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Sample records for brazil predictive risk

  1. Risk analysis and prediction of visceral leishmaniasis dispersion in São Paulo State, Brazil

    PubMed Central

    Mao, Liang; Galvis-Ovallos, Fredy; Tucker Lima, Joanna Marie; Valle, Denis

    2017-01-01

    Visceral leishmaniasis (VL) is an important neglected disease caused by a protozoan parasite, and represents a serious public health problem in many parts of the world. It is zoonotic in Europe and Latin America, where infected dogs constitute the main domestic reservoir for the parasite and play a key role in VL transmission to humans. In Brazil this disease is caused by the protozoan Leishmania infantum chagasi, and is transmitted by the sand fly Lutzomyia longipalpis. Despite programs aimed at eliminating infection sources, the disease continues to spread throughout the Country. VL in São Paulo State, Brazil, first appeared in the northwestern region, spreading in a southeasterly direction over time. We integrate data on the VL vector, infected dogs and infected human dispersion from 1999 to 2013 through an innovative spatial temporal Bayesian model in conjunction with geographic information system. This model is used to infer the drivers of the invasion process and predict the future progression of VL through the State. We found that vector dispersion was influenced by vector presence in nearby municipalities at the previous time step, proximity to the Bolívia-Brazil gas pipeline, and high temperatures (i.e., annual average between 20 and 23°C). Key factors affecting infected dog dispersion included proximity to the Marechal Rondon Highway, high temperatures, and presence of the competent vector within the same municipality. Finally, vector presence, presence of infected dogs, and rainfall (approx. 270 to 540mm/year) drove the dispersion of human VL cases. Surprisingly, economic factors exhibited no noticeable influence on disease dispersion. Based on these drivers and stochastic simulations, we identified which municipalities are most likely to be invaded by vectors and infected hosts in the future. Prioritizing prevention and control strategies within the identified municipalities may help halt the spread of VL while reducing monitoring costs. Our results

  2. Chikungunya risk for Brazil

    PubMed Central

    Azevedo, Raimunda do Socorro da Silva; Oliveira, Consuelo Silva; Vasconcelos, Pedro Fernando da Costa

    2015-01-01

    This study aimed to show, based on the literature on the subject, the potential for dispersal and establishment of the chikungunya virus in Brazil. The chikungunya virus, a Togaviridae member of the genus Alphavirus, reached the Americas in 2013 and, the following year, more than a million cases were reported. In Brazil, indigenous transmission was registered in Amapa and Bahia States, even during the period of low rainfall, exposing the whole country to the risk of virus spreading. Brazil is historically infested by Ae. aegypti and Ae. albopictus, also dengue vectors. Chikungunya may spread, and it is important to take measures to prevent the virus from becoming endemic in the country. Adequate care for patients with chikungunya fever requires training general practitioners, rheumatologists, nurses, and experts in laboratory diagnosis. Up to November 2014, more than 1,000 cases of the virus were reported in Brazil. There is a need for experimental studies in animal models to understand the dynamics of infection and the pathogenesis as well as to identify pathophysiological mechanisms that may contribute to identifying effective drugs against the virus. Clinical trials are needed to identify the causal relationship between the virus and serious injuries observed in different organs and joints. In the absence of vaccines or effective drugs against the virus, currently the only way to prevent the disease is vector control, which will also reduce the number of cases of dengue fever. PMID:26398876

  3. Chikungunya risk for Brazil.

    PubMed

    Azevedo, Raimunda do Socorro da Silva; Oliveira, Consuelo Silva; Vasconcelos, Pedro Fernando da Costa

    2015-01-01

    This study aimed to show, based on the literature on the subject, the potential for dispersal and establishment of the chikungunya virus in Brazil. The chikungunya virus, a Togaviridae member of the genusAlphavirus, reached the Americas in 2013 and, the following year, more than a million cases were reported. In Brazil, indigenous transmission was registered in Amapa and Bahia States, even during the period of low rainfall, exposing the whole country to the risk of virus spreading. Brazil is historically infested by Ae. aegypti and Ae. albopictus, also dengue vectors. Chikungunya may spread, and it is important to take measures to prevent the virus from becoming endemic in the country. Adequate care for patients with chikungunya fever requires training general practitioners, rheumatologists, nurses, and experts in laboratory diagnosis. Up to November 2014, more than 1,000 cases of the virus were reported in Brazil. There is a need for experimental studies in animal models to understand the dynamics of infection and the pathogenesis as well as to identify pathophysiological mechanisms that may contribute to identifying effective drugs against the virus. Clinical trials are needed to identify the causal relationship between the virus and serious injuries observed in different organs and joints. In the absence of vaccines or effective drugs against the virus, currently the only way to prevent the disease is vector control, which will also reduce the number of cases of dengue fever.

  4. Melanoma Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Cancer Risk Prediction and Assessment

    Cancer.gov

    Cancer prediction models provide an important approach to assessing risk and prognosis by identifying individuals at high risk, facilitating the design and planning of clinical cancer trials, fostering the development of benefit-risk indices, and enabling estimates of the population burden and cost of cancer.

  6. Ecological risk assessment, prediction, and assessing risk predictions.

    PubMed

    Gibbs, Mark

    2011-11-01

    Ecological risk assessment embodied in an adaptive management framework is becoming the global standard approach for formally assessing and managing the ecological risks of technology and development. Ensuring the continual improvement of ecological risk assessment approaches is partly achieved through the dissemination of not only the types of risk assessment approaches used, but also their efficacy. While there is an increasing body of literature describing the results of general comparisons between alternate risk assessment methods and models, there is a paucity of literature that post hoc assesses the performance of specific predictions based on an assessment of risk and the effectiveness of the particular model used to predict the risk. This is especially the case where risk assessments have been used to grant consent or approval for the construction of major infrastructure projects. While postconstruction environmental monitoring is increasingly commonplace, it is not common for a postconstruction assessment of the accuracy and performance of the ecological risk assessment and underpinning model to be undertaken. Without this "assessment of the assessment," it is difficult for other practitioners to gain insight into the performance of the approach and models used and therefore, as argued here, this limits the rate of improvement of risk assessment approaches.

  7. Shallow landslide prediction and analysis with risk assessment using a spatial model in a coastal region in the state of São Paulo, Brazil

    NASA Astrophysics Data System (ADS)

    Camarinha, P. I. M.; Canavesi, V.; Alvalá, R. C. S.

