Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

Active surveillance to determine the impact of methicillin resistance on mortality in patients with bacteremia and influences of the use of antibiotics on the development of MRSA infection

Introduction Methicillin-resistant Staphylococcus aureus (MRSA) is among the most important pathogens of nosocomial infections, mainly in intensive care units (ICUs), and accounts for 40-60% of all healthcare-associated S. aureus infections. We evaluated the incidence of nosocomial infection by S. aureus, identified the risk factors for MRSA infection, and evaluated the effect of resistance to methicillin on mortality in patients. Methods We conducted MRSA surveillance at a university hospital in Brazil from January 1, 2010, to December 31, 2010, and performed a retrospective case-control matched study to evaluate the frequency of subsequent MRSA bacteremia and death among patients. We evaluated and compared the risk factors between patients with MRSA and methicillin-sensitive Staphylococcus aureus (MSSA) infection. Results Sepsis was the most common cause of infection (17.7/1,000 patient-days), followed by surgical site (11.4/1,000 patient-days), pneumonia (4.1/1,000 patient-days), and urinary tract infection (2.4/1,000 patient-days). The significant risk factors were time of hospitalization, use of central vascular catheter (CVC), urinary catheter, nasogastric tube, parenteral nutrition, tracheostomy, mechanical ventilation, and previous antibiotic administration, the latter of which was the only independent risk factor for MRSA infection. Mortality was significantly higher in patients with MRSA. The number of antibiotics tested was not related to increases in the frequency of MRSA/1,000 patient-days. The incidence of mortality attributable to MRSA (bloodstream infection) BSI was 50%. Conclusions Surveillance results showed that the use of high levels of antibiotics was directly related to the development of MRSA infection, and the mortality attributable to MRSA in patients with bacteremia was significant.

High visceral leishmaniasis mortality rate in Barra Mansa, a new area of visceral leishmaniasis transmission in the State of Rio de Janeiro, Brazil

Introduction Nine cases of visceral leishmaniasis occurred recently in Barra Mansa, State of Rio de Janeiro, with a high mortality rate. Methods We reviewed the medical records of the patients. Results Eight were male; 7 were adults. Patients who died progressed to death quickly and presented with aggravating factors: systemic steroid therapy before diagnosis, bleeding, severe liver involvement, infection, and/or refusal to receive transfusion. Conclusions We warn clinicians to be aware of the emergence of visceral leishmaniasis in new areas and to keep in mind the possibility of atypical clinical pictures and aggravating factors, so timely diagnosis can be made and prompt and adequate treatment can be initiated.

Potential for entomopathogenic fungi to control Triatoma dimidiata (Hemiptera: Reduviidae), a vector of Chagas disease in Mexico

Introduction The use of entomopathogenic fungi to control disease vectors has become relevant because traditional chemical control methods have caused damage to the environment and led to the development of resistance among vectors. Thus, this study assessed the pathogenicity of entomopathogenic fungi in Triatoma dimidiata. Methods Preparations of 108 conidia/ml of Gliocladium virens, Talaromyces flavus, Beauveria bassiana and Metarhizium anisopliae were applied topically on T. dimidiata nymphs and adults. Controls were treated with the 0.0001% Tween-80 vehicle. Mortality was evaluated and recorded daily for 30 days. The concentration required to kill 50% of T. dimidiata (LC50) was then calculated for the most pathogenic isolate. Results Pathogenicity in adults was similar among B. bassiana, G. virens and T. flavus (p>0.05) and differed from that in triatomine nymphs (p=0.009). The most entomopathogenic strains in adult triatomines were B. bassiana and G. virens, which both caused 100% mortality. In nymphs, the most entomopathogenic strain was B. bassiana, followed by G. virens. The native strain with the highest pathogenicity was G. virens, for which the LC50 for T. dimidiata nymphs was 1.98 x108 conidia/ml at 13 days after inoculation. Conclusions Beauveria bassiana and G. virens showed entomopathogenic potential in T. dimidiata nymphs and adults. However, the native G. virens strain presents a higher probability of success in the field, and G. virens should thus be considered a potential candidate for the biological control of triatomine Chagas disease vectors.

Trends and factors associated with dengue mortality and fatality in Brazil

AbstractINTRODUCTION:Studies that generate information that may reduce the dengue death risk are essential. This study analyzed time trends and risk factors for dengue mortality and fatality in Brazil from 2001 to 2011.METHODS:Time trends for dengue mortality and fatality rates were analyzed using simple linear regression. Associations between the dengue mortality and the case fatality rates and socioeconomic, demographic, and health care indicators at the municipality level were analyzed using negative binomial regression.RESULTS:The dengue hemorrhagic fever case fatality rate increased in Brazil from 2001 to 2011 (β=0.67; p=0.036), in patients aged 0-14 years (β=0.48; p=0.030) and in those aged ≥15 years (β=1.1; p<0.01). Factors associated with the dengue case fatality rate were the average income per capita (MRR=0.99; p=0.038) and the number of basic health units per population (MRR=0.89; p<0.001). Mortality rates increased from 2001 to 2011 (β=0.350; p=0.002).Factors associated with mortality were inequality (RR=1.02; p=0.001) high income per capita (MRR=0.99; p=0.005), and higher proportions of populations living in urban areas (MRR=1.01; p<0.001).CONCLUSIONS:The increases in the dengue mortality and case fatality rates and the associated socioeconomic and health care factors, suggest the need for structural and intersectoral investments to improve living conditions and to sustainably reduce these outcomes.

