82 resultados para errors-in-variables model


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Background: There is only limited knowledge on how the quantification of valvular regurgitation by color Doppler is affected by changing blood viscosity. This study was designed to evaluate the effect of changing blood viscosity on the vena contracta width using an in vitro model of valvular insufficiency capable of providing ample variation in the rate and stroke volume. Methods: We constructed a pulsatile flow model filled with human blood at varying hematocrit (15%, 35%, and 55%) and corresponding blood viscosity (blood/water viscosity: 2.6, 4.8, 9.1) levels in which jets were driven through a known orifice (7 mm(2)) into a 110 mL compliant receiving chamber (compliance: 2.2 mL/mmHg) by a pulsatile pump. In addition, we used variable pump stroke volumes (5, 7.5, and 10 mL) and rates (40, 60, and 80 ppm). Vena contracta region was imaged using a 3.5 MHz transducer. Pressure and volume in the flow model were kept constant during each experimental condition, as well as ultrasound settings. Results: Blood viscosity variation in the experimental range did not induce significant changes in vena contracta dimensions. Also, vena contracta width did not change from normal to low hematocrit and viscosity levels. A very modest increase only in vena contracta dimension was observed at very high level of blood viscosity when hematocrit was set to 55% . Pump rate, in the evaluated range, did not influence vena contracta width. These results in controlled experimental settings suggest that the vena contracta is an accurate quantitative method for quantifying valvular regurgitation even when this condition is associated with anemia, a frequent finding in patients with valvular heart disease.

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Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

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This study was undertaken to test whether the structural remodelling of pulmonary parenchyma can be sequentially altered in a model and method that demonstrate the progression of the disease and result in remodelling within the lungs that is typical of idiopathic pulmonary fibrosis. Three groups of mice were studied: (i) animals that received 3-5-di-tert-butyl-4-hydroxytoluene (BHT) and were killed after 2 weeks (early BHT = 9); (ii) animals that received BHT and were killed after 4 weeks (late BHT = 11); (iii) animals that received corn oil solution (control = 10). The mice were placed in a ventilated Plexiglas chamber with a mixture of pure humidified oxygen and compressed air. Lung histological sections underwent haematoxylin-eosin, immunohistochemistry (epithelial, endothelial and immune cells) and specific staining (collagen/elastic fibres) methods for morphometric analysis. When compared with the control group, early BHT and late BHT groups showed significant decrease of type II pneumocytes, lower vascular density in both and higher endothelial activity. CD4 was increased in late BHT compared with early and control groups, while CD8, macrophage and neutrophil cells were more prominent only in early BHT. The collagenous fibre density were significantly higher only in late BHT, whereas elastic fibre content in late BHT was lower than that in control group. We conclude that the BHT experimental model is pathologically very similar to human usual interstitial pneumonia. This feature is important in the identification of animal models of idiopathic pulmonary fibrosis that can accurately reflect the pathogenesis and progression of the human disease.

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The purpose of this study is to determine the correlation of socioeconomic, dietary, and anthropometric-nutritional variables of parents and their children to overweight (including obesity) in schoolchildren in Santa Catarina State, Brazil. This is a transversal study conducted on 4,964, 6 to 10-year-old schoolchildren registered in 345 Santa Catarina elementary schools. The following data were acquired: the children`s current weight and height, birth weight and length, duration of breastfeeding, age at which water, herbal tea and other foods were introduced to their diet; parental income, education level, age, weight and height were also obtained. The prevalence of overweight and obese children were estimated by point and by interval with a 95% confidence; prevalence rates were obtained based on the Poisson model. An hierarchical approach was used, in which variables were adjusted within blocks and included in the model when they presented p<0.05 at the outcome (overweight including obesity). The results indicate that 47.8% of the subjects were male. The prevalence of overweight and obese students was 15.4% (C195%: 14.4%-16.5%) and 6.1% (CI95%: 5.4%-6.7%) respectively and were statistically similar among sexes and age ranges. BMI values were higher in males and among older children (p<0.05). After adjustment within and among blocks, the variables per capita household income and parents` BM I values remained associated with overweight (including obesity). Overweight (including obesity) in schoolchildren is associated with a higher per capita household income and parental overweight and obesity.

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Forty Cryptococcus gattii strains were submitted to antifungal susceptibility testing with fluconazole, itraconazole, amphotericin B and terbinafine. The minimum inhibitory concentration (MIC) ranges were 0.5-64.0 for fluconazole, < 0.015-0.25 for itraconazole, 0.015-0.5 for amphotericin B and 0.062-2.0 for terbinafine. A bioassay for the quantitation of fluconazole in murine brain tissue was developed. Swiss mice received daily injections of the antifungal, and their brains were withdrawn at different times over the 14-day study period. The drug concentrations varied from 12.98 to 44.60 mu g/mL. This assay was used to evaluate the therapy with fluconazole in a model of infection caused by C. gattii. Swiss mice were infected intracranially and treated with fluconazole for 7, 10 or 14 days. The treatment reduced the fungal burden, but an increase in fungal growth was observed on day 14. The MIC for fluconazole against sequential isolates was 16 mu g/mL, except for the isolates obtained from animals treated for 14 days (MIC = 64 mu g/mL). The quantitation of cytokines revealed a predominance of IFN-gamma and IL-12 in the non-treated group and elevation of IL-4 and IL-10 in the treated group. Our data revealed the possibility of acquired resistance during the antifungal drug therapy.

