867 resultados para full Bayes (FB) hierarchical


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Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

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Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

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Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of fMRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels in the statistical analysis of fMRI data is desirable in order to improve efficiency. Here we construct a hierarchical model and apply an Empirical Bayes framework on the analysis of group fMRI data, employing techniques used in high throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels, and subsequently to construct an improved test statistic in lieu of the classical t-statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances towards a common value. The shrunken estimator for voxelspecific variance components on the group analyses outperforms the classical residual error estimator in terms of mean squared error. Moreover, the shrunken test-statistic decreases false positive rate when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

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BACKGROUND: Abstracts of presentations at scientific meetings are usually available only in conference proceedings. If subsequent full publication of abstract results is based on the magnitude or direction of study results, publication bias may result. Publication bias, in turn, creates problems for those conducting systematic reviews or relying on the published literature for evidence. OBJECTIVES: To determine the rate at which abstract results are subsequently published in full, and the time between meeting presentation and full publication. To assess the association between study characteristics and full publication. SEARCH STRATEGY: We searched MEDLINE, EMBASE, The Cochrane Library, Science Citation Index, reference lists, and author files. Date of most recent search: June 2003. SELECTION CRITERIA: We included all reports that examined the subsequent full publication rate of biomedical results initially presented as abstracts or in summary form. Follow-up of abstracts had to be at least two years. DATA COLLECTION AND ANALYSIS: Two reviewers extracted data. We calculated the weighted mean full publication rate and time to full publication. Dichotomous variables were analyzed using relative risk and random effects models. We assessed time to publication using Kaplan-Meier survival analyses. MAIN RESULTS: Combining data from 79 reports (29,729 abstracts) resulted in a weighted mean full publication rate of 44.5% (95% confidence interval (CI) 43.9 to 45.1). Survival analyses resulted in an estimated publication rate at 9 years of 52.6% for all studies, 63.1% for randomized or controlled clinical trials, and 49.3% for other types of study designs.'Positive' results defined as any 'significant' result showed an association with full publication (RR = 1.30; CI 1.14 to 1.47), as did 'positive' results defined as a result favoring the experimental treatment (RR =1.17; CI 1.02 to 1.35), and 'positive' results emanating from randomized or controlled clinical trials (RR = 1.18, CI 1.07 to 1.30).Other factors associated with full publication include oral presentation (RR = 1.28; CI 1.09 to 1.49); acceptance for meeting presentation (RR = 1.78; CI 1.50 to 2.12); randomized trial study design (RR = 1.24; CI 1.14 to 1.36); and basic research (RR = 0.79; CI 0.70 to 0.89). Higher quality of abstracts describing randomized or controlled clinical trials was also associated with full publication (RR = 1.30, CI 1.00 to 1.71). AUTHORS' CONCLUSIONS: Only 63% of results from abstracts describing randomized or controlled clinical trials are published in full. 'Positive' results were more frequently published than not 'positive' results.

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CONTEXT: A polymorphism of the GH receptor (GHR) gene resulting in genomic deletion of exon 3 (GHR-d3) has been associated with responsiveness to GH therapy. However, the data reported so far do vary according to the underlying condition, replacement dose, and duration of the treatment. OBJECTIVE, DESIGN: The aim of this study was to analyze the impact of the GHR genotypes in terms of the initial height velocity (HV) resulting from treatment and the impact upon adult height in patients suffering from severe isolated GH deficiency. CONTROLS, PATIENTS, SETTING: A total of 181 subjects (peak stimulated GHfull-length/full-length genotype (P<0.05). A GHR-d3 allele dose-dependent effect was found for both HV SDS (r=0.72) and height gain (r=0.77). However, there was no significant difference in final adult height and height SDS according to the exon-3 genotypes. CONCLUSIONS: Our results indicate that in patients with severe isolated GH deficiency, although the GHR genotype might play a role in GH responsiveness, at least at the beginning of treatment, there is no effect on final height.

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When patients enter our emergency room with suspected multiple injuries, Statscan provides a full body anterior and lateral image for initial diagnosis, and then zooms in on specific smaller areas for a more detailed evaluation. In order to examine the possible role of Statscan in the management of multiply injured patients we implemented a modified ATLS((R)) algorithm, where X-ray of C-spine, chest and pelvis have been replaced by single-total a.p./lat. body radiograph. Between 15 October 2006 and 1 February 2007 143 trauma patients (mean ISS 15+/-14 (3-75)) were included. We compared the time in resuscitation room to 650 patients (mean ISS 14+/-14 (3-75)) which were treated between 1 January 2002 and 1 January 2004 according to conventional ATLS protocol. The total-body scanning time was 3.5 min (3-6 min) compared to 25.7 (8-48 min) for conventional X-rays, The total ER time was unchanged 28.7 min (13-58 min) compared to 29.1 min (15-65 min) using conventional plain radiography. In 116/143 patients additional CT scans were necessary. In 98/116 full body trauma CT scans were performed. In 18/116 patients selective CT scans were ordered based on Statscan findings. In 43/143 additional conventional X-rays had to be performed, mainly due to inadequate a.p. views of fractured bones. All radiographs were transmitted over the hospital network (Picture Archiving and Communication System, PACS) for immediate simultaneous viewing at different places. The rapid availability of images for interpretation because of their digital nature and the reduced need for repeat exposures because of faulty radiography are also felt to be strengths.

