935 resultados para Demographic Data


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We compared four strategies for inviting 91,456 women aged 50-69 years to one of six clinics for mammography screening and 40,142 men aged 60-79 years to one of 10 clinics for abdominal aortic aneurysm (AAA) screening. The strategies were invitation to the clinic nearest to the client and invitation to the clinic nearest to the client's area of residence defined by census small area, postcode and local government area. For each strategy we calculated the expected demand at each clinic and the travel distances for clients. We found that when women were allocated to mammography clinics on the basis of the local government area instead of their individual address, expected demand at one clinic increased by 60%, and 19% of clients were invited to attend a more remote clinic, entailing 99,000 km of additional travel. Similar results were obtained for men allocated to AAA clinics by their postcode of residence instead of their individual address: 55% difference in expected demand, 13% to a more remote clinic and 60,000 km of extra travel. Allocation on the basis of small areas did not show such great differences, except for travel distance, which was about 5% higher for each clinic type. We recommend that allocation of clients to screening clinics be made according to residential address, that assessment of the location of clinics be based on distances between residences and nearest clinic, but that planning new locations for clinics be aided with spatial analysis tools using small area demographic and social data. (C) 1997 Elsevier Science Ltd.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

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Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

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BACKGROUND: Early gastric cancer (EGC) is defined as adenocarcinoma limited to the mucosa or submucosa regardless of lymph node involvement. Local EGC recurrence rates have been described ill Lip to 6% of cases. OBJECTIVES: To evaluate predictive factors for incomplete resection and local recurrence of EGC treated by endoscopic mucosal resection (EMR) that was followed up for at least one year. METHODS: From June 1994 to December 2005, 46 patients with EGC underwent EMR. Possible predictive factors for incomplete endoscopic resection and local recurrence were identified by medical chart analysis. Demographic, endoscopic and histopathological data were retrospectively evaluated. EMR was considered complete or incomplete. Patients from the complete resection group were divided into subgroups (with and without local EGC recurrence). RESULTS: Complete resection was possible in 36 cases (76.6%). Predictive factors for incomplete resection were turnout location (P=0.035), histological type (P=0.021), lesion size (P=0.022) and number of resected fragments (P=0.013). On multivariate analysis, undifferentiated histological type (OR 0.8; 95% Cl 0.036 to 0.897) and number of resected fragments (OR 7.34; 95% Cl 1.266 to 42.629) were independent predictive factors for incomplete resection. In the complete resection group, a larger lesion size was associated with a higher the number of resected fragments (P=0.018). Local recurrence occurred in nine cases (25%). Use of the cap technique was the only predictive factor for local recurrence in five of seven cases (71.4%) (P=0.006). CONCLUSIONS: A larger lesion size was associated with a higher number of resected fragments. Undifferentiated adenocarcinoma and piecemeal resection were predictive factors for incomplete resection. Technique type was a predictive factor for local EGC recurrence.

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Background: There has been an increase in worldwide infections caused by carbapenem-resistant Acinetobacter. This poses a therapeutic challenge as few treatment options are available. Objectives: The aim of this study was to evaluate the efficacy and safety of polymyxins and ampicillin/sulbactam for treating infections caused by carbapenem-resistant Acinetobacter spp. and to evaluate prognostic factors. Methods: This was a retrospective review of patients from two teaching hospitals who had nosocomial infections caused by carbapenem-resistant Acinetobacter spp. from 1996 to 2004. Diagnosis of infection was based on CDC criteria plus the isolation of Acinetobacter from a usually sterile site or from bronchoalveolar lavage. Urinary tract infections were not included. Data on demographic and clinical features and treatment were collected from medical records. Prognostic factors associated with two outcomes (mortality during treatment and in-hospital mortality) were evaluated. Results: Eighty-two patients received polymyxins and 85 were treated with ampicillin/sulbactam. Multiple logistic regression analysis revealed that independent predictors of mortality during treatment were treatment with polymyxins, higher Acute Physiological and Chronic Health Evaluation II (APACHE II) score, septic shock, delay in starting treatment and renal failure. On multivariate analysis, prognostic factors for in-hospital mortality were older age, septic shock and higher APACHE II score. Conclusions: This is the first study comparing current therapeutic options for infections due to carbapenem-resistant Acinetobacter. The most important finding of the present study is that ampicillin/sulbactam appears to be more efficacious than polymyxins, which was an independent factor associated with mortality during treatment.

