78 resultados para artificially expanded genetic information system


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OBJECTIVE: To study the factors associated with the risk of in-hospital death in acute myocardial infarction in the Brazilian public health system in Rio de Janeiro, Brazil. METHODS: Sectional study of a sample with 391 randomly drawn medical records of the hospitalizations due to acute myocardial infarction recorded in the hospital information system in 1997. RESULTS: The diagnosis was confirmed in 91.7% of the cases; 61.5% males; age = 60.2 ± 2.4 years; delta time until hospitalization of 11 hours; 25.3% were diabetic; 58.1% were hypertensive; 82.6% were in Killip I class. In-hospital mortality was 20.6%. Thrombolysis was used in 19.5%; acetylsalicylic acid (ASA) 86.5%; beta-blockers 49%; angiotensin-converting enzyme (ACE) inhibitors 63.3%; calcium channel blockers 30.5%. Factors associated with increased death: age (61-80 years: OR=2.5; > 80 years: OR=9.6); Killip class (II: OR=1.9; III: OR=6; IV: OR=26.5); diabetes (OR=2.4); ventricular tachycardia (OR=8.5); ventricular fibrillation (OR=34); recurrent ischemia (OR=2.7). The use of ASA (OR=0.3), beta-blockers (OR=0.3), and ACE inhibitors (OR=0.4) was associated with a reduction in the chance of death. CONCLUSION: General lethality was high and some interventions of confirmed efficacy were underutilizated. The logistic model showed the beneficial effect of beta-blockers, and ACE inhibitors on the risk of in-hospital death.

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Cryptosporidiosis has recently attracted attention as an emerging waterborne and foodborne disease as well as an opportunistic infection in HIV infected individuals. The lack of genetic information, however, has resulted in confusion in the taxonomy of Cryptosporidium parasites and in the development of molecular tools for the identification and typing of oocysts in environmental samples. Phylogenetic analysis of the small subunit ribosomal RNA (SSU rRNA) gene has shown that the genus Cryptosporidium is comprised of several distinct species. Our data show the presence of at least four species: C. parvum, C. muris, C. baileyi and C. serpentis (C. meleagridis, C. nasorum and C. felis were not studied). Within each species, there is some sequence variation. Thus, various genotypes (genotype 1, genotype 2, guinea pig genotype, monkey genotype and koala genotype, etc.) of C. parvum differ from each other in six regions of the SSU rRNA gene. Information on polymorphism in Cryptosporidium parasites has been used in the development of species and strain-specific diagnostic tools. Use of these tools in the characterization of oocysts various samples indicates that C. parvum genotype 1 is the strain responsible for most human Cryptosporidium infections. In contrast, genotype 2 is probably the major source for environmental contamination of environment, and has been found in most oysters examined from Chesapeake Bay that serve as biologic monitors of surface water. Parasites of Cryptosporidium species other than C. parvum have not been detected in HIV+ individuals, indicating that the disease in humans is caused only by C. parvum.

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A 0.125 degree raster or grid-based Geographic Information System with data on tsetse, trypanosomosis, animal production, agriculture and land use has recently been developed in Togo. This paper addresses the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. A discriminant analysis model is tested using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration and Meteosat platforms. A split sample technique is adopted where a randomly selected part of the field measured data (training set) serves to predict the other part (predicted set). The obtained results are then compared with field measured data per corresponding grid-square. Depending on the size of the training set the percentage of concording predictions varies from 80 to 95 for distribution figures and from 63 to 74 for abundance. These results confirm the potential of satellite data application and multivariate analysis for the prediction, not only of the tsetse distribution, but more importantly of their abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen or substitute one another and thus reduce costs of field surveys.

