Depressão : detecção, diagnóstico e tratamento. Estudo de prevalência e despite das perturbações depressivas e tratamento

RESUMO:A depressão clínica é uma patologia do humor, dimensional e de natureza crónica, evoluindo por episódios heterogéneos remitentes e recorrentes, de gravidade variável, correspondendo a categorias nosológicas porventura artificiais mas clinicamente úteis, de elevada prevalência e responsável por morbilidade importante e custos sociais crescentes, calculando-se que em 2020 os episódios de depressão major constituirão, em todo o mundo, a segunda causa de anos de vida com saúde perdidos. Como desejável, na maioria dos países os cuidados de saúde primários são a porta de entrada para o acesso à recepção de cuidados de saúde. Cerca de 50% de todas as pessoas sofrendo de depressão acedem aos cuidados de saúde primários mas apenas uma pequena proporção é correctamente diagnosticada e tratada pelos médicos prestadores de cuidados primários apesar dos tratamentos disponíveis serem muito efectivos e de fácil aplicabilidade. A existência de dificuldades e barreiras a vários níveis – doença, doentes, médicos, organizações de saúde, cultura e sociedade – contribuem para esta generalizada ineficiência de que resulta uma manutenção do peso da depressão que não tem sido possível reduzir através das estratégias tradicionais de organização de serviços. A equipa comunitária de saúde mental e a psiquiatria de ligação são duas estratégias de intervenção com desenvolvimento conceptual e organizacional respectivamente na Psiquiatria Social e na Psicossomática. A primeira tem demonstrado sucesso na abordagem clínica das doenças mentais graves na comunidade e a segunda na abordagem das patologias não psicóticas no hospital geral. Todavia, a efectividade destas estratégias não se tem revelado transferível para o tratamento das perturbações depressivas e outras patologias mentais comuns nos cuidados de saúde primários. Novos modelos de ligação e de trabalho em equipa multidisciplinar têm sido demonstrados como mais eficazes e custo-efectivos na redução do peso da depressão, ao nível da prestação dos cuidados de saúde primários, quando são atinentes com os seguintes princípios estratégicos e organizacionais: detecção sistemática e abordagem da depressão segundo o modelo médico, gestão integrada de doença crónica incluindo a continuidade de cuidados mediante colaboração e partilha de responsabilidades intersectorial, e a aposta na melhoria contínua da qualidade. Em Portugal, não existem dados fiáveis sobre a frequência da depressão, seu reconhecimento e a adequação do tratamento ao nível dos cuidados de saúde primários nem se encontra validada uma metodologia de diagnóstico simples e fiável passível de implementação generalizada. Foi realizado um estudo descritivo transversal com os objectivos de estabelecer a prevalência pontual de depressão entre os utentes dos cuidados de saúde primários e as taxas de reconhecimento e tratamento pelos médicos de família e testar metodologias de despiste, com base num questionário de preenchimento rápido – o WHO-5 – associado a uma breve entrevista estruturada – o IED. Foram seleccionados aleatoriamente 31 médicos de família e avaliados 544 utentes consecutivos, dos 16 aos 90 anos, em quatro regiões de saúde e oito centros de saúde dotados com 219 clínicos gerais. Os doentes foram entrevistados por psiquiatras, utilizando um método padronizado, o SCAN, para diagnóstico de perturbação depressiva segundo os critérios da 10ª edição da Classificação Internacional de Doenças. Apurou-se que 24.8% dos utentes apresentava depressão. No melhor dos cenários, menos de metade destes doentes, 43%, foi correctamente identificada como deprimida pelo seu médico de família e menos de 13% dos doentes com depressão estavam bem medicados com antidepressivo em dose adequada. A aplicação seriada dos dois instrumentos não revelou dificuldades tendo permitido a identificação de pelo menos 8 em cada 10 doentes deprimidos e a exclusão de 9 em cada 10 doentes não deprimidos. Confirma-se a elevada prevalência da patologia depressiva ao nível dos cuidados primários em Portugal e a necessidade de melhorar a capacidade diagnóstica e terapêutica dos médicos de família. A intervenção de despiste, que foi validada, parece adequada para ser aplicada de modo sistemático em Centros de Saúde que disponham de recursos técnicos e organizacionais para o tratamento efectivo dos doentes com depressão. A obtenção da linha de base de indicadores de prevalência, reconhecimento e tratamento das perturbações depressivas nos cuidados de saúde primários, bem como a validação de instrumentos de uso clínico, viabiliza a capacitação do sistema para a produção de uma campanha nacional de educação de grande amplitude como a proposta no Plano Nacional de Saúde 2004-2010.