Dose de radiação e risco para a saúde em doentes com Linfoma não-Hodgkin submetidos a estudos de TC

RESUMO - A exposição a radiações ionizantes em tomografia computorizada (TC) pode constituir-se como um risco para a saúde dos utentes. A TC é utilizada no diagnóstico e follow-up de doentes com Linfoma não-Hodgkin, subtipo Linfoma Difuso das Grandes Células B (LDGCB). O objetivo deste estudo foi determinar a dose efetiva acumulada e o risco de segundas neoplasias nestes doentes, diagnosticados em 2011 no IPOLFG e seguidos na consulta de hematologia até 2013. Foram avaliados retrospetivamente 70 doentes com base nos registos de dose do “Patient Protocol” das TC efetuadas. Em média cada doente fez 12 TC e a dose efetiva acumulada foi de 64,76 mSv (percentil 75). Três doentes foram expostos a doses de radiação superiores 90 mSv e um atingiu 111,72 mSv. Os resultados demonstram ser necessário rever os parâmetros e protocolos de exames de TC: (i) TC crânio (DLP= 777 mGycm) e TC abdominal-pélvico (DLP= 628 mGycm). O aumento do número de exames de TC efetuados e a consequente dose parece corresponder a um aumento do risco de segundas neoplasias e risco de morte por doenças neoplásicas durante a vida destes doentes. Os resultados são aparentemente mais significativos para as mulheres, que apresentam o dobro do risco de cancro do pulmão e risco de mortalidade superior em 14% para todas as doenças neoplásicas. O elevado número de exames de TC realizados por cada doente contribui para o aumento da probabilidade de efeitos deletérios e também para o aumento dos níveis de dose efetiva coletiva na população em geral.

Implementação da Equipa de Emergência Médica Intra-hospitalar nos hospitais do Serviço Nacional de Saúde : análise de custo-efetividade perante a incidência da paragem cárdio-respiratória intra-hospitalar

RESUMO - Introdução: No âmbito das emergências intra-hospitalares investigou-se a hipótese da presença da Equipa Emergência Médica Intra-hospitalar (EEMI) (DGS, 2010) num Centro Hospitalar (CH), contribuir para a redução do número de mortos por Paragem Cárdiorespiratória (PCR) intra-hospitalar, quando comparado com outro CH dotado de uma equipa tradicional de resposta à PCR. Metodologia: Tratou-se de um estudo observacional, retrospetivo (2010 a 2014), com base nos dados do Grupo de Diagnóstico Homogéneo (GDH), analisado numa perspetiva de custo-efetividade no impacto sobre incidência de PCR e taxa de mortalidade. Resultados: Observou-se que o CH com EEMI apresentou uma Redução Risco Absoluto (RRA) de 9,01% de morte por PCR. A taxa de mortalidade calculada foi de 2,82 casos por 1000 episódios de internamento em que a incidência de PCR foi de 28,24 casos por cada 10 000 habitantes, duas vezes menor que CH em comparação. Quando introduzidas manobras de Ressuscitação Cárdiopulmonar (RCP), o mesmo CH teve um maior número de PCR revertidas, com uma taxa de mortalidade 2 vezes menor que o CH sem EEMI. Conclusão: Resultados demonstraram que os dois CH apresentaram riscos diferentes, em que a probabilidade do doente hospitalizado de morrer após ocorrência de PCR foi menor no grupo exposto à EEMI, com OR = 0,496 [IC 95% (0,372 a 0,662)] para dados populacionais (p = 0,0013), e OR = 0,618 [IC 95% (0,298 a 1,281)] para dados individuais, (p = 0,194). Face a melhores resultados em Saúde, considerou-se a implementação da EEMI, uma medida custo-efetiva, uma vez que o principal requisito traduz-se por reorganização das equipas tradicionais para uma vertente de prevenção da PCR.

