Custo-efetividade da trombólise pré-hospitalar vs intra-hospitalar no infarto agudo do miocárdio

FUNDAMENTO: Existe evidência de que a trombólise pré-hospitalar melhora os desfechos no infarto agudo do miocárdio (IAM) com supradesnivelamento do segmento ST. OBJETIVO: Comparar as relações de custo-efetividade entre trombólise pré-hospitalar e trombólise intra-hospitalar para o IAM com supradesnivelamento do segmento ST, pela perspectiva do Sistema Único de Saúde. MÉTODOS: Modelo analítico de decisão foi utilizado para comparar as duas estratégias. O desfecho do estudo foi "anos de vida ganhos". O uso de recursos e os custos foram estimados pela perspectiva do Sistema Único de Saúde. Árvore de decisão e modelo de Markov foram construídos com resultados de ensaios clínicos publicados. Os custos foram valorados em real (R$), para o ano de 2005. RESULTADOS: Para um horizonte de tempo de vinte anos, a expectativa de vida média com a trombólise pré-hospitalar foi de 11,48 anos e a trombólise intra-hospitalar proporcionou expectativa de vida média de 11,32 anos. Os custos foram de R$ 5.640,00 para a trombólise pré-hospitalar e de R$ 5.816,00 para a trombólise intra-hospitalar. Houve custo adicional de R$ 176,00 por paciente com a trombólise intra-hospitalar. A trombólise pré-hospitalar proporcionou adicional de 0,15 ano de expectativa de vida comparado à trombólise intra-hospitalar. CONCLUSÃO: Esse modelo sugere que, pela perspectiva do Sistema Único de Saúde, implementar a trombólise pré-hospitalar para o IAM com supradesnivelamento do segmento ST pode representar sobrevida extra e menor custo que comparativamente à trombólise intra-hospitalar.

Custo-efetividade de cardiodesfibriladores implantáveis no Brasil nos setores público e privado

FUNDAMENTO: Vários ensaios clínicos randomizados demonstraram a efetividade do cardiodesfibrilador implantável (CDI) na redução de morte de pacientes com insuficiência cardíaca congestiva (ICC). Estudos de países desenvolvidos já avaliaram a custo-efetividade do CDI, porém as informações não são transferíveis para o Brasil. OBJETIVO: Avaliar a custo-efetividade do CDI em pacientes com ICC sob duas perspectivas: pública e saúde suplementar. MÉTODOS: Um modelo de Markov foi criado para analisar a relação de custo-efetividade incremental (RCEI) do CDI, comparado à terapia convencional, em pacientes com ICC. Efetividade foi medida em anos de vida ajustados para qualidade (QALY). Na literatura, buscaram-se dados de efetividade e complicações. Custos foram extraídos das tabelas do SUS e de valores praticados pelos convênios, assim como médias de internações hospitalares. Análises de sensibilidade univariadas foram feitas em todas as variáveis do modelo. RESULTADOS: A RCEI foi de R$ 68.318/QALY no cenário público e R$ 90.942/QALY no privado. Esses valores são superiores aos sugeridos como pontos de corte pela Organização Mundial da Saúde, de três vezes o PIB per capita (R$ 40.545 no Brasil). Variáveis mais influentes na análise de sensibilidade foram: custo do CDI, intervalo de troca do gerador e efetividade do CDI. Em simulação de cenário semelhante ao MADIT-I, as relações foram de R$ 23.739/QALY no cenário público e R$ 33.592/QALY no privado. CONCLUSÃO: Para a população em geral com ICC, a relação de RCEI do CDI, tanto na perspectiva pública como na privada, é elevada. Resultados mais favoráveis ocorrem em pacientes com alto risco de morte súbita.

proxel-based method : formalisation, analysis and applications

Simulation, modelling, proxels, PDEs, Markov chains, Petri nets, stochastic, performability, transient analysis

Cost-Effectiveness of High, Moderate and Low-Dose Statins in the Prevention of Vascular Events in the Brazilian Public Health System

Background:Statins have proven efficacy in the reduction of cardiovascular events, but the financial impact of its widespread use can be substantial.Objective:To conduct a cost-effectiveness analysis of three statin dosing schemes in the Brazilian Unified National Health System (SUS) perspective.Methods:We developed a Markov model to evaluate the incremental cost-effectiveness ratios (ICERs) of low, intermediate and high intensity dose regimens in secondary and four primary scenarios (5%, 10%, 15% and 20% ten-year risk) of prevention of cardiovascular events. Regimens with expected low-density lipoprotein cholesterol reduction below 30% (e.g. simvastatin 10mg) were considered as low dose; between 30-40%, (atorvastatin 10mg, simvastatin 40mg), intermediate dose; and above 40% (atorvastatin 20-80mg, rosuvastatin 20mg), high-dose statins. Effectiveness data were obtained from a systematic review with 136,000 patients. National data were used to estimate utilities and costs (expressed as International Dollars - Int$). A willingness-to-pay (WTP) threshold equal to the Brazilian gross domestic product per capita (circa Int$11,770) was applied.Results:Low dose was dominated by extension in the primary prevention scenarios. In the five scenarios, the ICER of intermediate dose was below Int$10,000 per QALY. The ICER of the high versus intermediate dose comparison was above Int$27,000 per QALY in all scenarios. In the cost-effectiveness acceptability curves, intermediate dose had a probability above 50% of being cost-effective with ICERs between Int$ 9,000-20,000 per QALY in all scenarios.Conclusions:Considering a reasonable WTP threshold, intermediate dose statin therapy is economically attractive, and should be a priority intervention in prevention of cardiovascular events in Brazil.