    2014-09-01

    This study presents a methodology for susceptibility mapping of shallow landslides just from data and software from the public domain. The study was conducted in a mountainous region located on the southeastern Brazilian coast, in the state of São Paulo. The proposal is that the methodology can be replicated in a practical and reliable way in several other municipalities that do not have such mappings and that often suffer from landslide-related disasters. The susceptibility mapping was generated based on the following maps: geological, soils, slope, horizontal and vertical curvatures, and land use. The thematic classes of these maps were weighted according to technical and scientific criteria related to the triggering of landslides, and were crossed by the fuzzy gamma technique. The mapping was compared with the risk sector survey made by the Brazilian Geological Survey (CPRM), which is the official database used by municipalities and civil defense in risk management. The results showed positive correlations, so that the critical risk sectors had higher proportions for the more susceptible classes. To compare the approach with other studies using landslide-scar maps, correlated indices were evaluated, which also showed satisfactory results, thus indicating that the methodology presented is appropriate for risk assessment in urban areas.

  8. Neuroanatomy Predicts Individual Risk Attitudes

    PubMed Central

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W.; Glimcher, Paul W.

    2014-01-01

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  9. Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.

    PubMed

    Lowe, Rachel; Coelho, Caio As; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

    2016-02-24

    Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.

  10. Breast Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Esophageal Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Colorectal Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Prostate Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Pancreatic Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Lung Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Testicular Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Ovarian Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Cervical Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Bladder Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Developmental Dyslexia: Predicting Individual Risk

    ERIC Educational Resources Information Center

    Thompson, Paul A.; Hulme, Charles; Nash, Hannah M.; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J.

    2015-01-01

    Background: Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. Methods: The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6…

  1. Liver Cancer Risk Prediction Models

    Cancer.gov

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Family Factors Predicting Categories of Suicide Risk

    ERIC Educational Resources Information Center

    Randell, Brooke P.; Wang, Wen-Ling; Herting, Jerald R.; Eggert, Leona L.

    2006-01-01

    We compared family risk and protective factors among potential high school dropouts with and without suicide-risk behaviors (SRB) and examined the extent to which these factors predict categories of SRB. Subjects were randomly selected from among potential dropouts in 14 high schools. Based upon suicide-risk status, 1,083 potential high school…

  3. Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

    PubMed Central

    Lowe, Rachel; Coelho, Caio AS; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

    2016-01-01

    Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001 PMID:26910315

  4. Youth Perspectives on Risk and Resiliency: A Case Study from Juiz De Fora, Brazil

    ERIC Educational Resources Information Center

    Morrison, Penelope; Nikolajski, Cara; Borrero, Sonya; Zickmund, Susan

    2014-01-01

    The present work seeks to contribute to studies of cross-cultural risk and resiliency by presenting results from qualitative research with adolescents attending programs for at-risk youth in Juiz de Fora, Brazil. In 1990, Brazil introduced the Child and Adolescent Act (ECA), a significant piece of legislation that has had a direct impact on how…

  5. Calibrated predictions for multivariate competing risks models.

    PubMed

    Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni

    2014-04-01

    Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.

  6. Overview of entry risk predictions

    NASA Astrophysics Data System (ADS)

    Mrozinski, R.; Mendeck, G.; Cutri-Kohart, R.

    Risk to people on the ground from uncontrolled entries of spacecraft is a primary concern when analyzing end-of-life disposal options for satellites. Countries must balance this risk with the need to mitigate an exponentially growing space debris population. Currently the United States does this via guidelines that call for a satellite to be disposed of in a controlled manner if an uncontrolled entry would be too risky to people on the ground. This risk is measured by a quantity called "casualty expectation", or E , where casualty expectation is defined as the expectedc number of people suffering death or injury due to a spacecraft entry event. If Ec exceeds 1 in 10,000, U. S. guidelines state that the entry should be controlled rather than uncontrolled. Since this guideline can have serious impacts on the cost, lifetime, and even the mission and functionality of a satellite, it is critical that this quantity be estimated well, and decision makers understand all assumptions and limitations inherent in the resulting value. This paper discusses several issues regarding estimates of casualty expectation, beginning with an overview of relevant United States policies and guidelines. The equation the space industry typically uses to estimate casualty expectation is presented, along with a look at the sensitivity of the results to the typical assumptions, models, and initial condition uncertainties. Differences in these modeling issues with respect to launch failure Ec estimates are included in the discussion. An alternate quantity to assess risks due to spacecraft entries is introduced. "Probability of casualty", or Pc , is defined as the probability of one or more instances of people suffering death or injury due to a spacecraft entry event. The equation to estimate Pc is derived, where the same assumptions, modeling, and initial condition issues for Ec apply. Several examples are then given of both Ec and Pc estimate calculations. Due to the difficult issues in

  7. Risk terrain modeling predicts child maltreatment.

    PubMed

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.

  8. Gastrointestinal parasites of cats in Brazil: frequency and zoonotic risk.

    PubMed

    Monteiro, Maria Fernanda Melo; Ramos, Rafael Antonio Nascimento; Calado, Andréa Maria Campos; Lima, Victor Fernando Santana; Ramos, Ingrid Carla do Nascimento; Tenório, Rodrigo Ferreira Lima; Faustino, Maria Aparecida da Glória; Alves, Leucio Câmara

    2016-04-12

    Gastrointestinal helminths are considered to be the most common parasites affecting cats worldwide. Correct diagnosis of these parasites in animals living in urban areas is pivotal, especially considering the zoonotic potential of some species (e.g. Ancylostoma sp. and Toxocara sp.). In this study, a copromicroscopic survey was conducted using fecal samples (n = 173) from domestic cats living in the northeastern region of Brazil. Samples were examined through the FLOTAC technique and the overall results showed positivity of 65.31% (113/173) among the samples analyzed. Coinfections were observed in 46.01% (52/113) of the positive samples. The most common parasites detected were Ancylostoma sp., Toxocara cati, Strongyloides stercoralis, Trichuris sp., Dipylidium caninum and Cystoisospora sp. From an epidemiological point of view, these findings are important, especially considering that zoonotic parasites (e.g. Ancylostoma sp. and Toxocara sp.) were the nematodes most frequently diagnosed in this study. Therefore, the human population living in close contact with cats is at risk of infection caused by the zoonotic helminths of these animals. In addition, for the first time the FLOTAC has been used to diagnosing gastrointestinal parasites of cats in Brazil.