Determinants of mortality in oncology patients colonized or infected with Staphylococcus aureus

Oxacillin-resistant Staphylococcus aureus (ORSA) infection is an important cause of hospital morbidity and mortality. The objective of this study was to identify the main factors associated with death in patients colonized or infected with Staphylococcus aureus in a cancer center. A matched-pair case-control study enrolled all patients infected or colonized with ORSA (cases) admitted to the Hospital do Câncer in Rio de Janeiro from 01/01/1992 to 12/31/1994. A control was defined as a patient hospitalized during the same period as the case-patients and colonized or infected with oxacillin-susceptible Staphylococcus aureus (OSSA). The study enrolled 95 cases and 95 controls. Patient distribution was similar for the two groups (p > or = 0.05) with respect to gender, underlying diseases, hospital transfer, prior infection, age, temperature, heart and respiratory rates, neutrophil count, and duration of hospitalization. Univariate analysis of putative risk factors associated with mortality showed the following significant variables: admission to the intensive care unit (ICU), presence of bacteremia, use of central venous catheter (CVC), ORSA colonization or infection, pneumonia, use of urinary catheter, primary lung infection, prior use of antibiotics, mucositis, and absence of cutaneous abscesses. Multivariate analysis showed a strong association between mortality and the following independent variables: admission to ICU (OR [odds ratio]=7.2), presence of Staphylococcus bacteremia (OR=6.8), presence of CVC (OR=5.3), and isolation of ORSA (OR=2.7). The study suggests a higher virulence of ORSA in comparison to OSSA in cancer patients.

Gastric and colorectal cancer mortality in an urban and industrialized area of Brazil

PURPOSE: To study the gastric and colorectal cancer mortalities and their relation to the urban-industrialization in Baixada Santista, located in the southeastern region of Brazil. METHODS: Selected from the registries of the State System of Data Analysis Foundation (SEADE) were 1105 deaths due to gastric cancer (ICD 153--154) and 690 due to colorectal cancer (ICD 151) that occurred from 1980 to 1993 in males, above 10 years of age, residing in Baixada Santista. For each of these types of cancer, the standardized mortality rates, age-adjusted by world population in the 1960s, for 4 industrialized and 4 non-industrialized urban communities in that region were calculated. The ratios among those rates were calculated in order to compare the mortality in the periods 1980--93, 1980--1986, and 1987--1993. RESULTS: Standardized mortality rates for colorectal cancer were significantly higher in industrialized area, with ratios of 1.6 [95% CI 1.22 -- 2.29], 1.6 [95% CI 1.2 -- 2.0], and 1.6 [95% CI 1.3 -- 2.0] in the periods 1980--86, 1987--1993 and 1980--93, respectively. Gastric cancer did not show any statistical difference between the industrialized and non-industrialized areas, but there was a significant decrease in BS from the period 1980--1986 to 1987--1993. CONCLUSIONS: The significant elevation of colorectal cancer mortality in the industrialized area could be related to exposure to numerous carcinogens such as aromatic hydrocarbon, organic-chloride, metals, and industrial-port dust present in the region. Alternatively, the non-significant difference in gastric cancer between industrialized and non-industrialized areas and significant decrease in the last few years could be predominately reflecting the advances in the quality of life in urban areas. These results require further case-control studies that could help with the analysis of the associations among cancer and environmental factors (occupational, urban-industrial, habit, and life condition) and genetic susceptibility.

Prognostic factors influencing morbidity and mortality in esophageal carcinoma

PURPOSE: In 1980, operative mortality for esophageal resection was 29%. Over the last 15 years, technical and critical care improvements contributed to the reduction of postoperative mortality rate to 8%. The aim of this study is to analyze retrospectively the role of different factors (surgical procedure, stage of the disease, and anesthetic risk) on the postoperative mortality of 63 patients that underwent esophagectomy with gastric interposition for cancer. METHODS: Seventy-two patients underwent esophagectomy. The stomach was the esophageal substitute in 63 cases. Surgical procedures included transthoracic esophagectomy in 49 patients and transhiatal esophagectomy in 14 cases. Among the 49 transthoracic esophagectomy patients, there were 18 patients with a high anesthetic risk (ASA III). Among the patients that underwent transhiatal esophagectomy, there were 10 patients with a high anesthetic risk (ASA III). RESULTS: The operative mortality rate was 14% (2/14) in transhiatal esophagectomy group and 22% (11/49) in transthoracic esophagectomy group (P = ns). The postoperative mortality of patients with a high anesthetic risk (ASA III) was 47% (8/17) after transthoracic esophagectomy and 10% (1/10) after transhiatal esophagectomy (P <0.05). DISCUSSION: In our experience, the operative mortality was nearly 18% (16.6% after transhiatal esophagectomy and 20.8% after transthoracic esophagectomy). Among the patients with a high anesthetic risk (ASA III) that underwent surgery, the postoperative mortality was significantly lower after transhiatal esophagectomy (10%) compared to transthoracic esophagectomy (47%) (P <0.05).

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Electric vehicle assistant based in driver profile

This paper presents the outcomes of a research work consisting in the development of an Electric Vehicle Assistant (EVA), which creates and stores a driver profile where are contained the driving behaviours related with the EV energy consumption, the EV battery charging information, and the performed routes. This is an application for mobile devices that is able to passively track the driver behaviour and to access several information related with the EV in real time. It is also proposed a range prediction approach based on probability to take into account unpredictable effects of personal driving style, traffic or weather.

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.