the GlobCover data possesses only small biases, with the largest belonging to non–vegetated surfaces. In vegetated surfaces, the most prominent area of uncertainty is Southern Africa, which represents a complex heterogeneous landscape. It is also clear from this study that greater resources need to be devoted to the construction of comprehensive confusion matrices.
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Background: Physical and bioceramic incorporation surface treatments at the nanometer scale showed higher means of bone-to-implant contact (BIC) and torque values compared with surface topography at the micrometer scale; however, the literature concerning the effect of nanometer scale parameters is sparse. Purpose: The aim of this study was to evaluate the influence of two different implant surfaces on the percentage bone-to-implant contact (BIC%) and bone osteocyte density in the human posterior maxilla after 2 months of unloaded healing. Materials and Methods: The implants utilized presented dual acid-etched (DAE) surface and a bioceramic molecular impregnated treatment (Ossean(R), Intra-Lock International, Boca Raton, FL, USA) serving as control and test, respectively. Ten subjects (59 1 9 years of age) received two implants (one of each surface) during conventional implant surgery in the posterior maxilla. After the non-loaded period of 2 months, the implants and the surrounding tissue were removed by means of a trephine and were non-decalcified processed for ground sectioning and analysis of BIC%, bone density in threaded area (BA%), and osteocyte index (Oi). Results: Two DAE implants were found to be clinically unstable at time of retrieval. Histometric evaluation showed significantly higher BIC% and Oi for the test compared to the control surface (p < .05), and that BA% was not significantly different between groups. Wilcoxon matched pairs test was used to compare the differences of histomorphometric variables between implant surfaces. The significance test was conducted at a 5% level of significance. Conclusion: The histological data suggest that the bioceramic molecular impregnated surface-treated implants positively modulated bone healing at early implantation times compared to the DAE surface.
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The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.
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We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.
Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data
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We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.
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The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.
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To describe retinal nerve fiber layer changes in late-stage diffuse unilateral subacute neuroretinitis eyes and compare these results with healthy eyes observed through nerve fiber analyzer (GDx®). Methods: This is a retrospective case-control study in which 49 eyes in late-stage diffuse unilateral subacute neuroretinitis were examined from May/97 to December/ 01. First, eyes with diffuse unilateral subacute neuroretinitis and healthy contralateral eyes (Control Group I) were statistically matched. Subsequently, eyes with diffuse unilateral subacute neuroretinitis were compared with eyes of healthy patients (Control Group II). Results: Eyes from Control Groups I and II had higher relative frequency of “within normal limits” status. Eyes from the diffuse unilateral subacute neuroretinitis (DUSN) Group had higher frequency of “outside normal limits” and “borderline” status. Control Groups I and II had absolute values different from the DUSN Group regarding all parameters (p<0.05), except for Symmetry in Control Groups I and II, Average thickness and Superior Integral in control group II. Conclusion: Patients with late-stage diffuse unilateral subacute neuroretinitis presented presumed decrease in nerve fiber layer thickness shown by GDx®. Retinal zones with larger vascular support and larger amount of nerve fibers presented higher decrease in the delay of the reflected light measured by the nerve fiber analyzer
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The purpose of this study was to quantify cephalometric and three-dimensional alterations of the posterior airway space of patients who underwent maxillomandibular advancement surgery. 20 patients treated by maxillomandibular advancement were selected. The minimal postoperative period was 6 months. The treated patients underwent cone-beam computed tomography at 3 distinct time intervals, preoperative (T1), immediate postoperative period up to 15 days after surgery (T2), and late postoperative period at least 6 months after surgery. The results showed that the maxillomandibular advancement promoted an increase in the posterior airway space in each patient in all the analyses performed, with a statistically significant difference between T2 and T1, and between T3 and T1, p < 0.05. There was a statistical difference between T2 and T3 in the analysis of area and volume, which means that the airway space became narrower after 6 months compared with the immediate postoperative period. The maxillomandibular advancement procedure allowed great linear area and volume increase in posterior airway space in the immediate and late postoperative periods, but there was partial loss of the increased space after 6 months. The linear analysis of airway space has limited results when compared with analysis of area and volume.
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Purpose: This study aimed to evaluate the influence of implants with or without threads representation on the outcome of a two-dimensional finite element (FE) analysis. Materials and Methods: Two-dimensional FE models that reproduced a frontal section of edentulous mandibular posterior bone were constructed using a standard crown/implant/screw system representation. To evaluate the effect of implant threads, two models were created: a model in which the implant threads were accurately simulated (precise model) and a model in which implants with a smooth surface (press-fit implant) were used (simplified model). An evaluation was performed on ANSYS software, in which a load of 133 N was applied at a 30-degree angulation and 2 mm off-axis from the long axis of the implant on the models, The Von Mises stresses were measured. Results: The precise model (1.45 MPa) showed higher maximum stress values than the simplified model (1.2 MPa). Whereas in the cortical bone, the stress values differed by about 36% (292.95 MPa for the precise model and 401.14 MPa for the simplified model), in trabecular bone (19.35 MPa and 20.35 MPa, respectively), the stress distribution and stress values were similar. Stress concentrations occurred around the implant neck and the implant apex. Conclusions: Considering implant and cortical bone analysis, remarkable differences in stress values were found between the models. Although the models showed different absolute stress values, the stress distribution was similar. INT J ORAL MAXILLOFAC IMPLANTS 2009;24:1040-1044
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Purpose: Three-dimensional finite element analysis was used to evaluate the effect of vertical and angular misfit in three-piece implant-supported screw-retained fixed prostheses on the biomechanical response in the peri-implant bone, implants, and prosthetic components. Materials and Methods: Four three-dimensional models were fabricated to represent a right posterior mandibular section with one implant in the region of the second premolar (2PM) and another in the region of the second molar (2M). The implants were splinted by a three-piece implant-supported metal-ceramic prosthesis and differed according to the type of misfit, as represented by four different models: Control = prosthesis with complete fit to the implants; UAM (unilateral angular misfit) = prosthesis presenting unilateral angular misfit of 100 pm in the mesial region of the 2M; UVM (unilateral vertical misfit) = prosthesis presenting unilateral vertical misfit of 100 pm in the mesial region of the 2M; and TVM (total vertical misfit) = prosthesis presenting total vertical misfit of 100 pm in the platform of the framework in the 2M. A vertical load of 400 N was distributed and applied on 12 centric points by the software Ansys, ie, a vertical load of 150 N was applied to each molar in the prosthesis and a vertical load of 100 N was applied at the 2PM. Results: The stress values and distribution in peri-implant bone tissue were similar for all groups. The models with misfit exhibited different distribution patterns and increased stress magnitude in comparison to the control. The highest stress values in group UAM were observed in the implant body and retention screw. The groups UVM and TVM exhibited high stress values in the platform of the framework and the implant hexagon, respectively. Conclusions: The three types of misfit influenced the magnitude and distribution of stresses. The influence of misfit on peri-implant bone tissue was modest. Each type of misfit increased the stress values in different regions of the system. INT J ORAL MAXILLOFAC IMPLANTS 2011;26:788-796
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)