Fuzzy linguistic model for evaluating the risk of neonatal death

OBJECTIVE: To introduce a fuzzy linguistic model for evaluating the risk of neonatal death. METHODS: The study is based on the fuzziness of the variables newborn birth weight and gestational age at delivery. The inference used was Mamdani's method. Neonatologists were interviewed to estimate the risk of neonatal death under certain conditions and to allow comparing their opinions and the model values. RESULTS: The results were compared with experts' opinions and the Fuzzy model was able to capture the expert knowledge with a strong correlation (r=0.96). CONCLUSIONS: The linguistic model was able to estimate the risk of neonatal death when compared to experts' performance.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Risk factors for cesarean section by category of health service

OBJECTIVE: To analyze the rate of cesarean section and differences in risk factors by category of health service, either public or private. METHODS: A cross-sectional study was carried out including all pregnant women in labor admitted to hospitals in the city of Rio Grande, Southern Brazil, between January 1 and December 31, 2007. A pre-coded and pre-tested questionnaire was used to collect on social, demographic, obstetric and newborn care information. Two regression models were constructed: one for public users and the other one for private ones. Poisson regression was used in each model in the multivariate analysis. Prevalence rates and 95% confidence intervals were calculated for each adjusted factor. RESULTS: The rate of cesarean section was 43% and 86% among public and private users. Sociodemographic factors and twin births have a more significant impact among public users as well as number of pregnancies (25% vs. 13% reduction in public and private users, respectively) and previous cesarean section (86% vs. 24% increase in public and private users, respectively). Prenatal care visits and hospital admissions affected the outcome only in women users of public services. CONCLUSIONS: Cesarean section rates were high in both groups studied, but it was twice as high among women cared in the private sector. Associated factors differ in magnitude by category of service used.

Exposure to acellular blood products and risk of HIV infection in hemophiliacs from Belo Horizonte, Brazil

Results of a HIV prevalence study conducted in hemophiliacs from Belo Horizonte, Brazil are presented. History of exposure to acellular blood components was determined for the five year period prior to entry in the study, which occurred during 1986 and 1987. Patients with coagulations disorders (hemophilia A = 132, hemophilia B = 16 and coagulation disorders other than hemophilia = 16) were transfused with liquid cryoprecipitate, locally produced, lyophilized cryoprecipitate, imported from São Paulo (Brazil) and factor VIII and IX, imported from Rio de Janeiro (Brazil), Europe, and United States. Thirty six (22%) tested HIV seropositive. The univariate and multivariate analysis (logistic model) demonstrated that the risk of HIV infection during the study period was associated with the total units of acellular blood components transfused. In addition, the proportional contribution of the individual components to the total acellular units transfused, namely a increase in factor VIII/IX and lyophilized cryoprecipitate proportions, were found to be associated with HIV seropositivity. This analysis suggest that not only the total amount of units was an important determinant of HIV infection, but that the risk was also associated with the specific component of blood transfused

Risk factors for and mortality of extended-spectrum-β-lactamase-producing Klebsiella pneumoniae and Escherichia coli nosocomial bloodstream infections

A case-control study, involving patients with positive blood cultures for Klebsiella pneumoniae (KP) or Escherichia coli (EC) EC and controls with positive blood cultures for non-ESBL-KP or EC, was performed to assess risk factors for extended-spectrum-β-lactamase (ESBL) production from nosocomial bloodstream infections (BSIs). Mortality among patients with BSIs was also assessed. The study included 145 patients (81, 59.5% with K. pneumoniae and 64, 44.1% with E. coli BSI); 51 (35.2%) isolates were ESBL producers and 94 (64.8%) nonproducers. Forty-five (55.6%) K. pneumoniae isolates were ESBL producers, while only six (9.4%) E. coli isolates produced the enzyme. Multivariate analysis showed that recent exposure to piperacillin-tazobactam (adjusted Odds Ratio [aOR] 6.2; 95%CI 1.1-34.7) was a risk factor for ESBL BSI. K. pneumoniae was significantly more likely to be an ESBL-producing isolate than E. coli (aOR 6.7; 95%CI 2.3-20.2). No cephalosporin class was independently associated with ESBLs BSI; however, in a secondary model considering all oxymino-cephalosporins as a single variable, a significant association was demonstrated (aOR 3.7; 95%CI 1.3-10.8). Overall 60-day mortality was significantly higher among ESBL-producing organisms. The finding that piperacillin-tazobactam use is a risk factor for ESBL-production in KP or EC BSIs requires attention, since this drug can be recommended to limit the use of third-generation cephalosporins.

Is It Possible to Simplify Risk Stratification Scores for Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Angioplasty?

INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality.

Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.

Development of a fuzzy qualitative risk assessment model applied to construction industry

Dissertação para obtenção do Grau de Doutor em Engenharia Industrial

Enhancement of an implemented rating model and impact on existing risk management processes: A hands-on approach from financial supplier risk management within the automotive industry

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.

Prevalence and risk factors for Toxoplasma gondii infection among pregnant and postpartum women attended at public healthcare facilities in the City of Niterói, State of Rio de Janeiro, Brazil

IntroductionTo determine the prevalence of immunoglobulin G (IgG) and immunoglobulin M (IgM) anti-Toxoplasma gondii antibodies among pregnant and postpartum women attended within the public healthcare system in Niterói, State of Rio de Janeiro, and to detect possible exposure factors associated with T. gondii infection in this population.MethodsIgM and IgG anti-T. gondii antibodies were investigated in 276 pregnant and 124 postpartum women by using the indirect immunofluorescence (IFAT) and immunoenzymatic assay (ELISA) techniques. The participants were selected by convenience sampling. All these 400 patients filled out a free and informed consent statement, answered an epidemiological questionnaire and were informed about the disease.ResultsAmong the 400 samples analyzed, 234 (58.5%) were reactive to IgG anti-T. gondii antibodies, according to the IFAT and/or ELISA assay. One pregnant woman was found to be reactive to IgM anti-T. gondii antibodies, with an intermediate IgG avidity test. Risk factor analysis showed that seropositivity was significantly associated (p<0.05) with age, contact with cats and presence of rodents at home. Through a logistic regression model, these associations were confirmed for age and contact with cats, while education at least of the high school level was found to be a protective factor.ConclusionsThe prevalence rate of IgG anti-T. gondii antibodies in the City of Niterói was high and the risk factors for infection detected after multivariate analysis were: age over 30 years, contact with cats and education levels lower than university graduate level.

Development of a model for occupational risk acceptance criteria definition in industrial settings

Doctoral Dissertation for PhD degree in Industrial and Systems Engineering

Impact of TGF-ß1 -509C/T and 869T/C polymorphisms on glioma risk and patient prognosis

Transforming growth factor beta (TGF-ß) plays an important role in carcinogenesis. Two polymorphisms in the TGF-ß1 gene (-509C/T and 869T/C) were described to influence susceptibility to gastric and breast cancers. The 869T/C polymorphism was also associated with overall survival in breast cancer patients. In the present study, we investigated the relevance of these TGF-ß1 polymorphism in glioma risk and prognosis. A case-control study that included 114 glioma patients and 138 cancer-free controls was performed. Single nucleotide polymorphisms (SNPs) were evaluated by polymerase chain reaction followed by restriction fragment length polymorphism (PCR-RFLP). Univariate and multivariate logistic regression analyses were used to calculate odds ratio (OR) and 95 % confidence intervals (95 % CI). The influence of TGF-ß1 -509C/T and 869T/C polymorphisms on glioma patient survival was evaluated by a Cox regression model adjusted for patients' age and sex and represented in Kaplan-Meier curves. Our results demonstrated that TGF-ß1 gene polymorphisms -509C/T and 869T/C are not significantly associated with glioma risk. Survival analyses showed that the homozygous -509TT genotype associates with longer overall survival of glioblastoma (GBM) patients when compared with patients carrying CC + CT genotypes (OR, 2.41; 95 % CI, 1.06-5.50; p = 0.036). In addition, the homozygous 869CC genotype is associated with increased overall survival of GBM patients when compared with 869TT + TC genotypes (OR, 2.62; 95 % CI, 1.11-6.17; p = 0.027). In conclusion, this study suggests that TGF-ß1 -509C/T and 869T/C polymorphisms are not significantly associated with risk for developing gliomas but may be relevant prognostic biomarkers in GBM patients.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Learning about Risk and Return: A Simple Model of Bubbles and Crashes

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.

Universal banking, competition and risk in a macro model

A stylized macroeconomic model is developed with an indebted, heterogeneous Investment Banking Sector funded by borrowing from a retail banking sector. The government guarantees retail deposits. Investment banks choose how risky their activities should be. We compared the benefits of separated vs. universal banking modelled as a vertical integration of the retail and investment banks. The incidence of banking default is considered under different constellations of shocks and degrees of competitiveness. The benefits of universal banking rise in the volatility of idiosyncratic shocks to trading strategies and are positive even for very bad common shocks, even though government bailouts, which are costly, are larger compared to the case of separated banking entities. The welfare assessment of the structure of banks may depend crucially on the kinds of shock hitting the economy as well as on the efficiency of government intervention.