56 resultados para combinatorial protocol in multiple linear regressions


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OBJECTIVE: To assess the trends of the risk of death due to circulatory (CD), cerebrovascular (CVD), and ischemic heart diseases (IHD) in 11 Brazilian capitals from 1980 to 1998. METHODS: Data on mortality due to CD, CVD and IHD were obtained from the Brazilian Health Ministry, and the population estimates were calculated by interpolation with the Lagrange method based on census data from 1980 and 1991 and the population count of 1996. The trends were analyzed with the multiple linear regression method. RESULTS: CD showed a trend towards a decrease in most capitals, except for Brasília, where a mild increase was observed. The cities of Porto Alegre, Curitiba, Rio de Janeiro, Cuiabá, Goiânia, Belém, and Manaus showed a decrease in the risk of death due to CVD and IHD, while the city of Brasília showed an increase in CVD and IHD. The city of São Paulo showed a mild increase in IHD for individuals of both sexes aged 30 to 39 years and for females aged 40 to 59 years. In the cities of Recife and Salvador, a reduction in CD was observed for all ages and both sexes. In the city of Recife, however, an increase in IHD was observed at younger ages (30 to 49 years), and this trend decreased until a mild reduction (-4%) was observed in males ³ 70 years. CONCLUSION: In general, a reduction in the risk of death due to CD and an increase in IHD were observed, mainly in the cities of Recife and Brasília.

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Background: Changes in the properties of large arteries correlate with higher cardiovascular risk. Recent guidelines have included the assessment of those properties to detect subclinical disease. Establishing reference values for the assessment methods as well as determinants of the arterial parameters and their correlations in healthy individuals is important to stratify patients. Objective: To assess, in healthy adults, the distribution of the values of pulse wave velocity, diameter, intima-media thickness and relative distensibility of the carotid artery, in addition to assessing the demographic and clinical determinants of those parameters and their correlations. Methods: This study evaluated 210 individuals (54% women; mean age, 44 ± 13 years) with no evidence of cardiovascular disease. The carotid-femoral pulse wave velocity was measured with a Complior® device. The functional and structural properties of the carotid artery were assessed by using radiofrequency ultrasound. Results: The means of the following parameters were: pulse wave velocity, 8.7 ± 1.5 m/s; diameter, 6,707.9 ± 861.6 μm; intima-media thickness, 601 ± 131 μm; relative distensibility, 5.3 ± 2.1%. No significant difference related to sex or ethnicity was observed. On multiple linear logistic regression, the factors independently related to the vascular parameters were: pulse wave velocity, to age (p < 0.01) and triglycerides (p = 0.02); intima-media thickness, to age (p < 0.01); diameter, to creatinine (p = 0.03) and age (p = 0.02); relative distensibility, to age (p < 0.01) and systolic and diastolic blood pressures (p = 0.02 and p = 0.01, respectively). Pulse wave velocity showed a positive correlation with intima media thickness (p < 0.01) and with relative distensibility (p < 0.01), while diameter showed a positive correlation with distensibility (p = 0.03). Conclusion: In healthy individuals, age was the major factor related to aortic stiffness, while age and diastolic blood pressure related to the carotid functional measure. The carotid artery structure was directly related to aortic stiffness, which was inversely related to the carotid artery functional property.

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Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.

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A laboratory experiment was carried out to study the effects of chemical and physical characteristics of the soil on the phosphate fixing capacity. One hundred samples collected from various localities were at first characterized chemically and their particlesize distribution determined. They were then tested as to their phosphate fixing capacities. The results obtained were statistically analysed by means of both simple linear and multiple correlation. The following conclusions could be drawn: 1. simple linear regression analysis indicated that % C, exchangeable Al+3, CEC, % clay, pH and % sand were the soil characteristics which significantly affected phosphate fixing capacity of São Paulo State soils; 2. multiple linear regression analysis indicated that % C, exchangeable Mg(+2)9 exchangeable- Al+3 and % clay were the soil characteristics which significantly affected the phosphate fixing capacity of São Paulo State soils; 3. the phosphate phonomena fixing as they occur in the soils of the São Paulo State can be best described by the following equation: Y = -2,266 - 3,484 + 3,514 + 5,559 + 1,005 %C Mg+2 Al+3 % clay exchangeable exchangeable 4. phosphate fixation in the soil is affected by the combined effects of both soil chemical and physical characteristics.