  9. Risk analysis for occurrences of schistosomiasis in the coastal area of Porto de Galinhas, Pernambuco, Brazil

    PubMed Central

    2014-01-01

    Background Manson’s schistosomiasis continues to be a severe public health problem in Brazil, where thousands of people live under the risk of contracting this parasitosis. In the Northeast of Brazil, schistosomiasis has expanded from rural areas to the coast of Pernambuco State, where the intermediate host is Biomphalaria glabrata snails. This study aims at presenting situational analyses on schistosomiasis at the coastal locality of Porto de Galinhas, Pernambuco, Brazil, by determining the risk factors relating to its occurrence from the epidemiological and spatial perspectives. Methods In order to gather prevalence data, a parasitological census surveys were conducted in 2010 in the light of the Kato-Katz technique. Furthermore, malacological surveys were also conducted in the same years so as to define the density and infection rates of the intermediate host. Lastly, socioeconomic-behavioral survey was also conducted to determine the odds ratio for infection by Schistosoma mansoni. Based on these data, spatial analyses were done, resulting in maps of the risk of disease transmission. To predict the risk of schistosomiasis occurrence, a multivariate logistic regression was performed using R 2.13 software. Results Based on prevalence, malacological and socioeconomic-behavioural surveys, it was identified a prevalence of 15.7% in the investigated population (2,757 individuals). Due to the malacological survey, 36 breeding sites were identified, of which 11 were classified as foci of schistosomiasis transmission since they pointed out snails which were infected by Schistosoma mansoni. Overall, 11,012 snails (Biomphalaria glabrata) were collected. The multivariate regression model identified six explanatory variables of environmental, socioeconomic and demographic nature. Spatial sweep analysis by means of the Bernoulli method identified one statistically significant cluster in Salinas (RR = 2.2; p-value < 0.000), the district with the highest occurrence

  10. Landscape, Environmental and Social Predictors of Hantavirus Risk in São Paulo, Brazil

    PubMed Central

    Uriarte, Maria; Tambosi, Leandro Reverberi; Prado, Amanda; Pardini, Renata; D´Andrea, Paulo Sérgio; Metzger, Jean Paul

    2016-01-01

    Hantavirus Pulmonary Syndrome (HPS) is a disease caused by Hantavirus, which are negative-sense RNA viruses in the family Bunyaviridae that are highly virulent to humans. Numerous factors modify risk of Hantavirus transmission and consequent HPS risk. Human-driven landscape change can foster transmission risk by increasing numbers of habitat generalist rodent species that serve as the principal reservoir host. Climate can also affect rodent population dynamics and Hantavirus survival, and a number of social factors can influence probability of HPS transmission to humans. Evaluating contributions of these factors to HPS risk may enable predictions of future outbreaks, and is critical to development of effective public health strategies. Here we rely on a Bayesian model to quantify associations between annual HPS incidence across the state of São Paulo, Brazil (1993–2012) and climate variables (annual precipitation, annual mean temperature), landscape structure metrics (proportion of native habitat cover, number of forest fragments, proportion of area planted with sugarcane), and social factors (number of men older than 14 years and Human Development Index). We built separate models for the main two biomes of the state (cerrado and Atlantic forest). In both biomes Hantavirus risk increased with proportion of land cultivated for sugarcane and HDI, but proportion of forest cover, annual mean temperature, and population at risk also showed positive relationships in the Atlantic forest. Our analysis provides the first evidence that social, landscape, and climate factors are associated with HPS incidence in the Neotropics. Our risk map can be used to support the adoption of preventive measures and optimize the allocation of resources to avoid disease propagation, especially in municipalities that show medium to high HPS risk (> 5% of risk), and aimed at sugarcane workers, minimizing the risk of future HPS outbreaks. PMID:27780250

  11. A Comprehensive Quantitative Assessment of Bird Extinction Risk in Brazil

    PubMed Central

    Machado, Nathália; Loyola, Rafael Dias

    2013-01-01

    In an effort to avoid species loss, scientists have focused their efforts on the mechanisms making some species more prone to extinction than others. However, species show different responses to threats given their evolutionary history, behavior, and intrinsic biological features. We used bird biological features and external threats to (1) understand the multiple pathways driving Brazilian bird species to extinction, (2) to investigate if and how extinction risk is geographically structured, and (3) to quantify how much diversity is currently represented inside protected areas. We modeled the extinction risk of 1557 birds using classification trees and evaluated the relative contribution of each biological feature and external threat in predicting extinction risk. We also quantified the proportion of species and their geographic range currently protected by the network of Brazilian protected areas. The optimal classification tree showed different pathways to bird extinction. Habitat conversion was the most important predictor driving extinction risk though other variables, such as geographic range size, type of habitat, hunting or trapping and trophic guild, were also relevant in our models. Species under higher extinction risk were concentrated mainly in the Cerrado Biodiversity Hotspot and were not quite represented inside protected areas, neither in richness nor range. Predictive models could assist conservation actions, and this study could contribute by highlighting the importance of natural history and ecology in these actions. PMID:23951302

  12. A comprehensive quantitative assessment of bird extinction risk in Brazil.

    PubMed

    Machado, Nathália; Loyola, Rafael Dias

    2013-01-01

    In an effort to avoid species loss, scientists have focused their efforts on the mechanisms making some species more prone to extinction than others. However, species show different responses to threats given their evolutionary history, behavior, and intrinsic biological features. We used bird biological features and external threats to (1) understand the multiple pathways driving Brazilian bird species to extinction, (2) to investigate if and how extinction risk is geographically structured, and (3) to quantify how much diversity is currently represented inside protected areas. We modeled the extinction risk of 1557 birds using classification trees and evaluated the relative contribution of each biological feature and external threat in predicting extinction risk. We also quantified the proportion of species and their geographic range currently protected by the network of Brazilian protected areas. The optimal classification tree showed different pathways to bird extinction. Habitat conversion was the most important predictor driving extinction risk though other variables, such as geographic range size, type of habitat, hunting or trapping and trophic guild, were also relevant in our models. Species under higher extinction risk were concentrated mainly in the Cerrado Biodiversity Hotspot and were not quite represented inside protected areas, neither in richness nor range. Predictive models could assist conservation actions, and this study could contribute by highlighting the importance of natural history and ecology in these actions.

