Limited utility of exercise stress testing in the evaluation of suspected acute coronary syndrome in patients aged less than 40 years with intermediate risk features

Objective National guidelines for management of intermediate risk patients with suspected acute coronary syndrome, in whom AMI has been excluded, advocate provocative testing to final risk stratify these patients into low risk (negative testing) or high risk (positive testing suggestive of unstable angina). Adults less than 40 years have a low pretest probability of acute coronary syndrome. The utility of exercise stress testing in young adults with chest pain suspected of acute coronary syndrome who have National Heart Foundation intermediate risk features was evaluated Methods A retrospective analysis of exercise stress testing performed on patients less than 40 years was evaluated. Patients were enrolled on a chest pain pathway and had negative serial ECGs and cardiac biomarkers before exercise stress testing to rule-out acute coronary syndrome. Chart review was completed on patients with positive stress tests. Results The 3987 patients with suspected intermediate risk acute coronary syndrome underwent exercise stress testing. One thousand and twenty-seven (25.8%) were aged less than 40 years (age 33.3 ± 4.8 years). Four of these 1027 patients had a positive exercise stress test (0.4% incidence of positive exercise stress testing). Of those, three patients had subsequent non-invasive functional testing that yielded a negative result. One patient declined further investigations. Assuming this was a true positive exercise stress test, the incidence of true positive exercise stress testing would have been 0.097% (95% confidence interval: 0.079–0.115%) (one of 1027 patients). Conclusions Routine exercise stress testing has limited value in the risk stratification of adults less than 40 years with suspected intermediate risk of acute coronary syndrome

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing

This paper describes the development of a model, based on Bayesian networks, to estimate the likelihood that sheep flocks are infested with lice at shearing and to assist farm managers or advisers to assess whether or not to apply a lousicide treatment. The risk of lice comes from three main sources: (i) lice may have been present at the previous shearing and not eradicated; (ii) lice may have been introduced with purchased sheep; and (iii) lice may have entered with strays. A Bayesian network is used to assess the probability of each of these events independently and combine them for an overall assessment. Rubbing is a common indicator of lice but there are other causes too. If rubbing has been observed, an additional Bayesian network is used to assess the probability that lice are the cause. The presence or absence of rubbing and its possible cause are combined with these networks to improve the overall risk assessment.

Human error risk management methodology for rail crack incidents

The paper presents an innovative approach to modelling the causal relationships of human errors in rail crack incidents (RCI) from a managerial perspective. A Bayesian belief network is developed to model RCI by considering the human errors of designers, manufactures, operators and maintainers (DMOM) and the causal relationships involved. A set of dependent variables whose combinations express the relevant functions performed by each DMOM participant is used to model the causal relationships. A total of 14 RCI on Hong Kong’s mass transit railway (MTR) from 2008 to 2011 are used to illustrate the application of the model. Bayesian inference is used to conduct an importance analysis to assess the impact of the participants’ errors. Sensitivity analysis is then employed to gauge the effect the increased probability of occurrence of human errors on RCI. Finally, strategies for human error identification and mitigation of RCI are proposed. The identification of ability of maintainer in the case study as the most important factor influencing the probability of RCI implies the priority need to strengthen the maintenance management of the MTR system and that improving the inspection ability of the maintainer is likely to be an effective strategy for RCI risk mitigation.

Fatigue fractures in military conscripts : A study on risk factors, diagnostics and long-term consequences

