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Submitted by Maria Creuza Silva (mariakreuza@yahoo.com.br) on 2012-11-03T04:25:17Z No. of bitstreams: 1 The efect Per Intern 2012.pdf: 151918 bytes, checksum: 3cb35f6f28103a45dc6d2792a7313309 (MD5) Made available in DSpace on 2012-11-03T04:25:17Z (GMT). No. of bitstreams: 1 The efect Per Intern 2012.pdf: 151918 bytes, checksum: 3cb35f6f28103a45dc6d2792a7313309 (MD5) Previous issue date: 2012-02 Background: The current epidemic of asthma and atopy has been explained by alterations in immune responses related to reduction in childhood infections. However, the findings of epidemiologic studies investigating the association between infection with atopy and asthma have been inconsistent. Objective: We sought to investigate the effect of single or multiple infections (pathogen burden) on atopy and wheeze in urban children from Latin America. Methods: Specific IgE against aeroallergens (sIgE) and skin prick test (SPT) reactivity for the most common local allergens were measured in 1128 children aged 4 to 11 years. Data on wheezing and potential confounders were collected by questionnaire. Infections by 8 pathogens were assessed by using serology and stool examination. Associations of wheeze and atopic outcomes with single and multiple infections were analyzed by means of logistic regression. Results: Negative results for Toxoplasma gondii were associated with a higher prevalence of sIgE (>0.70 kU/L), whereas negative results for Ascaris lumbricoides, T gondii, erpes simplex virus, and EV were associated with a higher prevalence of SPT reactivity. Children with 3 or fewer infection markers had a higher prevalence of sIgE and SPT rectivity compared with those with 4 or more infection markers. However, isolated infections or pathogen burden were not associated with the prevalence of atopic or nonatopic wheeze. Conclusion: The findings provide support for the idea that the hygiene hypothesis is operating in an urban Latin American context, but its expression is thus far restricted to the atopic status of patients and not the perceived asthma symptoms. Canadá

Texto completo: acesso restrito. p. 209–214 Submitted by Edileide Reis (leyde-landy@hotmail.com) on 2013-12-13T12:58:59Z No. of bitstreams: 1 Inês Dourado.pdf: 221421 bytes, checksum: f1eead10d024bf7260aeac4b3775a892 (MD5) Made available in DSpace on 2013-12-13T12:58:59Z (GMT). No. of bitstreams: 1 Inês Dourado.pdf: 221421 bytes, checksum: f1eead10d024bf7260aeac4b3775a892 (MD5) Previous issue date: 2004 Background In addition to controversies as to the definition of nosocomial pneumonia (NP) because of the lack of a widely accepted diagnostic standard, there has been no agreement concerning the time span from hospital admission to disease onset. This study aims at both estimating the time span, in hours, from admission to the occurrence of suspected NP and investigating risk factors that might influence this time span. Methods This is a cohort study, and subjects were patients with nosocomial infection acquired in the intensive care unit of Edgard Santos University Hospital (HUPES/ICU) in Salvador, Brazil, from January 1995 to December 1997. Patients were observed from admission to 48 hours after discharge from the intensive care unit. The time span from admission to occurrence of suspected NP, the reason for admission, patient's origin, history of surgery, general anesthesia, mechanical ventilation, and use of antibiotic were analyzed and given a multivariate analysis using Cox regression model. Results Among 246 patients with nosocomial infection, 198 (80.5%) were suspected cases of NP, whereas 48 patients (19.5%) were not classified as such. The mean time, in hours, for the NP-free time span was 85.1 ± 3.5 hours, and the median time was 72 hours when estimated by Kaplan-Meier method. Patients admitted from surgical heart procedures who had been given general anesthesia, mechanical ventilation, and antibiotics showed statistically significant shorter mean time spans from admission to NP occurrence when compared with the other patients. Age ≥50 years, use of mechanical ventilation, and use of antibiotics were associated with NP. Conclusions Our finding for the estimated mean NP-free time span at the HUPES/ICU is somewhat in accordance with the literature (48 to 72 hours). Patients at HUPES/ICU might be considered as showing early NP, because they were diagnosed before the 5th day after admission. Preventive measures to NP should be reviewed and intensified at the HUPES/ICU, especially as related to mechanical ventilation.