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Candidemia is associated with high morbidity and mortality resulting in significant increases in the length of patients` hospitalization and in healthcare costs. Critically ill patients are at particular risk for candidemia because of their debilitated condition and frequent need for invasive procedures. The aim of this study was to characterize the incidence and epidemiology of candidemia over a seven-year period in intensive care units (ICUs) and the use of fluconazole and caspofungin in a large university-affiliated hospital. All cases of candidemia were identified by surveillance, using the Centers for Diseases Control and Prevention criteria. Demographic variables, use of antifungal (fluconazole and caspofungin) and patient outcomes were evaluated. The 2 test for linear trend was employed to evaluate the distribution of Candida spp. and the use of fluconazole and caspofungin by defined daily dose (DDD) per 1,000 patients-days during the study period. One hundred and eight episodes of candidemia were identified. The overall incidence of candidemia (P=0.20) and incidence of non-Candida albicans Candida infections (P=0.32) remained stable over the study period and ranged from 0.3-0.9 episodes per 1,000 catheter-days and 0.39-0.83 episodes per 1,000 patients-days. However, the use of fluconazole and caspofungin increased significantly (P0.001). While there were no reports of the use of fluconazole for prophylaxis in 1999, its use for this purpose increased from 3% in 2000 to 7.0% (P=0.07) in 2006. C. albicans was the most frequent specie isolated and burns and cancer were the most frequent underlying conditions. The overall mortality was 76%. There was no difference between C. albicans and non-C. albicans Candida infections when the crude and 14-day mortality rates were compared. Our data demonstrated that C. albicans is still the most frequent species causing candidemia in our intensive care units. Our rates of candidemia are lower than those reported from the region and similar to American and European hospitals. Although the incidence of blood stream infections (BSI) and candidemia remained stable, the use of fluconazole and caspofungin increased significantly over the years included in this study but had no impact on the incidence of infections caused by non-C. albicans Candida species.

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Although many mathematical models exist predicting the dynamics of transposable elements (TEs), there is a lack of available empirical data to validate these models and inherent assumptions. Genomes can provide a snapshot of several TE families in a single organism, and these could have their demographics inferred by coalescent analysis, allowing for the testing of theories on TE amplification dynamics. Using the available genomes of the mosquitoes Aedes aegypti and Anopheles gambiae, we indicate that such an approach is feasible. Our analysis follows four steps: (1) mining the two mosquito genomes currently available in search of TE families; (2) fitting, to selected families found in (1), a phylogeny tree under the general time-reversible (GTR) nucleotide substitution model with an uncorrelated lognormal (UCLN) relaxed clock and a nonparametric demographic model; (3) fitting a nonparametric coalescent model to the tree generated in (2); and (4) fitting parametric models motivated by ecological theories to the curve generated in (3).

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Mitochondrial DNA (mtDNA) population data for forensic purposes are still scarce for some populations, which may limit the evaluation of forensic evidence especially when the rarity of a haplotype needs to be determined in a database search. In order to improve the collection of mtDNA lineages from the Iberian and South American subcontinents, we here report the results of a collaborative study involving nine laboratories from the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) and EMPOP. The individual laboratories contributed population data that were generated throughout the past 10 years, but in the majority of cases have not been made available to the scientific community. A total of 1019 haplotypes from Iberia (Basque Country, 2 general Spanish populations, 2 North and 1 Central Portugal populations), and Latin America (3 populations from Sao Paulo) were collected, reviewed and harmonized according to defined EMPOP criteria. The majority of data ambiguities that were found during the reviewing process (41 in total) were transcription errors confirming that the documentation process is still the most error-prone stage in reporting mtDNA population data, especially when performed manually. This GHEP-EMPOP collaboration has significantly improved the quality of the individual mtDNA datasets and adds mtDNA population data as valuable resource to the EMPOP database (www.empop.org). (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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Cancer/testis Antigens (CTAs) are immunogenic proteins with a restricted expression pattern in normal tissues and aberrant expression in different types of tumors being considered promising candidates for immunotherapy. We used the alignment between EST sequences and the human genome sequence to identify novel CT genes. By examining the EST tissue composition of known CT clusters we defined parameters for the selection of 1184 EST clusters corresponding to putative CT genes. The expression pattern of 70 CT gene candidates was evaluated by RT-PCR in 21 normal tissues, 17 tumor cell lines and 160 primary tumors. We were able to identify 4 CT genes expressed in different types of tumors. The presence of antibodies against the protein encoded by 1 of these 4 CT genes (FAM46D) was exclusively detected in plasma samples from cancer patients. Due to its restricted expression pattern and immunogenicity FAM46D represents a novel target for cancer immunotherapy. (c) 2009 Elsevier Inc. All rights reserved.