------- ABSTRACT: Clinical depression is a dimensional and chronic affective disorder, evolving through remitting and recurring heterogeneous episodes with variable severity corresponding to clinically useful artificial diagnostic categories, highly prevalent and producing vast morbidity and growing social costs, being estimated that in 2020 unipolar major depression will be the second cause of healthy life years lost all over the world. In most countries, primary care are the entry point for access to health care. About 50% of all individuals suffering from depression within the community reach primary health care but a smaller proportion is correctly diagnosed and treated by primary care physicians though available treatments are effective and easily manageable. Barriers at various levels – pertaining to the illness itself, to patients, doctors, health care organizations, culture and society – contribute to the inefficiency of depression management and pervasiveness of depression burden, which has not been possible to reduce through classical service strategies. Community mental health teams and consultation-liaison psychiatry, two conceptual and organizational intervention strategies originating respectively within social psychiatry and psychosomatics, have succeeded in treating severe mental illness in community and managing non-psychotic disorders in the general hospital. However, these strategies effectiveness has not been replicated and transferable for the primary health care setting treatment of depressive disorders and other common mental pathology. New modified liaison and multidisciplinary team work models have been shown as more efficacious and cost-effective reducing depression burden at the primary care level namely when in agreement with principles such as: systematic detection of depression and approach accordingly to the medical model, chronic llness comprehensive management including continuity of care through collaboration and shared responsibilities between primary and specialized care, and continuous quality improvement. There are no well-founded data available in Portugal for depression prevalence, recognition and treatment adequacy in the primary care setting neither is validated a simple, teachable and implementable recognition and diagnostic methodology for primary care. With these objectives in mind, a cross-sectional descriptive study was performed involving 544 consecutive patients, aged 16-90 years, recruited from the ambulatory of 31 family doctors randomized within the 219 physicians working in eight health centres from four health regions. Screening strategies were tested based on the WHO-5 questionnaire in association with a short structured interview based on ICD-10 criteria. Depression ICD-10 diagnosis was reached according to the gold standard SCAN interview performed by trained psychiatrists. Any depressive disorder ICD-10 diagnosis was present in 24.8% of patients. Through the use of favourable recognition criteria, 43% of the patients were correctly identified as depressed by their family doctor and about 13% of the depressed patients were prescribed antidepressants at an adequate dosage. The serial administration of both instruments – WHO-5 and short structured interview – was feasible, allowing the detection of eight in ten positive cases and the exclusion of nine in ten non-cases. In Portugal, at the primary care level, high depressive disorder prevalence is confirmed as well as the need to improve depression diagnostic and treatment competencies of family doctors. A two-stage screening strategy has been validated and seems adequate for systematic use in health centres where technical and organizational resources for the effective management of depression are made available. These results can be viewed as primary care depressive disorders baseline indicators of prevalence, detection and treatment and, along with clinical useful instruments, the health system is more capacitated for the establishment of a national level large education campaign on depression such as proposed in the National Health Plan 2004-2010.

