25 resultados para multivariate hidden Markov model
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
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Here, we describe a female patient with autism spectrum disorder and dysmorphic features that harbors a complex genetic alteration, involving a de novo balanced translocation t(2;X)(q11;q24), a 5q11 segmental trisomy and a maternally inherited isodisomy on chromosome 5. All the possibly damaging genetic effects of such alterations are discussed. In light of recent findings on ASD genetic causes, the hypothesis that all these alterations might be acting in orchestration and contributing to the phenotype is also considered. (C) 2012 Wiley Periodicals, Inc.
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This paper studies the asymptotic optimality of discrete-time Markov decision processes (MDPs) with general state space and action space and having weak and strong interactions. By using a similar approach as developed by Liu, Zhang, and Yin [Appl. Math. Optim., 44 (2001), pp. 105-129], the idea in this paper is to consider an MDP with general state and action spaces and to reduce the dimension of the state space by considering an averaged model. This formulation is often described by introducing a small parameter epsilon > 0 in the definition of the transition kernel, leading to a singularly perturbed Markov model with two time scales. Our objective is twofold. First it is shown that the value function of the control problem for the perturbed system converges to the value function of a limit averaged control problem as epsilon goes to zero. In the second part of the paper, it is proved that a feedback control policy for the original control problem defined by using an optimal feedback policy for the limit problem is asymptotically optimal. Our work extends existing results of the literature in the following two directions: the underlying MDP is defined on general state and action spaces and we do not impose strong conditions on the recurrence structure of the MDP such as Doeblin's condition.
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In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.
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In this paper the influence of a secondary variable as a function of the correlation with the primary variable for collocated cokriging is examined. For this study five exhaustive data sets were generated in computer, from which samples with 60 and 104 data points were drawn using the stratified random sampling method. These exhaustive data sets were generated departing from a pair of primary and secondary variables showing a good correlation. Then successive sets were generated by adding an amount of white noise in such a way that the correlation gets poorer. Using these samples, it was possible to find out how primary and secondary information is used to estimate an unsampled location according to the correlation level.
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Background: Polycystic ovary syndrome (PCOS) is an endocrine disorder associated with metabolic dysfunction and changes in cardiovascular risk markers, and using oral contraceptives (OCs) may exert a further negative effect on these alterations in patients with PCOS. Thus, the primary objective of this study was to assess the effects on arterial function and structure of an OC containing chlormadinone acetate (2 mg) and ethinylestradiol (30 mcg), alone or combined with spironolactone (OC+SPL), in patients with PCOS. Study Design: This was a randomized, controlled clinical trial. Fifty women with PCOS between 18 and 35 years of age were randomized by a computer program to use OC or OC+SPL. Brachial artery flow-mediated vasodilation, carotid intima-media thickness and the carotid artery stiffness index were evaluated at baseline and after 6 and 12 months. Serum markers for cardiovascular disease were also analyzed. The intragroup data were analyzed using analysis of variance with Tukey's post hoc test. A multivariate linear regression model was used to analyze the intergroup data. Results: At 12 months, the increase in mean total cholesterol levels was greater in the OC+SPL group than in the OC group (27% vs. 13%, respectively; p=.02). The increase in mean sex hormone-binding globulin levels was greater in the OC group than in the OC+SPL group (424% vs. 364%, respectively; p=.01). No statistically significant differences between the groups were found for any of the other variables. Conclusion: The addition of spironolactone to an OC containing chlormadinone acetate and ethinylestradiol conferred no cardiovascular risk-marker advantages in young women with PCOS. (C) 2012 Elsevier Inc. All rights reserved.