  13. Trends and predictions for gastric cancer mortality in Brazil

    PubMed Central

    de Souza Giusti, Angela Carolina Brandão; de Oliveira Salvador, Pétala Tuani Candido; dos Santos, Juliano; Meira, Karina Cardoso; Camacho, Amanda Rodrigues; Guimarães, Raphael Mendonça; Souza, Dyego L B

    2016-01-01

    AIM: To analyze the effect of age-period and birth cohort on gastric cancer mortality, in Brazil and across its five geographic regions, by sex, in the population over 20 years of age, as well as make projections for the period 2010-2029. METHODS: An ecological study is presented herein, which distributed gastric cancer-related deaths in Brazil and its geographic regions. The effects of age-period and birth cohort were calculated by the Poisson regression model and projections were made with the age-period-cohort model in the statistical program R. RESULTS: Progressive reduction of mortality rates was observed in the 1980’s, and then higher and lower mortality rates were verified in the 2000’s, for both sexes, in Brazil and for the South, Southeast and Midwest regions. A progressive decrease in mortality rates was observed for the Northeast (both sexes) and North (men only) regions within the period 1995-1999, followed by rising rates. CONCLUSION: Regional differences were demonstrated in the mortality rates for gastric cancer in Brazil, and the least developed regions of the country will present increases in projected mortality rates. PMID:27605887

  14. Exploring Dynamic Risk Prediction for Dialysis Patients

    PubMed Central

    Ganssauge, Malte; Padman, Rema; Teredesai, Pradip; Karambelkar, Ameet

    2016-01-01

    Despite substantial advances in the treatment of end-stage renal disease, mortality of hemodialysis patients remains high. Several models exist that predict mortality for this population and identify patients at risk. However, they mostly focus on patients at a particular stage of dialysis treatment, such as start of dialysis, and only use the most recent patient data. Generalization of such models for predictions in later periods can be challenging since disease characteristics change over time and the evolution of biomarkers is not adequately incorporated. In this research, we explore dynamic methods which allow updates of initial predictions when patients progress in time and new data is observed. We compare a Dynamic Bayesian Network (DBN) to regularized logistic regression models and a Cox model with landmarking. Our preliminary results indicate that the DBN achieves satisfactory performance for short term prediction horizons, but needs further refinement and parameter tuning for longer horizons. PMID:28269937

  15. Two criteria for evaluating risk prediction models.

    PubMed

    Pfeiffer, R M; Gail, M H

    2011-09-01

    We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.

  16. Risk of Dengue for Tourists and Teams during the World Cup 2014 in Brazil

    PubMed Central

    van Panhuis, Willem G.; Hyun, Sangwon; Blaney, Kayleigh; Marques, Ernesto T. A.; Coelho, Giovanini E.; Siqueira, João Bosco; Tibshirani, Ryan; da Silva, Jarbas B.; Rosenfeld, Roni

    2014-01-01

    Abstract Background This year, Brazil will host about 600,000 foreign visitors during the 2014 FIFA World Cup. The concern of possible dengue transmission during this event has been raised given the high transmission rates reported in the past by this country. Methodology/Principal Findings We used dengue incidence rates reported by each host city during previous years (2001–2013) to estimate the risk of dengue during the World Cup for tourists and teams. Two statistical models were used: a percentile rank (PR) and an Empirical Bayes (EB) model. Expected IR's during the games were generally low (<10/100,000) but predictions varied across locations and between models. Based on current ticket allocations, the mean number of expected symptomatic dengue cases ranged from 26 (PR, 10th–100th percentile: 5–334 cases) to 59 (EB, 95% credible interval: 30–77 cases) among foreign tourists but none are expected among teams. These numbers will highly depend on actual travel schedules and dengue immunity among visitors. Sensitivity analysis for both models indicated that the expected number of cases could be as low as 4 or 5 with 100,000 visitors and as high as 38 or 70 with 800,000 visitors (PR and EB, respectively). Conclusion/Significance The risk of dengue among tourists during the World Cup is expected to be small due to immunity among the Brazil host population provided by last year's epidemic with the same DENV serotypes. Quantitative risk estimates by different groups and methodologies should be made routinely for mass gathering events. PMID:25079960

  17. Global Potential Distribution of Bactrocera carambolae and the Risks for Fruit Production in Brazil.

    PubMed

    Marchioro, Cesar A

    2016-01-01

    The carambola fruit fly, Bactrocera carambolae, is a tephritid native to Asia that has invaded South America through small-scale trade of fruits from Indonesia. The economic losses associated with biological invasions of other fruit flies around the world and the polyphagous behaviour of B. carambolae have prompted much concern among government agencies and farmers with the potential spread of this pest. Here, ecological niche models were employed to identify suitable environments available to B. carambolae in a global scale and assess the extent of the fruit acreage that may be at risk of attack in Brazil. Overall, 30 MaxEnt models built with different combinations of environmental predictors and settings were evaluated for predicting the potential distribution of the carambola fruit fly. The best model was selected based on threshold-independent and threshold-dependent metrics. Climatically suitable areas were identified in tropical and subtropical regions of Central and South America, Sub-Saharan Africa, west and east coast of India and northern Australia. The suitability map of B. carambola was intersected against maps of fruit acreage in Brazil. The acreage under potential risk of attack varied widely among fruit species, which is expected because the production areas are concentrated in different regions of the country. The production of cashew is the one that is at higher risk, with almost 90% of its acreage within the suitable range of B. carambolae, followed by papaya (78%), tangerine (51%), guava (38%), lemon (30%), orange (29%), mango (24%) and avocado (20%). This study provides an important contribution to the knowledge of the ecology of B. carambolae, and the information generated here can be used by government agencies as a decision-making tool to prevent the carambola fruit fly spread across the world.

  18. Global Potential Distribution of Bactrocera carambolae and the Risks for Fruit Production in Brazil

    PubMed Central

    Marchioro, Cesar A.

    2016-01-01

    The carambola fruit fly, Bactrocera carambolae, is a tephritid native to Asia that has invaded South America through small-scale trade of fruits from Indonesia. The economic losses associated with biological invasions of other fruit flies around the world and the polyphagous behaviour of B. carambolae have prompted much concern among government agencies and farmers with the potential spread of this pest. Here, ecological niche models were employed to identify suitable environments available to B. carambolae in a global scale and assess the extent of the fruit acreage that may be at risk of attack in Brazil. Overall, 30 MaxEnt models built with different combinations of environmental predictors and settings were evaluated for predicting the potential distribution of the carambola fruit fly. The best model was selected based on threshold-independent and threshold-dependent metrics. Climatically suitable areas were identified in tropical and subtropical regions of Central and South America, Sub-Saharan Africa, west and east coast of India and northern Australia. The suitability map of B. carambola was intersected against maps of fruit acreage in Brazil. The acreage under potential risk of attack varied widely among fruit species, which is expected because the production areas are concentrated in different regions of the country. The production of cashew is the one that is at higher risk, with almost 90% of its acreage within the suitable range of B. carambolae, followed by papaya (78%), tangerine (51%), guava (38%), lemon (30%), orange (29%), mango (24%) and avocado (20%). This study provides an important contribution to the knowledge of the ecology of B. carambolae, and the information generated here can be used by government agencies as a decision-making tool to prevent the carambola fruit fly spread across the world. PMID:27832144