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The development of biotechnology in the last three decades has generated the feeling that the newest scientific achievements will deliver high standard quality of life through abundance of food and means for successfully combating diseases. Where the new biotechnologies give access to genetic information, there is a common belief that physiological and pathological processes result from subtle modifications of gene expression. Trustfully, modern genetics has produced genetic maps, physical maps and complete nucleotide sequences from 141 viruses, 51 organelles, two eubacteria, one archeon and one eukaryote (Saccharomices cerevisiae). In addition, during the Centennial Commemoration of the Oswaldo Cruz Institute the nearly complete human genome map was proudly announced, whereas the latest Brazilian key stone contribution to science was the publication of the Shillela fastidiosa genomic sequence highlythed on a Nature cover issue. There exists a belief among the populace that further scientific accomplishments will rapidly lead to new drugs and methodological approaches to cure genetic diseases and other incurable ailments. Yet, much evidence has been accumulated, showing that a large information gap exists between the knowledge of genome sequence and our knowledge of genome function. Now that many genome maps are available, people wish to know what are we going to do with them. Certainly, all these scientific accomplishments will shed light on many more secrets of life. Nevertheless, parsimony in the weekly announcements of promising scientific achievements is necessary. We also need many more creative experimental biologists to discover new, as yet un-envisaged biotechnological approaches, and the basic resource needed for carrying out mile stone research necessary for leading us to that "promised land"often proclaimed by the mass media.

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The geographic information system approach has permitted integration between demographic, socio-economic and environmental data, providing correlation between information from several data banks. In the current work, occurrence of human and canine visceral leishmaniases and insect vectors (Lutzomyia longipalpis) as well as biogeographic information related to 9 areas that comprise the city of Belo Horizonte, Brazil, between April 2001 and March 2002 were correlated and georeferenced. By using this technique it was possible to define concentration loci of canine leishmaniasis in the following regions: East; Northeast; Northwest; West; and Venda Nova. However, as for human leishmaniasis, it was not possible to perform the same analysis. Data analysis has also shown that 84.2% of the human leishmaniasis cases were related with canine leishmaniasis cases. Concerning biogeographic (altitude, area of vegetation influence, hydrographic, and areas of poverty) analysis, only altitude showed to influence emergence of leishmaniasis cases. A number of 4673 canine leishmaniasis cases and 64 human leishmaniasis cases were georeferenced, of which 67.5 and 71.9%, respectively, were living between 780 and 880 m above the sea level. At these same altitudes, a large number of phlebotomine sand flies were collected. Therefore, we suggest control measures for leishmaniasis in the city of Belo Horizonte, giving priority to canine leishmaniasis foci and regions at altitudes between 780 and 880 m.

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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.

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This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

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Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

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Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R² = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

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Praziquantel chemotherapy has been the focus of the Schistosomiasis Control Program in Brazil for the past two decades. Nevertheless, information on the impact of selective chemotherapy against Schistosoma mansoni infection under the conditions confronted by the health teams in endemic municipalities remains scarce. This paper compares the spatial pattern of infection before and after treatment with either a 40 mg/kg or 60 mg/kg dose of praziquantel by determining the intensity of spatial cluster among patients at 180 and 360 days after treatment. The spatial-temporal distribution of egg-positive patients was analysed in a Geographic Information System using the kernel smoothing technique. While all patients became egg-negative after 21 days, 17.9% and 30.9% reverted to an egg-positive condition after 180 and 360 days, respectively. Both the prevalence and intensity of infection after treatment were significantly lower in the 60 mg/kg than in the 40 mg/kg treatment group. The higher intensity of the kernel in the 40 mg/kg group compared to the 60 mg/kg group, at both 180 and 360 days, reflects the higher number of reverted cases in the lower dose group. Auxiliary, preventive measures to control transmission should be integrated with chemotherapy to achieve a more enduring impact.

