Functional and morphologic evaluation of kidney proximal tubuli and correlation with renal allograft prognosis

P>Renal transplant patients with stable graft function and proximal tubular dysfunction (PTD) have an increased risk for chronic allograft nephropathy (CAN). In this study, we investigated the histologic pattern associated with PTD and its correlation with graft outcome. Forty-nine transplant patients with stable graft function were submitted to a biopsy. Simultaneously, urinary retinol-binding protein (uRBP) was measured and creatinine clearance was also determined. Banff`s score and semi-quantitative histologic analyses were performed to assess tubulointerstitial alterations. Patients were followed for 24.0 +/- 7.8 months. At biopsy time, mean serum creatinine was 1.43 +/- 0.33 mg/dl. Twelve patients (24.5%) had uRBP >= 1 mg/l, indicating PTD and 67% of biopsies had some degree of tubulointerstitial injury. At the end of the study period, 18 (36.7%) patients had lost renal function. uRBP levels were not associated with morphologic findings of interstitial fibrosis and tubular atrophy (IF/TA), interstitial fibrosis measured by Sirius red or tubulointerstitial damage. However, in multivariate analysis, the only variable associated with the loss of renal function was uRBP level >= 1 mg/l, determining a risk of 5.290 of loss of renal function (P = 0.003). Renal transplant patients who present PTD have functional alteration, which is not associated with morphologic alteration. This functional alteration is associated to progressive decrease in renal function.

Benefits of a year-long workplace weight loss program on cardiovascular risk factors

Objective: To assess the effectiveness of a year-long workplace weight loss program in reducing risk factors of coronary heart disease.

Design: A randomised, controlled study of low fat (25% of dietary energy) diet- and/or moderate exercise-induced weight loss interventions in free-living, middle-aged men. Compliance was monitored from food and activity diaries at monthly blood pressure measurement sessions. Blood was sampled and body composition determined from dual energy X-ray absorptiometry before and after 12 months.

Subjects and setting: Fifty-eight overweight men (mean [+ or -] SD age: 43.4 [+ or -] 5.7 years; BMI 29.0 [+ or -] 2.6 kg/[m.sup.2]), recruited from a national corporation, were instructed into diet (n = 18) exercise (a 21) or control (n = 19) groups over 12 months; 16 control subjects combined diet and exercise (n = 16) for the subsequent 12 months.

Main outcome measures: At 12 months, weight, total and regional fat and lean mass, dietary energy and percentage dietary fat intake, physical activity indices, systolic and diastolic blood pressure, serum insulin, blood lipids and lipoproteins.

Statistical analyses: Differences between groups were tested using analysis of variance with Scheffe post hoc test. Differences between pre- and post-intervention variables were tested using Students' paired t-tests. Pearson's correlation coefficient and univariate linear regression identified association between dependent variables, multiple stepwise regression identified specific predictors.

Results: Weight loss with either diet or exercise resulted in a reduction in systolic blood pressure (-3.3 [+ or -] 1.7%), diastolic blood pressure (-4.8 [+ or -] 1.3%) and LDL cholesterol (-3.9 [+ or -] 2.8%), a rise in HDL cholesterol (+10.0 [+ or -] 3.8%) and a change in the LDL/HDL ratio (-8.9 [+ or -] 3.5%). Abdominal fat loss (-26.8 [+ or -] 3.6% after diet; -16.6 [+ or -] 4.5% after exercise; -21.0 [+ or -] 4.7% after diet and exercise) was the strongest predictor of change in blood pressure: twenty percent abdominal fat loss predicted a percentage fall of 2.4 [+ or -] 0.05% in systolic blood pressure and 5.4 [+ or -] 0.07% in diastolic blood pressure. Greater abdominal fat loss was associated with the greatest decrease in serum insulin (P < 0.05).

Conclusion: Modest changes in diet and exercise effected by a low cost workplace-based education program achieved weight loss, loss of abdominal fat, reduced blood pressure and serum insulin and improved blood lipid concentrations. (Nutr Diet 2002;59:87-96)

Higher leptin levels in Asian Indians than Creoles and Europids : a potential explanation for increased metabolic risk

Background and purpose: Leptin predicts cardiovascular diseases and type 2 diabetes, diseases to which Asian Indians are highly susceptible. As a risk marker, leptin’s intra-individual and seasonal stability is unstudied and only small studies have compared leptin levels in Asian Indians with other populations. The aim of this study was to explore ethnicity related differences in leptin levels and its intra-individual and seasonal stability.