  19. Mortality Risk After Cardiac Surgery: Application of Inscor in a University Hospital in Brazil's Northeast

    PubMed Central

    Fortes, João Vyctor Silva; Silva, Mayara Gabrielle Barbosa e; Baldez, Thiago Eduardo Pereira; Costa, Marina de Albuquerque Gonçalves; da Silva, Luan Nascimento; Pinheiro, Renata Silva; Fecks, Zullma Sampaio; Borges, Daniel Lago

    2016-01-01

    Objective To apply the InsCor in patients undergoing cardiac surgery in a university hospital in Brazil's northeast. Methods It is a retrospective, quantitative and analytical study, carried out at the University Hospital of the Federal University of Maranhão. InsCor is a remodeling of two risk score models. It evaluates the prediction of mortality through variables such as gender, age, type of surgery or reoperation, exams, and preoperative events. Data from January to December 2015 were collected, using a Physical Therapy Evaluation Form and medical records. Quantitative variables were expressed as mean and standard deviation and qualitative variables as absolute and relative frequencies. Fisher's exact and Kruskal-Wallis tests were applied, considering significant differences when P value was < 0.05. Calibration was performed by Hosmer-Lemeshow test. Results One hundred and forty-eight patients were included. Thirty-six percent were female, with mean age of 54.7±15.8 years and mean body mass index (BMI) equal to 25.6 kg/m2. The most frequent surgery was coronary artery bypass grafting (51.3%). According to InsCor, 73.6% of the patients had low risk, 20.3% medium risk, and only 6.1% high risk. In this sample, 11 (7.4%) patients died. The percentage of death in patients classified as low, medium and high risk was 6.3, 7.1% and 11.1%, respectively. Conclusion InsCor presented easy applicability due to the reduced number of variables analyzed and it showed satisfactory prediction of mortality in this sample of cardiac surgery patients. PMID:27982349

  20. Crime and violence in Brazil: Systematic review of time trends, prevalence rates and risk factors☆

    PubMed Central

    Murray, Joseph; Cerqueira, Daniel Ricardo de Castro; Kahn, Tulio

    2013-01-01

    Between 1980 and 2010 there were 1 million homicides in Brazil. Dramatic increases in homicide rates followed rises in inequality, more young men in the population, greater availability of firearms, and increased drug use. Nevertheless, disarmament legislation may have helped reduce homicide rates in recent years. Despite its very high rate of lethal violence, Brazil appears to have similar levels of general criminal victimization as several other Latin American and North American countries. Brazil has lower rates of drug use compared to other countries such as the United States, but the prevalence of youth drug use in Brazil has increased substantially in recent years. Since 1990, the growth of the Brazilian prison population has been enormous, resulting in the fourth largest prison population in the world. Through a systematic review of the literature, we identified 10 studies assessing the prevalence of self-reported offending in Brazil and 9 studies examining risk factors. Levels of self-reported offending seem quite high among school students in Brazil. Individual and family-level risk factors identified in Brazil are very similar to those found in high-income countries. PMID:24027422

  1. Crime and violence in Brazil: Systematic review of time trends, prevalence rates and risk factors.

    PubMed

    Murray, Joseph; Cerqueira, Daniel Ricardo de Castro; Kahn, Tulio

    2013-09-01

    Between 1980 and 2010 there were 1 million homicides in Brazil. Dramatic increases in homicide rates followed rises in inequality, more young men in the population, greater availability of firearms, and increased drug use. Nevertheless, disarmament legislation may have helped reduce homicide rates in recent years. Despite its very high rate of lethal violence, Brazil appears to have similar levels of general criminal victimization as several other Latin American and North American countries. Brazil has lower rates of drug use compared to other countries such as the United States, but the prevalence of youth drug use in Brazil has increased substantially in recent years. Since 1990, the growth of the Brazilian prison population has been enormous, resulting in the fourth largest prison population in the world. Through a systematic review of the literature, we identified 10 studies assessing the prevalence of self-reported offending in Brazil and 9 studies examining risk factors. Levels of self-reported offending seem quite high among school students in Brazil. Individual and family-level risk factors identified in Brazil are very similar to those found in high-income countries.

  2. Evaluation of a Training Program for Street Children and Adolescents At Risk in Brazil.

    ERIC Educational Resources Information Center

    Bandeira, Denise R.; And Others

    An experience in evaluating a program which is designed to help high risk adolescents is described. The program attempts to develop basic work and social skills of adolescents (N=40) living in slums or on the streets in Brazil. Psychological and social effects of the program were assessed by means of interviews and psychological tests…

  3. Brief Report: Young People at Risk for Eating Disorders in Southeast Brazil

    ERIC Educational Resources Information Center

    Moya, Tatiana; Fleitlich-Bilyk, Bacy; Goodman, Robert

    2006-01-01

    A representative sample of 7-14-year-old young people in southeast Brazil (N=1251) was assessed using standardized parent and youth interviews, thereby identifying an "at-risk" group of young people who met one or more DSM-IV criteria for anorexia and/or bulimia nervosa. These young people were compared with an age and gender matched…

  4. Risk factors for death from pandemic (H1N1) 2009, southern Brazil.

    PubMed

    Yokota, Renata T C; Skalinski, Lacita M; Igansi, Cristine N; de Souza, Libia R O; Iser, Betine P M; Reis, Priscilleyne O; Barros, Eliana N C; Macário, Eduardo M; Bercini, Marilina A; Ranieri, Tani M S; Araújo, Wildo N

    2011-08-01

    To identify risk factors for death from pandemic (H1N1) 2009, we obtained data for 157 hospitalized patients with confirmed cases of this disease. Multivariate analysis showed that diabetes and class III obesity were associated with death. These findings helped define priority vaccination groups in Brazil.