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In Brazil, malaria remains a disease of major epidemiological importance because of the high number of cases in the Amazonian Region. Plasmodium spp infections during pregnancy are a significant public health problem with substantial risks for the pregnant woman, the foetus and the newborn child. In Brazil, the control of malaria during pregnancy is primarily achieved by prompt and effective treatment of the acute episodes. Thus, to assure rapid diagnosis and treatment for pregnant women with malaria, one of the recommended strategy for low transmission areas by World Health Organization and as part of a strategy by the Ministry of Health, the National Malaria Control Program has focused on integrative measures with woman and reproductive health. Here, we discuss the approach for the prevention and management of malaria during pregnancy in Brazil over the last 10 years (2003-2012) using morbidity data from Malaria Health Information System. Improving the efficiency and quality of healthcare and education and the consolidation of prevention programmes will be challenges in the control of malaria during pregnancy in the next decade.

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Based on data available in the Information System for Notifiable Diseases, predictive factors of favorable results were identified in the treatment of pulmonary tuberculosis, diagnosed between 2001 and 2004 and living in Recife-PE, Brazil. Uni- and multivariate logistic regression methods were used. In multivariate analysis, the following factors remained: Age (years), 0 to 9 (OR=4.27; p=0.001) and 10 to 19 (OR=1.78; p=0.011), greater chance of cure than over 60; Education (years), 8 to 11 (OR=1.52; p=0.049), greater chance of cure than no education; Type of entry, new cases (OR=3.31; p<0.001) and relapse (OR=3.32; p<0.001), greater chances of cure than restart after abandonment; Time (months) 2, 5-|6 (OR=9.15; p<0.001); 6-|9 (OR=27.28; p<0.001) and More than 9 (OR=24.78; p<0.001), greater chances of cure than less than 5; Health Unit District, DS I (OR=1.60; p=0.018) and DS IV (OR=2.87; p<0.001), greater chances of cure than DS VI.

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Hemorrhage represents a set of causes that focuses on women during the pregnancy and puerperal period, and that, with improper attention, results in death. The authors aimed to analyze maternal deaths related to hemorrhage that occurred in the state of Santa Catarina, Brazil. The data were obtained from the Mortality Information System and Live Births Information System from the Brazilian Ministry of Health. This was a descriptive study, in which 491 maternal deaths that occurred in the period 1997-2010 were analyzed. Of these, 61 were related to hemorrhage, corresponding to 12.42%; postpartum hemorrhage was the most prevalent cause, with 26 deaths, followed by placental abruption with 15, representing 67.21% of the cases. The maternal mortality from hemorrhage is a public health problem in the state of Santa Catarina, due to its high prevalence and the fact that its underlying causes are preventable.

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Objective To evaluate the factors associated with neonatal mortality in infant born with low birth weight. Method Cross-sectional study that analyzed data from 771 live births with low birth weight (<2500 g) in the city of Cuiabá, MT, in 2010, of whom 54 died in the neonatal period. We obtained data from the Information System on Live Births and Mortality, by integrated linkage. Results In multiple logistic regression, neonatal mortality was associated with: number of prenatal visits less than 7 (OR=3.80;CI:1,66-8,70); gestational age less than 37 weeks (OR=4.77;CI:1.48-15.38), Apgar score less than 7 at the 1st minute (OR=4.25;CI:1.84-9.81) and the 5th minute (OR=5.72,CI:2.24-14.60) and presence of congenital anomaly (OR=14.39;IC:2.72-76.09). Conclusion Neonatal mortality in infants with low birth weight is associated with avoidable factors through adequate attention to prenatal care, childbirth and infants.


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The study goals present an overview of Hospitalizations for Ambulatory Care Sensitive Conditions (ACSC) in Guarulhos, SP, from 2008 to 2012. This is an ecological study based on secondary data obtained from the Brazilian Hospital Information System, and supported by the Praxical Theory of Intervention of Collective Health Nursing. Applied descriptive statistics for analysis. It was observed that Guarulhos shows an upward trend in hospitalizations by ACSC (20% increase), the most frequent causes of heart failure (11.8%), cerebrovascular disease (10.6%) and angina (9.7%), most frequently in the age group ≥ 65years old, for both sexes. The results are similar to other Brazilian studies, but their analysis should extrapolate the biological limits and the supply of healthcare resources, focusing on the social determinants of the health-disease process.