Fatigue fracture is an overuse injury commonly encountered in military and sports medicine, and known to relate to intensive or recently intensified physical activity. Bone responds to increased stress by enhanced remodeling. If physical stress exceeds bone s capability to remodel, accumulation of microfractures can lead to bone fatigue and stress fracture. Clinical diagnosis of stress fractures is complex and based on patient s anamnesis and radiological imaging. Bone stress fractures are mostly low-risk injuries, healing well after non-operative management, yet, occurring in high-risk areas, stress fractures can progress to displacement, often necessitating surgical treatment and resulting in prolonged morbidity. In the current study, the role of vitamin D as a predisposing factor for fatigue fractures was assessed using serum 25OHD level as the index. The average serum 25OHD concentration was significantly lower in conscripts with fatigue fracture than in controls. Evaluating TRACP-5b bone resorption marker as indicator of fatigue fractures, patients with elevated serum TRACP-5b levels had eight times higher probability of sustaining a stress fracture than controls. Among the 154 patients with exercise induced anterior lower leg pain and no previous findings on plain radiography, MRI revealed a total of 143 bone stress injuries in 86 patients. In 99% of the cases, injuries were in the tibia, 57% in the distal third of the tibial shaft. In patients with injury, forty-nine (57%) patients exhibited bilateral stress injuries. In a 20-year follow-up, the incidence of femoral neck fatigue fractures prior to the Finnish Defence Forces new regimen in 1986 addressing prevention of these fractures was 20.8/100,000, but rose to 53.2/100,000 afterwards, a significant 2.6-fold increase. In nineteen subjects with displaced femoral neck fatigue fractures, ten early local complications (in first postoperative year) were evident, and after the first postoperative year, osteonecrosis of the femoral head in six and osteoarthritis of the hip in thirteen patients were found. It seems likely that low vitamin D levels are related to fatigue fractures, and that an increasing trend exists between TRACP-5b bone resorption marker elevation and fatigue fracture incidence. Though seldom detected by plain radiography, fatigue fractures often underlie unclear lower leg stress-related pain occurring in the distal parts of the tibia. Femoral neck fatigue fractures, when displaced, lead to long-term morbidity in a high percentage of patients, whereas, when non-displaced, they do not predispose patients to subsequent adverse complications. Importantly, an educational intervention can diminish the incidence of fracture displacement by enhancing awareness and providing instructions for earlier diagnosis of fatigue fractures.

The effects of marriage partners' socio-economic positions on the risk of divorce in Finland

Väitöskirjatutkimuksen tavoitteena oli selvittää, miten aviopuolisoiden sosioekonominen asema vaikuttaa avioeroriskiin Suomessa. Tutkimuksessa käytettiin Tilastokeskuksen rekistereistä koottua aineistoa, joka koskee suomalaisten ensimmäisiä avioliittoja vuoden 1990 lopussa ja avioeroja vuosina 1991−93. Väitöskirjaan sisältyy kolme osatutkimusta. Ensimmäinen osatutkimus käsitteli avioeroriskin vaihtelua aviopuolisoiden sosioekonomisen aseman eri osatekijöiden (koulutusaste, sosiaaliryhmä, pääasiallinen toiminta, tulotaso, asunnon omistaminen ja asumisahtaus) mukaan. Kaiken kaikkiaan avioeroriski oli sitä pienempi, mitä paremmassa taloudellisessa ja sosiaalisessa asemassa aviopuolisot olivat. Esimerkiksi miehen ja vaimon korkea koulutusaste, toimihenkilöammatti, työssäkäynti (etenkin verrattuna työttömyyteen) sekä omistusasunnossa asuminen liittyivät pienentyneeseen avioeroriskiin. Vaimon sosioekonomisen aseman yhteys avioeroriskiin oli paljolti samanlainen kuin miehen aseman yhteys. Huomattavin poikkeus tähän oli, että vaimon suuret tulot lisäsivät avioeroriskiä, vaikka miehen suurilla tuloilla oli päinvastainen vaikutus. Lisäksi kotitaloustyötä pääasiallisena toimintanaan tekevillä naisilla (pääasiallisen toiminnan luokka ”muut”) oli vielä pienempi avioeroriski kuin työssäkäyvillä naisilla. Toisessa osatutkimuksessa keskityttiin aviomiehen ja vaimon aseman yhdistettyyn vaikutukseen. Selviä viitteitä siitä, että puolisoiden koulutustasojen erilaisuus lisäisi eroriskiä, ei saatu. Pareilla, joissa molemmilla oli enintään perusasteen koulutus, oli kuitenkin odotettua pienempi avioeroriski. Eroriski oli suhteellisen alhainen pareilla, joissa vaimo oli työssäkäyvä tai kotitaloustyötä tekevä ja aviomies työssäkäyvä. Eroriskiä kasvatti se, että aviomies, vaimo tai molemmat puolisot olivat työttömiä. Vaimon korkea tulotaso lisäsi eroriskiä miehen kaikilla tulotasoilla mutta erityisen voimakkaasti silloin, kun miehen tulotaso oli alhainen. Kolmanneksi selvitettiin, vaikuttaako puolisoiden sosioekonominen asema avioeroriskiin eri tavalla riippuen siitä, kauanko avioliitto on kestänyt. Tällöin havaittiin, että vähän koulutettujen ja työntekijäammateissa toimivien puolisoiden suuri eroriski rajoittuu paljolti nuorimpiin avioliittoihin. Sen sijaan esim. puolisoiden työttömyys, vaimon korkea tulotaso ja vuokra-asunnossa asuminen kasvattivat eroriskiä riippumatta siitä, kuinka kauan avioliitto oli kestänyt. Kaiken kaikkiaan eroriski oli siis sitä pienempi, mitä paremmassa taloudellisessa ja sosiaalisessa asemassa puolisot olivat. Vaimon taloudellisilla ja sosiaalisilla resursseilla näyttää kuitenkin olevan myös joitakin avioeroriskiä lisääviä vaikutuksia.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Political Risk in Credit Evaluation: Empirical Studies and Survey Results