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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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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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Seasonality in insect abundance in the "Cerrado" of Goiás State, Brazil. Many studies have provided evidence that tropical insects undergo seasonal changes in abundance and that this is partly due to alternation between the dry and rainy seasons. In the Brazilian "Cerrado" (savannah), this season alternation is particularly evident. The purpose of this work was to study the seasonal abundance of insects in a "Cerrado" area in the municipality of Pirenópolis, Goiás State, Brazil. The insects were captured fortnightly using a light trap between September 2005 and August 2006. The insects collected were separated at the order level and counted. Faunistic analysis was performed to select the predominant insect orders, a multiple linear regression to examine the relation between climatic variables (temperature and precipitation) with the abundance of insects and a circular distribution analysis to evaluate the existence of seasonality in the abundance of insect orders. A total of 34,741 insect specimens were captured, belonging to 19 orders. The orders with the greatest number of specimens were Hymenoptera (8,022), Coleoptera (6,680), Diptera (6,394), Lepidoptera (6,223), Isoptera (2,272), Hemiptera (2,240) and Trichoptera (1,967), which represent 97.3% of all the specimens collected. All the orders, except for Diptera, Isoptera and Trichoptera, showed a relationship with the climate variables (temperature), and all the orders, except for Diptera, presented a grouped distribution, with greater abundance in the transition from the end of the dry season (September) to the start of the rainy one (October/November). A discussion about seasonality on the abundance of the insects is presented.

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Polistine wasps are important in Neotropical ecosystems due to their ubiquity and diversity. Inventories have not adequately considered spatial attributes of collected specimens. Spatial data on biodiversity are important for study and mitigation of anthropogenic impacts over natural ecosystems and for protecting species. We described and analyzed local-scale spatial patterns of collecting records of wasp species, as well as spatial variation of diversity descriptors in a 2500-hectare area of an Amazon forest in Brazil. Rare species comprised the largest fraction of the fauna. Close range spatial effects were detected for most of the more common species, with clustering of presence-data at short distances. Larger spatial lag effects could also be identified in some species, constituting probably cases of exogenous autocorrelation and candidates for explanations based on environmental factors. In a few cases, significant or near significant correlations were found between five species (of Agelaia, Angiopolybia, and Mischocyttarus) and three studied environmental variables: distance to nearest stream, terrain altitude, and the type of forest canopy. However, association between these factors and biodiversity variables were generally low. When used as predictors of polistine richness in a linear multiple regression, only the coefficient for the forest canopy variable resulted significant. Some level of prediction of wasp diversity variables can be attained based on environmental variables, especially vegetation structure. Large-scale landscape and regional studies should be scheduled to address this issue.

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Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

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The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average daily mean air temperature and cumulative solar radiation, during seed filling; precipitation minus potential evapotranspiration, during the whole reproductive period; and the combinations of these climatic variables. Each amino acid behaves differently according to environmental conditions, indicating compensatory effects among them.

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BACKGROUND: E-learning techniques are spreading at great speed in medicine, raising concerns about the impact of adopting them. Websites especially designed to host courses are becoming more common. There is a lack of evidence that these systems could enhance student knowledge acquisition. GOAL: To evaluate the impact of using dedicated-website tools over cognition of medical students exposed to a first-aid course. METHODS: Prospective study of 184 medical students exposed to a twenty-hour first-aid course. We generated a dedicated-website with several sections (lectures, additional reading material, video and multiple choice exercises). We constructed variables expressing the student's access to each section. The evaluation was composed of fifty multiple-choice tests, based on clinical problems. We used multiple linear regression to adjust for potential confounders. RESULTS: There was no association of website intensity of exposure and the outcome - beta-coeficient 0.27 (95%CI - 0.454 - 1.004). These findings were not altered after adjustment for potential confounders - 0.165 (95%CI -0.628 - 0.960). CONCLUSION: A dedicated website with passive and active capabilities for aiding in person learning had not shown association with a better outcome.

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The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.