Methods: Leptin and anthropometric data from the northern Sweden MONICA (3513 Europids) and the Mauritius Non-communicable Disease (2480 Asian Indians and Creoles) studies were used. In both studies men and women, 25- to 74-year old, participated in both an initial population survey and a follow-up after 5–13 years. For the analysis of seasonal leptin variation, a subset of 1780 participants, 30- to 60-year old, in the Vasterbotten Intervention Project was used.

Results: Asian Indian men and women had higher levels of leptin, leptin per body mass index (BMI) unit (leptin/BMI) or per cm in waist circumference (WC; leptin/waist) than Creoles and Europids when adjusted for BMI (all P<0.0005) or WC (all P<0.005). In men, Creoles had higher leptin, leptin/BMI and leptin/waist than Europids when adjusted for BMI or WC (all P<0.0005). In women, Creoles had higher leptin/BMI and leptin/waist than Europids only when adjusted for WC (P<0.0005). Asian Indian ethnicity in both sexes, and Creole ethnicity in men, was independently associated with high leptin levels. The intra-class correlation for leptin was similar (0.6–0.7), independently of sex, ethnicity or follow-up time. No seasonal variation in leptin levels was seen.

Conclusion: Asian Indians have higher levels of leptin, leptin/BMI and leptin/waist than Creoles and Europids. Leptin has a high intra-individual stability and seasonal leptin variation does not appear to explain the ethnic differences observed here.

Functional capacity and quality of life in middle-age men and women with high and low number of metabolic risk factors

It is not clear if men and women with high numbers of risk factors (HiMF) for metabolic syndrome (MetS) have impaired capacities to perform activities of daily living (ADL's) and lower quality of life (QoL) in the absence of symptomatic heart disease. Our results indicate that in women there is a correlation between the number of risk factors and the capacity to perform ADL's and QoL. This was not evident for men. These findings may partly explain why women tend to consult healthcare practitioners earlier in the disease process than men.

Network traffic classification using correlation information

Traffic classification has wide applications in network management, from security monitoring to quality of service measurements. Recent research tends to apply machine learning techniques to flow statistical feature based classification methods. The nearest neighbor (NN)-based method has exhibited superior classification performance. It also has several important advantages, such as no requirements of training procedure, no risk of overfitting of parameters, and naturally being able to handle a huge number of classes. However, the performance of NN classifier can be severely affected if the size of training data is small. In this paper, we propose a novel nonparametric approach for traffic classification, which can improve the classification performance effectively by incorporating correlated information into the classification process. We analyze the new classification approach and its performance benefit from both theoretical and empirical perspectives. A large number of experiments are carried out on two real-world traffic data sets to validate the proposed approach. The results show the traffic classification performance can be improved significantly even under the extreme difficult circumstance of very few training samples.

Exploring known risk factors for pressure injury with visual technology

This research has identified that the use of visual technology can support the correlation between peak interface pressure and pressure gradients in the understanding of deep tissue injury. In addition as a pilot study the visual assessment of buttock shape has demonstrated potential for identifying risk of ischial or sacral pressure injury.

The pricing of deposit insurance in the presence of systematic risk

Based on the Merton (1977) put option framework, we develop a deposit insurance pricing model that incorporates asset correlations, a measurement for the systematic risk of a bank, to account for the risk of joint bank failures. Estimates from our model suggest that actuarially fair risk-based deposit insurance that considers only individual bank failure risk is underpriced, leaving insurance providers exposed to net losses. Our estimates also capture the size premium where big banks are priced with higher deposit insurance than small banks. This result is particularly relevant to the current regulatory concerns on big banks that are too-big-to-fail. Above all, our approach provides a unifying framework for integrating risk-based deposit insurance with risk-based Basel capital requirements.