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It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

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Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

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Objective. To investigate the short-term effects of exposure to particulate matter from biomass burning in the Amazon on the daily demand for outpatient care due to respiratory diseases in children and the elderly. Methods. Epidemiologic study with ecologic time series design. Daily consultation records were obtained from the 14 primary health care clinics in the municipality of Alta Floresta, state of Mato Grosso, in the southern region of the Brazilian Amazon, between January 2004 and December 2005. Information on the daily levels of fine particulate matter was made available by the Brazilian National Institute for Spatial Research. To control for confounding factors ( situations in which a non-causal association between exposure and disease is observed due to a third variable), variables related to time trends, seasonality, temperature, relative humidity, rainfall, and calendar effects ( such as occurrence of holidays and weekends) were included in the model. Poisson regression with generalized additive models was used. Results. A 10 mu g/m(3) increase in the level of exposure to particulate matter was associated with increases of 2.9% and 2.6% in outpatient consultations due to respiratory diseases in children on the 6th and 7th days following exposure. Significant associations were not observed for elderly individuals. Conclusions. The results suggest that the levels of particulate matter from biomass burning in the Amazon are associated with adverse effects on the respiratory health of children.

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A previously proposed model describing the trapping site of the interstitial atomic hydrogen in borate glasses is analyzed. In this model the atomic hydrogen is stabilized at the centers of oxygen polygons belonging to B-O ring structures in the glass network by van der Waals forces. The previously reported atomic hydrogen isothermal decay experimental data are discussed in the light of this microscopic model. A coupled differential equation system of the observed decay kinetics was solved numerically using the Runge Kutta method. The experimental untrapping activation energy of 0.7 x 10(-19) J is in good agreement with the calculated results of dispersion interaction between the stabilized atomic hydrogen and the neighboring oxygen atoms at the vertices of hexagonal ring structures. (C) 2009 Elsevier B.V. All rights reserved.

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The Birnbaum-Saunders regression model is becoming increasingly popular in lifetime analyses and reliability studies. In this model, the signed likelihood ratio statistic provides the basis for testing inference and construction of confidence limits for a single parameter of interest. We focus on the small sample case, where the standard normal distribution gives a poor approximation to the true distribution of the statistic. We derive three adjusted signed likelihood ratio statistics that lead to very accurate inference even for very small samples. Two empirical applications are presented. (C) 2010 Elsevier B.V. All rights reserved.

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This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.

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Hajnal and Juhasz proved that under CH there is a hereditarily separable, hereditarily normal topological group without non-trivial convergent sequences that is countably compact and not Lindelof. The example constructed is a topological subgroup H subset of 2(omega 1) that is an HFD with the following property (P) the projection of H onto every partial product 2(I) for I is an element of vertical bar omega(1)vertical bar(omega) is onto. Any such group has the necessary properties. We prove that if kappa is a cardinal of uncountable cofinality, then in the model obtained by forcing over a model of CH with the measure algebra on 2(kappa), there is an HFD topological group in 2(omega 1) which has property (P). Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

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PURPOSE: Evaluate the bone tissue recovery following transplantation of ovine mesenchymal stem cells (MSC) from bone marrow and human immature dental-pulp stem cells (hIDPSC) in ovine model of induced osteonecrosis of femoral head (ONFH). METHODS: Eight sheep were divided in three experimental groups. First group was composed by four animals with ONFH induced by ethanol through central decompression (CD), for control group without any treatment. The second and third group were compose by two animals, six weeks after ONFH induction received transplantation of heterologous ovine MSC (CD + oMSC), and hIDPSC (CD + hIDPSC), respectively. In both experiments the cells were transplanted without application of any type of immunosupression protocol. RESULTS: Our data indicate that both cell types used in experiments were able to proliferate within injured site providing bone tissue recovery. The histological results obtained from CD+hIDPSC suggested that the bone regeneration in such animals was better than that observed in CD animals. CONCLUSION: Mesenchymal stem cell transplant in induced ovine osteonecrosis of femoral head by central decompression technique is safe, and apparently favors bone regeneration of damaged tissues.

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Malignant brain tumor experimental models tend to employ cells that are immunologically compatible with the receptor animal. In this study, we have proposed an experimental model of encephalic tumor development by injecting C6 cells into athymic Rowett rats, aiming at reaching a model which more closely resembles to the human glioma tumor. In our model, we observed micro-infiltration of tumor cell clusters in the vicinity of the main tumor mass, and of more distal isolated tumor cells immersed in normal encephalic parenchyma. This degree of infiltration is superior to that usually observed in other C6 models.

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We evaluated the impact of a lifestyle intervention on the cardiometabolic risk profile of women participating in the Study on Diabetes and Associated Diseases in the Japanese-Brazilian Population in Bauru. This was a non-controlled experimental study including clinical and laboratory values at baseline and after a 1-year intervention period. 401 Japanese-Brazilian women were examined (age 60.8±11.7 years), and 365 classified for metabolic syndrome (prevalence = 50.6%). Subjects with metabolic syndrome were older than those without (63.0±10.0 vs. 56.7±11.6 years, p < 0.01). After intervention, improvements in variables were found, except for C-reactive protein. Body mass index and waist circumference decreased, but adiposity reduction was more pronounced in the abdominal region (87.0±9.7 to 84.5±11.2cm, p < 0.001). Intervention-induced differences in total cholesterol, LDL, and post-challenge glucose were significant; women who lost more than 5% body weight showed a better profile than those who did not. The lifestyle intervention in Japanese-Brazilian women at high cardiometabolic risk improved anthropometric and laboratory parameters, but it is not known whether such benefits will persist and result in long-term reduction in cardiovascular events.