985 resultados para Extensive
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Tese de Doutoramento em Engenharia Civil.
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Tese de Doutoramento em Ciências (área de especialização em Química)
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Tese de Doutoramento em Biologia das Plantas - MAP BIOPLANT
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Dissertação de mestrado integrado em Engenharia Civil
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Relatório de estágio de mestrado em Média Interativos
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)
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This is a report of a nine-year-old boy with both mitral stenosis and regurgitation and extensive endomyocardial fibrosis of the left ventricle. Focus is given to the singularity of the fibrotic process, with an emphasis on the etiopathogenic aspects.
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A 48-year-old man with essential thrombocythemia suffered an extensive anterior acute myocardial infarction; this is a rare association. A pharmacological thrombolysis was performed, without success. He subsequently underwent successful rescue coronary angioplasty. To our knowledge, there is no other report in the literature relating the triad of essential thrombocythemia, acute myocardial infarction and rescue coronary angioplasty.
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Coronary dissection occurs frequently and in several degrees during coronary angioplasty, which is one of the mechanisms for increasing the lumen diameter of a vessel. However the length of the dissection may affect the procedure, becoming the most frequent cause of total occlusion after coronary angioplasty. We report here a case of extensive dissection that occurred during the coronary angioplasty of a focused lesion, which we treated with two long stents.
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OBJECTIVE: To assess by Doppler echocardiography the structural and functional alterations of rat heart with surgical induced extensive myocardial infarction. METHODS: Five weeks after surgical ligature of the left coronary artery, 38 Wistar-EPM rats of both sexes, 10 of them with extensive infarction, undergone anatomical and functional evaluation by Doppler echocardiography and then euthanized for anatomopathological analysis. RESULTS: Echocardiography was 100% sensible and specific to anatomopathological confirmed extensive miocardial infarction. Extensive infarction lead to dilatation of left ventricle (diastolic diameter: 0.89cm vs.0.64cm; systolic: 0.72cm vs. 0.33cm) and left atrium (0.55cm vs. 0.33cm); thinning of left ventricular anterior wall (systolic: 0.14cm vs. 0.23cm, diastolic: 0.11cm vs. 0.14cm); increased mitral E/ A wave relation (6.45 vs. 1.95). Signals of increased end diastolic ventricle pressure, B point in mitral valve tracing in 62.5% and signs of pulmonary hypertension straightening of pulmonary valve (90%) and notching of pulmonary systolic flow (60%) were observed in animals with extensive infarction. CONCLUSION: Doppler echocardiography has a high sensitivity and specificity for detection of chronic extensive infarction. Extensive infarction caused dilatation of left cardiac chambers and showed in Doppler signals of increased end diastolic left ventricular pressure and pulmonary artery pressure.
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The patient arrived at the emergency unit with a history of acute myocardial infarction, for which she was treated. Without improvement in the pain, the patient developed heart failure and underwent a hemodynamic study, which showed normal coronary arteries and extensive ventricular impairment. During evolution, the clinical findings improved and herpes zoster appeared on the right shoulder. In a few months the clinical findings subsided, and the findings of the electrocardiogram, chest X-ray, and ventricular function were normal. The patient is currently asymptomatic.
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OBJECTIVE: To determine the characteristics associated with the dropout of patients followed up in a Brazilian out patient clinic specializing in hypertension. METHODS: Planned prospective cohort study of patients who were prescribed an antihypertensive treatment after an extensive initial evaluation. The following parameters were analyzed: sex, age, educational level, duration of disease, pressure level used for classifying the patient, previous treatment, physical activity, smoking, alcohol consumption, familial history of hypertension, and lesion in a target organ. RESULTS: We studied 945 hypertensive patients, 533 (56%) of whom dropped out of the follow-up. The mean age was 52.3±12.9 years. The highest probabilities of dropout of the follow-up were associated with current smoking, relative risk of 1.46 (1.04-2.06); educational level equal to or below 5 years of schooling, relative risk of 1.52 (1.11-2.08); and hypertension duration below 5 years, relative risk of 1.78 (1.28-2.48). Age increase was associated with a higher probability of follow-up with a relative risk of 0.98 (0.97-0.99). CONCLUSION: We identified a group at risk for dropping out the follow-up, which comprised patients with a lower educational level, a recent diagnosis of hypertension, and who were smokers. We think that measures assuring adherence to treatment should be directed to this group of patients.
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Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
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A woman aged 98 years entered the tertiary hospital service with a picture of acute myocardial infarction of the extensive anterior wall, which began 4 hours earlier. Due to the large myocardial risk area suggested by the electrocardiogram, the patient was taken to the hemodynamics laboratory for the performance of emergency coronary arteriography, which revealed occlusion in the proximal third of the anterior descending artery. Primary angioplasty followed by stent grafting was successfully performed. The patient had a satisfactory evolution (Killip I) and was discharged from the hospital on the seventh postinfarction day. We discuss here aspects of thrombolysis and coronary percutaneous interventions in the aged.
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Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.