12 resultados para medication incidents
em Universidade do Minho
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The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.
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Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1ºCiclo do Ensino Básico
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Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.
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In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed
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A significant number of psychotherapy clients remain untreated, and dropping out is one of the main reasons. Still, the literature around this subject is incoherent. The present study explores potential pre-treatment predictors of dropout in a sample of clients who took part in a clinical trial designed to test the efficacy of narrative therapy for major depressive disorder compared to cognitive-behavioral therapy. Logistic regression analysis showed that: (1) treatment assignment did not predict dropout, (2) clients taking psychiatric medication at intake were 80% less likely to drop out from therapy, compared to clients who were not taking medication, and (3) clients presenting anxious comorbidity at intake were 82% less likely to dropout compared to those clients not presenting anxious comorbidity. Results suggest that clinicians should pay attention to depressed clients who are not taking psychiatric medication or have no comorbid anxiety. More research is needed in order to understand this relationship.
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This study analyzed the mediating role of psychological morbidity and the variables that discriminated low versus high disability, in patients receiving physiotherapy and acupuncture. A total of 203 patients answered measures of illness and medication representations, coping, depression, anxiety, quality of life, and functional disability. Morbidity was a mediator between functional disability and quality of life. Treatment consequences and quality of life, in the acupuncture group, and emotional representations, quality of life, depression, anxiety, and active strategies for pain relief, in the physiotherapy group, discriminated patients with low versus high disability. These results have important implications for identifying high-risk patients.
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BACKGROUND: An autoimmune disease is characterized by tissue damage, caused by self-reactivity of different effector mechanisms of the immune system, namely antibodies and T cells. All autoimmune diseases, to some extent, have implications for fertility and obstetrics. Currently, due to available treatments and specialised care for pregnant women with autoimmune disease, the prognosis for both mother and child has improved significantly. However these pregnancies are always high risk. The purpose of this study is to analyse the fertility/pregnancy process of women with systemic and organ-specific autoimmune diseases and assess pathological and treatment implications. METHODS: The authors performed an analysis of the clinical records and relevant obstetric history of five patients representing five distinct autoimmune pathological scenarios, selected from Autoimmune Disease Consultation at the Hospital of Braga, and reviewed the literature. RESULTS: The five clinical cases are the following: Case 1-28 years old with systemic lupus erythematosus, and clinical remission of the disease, under medication with hydroxychloroquine, prednisolone and acetylsalicylic acid, with incomplete miscarriage at 7 weeks of gestation without signs of thrombosis. Case 2-44 years old with history of two late miscarriages, a single preterm delivery (33 weeks) and multiple thrombotic events over the years, was diagnosed with antiphospholipid syndrome after acute myocardial infarction. Case 3-31 years old with polymyositis, treated with azathioprine for 3 years with complete remission of the disease, took the informed decision to get pregnant after medical consultation and full weaning from azathioprine, and gave birth to a healthy term new-born. Case 4-38 years old pregnant woman developed Behcet's syndrome during the final 15 weeks of gestation and with disease exacerbation after delivery. Case 5-36 years old with autoimmune thyroiditis diagnosed during her first pregnancy, with difficult control over the thyroid function over the years and first trimester miscarriage, suffered a second miscarriage despite clinical stability and antibody regression. CONCLUSIONS: As described in literature, the authors found a strong association between autoimmune disease and obstetric complications, especially with systemic lupus erythematosus, antiphospholipid syndrome and autoimmune thyroiditis.
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Dissertação de mestrado integrado em Biomedical Engineering Biomaterials, Biomechanics and Rehabilitation
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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação
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Background Despite the small size of the incision, the scar left by open repair of epigastric hernia in children is unaesthetic. Few laparoscopic approaches to epigastric hernia repair have been previously proposed, but none has gain wide acceptance from pediatric surgeons. In this study, we present our experience with a scarless laparo- scopic approach using a percutaneous suturing technique for epigastric hernia repair in children. Methods Ten consecutive patients presenting with epi- gastric hernia 15 mm or further from the umbilicus were submitted to laparoscopic hernia repair. A 5-mm 308-angle laparoscope is introduced through a umbilical trocar and a 3-mm laparoscopic dissector is introduced through a stab incision in the right flank. After opening and dissecting the parietal peritoneum, the fascial defect is identified and closed using 2–0 polyglactin thread through a percutaneous suturing technique. Intraoperative and postoperative clinical data were collected. Results All patients were successfully submitted to la- paroscopic epigastric hernia repair. Median age at surgery was 79 months old and the median distance from the um- bilicus to the epigastric defect was 4 cm. Operative time ranged from 35 to 75 min. Every hernia was successfully closed without any incidents. Follow-up period ranges from 2 to 12 months. No postoperative complications or recurrence was registered. No scar was visible in these patients. Conclusion This scarless laparoscopic technique for epi- gastric hernia repair is safe and reliable. We believe this technique might become gold standard of care in the near future.
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)
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This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows the intensivists to analyse data regarding vital signs, medication, exams, data mining predictions, among others. Due to the pervasive features, intensivists can have access to the timeline anywhere and anytime, allowing them to make decisions when they need to be made. This platform is patient-centred and is prepared to support the decision process allowing the intensivists to provide better care to patients due the inclusion of clinical forecasts.