Modelagem de ocorrência e densidade de juvenis de Callinectes sapidus (Decapoda, Portunidae) em dois estuários do Rio Grande do Sul, com dados zero-inflacionados

Dados de contagem de juvenis de siri-azul (Callinectes sapidus Rathbun, 1896) coletados em dois estuários do Rio Grande do Sul são objeto do presente estudo. Por se encontrarem zero-inflacionados, esses dados motivaram a formulação de modelos hierárquicos, que quantificam o efeito das covariáveis categóricas mês e local sobre a probabilidade de ocorrência e densidade dessas populações, levando em conta a detecção imperfeita. Foram também desenvolvidos modelos não-hierárquicos para comparação. Uma abordagem Bayesiana foi adotada para a estimação dos parâmetros dos modelos por simulação Monte Carlo com Cadeias de Markov (MCMC). A comparação entre modelos foi feita com o Critério de Informação da Deviância (DIC). Os modelos hierárquicos apresentaram ajustes melhores que os modelos convencionais, mitigaram o problema do excesso de zeros e permitiram analisar simultaneamente as probabilidades de ocorrência e a densidade de juvenis de siri-azul. No estuário da Lagoa dos Patos, a probabilidade de ocorrência de juvenis na Classe 2 aumenta com a distância da desembocadura, enquanto em Tramandaí os pontos intermediários apresentam as maiores probabilidades. Em ambos os estuários a ocorrência é mais provável nos meses de verão e de inverno. A densidade de juvenis da Classe 2 apresenta marcada variação em relação aos meses do ano sendo, em geral, maior no estuário de Tramandaí.

Dance movement patterns recognition

"Es tracta d'un projecte dividit en dues parts independents però complementàries, realitzades per autors diferents. Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia"

Comparing impact and cost-effectiveness of primary prevention strategies for lipid-lowering.

BACKGROUND: Lipid-lowering therapy is costly but effective at reducing coronary heart disease (CHD) risk. OBJECTIVE: To assess the cost-effectiveness and public health impact of Adult Treatment Panel III (ATP III) guidelines and compare with a range of risk- and age-based alternative strategies. DESIGN: The CHD Policy Model, a Markov-type cost-effectiveness model. DATA SOURCES: National surveys (1999 to 2004), vital statistics (2000), the Framingham Heart Study (1948 to 2000), other published data, and a direct survey of statin costs (2008). TARGET POPULATION: U.S. population age 35 to 85 years. Time Horizon: 2010 to 2040. PERSPECTIVE: Health care system. INTERVENTION: Lowering of low-density lipoprotein cholesterol with HMG-CoA reductase inhibitors (statins). OUTCOME MEASURE: Incremental cost-effectiveness. RESULTS OF BASE-CASE ANALYSIS: Full adherence to ATP III primary prevention guidelines would require starting (9.7 million) or intensifying (1.4 million) statin therapy for 11.1 million adults and would prevent 20,000 myocardial infarctions and 10,000 CHD deaths per year at an annual net cost of $3.6 billion ($42,000/QALY) if low-intensity statins cost $2.11 per pill. The ATP III guidelines would be preferred over alternative strategies if society is willing to pay $50,000/QALY and statins cost $1.54 to $2.21 per pill. At higher statin costs, ATP III is not cost-effective; at lower costs, more liberal statin-prescribing strategies would be preferred; and at costs less than $0.10 per pill, treating all persons with low-density lipoprotein cholesterol levels greater than 3.4 mmol/L (>130 mg/dL) would yield net cost savings. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the assumptions that LDL cholesterol becomes less important as a risk factor with increasing age and that little disutility results from taking a pill every day. LIMITATION: Randomized trial evidence for statin effectiveness is not available for all subgroups. CONCLUSION: The ATP III guidelines are relatively cost-effective and would have a large public health impact if implemented fully in the United States. Alternate strategies may be preferred, however, depending on the cost of statins and how much society is willing to pay for better health outcomes. FUNDING: Flight Attendants' Medical Research Institute and the Swanson Family Fund. The Framingham Heart Study and Framingham Offspring Study are conducted and supported by the National Heart, Lung, and Blood Institute.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

Booms, Recessions and Financial Turmoil: A Fresh Look at Investment Decisions under Cyclical Uncertainty

The paper studies the interaction between cyclical uncertainty and investment in a stochastic real option framework where demand shifts stochastically between three different states, each with different rates of drift and volatility. In our setting the shifts are governed by a three-state Markov switching model with constant transition probabilities. The magnitude of the link between cyclical uncertainty and investment is quantified using simulations of the model. The chief implication of the model is that recessions and financial turmoil are important catalysts for waiting. In other words, our model shows that macroeconomic risk acts as an important deterrent to investments.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach

This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

Optimism and commitment: An elementary theory of bargaining and war

We propose an elementary theory of wars fought by fully rational contenders. Two parties play a Markov game that combines stages of bargaining with stages where one side has the ability to impose surrender on the other. Under uncertainty and incomplete information, in the unique equilibrium of the game, long confrontations occur: war arises when reality disappoints initial (rational) optimism, and it persist longer when both agents are optimists but reality proves both wrong. Bargaining proposals that are rejected initially might eventually be accepted after several periods of confrontation. We provide an explicit computation of the equilibrium, evaluating the probability of war, and its expected losses as a function of i) the costs of confrontation, ii) the asymmetry of the split imposed under surrender, and iii) the strengths of contenders at attack and defense. Changes in these parameters display non-monotonic effects.

Bayesian Model Averaging in the Instrumental Variable Regression Model

This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.