28 resultados para Multivariate risk model


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Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Nowadays manufacturing companies are facing a more challenging environment due to the unpredictability of the markets in order to survive. Enterprises need to keep innovating and deliver products with new internal or external characteristics. There are strategies and solutions, to different organisational level from strategic to operational, when technology is growing faster in operational level, more specifically in manufacturing system. This means that companies have to deal with the changes of the emergent manufacturing systems while it can be expensive and not easy to be implement. An agile manufacturing system can help to cope with the markets changeability. Evolvable Production Systems (EPS) is an emergent paradigm which aims to bring new solutions to deal with changeability. The proposed paradigm is characterised by modularity and intends to introduce high flexibility and dynamism at shop floor level through the use of the evolution of new computational devices and technology. This new approach brings to enterprises the ability to plug and unplug new devices and allowing fast reformulation of the production line without reprogramming. There is no doubt about the advantages and benefits of this emerging technology but the feasibility and applicability is still under questioned. Most researches in this area are focused on technical side, explaining the advantages of those systems while there are no sufficient works discussing the implementation risks from different perspective, including business owner. The main objective of this work is to propose a methodology and model to identify, classify and measure potential risk associated with an implementation of this emergent paradigm. To quantify the proposed comprehensive risk model, an Intelligent Decision system is developed employing Fuzzy Inference System to deal with the knowledge of experts, as there are no historical data and sufficient research on this area. The result can be the vulnerability assessment of implementing EPS technology in manufacturing companies when the focus is more on SMEs. The present dissertation used the experts’ knowledge and experiences, who were involved in FP7 project IDEAS, which is one of the leading projects in this area.

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Trabalho de projecto apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica.

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Dissertação para obtenção do Grau de Doutor em Engenharia Industrial

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The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

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Dissertation submitted to Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the achievement of Integrated Master´s degree in Industrial Management Engineering

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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

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Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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ABSTRACT:C-reactive protein (CRP) has been widely used in the early risk assessment of patients with acute pancreatitis (AP), but unclear aspects about its prognostic accuracy in this setting persist. This project evaluated first CRP prognostic accuracy for severity, pancreatic necrosis (PNec), and in-hospital mortality (IM) in AP in terms of the best timing for CRP measurement and the optimal CRP cutoff points. Secondly it was evaluated the CRP measured at approximately 24 hours after hospital admission (CRP24) prognostic accuracy for IM in AP individually and in a combined model with a recent developed tool for the early risk assessment of patients with AP, the Bedside Index for Severity in AP (BISAP). Two single-centre retrospective cohort studies were held. The first study included 379 patients and the second study included 134 patients. Statistical methods such as the Hosmer-Lemeshow goodness-of-fit test, the area under the receiver-operating characteristic curve, the net reclassification improvement, and the integrated discrimination improvement were used. It was found that CRP measured at approximately 48 hours after hospital admission (CRP48) had a prognostic accuracy for severity, PNec, and IM in AP better than CRP measured at any other timing. It was observed that the optimal CRP48 cutoff points for severity, PNec, and IM in AP varied from 170mg/l to 190mg/l, values greater than the one most often recommended in the literature – 150mg/l. It was found that CRP24 had a good prognostic accuracy for IM in AP and that the cutoff point of 60mg/l had a negative predictive value of 100%. Finally it was observed that the prognostic accuracy of a combined model including BISAP and CRP24 for IM in AP could perform better than the BISAP alone model. These results might have a direct impact on the early risk assessment of patients with AP in the daily clinical practice.--------- RESUMO: A proteina c-reactiva (CRP) tem sido largamente usada na avaliação precoce do risco em doentes com pancreatite aguda (AP), mas aspectos duvidosos acerca do seu valor prognóstico neste contexto persistem. Este projecto avaliou primeiro o valor prognóstico da CRP para a gravidade, a necrose pancreática (PNec) e a mortalidade intra-hospitalar (IM) na AP em termos do melhor momento para efectuar a sua medição e dos seus pontos-de-corte óptimos. Em segundo lugar foi avaliado o valor prognóstico da proteína c-reactiva medida aproximadamente às 24 horas após a admissão hospitalar (CRP24) para a IM na AP isoladamente e num modelo combinado, que incluiu uma ferramenta de avaliação precoce do risco em doentes com AP recentemente desenvolvida, o Bedside Index for Severity in Acute Pancreatitis (BISAP). Dois estudos unicêntricos de coorte retrospectivo foram realizados. O primeiro estudo incluiu 379 doentes e o segundo estudo incluiu 134 doentes. Metodologias estatísticas como o teste de Hosmer-Lemeshow goodness-of-fit, a area under the receiver-operating characteristic curve, o net reclassification improvement e o integrated discrimination improvement foram usadas. Verificou-se que a CRP medida às 48 horas após a admissão hospitalar (CRP48) teve um valor prognóstico para a gravidade, a PNec e a IM na AP melhor do que a CRP medida em qualquer outro momento. Observou-se que os pontos de corte óptimos da CRP48 para a gravidade, a PNec e a IM na AP variaram entre 170mg/l e 190mg/l, valores acima do valor mais frequentemente recomendado na literatura – 150mg/l. Verificou-se que a CRP medida aproximadamente às 24 horas após a admissão hospitalar (CRP24) teve um bom valor prognóstico para a IM na AP e que o ponto de corte 60mg/l teve um valor preditivo negativo de 100%. Finalmente observou-se que o valor prognóstico de um modelo combinado incluindo o BISAP e a CRP24 para a IM na AP pode ter um desempenho melhor do que o do BISAP isoladamente. Estes resultados podem ter um impacto directo na avaliação precoce do risco em doentes com AP na prática clínica diária.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Biotecnologia