Financing trade between economic agents located in different countries is affected by many types of risks, resulting from incomplete information about the debtor, the problems of enforcing international contracts, or the prevalence of political and financial crises. Trade is important for economic development and the availability of trade finance is essential, especially for developing countries. Relatively few studies treat the topic of political risk, particularly in the context of international lending. This thesis explores new ground to identify links between political risk and international debt defaults. The core hypothesis of the study is that the default probability of debt increases with increasing political risk in the country of the borrower. The thesis consists of three essays that support the hypothesis from different angles of the credit evaluation process. The first essay takes the point of view of an international lender assessing the credit risk of a public borrower. The second investigates creditworthiness assessment of companies. The obtained results are substantiated in the third essay that deals with an extensive political risk survey among finance professionals in developing countries. The financial instruments of core interest are export credit guaranteed debt initiated between the Export Credit Agency of Finland and buyers in 145 countries between 1975 and 2006. Default events of the foreign credit counterparts are conditioned on country-specific macroeconomic variables, corporate-specific accounting information as well as political risk indicators from various international sources. Essay 1 examines debt issued to government controlled institutions and conditions public default events on traditional macroeconomic fundamentals, in addition to selected political and institutional risk factors. Confirming previous research, the study finds country indebtedness and the GDP growth rate to be significant indicators of public default. Further, it is shown that public defaults respond to various political risk factors. However, the impact of the risk varies between countries at different stages of economic development. Essay 2 proceeds by investigating political risk factors as conveivable drivers of corporate default and uses traditional accounting variables together with new political risk indicators in the credit evaluation of private debtors. The study finds links between corporate default and leverage, as well as between corporate default and the general investment climate and measeures of conflict in the debtor country. Essay 3 concludes the thesis by offering survey evidence on the impact of political risk on debt default, as perceived and experienced by 103 finance professionals in 38 developing countries. Taken together, the results of the thesis suggest that various forms of political risk are associated with international debt defaults and continue to pose great concerns for both international creditors and borrowers in developing countries. The study provides new insights on the importance of variable selection in country risk analysis, and shows how political risk is actually perceived and experienced in the riskier, often lower income countries of the global economy.

Bank Run Risk and Optimal Reserves

We characterize the optimal reserves, and the generated probability of a bank run, as a function of the penalty imposed by the central bank, the probability of depositors’ liquidity needs, and the return on outside investment opportunities.

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.

Noise tolerance under risk minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Risk-sensitive control of continuous time Markov chains

We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterize the value function via Hamilton Jacobi Bellman equation and obtain an optimal Markov control. We do the same for infinite horizon discounted cost case. In the infinite horizon average cost case we establish the existence of an optimal stationary control under certain Lyapunov condition. We also develop a policy iteration algorithm for finding an optimal control.

AN OPTIMUM SHRINKAGE ESTIMATOR BASED ON MINIMUM-PROBABILITY-OF-ERROR CRITERION AND APPLICATION TO SIGNAL DENOISING

We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.

A probability-based approach to setting annual catch levels.

The requirement of setting annual catch limits to prevent overfishing has been added to the Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006 (MSRA). Because this requirement is new, a body of applied scientific practice for deriving annual catch limits and accompanying targets does not yet exist. This article demonstrates an approach to setting levels of catch that is intended to keep the probability of future overfishing at a preset low level. The proposed framework is based on stochastic projection with uncertainty in population dynamics. The framework extends common projection methodology by including uncertainty in the limit reference point and in management implementation, and by making explicit the risk of overfishing that managers consider acceptable. The approach is illustrated with application to gag (Mycteroperca microlepis), a grouper that inhabits the waters off the southeastern United States. Although devised to satisfy new legislation of the MSRA, the framework has potential application to any fishery where the management goal is to limit the risk of overfishing by controlling catch.

Flood risk management: What are the main drivers of prevention?

4 p.