202 resultados para Cox regression model

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

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Um modelo bayesiano de regressão binária é desenvolvido para predizer óbito hospitalar em pacientes acometidos por infarto agudo do miocárdio. Métodos de Monte Carlo via Cadeias de Markov (MCMC) são usados para fazer inferência e validação. Uma estratégia para construção de modelos, baseada no uso do fator de Bayes, é proposta e aspectos de validação são extensivamente discutidos neste artigo, incluindo a distribuição a posteriori para o índice de concordância e análise de resíduos. A determinação de fatores de risco, baseados em variáveis disponíveis na chegada do paciente ao hospital, é muito importante para a tomada de decisão sobre o curso do tratamento. O modelo identificado se revela fortemente confiável e acurado, com uma taxa de classificação correta de 88% e um índice de concordância de 83%.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Introduction: The present study examines cardiovascular risk factor profiles and 24-month mortality in patients with symptomatic peripheral arterial disease. Design Study: Prospective observational study including 75 consecutive patients with PAD (67 ± 9.7 years of age; 52 men and 23 women) hospitalized for planned peripheral vascular reconstruction. Doppler echocardiograms were performed before surgery in 54 cases. Univariate analyses were performed using Student's t-test or Fisher's exact test. Survival analysis at 24-month follow-up was performed using the Cox regression model and Kaplan-Meier method including age and chronic use of aspirin as covariates. Survival curves were compared using the log-rank test. Results: Hypertension and smoking were the most frequent risk factors (52 cases and 51 cases, respectively), followed by diabetes (32 cases). Undertreated dyslipidemia was found in 26 cases. Fasting glycine levels (131 ± 69.1 mg/dl) were elevated in 29 cases. Myocardial hypertrophy was found in 18 out of 54 patients. Thirty-four patients had been treated with aspirin. Overall mortality over 24 months was 24% and was associated with age (HR: 0.064; CI95: 0.014-0.115; p=0.013) and lack of use of aspirin, as no deaths occurred among those using this drug (p<0.001). No association was found between cardiovascular death (11 cases) and the other risk factors. Conclusion: There is a high prevalence of uncontrolled (treated or untreated) cardiovascular risk factors in patients undergoing planned peripheral vascular reconstruction, and chronic use of aspirin is associated with reduced all-cause mortality in these patients.

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The aim of the present study was to evaluate the Mini Nutritional Assessment (MNA), the Nutritional Risk Screening (NRS) 2002 and the American Society of Anesthesiologists Physical Status Score (ASA) as predictors of gait status and mortality 6 months after hip fracture. A total of eighty-eight consecutive patients over the age of 65 years with hip fracture admitted to an orthopaedic unit were prospectively evaluated. Within the first 72 h of admission, each patient's characteristics were recorded, and the MNA, the NRS 2002 and the ASA were performed. Gait status and mortality were evaluated 6 months after hip fracture. Of the total patients, two were excluded because of pathological fractures. The remaining eighty-six patients (aged 80·2 (sd 7·3) years) were studied. Among these patients 76·7 % were female, 69·8 % walked with or without support and 12·8 % died 6 months after the fracture. In a multivariate analysis, only the MNA was associated with gait status 6 months after hip fracture (OR 0·773, 95 % CI 0·663, 0·901; P= 0·001). In the Cox regression model, only the MNA was associated with mortality 6 months after hip fracture (hazard ratio 0·869, 95 % CI 0·757, 0·998; P= 0·04). In conclusion, the MNA best predicts gait status and mortality 6 months after hip fracture. These results suggest that the MNA should be included in the clinical stratification of patients with hip fracture to identify and treat malnutrition in order to improve the outcomes.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.