11 resultados para multiple data
em Scielo Saúde Pública - SP
Resumo:
The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.
Resumo:
This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.). In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data). In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.
Resumo:
In an attempt to be as close as possible to the infected and treated patients of the endemic areas of schistosomiasis (S. mansoni) and in order to achieve a long period of follow-up, mice were repeatedly infected with a low number of cercariae. Survival data and histological variables such as schistosomal granuloma, portal changes, hepatocellular necrosis, hepatocellular regeneration, schistosomotic pigment, periductal fibrosis and chiefly bile ducts changes were analysed in the infected treated and non treated mice. Oxamniquine chemotherapy in repeatedly infected mice prolonged survival significantly when compared to non-treated animals (chi-square 9.24, p = 0.0024), thus confirming previous results with a similar experimental model but with a shorter term follow-up. Furthermore, mortality decreased rapidly after treatment suggesting an abrupt reduction in the severity of hepatic lesions. A morphological and immunohistochemical study of the liver was carried out. Portal fibrosis, with a pattern resembling human Symmers fibrosis was present at a late phase in the infected animals. Bile duct lesions were quite close to those described in human Mansonian schistosomiasis. Schistosomal antigen was observed in one isolated altered bile duct cell. The pathogenesis of the bile duct changes and its relation to the parasite infection and/or their antigens are discussed.
Resumo:
INTRODUCTION: Chagas' disease is a major public health problem in Brazil and needs extensive and reliable information to support consistent prevention and control actions. This study describes the most common causes of death associated with deaths related to Chagas' disease (underlying or associated cause of death). METHODS: Mortality data were obtained from the Mortality Information System of the Ministry of Health (approximately 9 million deaths). We analyzed all deaths that occurred in Brazil between 1999 and 2007, where Chagas' disease was mentioned on the death certificate as underlying or associated cause (multiple causes of death). RESULTS: There was a total of 53,930 deaths related to Chagas' disease, 44,543 (82.6%) as underlying cause and 9,387 (17.4%) as associated cause. The main diseases and conditions associated with death by Chagas' disease as underlying cause included direct complications of cardiac involvement, such as conduction disorders/arrhythmias (41.4%) and heart failure (37.7%). Cerebrovascular disease (13.2%), ischemic heart disease (13.2%) and hypertensive diseases (9.3%) were the main underlying causes of deaths in which Chagas' disease was identified as an associated cause. CONCLUSIONS: Cardiovascular diseases were often associated with deaths related to Chagas' disease. Information from multiple causes of death recorded on death certificates allows reconstruction of the natural history of Chagas' disease and suggests preventive and therapeutic potential measures more adequate and specifics.
Resumo:
The initial effort of the Brazilian Ministry of Health to be an active partner in the world effort in the preparation of future accurate human immune deficiency virus (HIV) efficacy trials was the establishment of a multi-centered cohort of homosexual and bisexual men. An open cohort was established to determine the HIV incidence and the socio-behavioral aspects involved in Rio de Janeiro. A total of 318 potential participants, originated from multiple sources (health units, public information, snowball recruitment), were screened and recruitment became effective through the direct involvement of target communities (with the support of Non Governmental Organizations) and the population. Among this group, seropositivity for sexually transmitted diseases was high with 23, 32 and 46% for HIV, syphilis and hepatitis B, respectively. The socio-demographic data from the first 200 participants of this HIV negative cohort suggests that the cohort volunteers are an appropriate sample of the general male population of the State of Rio de Janeiro
Resumo:
We analyze the social representations of violence against women from the perspective of city managers, professionals and health workers in rural settings of the southern half of Rio Grande do Sul. The study has a qualitative approach and adds a theoretical/methodological perspective of social representations. The data were generated by means of the associative method, question-stimulus of words and expressions emergence. The analysis of word association was performed with EVOC software, considering frequency and order of association with inducing terms. Participants recognize violence against women as gender destination that induces consent, resignation, guilt and fear, and results in naturalization and trivialization of this social phenomenon. We highlight the need to produce ruptures in established and traditional forms of health care, in the conservative and stereotypical views of violence, favoring access to friendly service and avoiding the reproduction of gender inequalities.
Resumo:
ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).
Resumo:
The objective of this work was to determine the efficiency of the Papadakis method on the quality evaluation of experiments with multiple-harvest oleraceous crops, and on the estimate of the covariate and the ideal plot size. Data from nine uniformity trials (five with bean pod, two with zucchini, and two with sweet pepper) and from one experiment with treatments (with sweet pepper) were used. Through the uniformity trials, the best way to calculate the covariate was defined and the optimal plot size was calculated. In the experiment with treatments, analyses of variance and covariance were performed, in which the covariate was calculated by the Papadakis method, and experimental precision was evaluated based on four statistics. The use of analysis of covariance with the covariate obtained by the Papadakis method increases the quality of experiments with multiple-harvest oleraceous crops and allows the use of smaller plot sizes. The best covariate is the one that considers a neighboring plot of each side of the reference plot.
Resumo:
Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.
Resumo:
This paper analyzes the profile of the Brazilian output in the field of multiple sclerosis from 1981 to 2004. The search was conducted through the MEDLINE and LILACS databases, selecting papers in which the term "multiple sclerosis" was defined as the main topic and "Brazil" or "Brasil" as others. The data were analyzed regarding the themes, the state in Brazil and institution where the papers were produced, the journals where the papers were published, journal's impact factor, and language. The search disclosed 141 documents (91 from MEDLINE and LILACS, and 50 from LILACS only) published in 44 different journals (23 of them MEDLINE-indexed). A total of 111 documents were produced by 17 public universities, 29 by 3 private medical schools and 1 by a non-governmental organization. There were 65 original contributions, 37 case reports, 20 reviews, 6 PhD dissertations, 5 guidelines, 2 validation studies, 2 clinical trials, 2 chapters in textbooks, 1 Master of Science thesis, and 1 patient education handout. The journal impact factor ranged from 0.0217 to 6.039 (median 3.03). Of 91 papers from MEDLINE, 65 were published by Arquivos de Neuro-Psiquiatria. More than 90% of the papers were written in Portuguese. São Paulo was the most productive state in the country, followed by Rio de Janeiro, Minas Gerais and Paraná. Eighty-two percent of the Brazilian output came from the Southeastern region.
Resumo:
The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.