Battery management system for electric racing cars

With the introduction of the electrics cars into the market new technologies regarding the battery are being developed and new problems to be solved, one of them the battery management system because each type of cell requires a specific way of handling. This research is done using the active research method to find out the actual problem on this subject and features a BMS should have, understand how they work and how to develop them applied to the purpose on this work. Once the features the BMS should have are clarified, it’s possible to develop a BMS for an electric racing car. The decisions are made taking into consideration the nature of the vehicle being developed. After the project done it’s clear to see that what was developed was not only the BMS itself but all the other factors around it, such as CAN communication, safety control, diagnostics and so on.

Energy resources management in three distinct time horizons considering a large variation in wind power

The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.

SCADA House Intelligent Management for Energy Efficiency Analysis in Domestic Consumers

The implementation of smart homes allows the domestic consumer to be an active player in the context of the Smart Grid (SG). This paper presents an intelligent house management system that is being developed by the authors to manage, in real time, the power consumption, the micro generation system, the charge and discharge of the electric or plug-in hybrid vehicles, and the participation in Demand Response (DR) programs. The paper proposes a method for the energy efficiency analysis of a domestic consumer using the SCADA House Intelligent Management (SHIM) system. The main goal of the present paper is to demonstrate the economic benefits of the implemented method. The case study considers the consumption data of some real cases of Portuguese house consumption over 30 days of June of 2012, the Portuguese real energy price, the implementation of the power limits at different times of the day and the economic benefits analysis.

Intelligent Micro Grid Management using a Multi-Agent approach

Recent changes in electricity markets (EMs) have been potentiating the globalization of distributed generation. With distributed generation the number of players acting in the EMs and connected to the main grid has grown, increasing the market complexity. Multi-agent simulation arises as an interesting way of analysing players’ behaviour and interactions, namely coalitions of players, as well as their effects on the market. MASCEM was developed to allow studying the market operation of several different players and MASGriP is being developed to allow the simulation of the micro and smart grid concepts in very different scenarios This paper presents a methodology based on artificial intelligence techniques (AI) for the management of a micro grid. The use of fuzzy logic is proposed for the analysis of the agent consumption elasticity, while a case based reasoning, used to predict agents’ reaction to price changes, is an interesting tool for the micro grid operator.

Environmental management and mudit training at the New University of Lisbon by University-Industry co-operation

Environmental Training in Engineering Education (ENTREE 2001) - integrated green policies: progress for progress, p. 329-339 (Florence, 14-17 November 2001; proceedings published as book)

Virtual Power Players Internal Negotiation and Management in MASCEM

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in very helpful sophisticated tools. This paper presents a new methodology for the management of coalitions in electricity markets. This approach is tested using the multi-agent market simulator MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), taking advantage of its ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market and internally, with their members in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. A case study using real data from the Iberian Electricity Market is performed to validate and illustrate the proposed approach.

A new model for EEZ surveillance and management in Portugal

Management Information Systems 2000, p. 103-111

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Reactive power management strategies in future smart grids

The reactive power management in distribution network with large penetration of distributed energy resources is an important task in future power systems. The control of reactive power allows the inclusion of more distributed recourses and a more efficient operation of distributed network. Currently, the reactive power is only controlled in large power plants and in high and very high voltage substations. In this paper, several reactive power control strategies considering a smart grids paradigm are proposed. In this context, the management of distributed energy resources and of the distribution network by an aggregator, namely Virtual Power Player (VPP), is proposed and implemented in a MAS simulation tool. The proposed methods have been computationally implemented and tested using a 32-bus distribution network with intensive use of distributed resources, mainly the distributed generation based on renewable resources. Results concerning the evaluation of the reactive power management algorithms are also presented and compared.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Distributed Energy Resources Management using Plug-in Hybrid Electric Vehicles as a Fuel-Shifting Demand Response Resource

In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required.

Real-Time Simulation of energy Management in a Domestic Consumer

Recent and future changes in power systems, mainly in the smart grid operation context, are related to a high complexity of power networks operation. This leads to more complex communications and to higher network elements monitoring and control levels, both from network’s and consumers’ standpoint. The present work focuses on a real scenario of the LASIE laboratory, located at the Polytechnic of Porto. Laboratory systems are managed by the SCADA House Intelligent Management (SHIM), already developed by the authors based on a SCADA system. The SHIM capacities have been recently improved by including real-time simulation from Opal RT. This makes possible the integration of Matlab®/Simulink® real-time simulation models. The main goal of the present paper is to compare the advantages of the resulting improved system, while managing the energy consumption of a domestic consumer.