44 resultados para Sucessão cronológica


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PURPOSE: To describe the main success attitudes of young ophthalmologists in the first decade of their career. METHODS: This descriptive study comprised subjects selected from a sample of ophthalmologists who were participating in a congress, using a semi-structured questionnaire. The inclusion criteria were as follows: ophthalmologists under the age of 40 years, within 5-10 years from ophthalmology residency conclusion. The subjects were asked about the three main success attitudes in their personal experience during the first years of ophthalmology practice. After the initial results, the 10 most frequently mentioned attitudes were listed and volunteers were again interviewed to choose, within the latter list, the three main attitudes. RESULTS: Forty-eight ophthalmologists were interviewed, 24 (50%) were male; the mean age was 37 years (SD: 2 years, range: 33-40 years) and the mean time from ophthalmology residency conclusion was 8 years (SD: 1 year, range: 5-10 years). The frequency of such mentioned success attitudes were as follows: to invest in professional updating (22.9%), to have a good relationship with patients and professional partners (18.8%), to prioritize individual and family happiness (12.5%), initially to work in an established group (11.1%), to work in public service (9.7%), to have their own business with a homogeneous group (7.6%), to save money (7.6%), to be ready to resume work (4.2%), to get business administration skills (4.2%), and to have professional insurance (0.7%). CONCLUSIONS: The three main success attitudes consisted in investing in professional updating (22.9%), maintaining a good relationship with patients and professional partners (18.8%), and prioritizing individual and family happiness (12.5%). Although these results should not be generalized, they are helpful not only for those ophthalmologists at the beginning of a career but also those who want to reflect on what to prioritize in their professional practice.

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A 33-year-old woman complained of unilateral eyelid edema and blurred vision. Initial ophthalmic examination disclosed anterior chamber reaction with keratic precipitates on the cornea, without posterior abnormalities. Anterior uveitis was treated. Despite that, patient showed rapidly progressive unilateral vision loss with optic nerve swelling. Systemic workup was inconclusive, as well as cranial magnetic resonance imaging and cerebrospinal fluid examination. Based on the hypothesis of optic neuritis, intravenous methylprednisolone pulse was performed with no success. During the following days, the patient presented pericardial effusion and cardiac tamponade, progressing to death. Necropsy was performed and diagnosis of extranodal natural killers/T-cell lymphoma, nasal type with ocular involvement was confirmed by immunohistochemistry.

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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

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A case of giant aneurysm of the left middle cerebral artery, in a 28-year-old right-handed woman, successfuly operated is reported. The aneurysm measur- ing 35 x 27 x 23 mm showed clinical manifestations as a space-occupying lesion. The patient recovered completely after the total excision of the aneurysm.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas. Faculdade de Educação Física

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Universidade Estadual de Campinas. Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas. Faculdade de Educação Física

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Universidade Estadual de Campinas. Faculdade de Educação Física