Rain or shine: happiness and risk-taking

In this paper, we focus on the effects of weather, such as sunshine, as an exogenous shifter of happiness using happiness data at the individual level, and estimate sunshine as a predictor of happiness. Then we relate the predicted happiness to risk-taking. By doing so, we estimate a relationship, stronger than a simple correlation, between happiness and risky behavior. Weather changes, and sunshine in particular, have substantial influences on personal happiness. However, unexpected weather changes appear to be more important than expected changes for happiness. We include several risk measures such as subjective risk-taking and financial assets in our analysis. Happier people appear to be more risk-averse in general and more specifically in financial decisions, and choose accordingly safer investments. This might be explained by the fact that happy people take more time for making decisions and have more self-control. In addition, predicted happiness affects expectations about longevity and inflation. Happy people expect to live longer and accordingly seem more concerned about the future than the present, and expect less inflation.

FRAX (Aus) and falls risk: Association in men and women

Purpose: The WHO fracture risk prediction tool (FRAX®) utilises clinical risk factors to estimate the probability of fracture over a 10-year period. Although falls increase fracture risk, they have not been incorporated into FRAX. It is currently unclear if FRAX captures falls risk and whether addition of falls would improve fracture prediction. We aimed to investigate the association of falls risk and Australian-specific FRAX. Methods: Clinical risk factors were documented for 735 men and 602 women (age 40-90. yr) assessed at follow-up (2006-2010 and 2000-2003, respectively) of the Geelong Osteoporosis Study. FRAX scores with and without BMD were calculated. A falls risk score was determined at the time of BMD assessment and self-reported incident falls were documented from questionnaires returned one year later. Multivariable analyses were performed to determine: (i) cross-sectional association between FRAX scores and falls risk score (Elderly Falls Screening Test, EFST) and (ii) prospective relationship between FRAX and time to a fall. Results: There was an association between FRAX (hip with BMD) and EFST scores (. β=. 0.07, p<. 0.001). After adjustment for sex and age, the relationship became non-significant (. β=. 0.00, p=. 0.79). The risk of incident falls increased with increasing FRAX (hip with BMD) score (unadjusted HR 1.04, 95% CI 1.02, 1.07). After adjustment for age and sex, the relationship became non-significant (1.01, 95% CI 0.97, 1.05). Conclusions: There is a weak positive correlation between FRAX and falls risk score, that is likely explained by the inclusion of age and sex in the FRAX model. These data suggest that FRAX score may not be a robust surrogate for falls risk and that inclusion of falls in fracture risk assessment should be further explored.

Fuzzy portfolio allocation models through a new risk measure and fuzzy sharpe ratio

A new portfolio risk measure that is the uncertainty of portfolio fuzzy return is introduced in this paper. Beyond the well-known Sharpe ratio (i.e., the reward-to-variability ratio) in modern portfolio theory, we initiate the so-called fuzzy Sharpe ratio in the fuzzy modeling context. In addition to the introduction of the new risk measure, we also put forward the reward-to-uncertainty ratio to assess the portfolio performance in fuzzy modeling. Corresponding to two approaches based on TM and TW fuzzy arithmetic, two portfolio optimization models are formulated in which the uncertainty of portfolio fuzzy returns is minimized, while the fuzzy Sharpe ratio is maximized. These models are solved by the fuzzy approach or by the genetic algorithm (GA). Solutions of the two proposed models are shown to be dominant in terms of portfolio return uncertainty compared with those of the conventional mean-variance optimization (MVO) model used prevalently in the financial literature. In terms of portfolio performance evaluated by the fuzzy Sharpe ratio and the reward-to-uncertainty ratio, the model using TW fuzzy arithmetic results in higher performance portfolios than those obtained by both the MVO and the fuzzy model, which employs TM fuzzy arithmetic. We also find that using the fuzzy approach for solving multiobjective problems appears to achieve more optimal solutions than using GA, although GA can offer a series of well-diversified portfolio solutions diagrammed in a Pareto frontier.