  5. Brazil.

    PubMed

    1983-07-01

    Attention in this discussion of Brazil focuses: the history of the country's demographic situation; government's overall approach to population problems; population data systems and development planning; institutional arrangements for the integration of population within development planning; government's view of the importance of population policy in achieving development objectives; population size, growth, and natural increase; fertility; international migration; and spatial distribution. The population of Brazil grew from 17 million in 1900 to about 119 million in 1960, making it the most populous country in the world and 1 of the relatively few countries to have sustained rates of population growth of more than 2% for over a century. The government has not adopted an explicit policy to modify fertility or population growth. Initially this was because of its positive perception of the benefits of population growth and a large population size and, amore recently, because of Brazil's gradual transition to more moderate levels of fertility and population growth. Brazil's main sources of demographic data are its 9 censuses, conducted in 1982, 1890, 1900, 1920, 1940, 1950, 1960, 1970, and most recently in August 1980. A nationwide system of vital registration data are still lacking in many geographic areas, researchers have had to rely on indirect estimation techniques to derive estimates of past trends in fertility and mortality. Population policy has been regarded as a highly sensitive issue by Brazilian officials, and the government remains cautious in regard to population issues. Preliminary results of Brazil's 1980 census indicate a population of 119 million and an annual rate of population growth of 2.1%, continuing the downward trend that was first evident in 1976. The government considers levels and trends of population growth to be satisfactory, and morbidity and mortality to be unacceptable, partly because of a lack of success in reducing the incidence of

  6. Mitochondrial DNA haplotype predicts deafness risk

    SciTech Connect

    Hutchin, T.; Cortopassi, G.

    1995-12-18

    Since mitochondrial DNA (mtDNA) does not recombine in humans, once deleterious variation arises within a particular mtDNA clone it remains linked to that clonal type. An A to G mutation at mtDNA position 1555 confers matrilineal deafness among Asians and others. Two major mtDNA types (I and II) have been defined in Asians by D-loop sequencing. We have determined the D-loop sequence of 8 unrelated deaf Asians bearing the 1555G mutation, and find that 7 are of type II, whereas only one is of type I. Thus the frequency of the 1555G mutation is higher in type II mtDNA than type I (P = 0.035, binomial test), and persons with type II mtDNA are more likely to become deaf. Type II mtDNAs are rare in the Caucasian population, which may explain the rarity of this form of deafness in the United States. Negative Darwinian selection is expected to rapidly eliminate mtDNAs bearing severely deleterious mutations; but mildly deleterious mutations whose phenotype is expressed after reproduction should persist on the mtDNA background in which they arose. Thus determination of mtDNA clonal type has the potential to predict human risk for diseases that are the result of mildly deleterious mtDNA mutations which confer a post-reproductive phenotype. 4 refs., 1 fig.

  7. Brain Scan Test Predicts Fall Risk in Elderly

    MedlinePlus

    ... page: https://medlineplus.gov/news/fullstory_162417.html Brain Scan Test Predicts Fall Risk in Elderly Such ... research suggests that measurements of healthy older adults' brain activity may help determine their future risk. "Our ...

  8. Elderly fall risk prediction using static posturography

    PubMed Central

    2017-01-01

    Maintaining and controlling postural balance is important for activities of daily living, with poor postural balance being predictive of future falls. This study investigated eyes open and eyes closed standing posturography with elderly adults to identify differences and determine appropriate outcome measure cut-off scores for prospective faller, single-faller, multi-faller, and non-faller classifications. 100 older adults (75.5 ± 6.7 years) stood quietly with eyes open and then eyes closed while Wii Balance Board data were collected. Range in anterior-posterior (AP) and medial-lateral (ML) center of pressure (CoP) motion; AP and ML CoP root mean square distance from mean (RMS); and AP, ML, and vector sum magnitude (VSM) CoP velocity were calculated. Romberg Quotients (RQ) were calculated for all parameters. Participants reported six-month fall history and six-month post-assessment fall occurrence. Groups were retrospective fallers (24), prospective all fallers (42), prospective fallers (22 single, 6 multiple), and prospective non-fallers (47). Non-faller RQ AP range and RQ AP RMS differed from prospective all fallers, fallers, and single fallers. Non-faller eyes closed AP velocity, eyes closed VSM velocity, RQ AP velocity, and RQ VSM velocity differed from multi-fallers. RQ calculations were particularly relevant for elderly fall risk assessments. Cut-off scores from Clinical Cut-off Score, ROC curves, and discriminant functions were clinically viable for multi-faller classification and provided better accuracy than single-faller classification. RQ AP range with cut-off score 1.64 could be used to screen for older people who may fall once. Prospective multi-faller classification with a discriminant function (-1.481 + 0.146 x Eyes Closed AP Velocity—0.114 x Eyes Closed Vector Sum Magnitude Velocity—2.027 x RQ AP Velocity + 2.877 x RQ Vector Sum Magnitude Velocity) and cut-off score 0.541 achieved an accuracy of 84.9% and is viable as a screening tool for older

  9. Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil.

    PubMed

    Massad, Eduardo; Wilder-Smith, Annelies; Ximenes, Raphael; Amaku, Marcos; Lopez, Luis Fernandez; Coutinho, Francisco Antonio Bezerra; Coelho, Giovanini Evelim; Silva, Jarbas Barbosa da; Struchiner, Claudio José; Burattini, Marcelo Nascimento

    2014-06-01

    Brazil will host the FIFA World Cup™, the biggest single-event competition in the world, from June 12-July 13 2014 in 12 cities. This event will draw an estimated 600,000 international visitors. Brazil is endemic for dengue. Hence, attendees of the 2014 event are theoretically at risk for dengue. We calculated the risk of dengue acquisition to non-immune international travellers to Brazil, depending on the football match schedules, considering locations and dates of such matches for June and July 2014. We estimated the average per-capita risk and expected number of dengue cases for each host-city and each game schedule chosen based on reported dengue cases to the Brazilian Ministry of Health for the period between 2010-2013. On the average, the expected number of cases among the 600,000 foreigner tourists during the World Cup is 33, varying from 3-59. Such risk estimates will not only benefit individual travellers for adequate pre-travel preparations, but also provide valuable information for public health professionals and policy makers worldwide. Furthermore, estimates of dengue cases in international travellers during the World Cup can help to anticipate the theoretical risk for exportation of dengue into currently non-infected areas.