Submitted by (ana.araujo@ufrpe.br) on 2016-08-04T13:26:23Z No. of bitstreams: 1 Magali Teresopolis Reis Amaral.pdf: 5438608 bytes, checksum: a3ca949533ae94adaf7883fd465a627a (MD5) Made available in DSpace on 2016-08-04T13:26:23Z (GMT). No. of bitstreams: 1 Magali Teresopolis Reis Amaral.pdf: 5438608 bytes, checksum: a3ca949533ae94adaf7883fd465a627a (MD5) Previous issue date: 2008-08-18 The adjustment of the weight-age growth curves for animals plays an important role in animal production planning. These adjusted growth curves must be coherent with the biological interpretation of animal growth, which often demands imposition of constraints on model parameters.The inference of the parameters of nonlinear models with constraints, using classical techniques, presents various difficulties. In order to bypass those difficulties, a bayesian approach for adjustment of the growing curves is proposed. In this respect the bayesian proposed approach introduces restrictions on model parameters through choice of the prior density. Due to the nonlinearity, the posterior density of those parameters does not have a kernel that can be identified among the traditional distributions, and their moments can only be obtained using numerical techniques. In this work the MCMC simulation (Monte Carlo chain Markov) was implemented to obtain a summary of the posterior density. Besides, selection model criteria were used for the observed data, based on generated samples of the posterior density.The main purpose of this work is to show that the bayesian approach can be of practical use, and to compare the bayesian inference of the estimated parameters considering noninformative prior density (from Jeffreys), with the classical inference obtained by the Gauss-Newton method. Therefore it was possible to observe that the calculation of the confidence intervals based on the asymptotic theory fails, indicating non significance of certain parameters of some models, while in the bayesian approach the intervals of credibility do not present this problem. The programs in this work were implemented in R language,and to illustrate the utility of the proposed method, analysis of real data was performed, from an experiment of evaluation of system of crossing among cows from different herds, implemented by Embrapa Pecuária Sudeste. The data correspond to 12 measurements of weight of animals between 8 and 19 months old, from the genetic groups of the races Nelore and Canchim, belonging to the genotype AALLAB (Paz 2002). The results reveal excellent applicability of the bayesian method, where the model of Richard presented difficulties of convergence both in the classical and in the bayesian approach (with non informative prior). On the other hand the logistic model provided the best adjustment of the data for both methodologies when opting for non informative and informative prior density. O ajuste de curva de crescimento peso-idade para animais tem um papel importante no planejamento da produção animal. No entanto, as curvas de crescimento ajustadas devem ser coerentes com as interpretações biológicas do crescimento do animal, o que exige muitas vezes que sejam impostas restrições aos parâmetros desse modelo.A inferência de parâmetros de modelos não lineares sujeito a restrições, utilizando técnicas clássicas apresenta diversas dificuldades. Para contornar estas dificuldades, foi proposta uma abordagem bayesiana para ajuste de curvas de crescimento. Neste sentido,a abordagem bayesiana proposta introduz as restrições nos parâmetros dos modelos através das densidades de probabilidade a priori adotadas. Devido à não linearidade, as densidades a posteriori destes parâmetros não têm um núcleo que possa ser identificado entre as distribuições tradicionalmente conhecidas e os seus momentos só podem ser obtidos numericamente. Neste trabalho, as técnicas de simulação de Monte Carlo Cadeia de Markov (MCMC) foram implementadas para obtenção de um sumário das densidades a posteriori. Além disso, foram utilizados critérios de seleção do melhor modelo para um determinado conjunto de dados baseados nas amostras geradas das densidades a posteriori.O objetivo principal deste trabalho é mostrar a viabilidade da abordagem bayesiana e comparar a inferência bayesiana dos parâmetros estimados, considerando-se densidades a priori não informativas (de Jeffreys), com a inferência clássica das estimativas obtidas pelo método de Gauss-Newton. Assim, observou-se que o cálculo de intervalos de confiança, baseado na teoria assintótica, falha, levando a não significância de certos parâmetros de alguns modelos. Enquanto na abordagem bayesiana os intervalos de credibilidade não apresentam este problema. Os programas utilizados foram implementados no R e para ilustração da aplicabilidade do método proposto, foram realizadas análises de dados reais oriundos de um experimento de avaliação de sistema de cruzamento entre raças bovinas de corte, executado na Embrapa Pecuária Sudeste. Os dados correspondem a 12 mensurações de peso dos 8 aos 19 meses de idade do grupo genético das raças Nelore e Canchim, pertencente ao grupo de genotípico AALLAB, ver (Paz 2002). Os resultados revelaram excelente aplicabilidade do método bayesiano, destacando que o modelo de Richard apresentou dificuldades de convergência tanto na abordagem clássica como bayesiana (com priori não informativa). Por outro lado o modelo Logístico foi quem melhor se ajustou aos dados em ambas metodologias quando se optou por densidades a priori não informativa e informativa.