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The present study aimed to investigate the association of endothelial nitric oxide synthase (eNOS) gene polymorphisms with primary open angle glaucoma (POAG). We conducted a case-control study that included 90 patients with POAG and 127 healthy controls whose blood samples were genotyped for the functional polymorphisms T-786C and Glu298Asp of the eNOS gene by Taqman fluorescent allelic discrimination assay. The T-786C polymorphism was significantly associated as a risk factor for POAG among women (OR: 228; 95% CI: 1.11 to 4.70, p = 0.024) and marginally associated to the risk of POAG in the patients >= 52 years of age at diagnosis (OR: 2.11; 95% CI: 0.98 to 4.55, p = 0,055). However, these results was not confirmed after adjustments for gender, age, self-declared skin color, tobacco smoking and eNOS genotypes by multivariate logistic regression model (OR: 2.08; 95% CI: 0.87 to 5.01, p = 0.101 and OR: 2.20; 95% CI: 0.95 to 5.12, p = 0.067, respectively). The haplotype CG of T-786C and Glu298Asp showed a borderline association with risk of POAG in the overall analysis (OR: 1.76; 95% CI: 0.98 to 3.14, p = 0.055) and among women (OR: 2.02; 95% CI: 0.98 to 4.16, p = 0.052). Furthermore, the CG haplotype was significantly associated with the development of POAG for the age at diagnosis group >= 52 years (OR: 3.48; 95% CI: 1.54 to 7.84, p = 0.002). We suggested that haplotypes of the polymorphisms T-786C and Glu298Asp of eNOS may interact with gender and age in modulating the risk of POAG. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Background: Lymphangioleiomyomatosis (LAM) is characterised by progressive airway obstruction and hypoxaemia in young women. Although sleep may trigger hypoxaemia in patients with airway obstruction, it has not been previously investigated in patients with LAM. Methods: Consecutive women with lung biopsy proven LAM and absence of hypoxaemia while awake were evaluated with pulmonary function test, echocardiography, 6-min walk test, overnight full polysomnography, and Short Form 36 health-related quality-of-life questionnaire. Results: Twenty-five patients with (mean +/- SD) age 45 +/- 10 years, SpO(2) awake 95% +/- 2, forced expiratory volume in the first second (median-interquartile) FEV1 (% predicted) 77 (47-90) and carbonic monoxide diffusion capacity, DLCO (%) 55 (34-74) were evaluated. Six-minute walk test distance and minimum SpO(2) (median-interquartile) were, respectively, 447 m (411 -503) and 90% (82-94). Median interquartile apnoea-hypopnoea index was in the normal range 2 (1-5). Fourteen patients (56%) had nocturnal hypoxaemia (10% total sleep time with SpO(2) <90%), and the median sleep time spent with SpO(2) <90% was 136 (13-201) min. Sleep time spent with SpO(2) <90% correlated with the residual volume/total lung capacity ratio (r(s) = 0.5, p: 0.02), DLCO (r(s) = -0.7, p: 0.001), FEV1 (r(s) = -0.6, p: 0.002). Multivariate linear regression model showed that RV/TLC ratio was the most important functional variable related to sleep hypoxaemia. Conclusion: Significant hypoxaemia during sleep is common in LAM patients with normal SpO(2) while awake, especially among those with some degree of hyperinflation in lung function tests. (C) 2011 Published by Elsevier Ltd.
Resumo:
Background. The link between endogenous estrogen, coronary artery disease (CAD), and death in postmenopausal women is uncertain. We analyzed the association between death and blood levels of estrone in postmenopausal women with known coronary artery disease (CAD) or with a high-risk factor score for CAD. Methods. 251 postmenopausal women age 50-90 years not on estrogen therapy. Fasting blood for estrone and heart disease risk factors were collected at baseline. Women were grouped according to their estrone levels (<15 and >= 15 pg/mL). Fatal events were recorded after 5.8 perpendicular to 1.4 years of followup. Results. The Kaplan-Meier survival curve showed a significant trend (P = 0.039) of greater all-cause mortality in women with low estrone levels (< 15 pg/mL). Cox multivariate regression analysis model adjusted for body mass index, diabetes, dyslipidemia, family history, and estrone showed estrone (OR = 0.45; P = 0.038) as the only independent variable for all-cause mortality. Multivariate regression model adjusted for age, body mass index, hypertension, diabetes, dyslipidemia, family history, and estrone showed that only age (OR = 1.06; P = 0.017) was an independent predictor of all-cause mortality. Conclusions. Postmenopausal women with known CAD or with a high-risk factor score for CAD and low estrone levels (< 15 pg/mL) had increased all-cause mortality.