  10. Risk of microcephaly after Zika virus infection in Brazil, 2015 to 2016

    PubMed Central

    Rosenberger, Kerstin Daniela; Brito, Carlos; Brady, Oliver; Brasil, Patrícia; Marques, Ernesto TA

    2017-01-01

    Abstract Objective To estimate the risk of microcephaly in babies born to women infected by the Zika virus during pregnancy in Brazil in an epidemic between 2015 and 2016. Methods We obtained data on the number of notified and confirmed microcephaly cases in each Brazilian state between November 2015 and October 2016 from the health ministry. For Pernambuco State, one of the hardest hit, weekly data were available from August 2015 to October 2016 for different definitions of microcephaly. The absolute risk of microcephaly was calculated using the average number of live births reported in each state in the corresponding time period between 2012 and 2014 and assuming two infection rates: 10% and 50%. The relative risk was estimated using the reported background frequency of microcephaly in Brazil of 1.98 per 10 000 live births. Findings The estimated absolute risk of a notified microcephaly case varied from 0.03 to 17.1% according to geographical area, the definition of microcephaly used and the infection rate. Assuming a 50% infection rate, there was an 18–127 fold higher probability of microcephaly in children born to mothers with infection during pregnancy compared with children born to mothers without infection during pregnancy in Pernambuco State. For a 10% infection rate, the probability was 88–635 folds higher. Conclusion A large variation in the estimated risk of microcephaly was found in Brazil. Research is needed into possible effect modifiers, reliable measures of Zika virus infection and clear endpoints for congenital malformations. PMID:28250532

  11. Risk of symptomatic dengue for foreign visitors to the 2014 FIFA World Cup in Brazil

    PubMed Central

    Massad, Eduardo; Wilder-Smith, Annelies; Ximenes, Raphael; Amaku, Marcos; Lopez, Luis Fernandez; Coutinho, Francisco Antonio Bezerra; Coelho, Giovanini Evelim; da Silva, Jarbas Barbosa; Struchiner, Claudio José; Burattini, Marcelo Nascimento

    2014-01-01

    Brazil will host the FIFA World Cup™, the biggest single-event competition in the world, from June 12-July 13 2014 in 12 cities. This event will draw an estimated 600,000 international visitors. Brazil is endemic for dengue. Hence, attendees of the 2014 event are theoretically at risk for dengue. We calculated the risk of dengue acquisition to non-immune international travellers to Brazil, depending on the football match schedules, considering locations and dates of such matches for June and July 2014. We estimated the average per-capita risk and expected number of dengue cases for each host-city and each game schedule chosen based on reported dengue cases to the Brazilian Ministry of Health for the period between 2010-2013. On the average, the expected number of cases among the 600,000 foreigner tourists during the World Cup is 33, varying from 3-59. Such risk estimates will not only benefit individual travellers for adequate pre-travel preparations, but also provide valuable information for public health professionals and policy makers worldwide. Furthermore, estimates of dengue cases in international travellers during the World Cup can help to anticipate the theoretical risk for exportation of dengue into currently non-infected areas. PMID:24863976

  12. Determination of aflatoxin risk components for in-shell Brazil nuts.

    PubMed

    Vargas, E A; dos Santos, E A; Whitaker, T B; Slate, A B

    2011-09-01

    A study was conducted on the risk from aflatoxins associated with the kernels and shells of Brazil nuts. Samples were collected from processing plants in Amazonia, Brazil. A total of 54 test samples (40 kg) were taken from 13 in-shell Brazil nut lots ready for market. Each in-shell sample was shelled and the kernels and shells were sorted in five fractions: good kernels, rotten kernels, good shells with kernel residue, good shells without kernel residue, and rotten shells, and analysed for aflatoxins. The kernel:shell ratio mass (w/w) was 50.2/49.8%. The Brazil nut shell was found to be contaminated with aflatoxin. Rotten nuts were found to be a high-risk fraction for aflatoxin in in-shell Brazil nut lots. Rotten nuts contributed only 4.2% of the sample mass (kg), but contributed 76.6% of the total aflatoxin mass (µg) in the in-shell test sample. The highest correlations were found between the aflatoxin concentration in in-shell Brazil nuts samples and the aflatoxin concentration in all defective fractions (R(2)=0.97). The aflatoxin mass of all defective fractions (R(2)=0.90) as well as that of the rotten nut (R(2)=0.88) were also strongly correlated with the aflatoxin concentration of the in-shell test samples. Process factors of 0.17, 0.16 and 0.24 were respectively calculated to estimate the aflatoxin concentration in the good kernels (edible) and good nuts by measuring the aflatoxin concentration in the in-shell test sample and in all kernels, respectively.

  13. Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity.

    PubMed

    Ng, Kenney; Sun, Jimeng; Hu, Jianying; Wang, Fei

    2015-01-01

    Personalized predictive models are customized for an individual patient and trained using information from similar patients. Compared to global models trained on all patients, they have the potential to produce more accurate risk scores and capture more relevant risk factors for individual patients. This paper presents an approach for building personalized predictive models and generating personalized risk factor profiles. A locally supervised metric learning (LSML) similarity measure is trained for diabetes onset and used to find clinically similar patients. Personalized risk profiles are created by analyzing the parameters of the trained personalized logistic regression models. A 15,000 patient data set, derived from electronic health records, is used to evaluate the approach. The predictive results show that the personalized models can outperform the global model. Cluster analysis of the risk profiles show groups of patients with similar risk factors, differences in the top risk factors for different groups of patients and differences between the individual and global risk factors.

  14. CSF 5-HIAA Predicts Suicide Risk after Attempted Suicide.

    ERIC Educational Resources Information Center

    Nordstrom, Peter; And Others

    1994-01-01

    Studied suicide risk after attempted suicide, as predicted by cerebrospinal fluid (CSF) monoamine metabolite concentrations, in 92 psychiatric mood disorder inpatients admitted shortly after attempting suicide. Results revealed that low CSF 5-hydroxyindoleacetic acid (5-HIAA) predicted short-range suicide risk after attempted suicide in mood…

  15. A Risk Score for Predicting Multiple Sclerosis

    PubMed Central

    Dobson, Ruth; Ramagopalan, Sreeram; Topping, Joanne; Smith, Paul; Solanky, Bhavana; Schmierer, Klaus; Chard, Declan; Giovannoni, Gavin

    2016-01-01

    Objective Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI. Methods 78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals. Results There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88). Interpretations The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies. PMID:27802296

  16. Substance use and sexual risk among at-risk adolescents in Juiz de Fora, Minas Gerais State, Brazil.

    PubMed

    Morrison, Penelope; Smith, Amy Erica; Akers, Aletha

    2014-04-01

    We examined the difference in prevalence of substance use and sexual risk behaviors among at-risk youth participants in programs offered by community-based organizations in Juiz de Fora, Minas Gerais State, Brazil, by gender and organization type (governmental vs. non-governmental). 388 adolescents were recruited from 25 intervention-based organizations servicing at-risk youth between the ages of 12 and 17 in Juiz de Fora. Participants completed a 15-item survey assessing substance use and sexual risk behaviors, along with socio-demographic predictors of these behaviors. Males were more likely to report drug and alcohol use associated with homelessness and abandonment. Females were more likely to report sexual risk taking associated with neighborhood crime. Participants from non-governmental organizations were less likely to engage in all measured risk behaviors. The present analysis points to the need to understand how Brazil's Child and Adolescent Act is being applied and the implications this has for intervention and the promotion of positive health outcomes for young people.