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Hypomagnesemia is the most common electrolyte disturbance seen upon admission to the intensive care unit (ICU). Reliable predictors of its occurrence are not described. The objective of this prospective study was to determine factors predictive of hypomagnesemia upon admission to the ICU. In a single tertiary cancer center, 226 patients with different diagnoses upon entering were studied. Hypomagnesemia was defined by serum levels <1.5 mg/dl. Demographic data, type of cancer, cause of admission, previous history of arrhythmia, cardiovascular disease, renal failure, drug administration (particularly diuretics, antiarrhythmics, chemotherapy and platinum compounds), previous nutrition intake and presence of hypovolemia were recorded for each patient. Blood was collected for determination of serum magnesium, potassium, sodium, calcium, phosphorus, blood urea nitrogen and creatinine levels. Upon admission, 103 (45.6%) patients had hypomagnesemia and 123 (54.4%) had normomagnesemia. A normal dietary habit prior to ICU admission was associated with normal Mg levels (P = 0.007) and higher average levels of serum Mg (P = 0.002). Postoperative patients (N = 182) had lower levels of serum Mg (0.60 ± 0.14 mmol/l compared with 0.66 ± 0.17 mmol/l, P = 0.006). A stepwise multiple linear regression disclosed that only normal dietary habits (OR = 0.45; CI = 0.26-0.79) and the fact of being a postoperative patient (OR = 2.42; CI = 1.17-4.98) were significantly correlated with serum Mg levels (overall model probability = 0.001). These findings should be used to identify patients at risk for such disturbance, even in other critically ill populations.

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We determined whether over-expression of one of the three genes involved in reverse cholesterol transport, apolipoprotein (apo) AI, lecithin-cholesterol acyl transferase (LCAT) and cholesteryl ester transfer protein (CETP), or of their combinations influenced the development of diet-induced atherosclerosis. Eight genotypic groups of mice were studied (AI, LCAT, CETP, LCAT/AI, CETP/AI, LCAT/CETP, LCAT/AI/CETP, and non-transgenic) after four months on an atherogenic diet. The extent of atherosclerosis was assessed by morphometric analysis of lipid-stained areas in the aortic roots. The relative influence (R²) of genotype, sex, total cholesterol, and its main sub-fraction levels on atherosclerotic lesion size was determined by multiple linear regression analysis. Whereas apo AI (R² = 0.22, P < 0.001) and CETP (R² = 0.13, P < 0.01) expression reduced lesion size, the LCAT (R² = 0.16, P < 0.005) and LCAT/AI (R² = 0.13, P < 0.003) genotypes had the opposite effect. Logistic regression analysis revealed that the risk of developing atherosclerotic lesions greater than the 50th percentile was 4.3-fold lower for the apo AI transgenic mice than for non-transgenic mice, and was 3.0-fold lower for male than for female mice. These results show that apo AI overexpression decreased the risk of developing large atherosclerotic lesions but was not sufficient to reduce the atherogenic effect of LCAT when both transgenes were co-expressed. On the other hand, CETP expression was sufficient to eliminate the deleterious effect of LCAT and LCAT/AI overexpression. Therefore, increasing each step of the reverse cholesterol transport per se does not necessarily imply protection against atherosclerosis while CETP expression can change specific athero genic scenarios.

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The association between early life factors and body mass index (BMI) in adulthood has been demonstrated in developed countries. The aim of the present study was to assess the influence of early life factors (birth weight, gestational age, maternal smoking, and social class) on BMI in young adulthood with adjustment for adult socioeconomic position. A cohort study was carried out in 1978/79 with 6827 mother-child pairs from Ribeirão Preto city, located in the most developed economic area of the country. Biological, economic and social variables and newborn anthropometric measurements were obtained shortly after delivery. In 1996, 1189 males from this cohort, 34.3% of the original male population, were submitted to anthropometric measurements and were asked about their current schooling on the occasion of army recruitment. A multiple linear regression model was applied to determine variables associated with BMI. Mean BMI was 22.7 (95%CI = 22.5-23.0). After adjustment, BMI was 1.22 kg/m² higher among infants born with high birth weight (³4000 g), 1.21 kg/m² higher among individuals of low social class at birth and 0.69 kg/m² higher among individuals whose mothers smoked during pregnancy (P < 0.05). The association between social class at birth and BMI remained statistically significant (P < 0.05) even after adjustment for adult schooling. These findings suggest that early life social influences on BMI were more important and were not reversed by late socioeconomic position. Therefore, prevention of overweight and obesity should focus not only on changes in adult life styles but also on factors such as high birth weight.