Fatores de risco pré-operatórios para mediastinite após cirurgia cardíaca: análise de 2768 pacientes
Resumo:
INTRODUÇÃO: A esternotomia mediana longitudinal é a via de acesso mais utilizada no tratamento das doenças cardíacas. As infecções profundas da ferida operatória no pós-operatório das cirurgias cardiovasculares são uma complicação séria, com alto custo durante o tratamento. Diferentes estudos têm encontrado fatores de risco para o desenvolvimento de mediastinite e as variáveis pré-operatórias têm tido especial destaque. OBJETIVO: O objetivo deste estudo é identificar fatores de risco pré-operatórios para o desenvolvimento de mediastinite em pacientes submetidos a revascularização do miocárdio e a substituição valvar. MÉTODOS: Este estudo observacional representa uma coorte de 2768 pacientes operados consecutivamente. O período considerado para análise foi de maio de 2007 a maio de 2009 e não houve critérios de exclusão. Foi realizada análise univariada e multivariada pelo modelo de regressão logística das 38 variáveis pré-operatórias eleitas. RESULTADOS: Nesta série, 35 (1,3%) pacientes evoluíram com mediastinite e 19 (0,7%) com osteomielite associada. A idade média dos pacientes foi de 59,9 ± 13,5 anos e o EuroSCORE de 4,5 ± 3,6. A mortalidade hospitalar foi de 42,8%. Na análise multivariada, foram identificadas três variáveis como preditoras independentes de mediastinite: balão intra-aórtico (OR 5,41, 95% IC [1,83 -16,01], P=0,002), hemodiálise (OR 4,87, 95% IC [1,41 - 16,86], P=0,012) e intervenção vascular extracardíaca (OR 4,39, 95% IC [1,64 - 11,76], P=0,003). CONCLUSÃO: O presente estudo demonstrou que necessidade do suporte hemodinâmico pré-operatório com balão intra-aórtico, hemodiálise e intervenção vascular extracardíaca são fatores de risco para o desenvolvimento de mediastinite após cirurgia cardíaca.
Resumo:
Santos C.S.A.B., Piatti R.M., Azevedo S.S., Alves C.J., Higino S.S.S., Silva M.L.C.R., Brasil A.W.L. & Gennari S.M. 2012. Seroprevalence and risk factors associated with Chlamydophila abortus infection in dairy goats in the Northeast of Brazil. Pesquisa Veterinaria Brasileira 32(11):1082-1086. Unidade Academica de Medicina Veterinaria, Centro de Sa de e Tecnologia Rural, Universidade Federal de Campina Grande, Av. Universitaria s/n, Bairro Santa Cecilia, Patos, PB 58700-970, Brazil. E-mail: sergio.azevedo@pq.cnpq.br Few data are available on the prevalence and risk factors of Chlamydophila abortus infection in goats in Brazil. A cross-sectional study was carried out to determine the flock-level prevalence of C. abortus infection in goats from the semiarid region of the Paraiba State, Northeast region of Brazil, as well as to identify risk factors associated with the infection. Flocks were randomly selected and a pre-established number of female goats >= 12 mo old were sampled in each of these flocks. A total of 975 serum samples from 110 flocks were collected, and structured questionnaire focusing on risk factors for C. abortus infection was given to each farmer at the time of blood collection. For the serological diagnosis the complement fixation test (CFT) using C. abortus S26/3 strain as antigen was performed. The flock-level factors for C. abortus prevalence were tested using multivariate logistic regression model. Fifty-five flocks out of 110 presented at least one seropositive animal with an overall prevalence of 50.0% (95%; CI: 40.3%, 59.7%). Ninety-one out of 975 dairy goats examined were seropositive with titers >= 32, resulting in a frequency of 9.3%. Lend buck for breeding (odds ratio = 2.35; 95% CI: 1.04-5.33) and history of abortions (odds ratio = 3.06; 95% CI: 1.37-6.80) were associated with increased flock prevalence.
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Objective: To assess the frequency of drug use among Brazilian college students and its relationship to gender and age. Methods: A nationwide sample of 12,721 college students completed a questionnaire concerning the use of drugs and other behaviors. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-WHO) criteria were used to assess were used to assess hazardous drug use. A multivariate logistic regression model tested the associations of ASSIST-WHO scores with gender and age. The same analyses were carried out to measure drug use in the last 30 days. Results: After controlling for other sociodemographic, academic and administrative variables, men were found to be more likely to use and engage in the hazardous use of anabolic androgenic steroids than women across all age ranges. Conversely, women older than 34 years of age were more likely to use and engage in the hazardous use of amphetamines. Conclusions: These findings are consistent with results that have been reported for the general Brazilian population. Therefore, these findings should be taken into consideration when developing strategies at the prevention of drug use and the early identification of drug abuse among college students.
Resumo:
Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.
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Multivariate analyses of UV-Vis spectral data from cachaca wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. The model is based on inspection of 93 extracts of oak and different Brazilian wood species by a non-aged cachaca used as an extraction solvent. Application of PCA (Principal Components Analysis) and HCA (Hierarchical Cluster Analysis) leads to identification of 6 clusters of cachaca wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaca extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatoba, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (balsamo and jequitiba-rosa). The methodology provides a low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachacas aged in barrels that are composed of different wood species.
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In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.
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The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.