3 resultados para C30 - General-Sectional Models

em Repositório da Produção Científica e Intelectual da Unicamp


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Universidade Estadual de Campinas . Faculdade de Educação Física

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Here, we describe our experience with different therapeutic modalities used to treat cystic lymphangiomas in children in our hospital, including single therapy with OK-432, bleomycin and surgery, and a combination of the three modalities. We performed a retrospective, cross-sectional study including patients treated from 1998 to 2011. The effects on macrocystic lymphangiomas and adverse reactions were evaluated. Twenty-nine children with cystic lymphangiomas without any previous treatment were included. Under general anesthesia, patients given sclerosing agents underwent puncture of the lesion (guided by ultrasound when necessary) and complete aspiration of the intralesional liquid. The patients were evaluated with ultrasound and clinical examinations for a maximum follow-up time of 4 years. The proportions of patients considered cured after the first therapeutic approach were 44% in the surgery group, 29% in the bleomycin group and 31% in the OK-432 group. These proportions were not significantly different. Sequential treatment increased the rates of curative results to 71%, 74% and 44%, respectively, after the final treatment, which in our case was approximately 1.5 applications per patient. The results of this study indicate that most patients with cystic lymphangiomas do not show complete resolution after the initial therapy, regardless of whether the therapy is surgical or involves the use of sclerosing agents. To achieve complete resolution of the lesions, either multiple operations or a combination of surgery and sclerotherapy must be used and should be tailored to the characteristics of each patient.

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Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.