Web search activity data accurately predict population chronic disease risk in the USA

BACKGROUND: The WHO framework for non-communicable disease (NCD) describes risks and outcomes comprising the majority of the global burden of disease. These factors are complex and interact at biological, behavioural, environmental and policy levels presenting challenges for population monitoring and intervention evaluation. This paper explores the utility of machine learning methods applied to population-level web search activity behaviour as a proxy for chronic disease risk factors. METHODS: Web activity output for each element of the WHO's Causes of NCD framework was used as a basis for identifying relevant web search activity from 2004 to 2013 for the USA. Multiple linear regression models with regularisation were used to generate predictive algorithms, mapping web search activity to Centers for Disease Control and Prevention (CDC) measured risk factor/disease prevalence. Predictions for subsequent target years not included in the model derivation were tested against CDC data from population surveys using Pearson correlation and Spearman's r. RESULTS: For 2011 and 2012, predicted prevalence was very strongly correlated with measured risk data ranging from fruits and vegetables consumed (r=0.81; 95% CI 0.68 to 0.89) to alcohol consumption (r=0.96; 95% CI 0.93 to 0.98). Mean difference between predicted and measured differences by State ranged from 0.03 to 2.16. Spearman's r for state-wise predicted versus measured prevalence varied from 0.82 to 0.93. CONCLUSIONS: The high predictive validity of web search activity for NCD risk has potential to provide real-time information on population risk during policy implementation and other population-level NCD prevention efforts.

US real interest rates and default risk in emerging economies

This paper empirically investigates the impact of changes in US real interest rates on sovereign default risk in emerging economies using the method of identification through heteroskedasticity. Policy-induced increases in US interest rates starkly raise default risk in emerging market economies. However, the overall correlation between US real interest rates and the risk of default is negative, demonstrating that the effects of other variables dominate the anterior relationship

Cálculo do Value at Risk (VaR) para o Ibovespa, pós crise de 2008, por meio dos modelos de heterocedasticidade condicional (GARCH) e de volatilidade estocástica (Local Scale Model - LSM)

O objetivo deste estudo é propor a implementação de um modelo estatístico para cálculo da volatilidade, não difundido na literatura brasileira, o modelo de escala local (LSM), apresentando suas vantagens e desvantagens em relação aos modelos habitualmente utilizados para mensuração de risco. Para estimação dos parâmetros serão usadas as cotações diárias do Ibovespa, no período de janeiro de 2009 a dezembro de 2014, e para a aferição da acurácia empírica dos modelos serão realizados testes fora da amostra, comparando os VaR obtidos para o período de janeiro a dezembro de 2014. Foram introduzidas variáveis explicativas na tentativa de aprimorar os modelos e optou-se pelo correspondente americano do Ibovespa, o índice Dow Jones, por ter apresentado propriedades como: alta correlação, causalidade no sentido de Granger, e razão de log-verossimilhança significativa. Uma das inovações do modelo de escala local é não utilizar diretamente a variância, mas sim a sua recíproca, chamada de “precisão” da série, que segue uma espécie de passeio aleatório multiplicativo. O LSM captou todos os fatos estilizados das séries financeiras, e os resultados foram favoráveis a sua utilização, logo, o modelo torna-se uma alternativa de especificação eficiente e parcimoniosa para estimar e prever volatilidade, na medida em que possui apenas um parâmetro a ser estimado, o que representa uma mudança de paradigma em relação aos modelos de heterocedasticidade condicional.

We're Chained: an analysis of systemic risk in finance

This dissertation presents two papers on how to deal with simple systemic risk measures to assess portfolio risk characteristics. The first paper deals with the Granger-causation of systemic risk indicators based in correlation matrices in stock returns. Special focus is devoted to the Eigenvalue Entropy as some previous literature indicated strong re- sults, but not considering different macroeconomic scenarios; the Index Cohesion Force and the Absorption Ratio are also considered. Considering the S&P500, there is not ev- idence of Granger-causation from Eigenvalue Entropies and the Index Cohesion Force. The Absorption Ratio Granger-caused both the S&P500 and the VIX index, being the only simple measure that passed this test. The second paper develops this measure to capture the regimes underlying the American stock market. New indicators are built using filtering and random matrix theory. The returns of the S&P500 is modelled as a mixture of normal distributions. The activation of each normal distribution is governed by a Markov chain with the transition probabilities being a function of the indicators. The model shows that using a Herfindahl-Hirschman Index of the normalized eigenval- ues exhibits best fit to the returns from 1998-2013.