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Objective. To evaluate the effect of 6-sulphatoxymelatonin on the sleep quality of girls with precocious puberty. Study design. Ninety-nine girls were divided into three groups: GI, precocious puberty; GII, normal prepubescent; GIII, normal puberty. Questionnaires containing demographic and clinical data were applied. Blood was collected for hormonal evaluation for 6-sulphatoxymelatonin. The modified Rush Sleep Diary was used. Results. The levels of 6-sulphatoxymelatonin were highest in the group without pubertal development (75.23 +/- 10.84 ng/ml), second highest in the group with normal puberty (45.66 +/- 3.87 ng/ml, p < 0.001) and lowest in the group with true precocious puberty (37.04 +/- 5.47 ng/ml). The amount of day sleep was greater in the group without pubertal development compared to other groups. Conclusion. Despite the sleep data, melatonin may be involved in the precocious puberty process.

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Introduction: Data on epidemiology of HPV infection are needed for the development of human papillomavirus (HPV) vaccine recommendations, especially in countries where HPV vaccination is not yet included in public vaccination programs. The aim of this study was to determine the prevalence of serum antibodies to HPV types 6, 11, 16, and 18 and associated factors among young women after birth of the first child. Methods: This cross-sectional study was carried out in a large public maternity hospital in Sao Paulo, Brazil. Three hundred one women aged 15 to 24 years who gave birth to their first child were recruited between 43 and 60 days after delivery. Seroprevalence was performed using a type-specific enzyme-linked immunosorbent assay based on HPV Late protein 1 viruslike particles. The association of seroreactivity with these 4 HPV types with selected demographic and behavioral factors was assessed by Generalized Linear Model analysis. Results: Fifty-eight (19.3%) women (95% confidence interval, 15.0%-24.2%) had antibodies to any of the 4 viruslike particles tested. The overall seroprevalence rates of the HPV types were: HPV16, 9.0%; HPV18, 7.0%; and HPV 6+11, 7.7%, which are targeted by the HPV prophylactic vaccines. In the multivariate analysis, only age (inversely, P = 0.044 for trend) and previous sexually transmitted disease (P = 0.008) were 2 factors independently associated with HPV seropositivity. Conclusions: These data offer additional information on the epidemiology of HPV in a group of young Brazilian women after first delivery and contribute to establish a baseline of HPV seroprevalence against which post-HPV vaccine era seroprevalence can be compared.

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Greater tobacco smoking and alcohol consumption and lower body mass index (BMI) increase odds ratios (OR) for oral cavity, oropharyngeal, hypopharyngeal, and laryngeal cancers; however, there are no comprehensive sex-specific comparisons of ORs for these factors. We analyzed 2,441 oral cavity (925 women and 1,516 men), 2,297 oropharynx (564 women and 1,733 men), 508 hypopharynx (96 women and 412 men), and 1,740 larynx (237 women and 1,503 men) cases from the INHANCE consortium of 15 head and neck cancer case-control studies. Controls numbered from 7,604 to 13,829 subjects, depending on analysis. Analyses fitted linear-exponential excess ORs models. ORs were increased in underweight (< 18.5 BMI) relative to normal weight (18.5-24.9) and reduced in overweight and obese categories (a parts per thousand yen25 BMI) for all sites and were homogeneous by sex. ORs by smoking and drinking in women compared with men were significantly greater for oropharyngeal cancer (p < 0.01 for both factors), suggestive for hypopharyngeal cancer (p = 0.05 and p = 0.06, respectively), but homogeneous for oral cavity (p = 0.56 and p = 0.64) and laryngeal (p = 0.18 and p = 0.72) cancers. The extent that OR modifications of smoking and drinking by sex for oropharyngeal and, possibly, hypopharyngeal cancers represent true associations, or derive from unmeasured confounders or unobserved sex-related disease subtypes (e.g., human papillomavirus-positive oropharyngeal cancer) remains to be clarified.

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Aims: To estimate the prevalence of cannabis use in the last 12 months in the Brazilian population and to examine its association with individual and geographic characteristics. Design: Cross-sectional survey with a national probabilistic sample. Participants: 3006 individuals aged 14 to 65 years. Measurements: Questionnaire based on well established instruments, adapted to the Brazilian population. Findings: The 12-month prevalence of cannabis use was 2.1% (95%Cl 1.3-2.9). Male gender, better educational level, unemployment and living in the regions South and Southeast were independently associated with higher 12-month prevalence of cannabis use. Conclusion: While the prevalence of cannabis use in Brazil is lower than in many countries, the profile of those who are more likely to have used it is similar. Educational and prevention policies should be focused on specific population groups. (C) 2009 Elsevier Ltd. All rights reserved.