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OBJECTIVES: To assess the clinical and microbiological effects of full-mouth debridement with (FMD) and without the use of antiseptics [full-mouth scaling and root planing (FMSRP)] in comparison with conventional staged debridement (CSD) in patients with chronic periodontitis after at least 6 months. MATERIAL AND METHODS: The search in MEDLINE (PubMed), covering a period of 1975 to October 2007, and hand searching yielded 207 titles. Forty-two abstracts and 17 full-text articles were screened for inclusion. RESULTS: Twelve articles allowed a direct comparison of FMD with CSD, FMSRP with CSD and FMD with FMSRP. Probing pocket depth reductions were significantly greater (0.2 mm) with FMD and FMSRP compared with CSD. Moreover, a modest reduction in BOP (9%) favoured FMD. Likewise, clinical attachment levels were improved by 0.2-0.4 mm in favour of FMD and FMSRP, respectively. In all comparisons, single-rooted teeth and deep pockets benefitted slightly from FMD and FMSRP. Limited differences in the changes of the subgingival microbiota were noted between the treatment modalities. CONCLUSIONS: Despite the significant differences of modest magnitude, FMD or FMSRP do not provide clinically relevant advantages over CSD. Hence, all three treatment modalities may be recommended for debridement in the initial treatment of patients with chronic periodontitis.

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OBJECTIVE: Meta-analysis of studies of the accuracy of diagnostic tests currently uses a variety of methods. Statistically rigorous hierarchical models require expertise and sophisticated software. We assessed whether any of the simpler methods can in practice give adequately accurate and reliable results. STUDY DESIGN AND SETTING: We reviewed six methods for meta-analysis of diagnostic accuracy: four simple commonly used methods (simple pooling, separate random-effects meta-analyses of sensitivity and specificity, separate meta-analyses of positive and negative likelihood ratios, and the Littenberg-Moses summary receiver operating characteristic [ROC] curve) and two more statistically rigorous approaches using hierarchical models (bivariate random-effects meta-analysis and hierarchical summary ROC curve analysis). We applied the methods to data from a sample of eight systematic reviews chosen to illustrate a variety of patterns of results. RESULTS: In each meta-analysis, there was substantial heterogeneity between the results of different studies. Simple pooling of results gave misleading summary estimates of sensitivity and specificity in some meta-analyses, and the Littenberg-Moses method produced summary ROC curves that diverged from those produced by more rigorous methods in some situations. CONCLUSION: The closely related hierarchical summary ROC curve or bivariate models should be used as the standard method for meta-analysis of diagnostic accuracy.

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Beer bottles are often used in physical disputes. If the bottles break, they may give rise to sharp trauma. However, if the bottles remain intact, they may cause blunt injuries. In order to investigate whether full or empty standard half-litre beer bottles are sturdier and if the necessary breaking energy surpasses the minimum fracture-threshold of the human skull, we tested the fracture properties of such beer bottles in a drop-tower. Full bottles broke at 30 J impact energy, empty bottles at 40 J. These breaking energies surpass the minimum fracture-threshold of the human neurocranium. Beer bottles may therefore fracture the human skull and therefore serve as dangerous instruments in a physical dispute.

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The performance of memory-guided saccades with two different delays (3 and 30 s of memorization) was studied in seven healthy subjects. Double-pulse transcranial magnetic stimulation (dTMS) with an interstimulus interval of 100 ms was applied over the right dorsolateral prefrontal cortex (DLPFC) early (1 s after target presentation) and late (28 s after target presentation). Early stimulation significantly increased in both delays the percentage of error in amplitude (PEA) of contralateral memory-guided saccades compared to the control experiment without stimulation. dTMS applied late in the delay had no significant effect on PEA. Furthermore, we found a significantly smaller effect of early stimulation in the long-delay paradigm. These results suggest a time-dependent hierarchical organization of the spatial working memory with a functional dominance of DLPFC during the early memorization, independent from the memorization delay. For a long memorization delay, however, working memory seems to have an additional, DLPFC-independent component.