  17. Rural tourism: a risk factor for schistosomiasis transmission in Brazil.

    PubMed

    Enk, Martin Johannes; Amaral, Graciela Larissa; Costa e Silva, Matheus Fernandes; Silveira-Lemos, Denise; Teixeira-Carvalho, Andréa; Martins-Filho, Olindo Assis; Correa-Oliveira, Rodrigo; Gazinnelli, Giovanni; Coelho, Paulo Marcos Zech; Massara, Cristiano Lara

    2010-07-01

    This paper reports an outbreak of acute schistosomiasis among 38 tourists who rented a country house in the district of Igarapé, the metropolitan region of Belo Horizonte, Brazil, during a holiday period in 2006. A total number of 32 individuals were positive for Schistosoma mansoni. Results of stool examinations revealed individual S. mansoni egg counts per gram of faeces (epg) ranging from 4-768 epg with a geometric mean egg count of 45. The most frequent clinical symptoms were abdominal pain (78.1%), headache (75%), fever (65.6%), dry cough (65.2%) and both diarrhoea and asthenia (59.4%). A malacological survey of the area, where 22 specimens of Biomphalaria glabrata were collected, revealed three (13.6%) specimens eliminating Schistosoma cercariae. This investigation re-confirms a recently described pattern of schistosomiasis infection, resulting in the acute form of the disease and connected to rural tourism, which contributes to the spread of the disease among the middle-class and into non-endemic areas. The lack of specific knowledge about acute schistosomiasis among health services causes an increased number of unnecessary diagnostic procedures and delays in accurate diagnosis and treatment, resulting in considerable discomfort for the patients.

  18. Municipal temperature and heatwave predictions as a tool for integrated socio-environmental impact analysis in Brazil

    NASA Astrophysics Data System (ADS)

    Costa, D.

    2015-12-01

    Numerical climate models render data in a gridded format which is often problematic for integrated analysis with other kinds of data in jurisdictional formats. In this paper a joint analysis of municipal Gross Domestic Product per capita (GDPc) and predicted temperature increase was undertaken in order to estimate different levels of human and economic exposure. This is based on a method of converting model outputs into a country municipal grid which enabled depicting climate predictions from the Eta-Hadgem2-ES Regional Climate Model (RCM) into the municipal level in Brazil. The conversion to country municipality grid was made using a combination of interpolation and buffering techniques in ArcGIS for two emission scenarios (RCP 4.5 and 8.5) and three timeframes (2011-2040, 2041-2070, 2071-2100) for mean temperature increase and number of heatwave days (WSDI). The results were used to support the Third National Communication (TCN) of Brazil to the United Nations Framework Convention on Climate Change (UNFCCC) and show a coherent matching of the gridded output from the original RCM. The joint climate and GDPc analysis show that in the beginning of the century the more severe warming is centred over regions where GDPc is generally higher (Centre-West and Southeast). At the end of the century, critical levels of warming spread north and northeastwards where municipalities have the lowest GDPc levels. In the high emission scenario (RCP 8.5) the strongest warming and the spreading over poorer regions is anticipated to the mid-century. These results are key to further explore solutions for climate change adaptation based on current resources and prepare in different sectors, for long-term risk management and climate adaptation planning strategies.

  19. Using open source data for flood risk mapping and management in Brazil

    NASA Astrophysics Data System (ADS)

    Whitley, Alison; Malloy, James; Chirouze, Manuel

    2013-04-01

    Whitley, A., Malloy, J. and Chirouze, M. Worldwide the frequency and severity of major natural disasters, particularly flooding, has increased. Concurrently, countries such as Brazil are experiencing rapid socio-economic development with growing and increasingly concentrated populations, particularly in urban areas. Hence, it is unsurprising that Brazil has experienced a number of major floods in the past 30 years such as the January 2011 floods which killed 900 people and resulted in significant economic losses of approximately 1 billion US dollars. Understanding, mitigating against and even preventing flood risk is high priority. There is a demand for flood models in many developing economies worldwide for a range of uses including risk management, emergency planning and provision of insurance solutions. However, developing them can be expensive. With an increasing supply of freely-available, open source data, the costs can be significantly reduced, making the tools required for natural hazard risk assessment more accessible. By presenting a flood model developed for eight urban areas of Brazil as part of a collaboration between JBA Risk Management and Guy Carpenter, we explore the value of open source data and demonstrate its usability in a business context within the insurance industry. We begin by detailing the open source data available and compare its suitability to commercially-available equivalents for datasets including digital terrain models and river gauge records. We present flood simulation outputs in order to demonstrate the impact of the choice of dataset on the results obtained and its use in a business context. Via use of the 2D hydraulic model JFlow+, our examples also show how advanced modelling techniques can be used on relatively crude datasets to obtain robust and good quality results. In combination with accessible, standard specification GPU technology and open source data, use of JFlow+ has enabled us to produce large-scale hazard maps

  20. Lipoprotein metabolism indicators improve cardiovascular risk prediction

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Background: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to inves...

  1. Relative Risk of Visceral Leishmaniasis in Brazil: A Spatial Analysis in Urban Area

    PubMed Central

    de Araújo, Valdelaine Etelvina Miranda; Pinheiro, Letícia Cavalari; Almeida, Maria Cristina de Mattos; de Menezes, Fernanda Carvalho; Morais, Maria Helena Franco; Reis, Ilka Afonso; Assunção, Renato Martins; Carneiro, Mariângela

    2013-01-01

    Background Visceral leishmaniasis (VL) is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission. Methodology This is an ecological study on the relative risk of human VL. Spatial units of analysis were the coverage areas of the Basic Health Units (146 small-areas) of Belo Horizonte, Minas Gerais State, Brazil. Human VL cases, from 2007 to 2009 (n = 412), were obtained in the Brazilian Reportable Disease Information System. Bayesian approach was used to model the relative risk of VL including potential risk factors involved in transmission (canine infection, socioeconomic and environmental features) and to identify the small-areas of greater risk to human VL. Principal Findings The relative risk of VL was shown to be correlated with income, education, and the number of infected dogs per inhabitants. The estimates of relative risk of VL were higher than 1.0 in 54% of the areas (79/146). The spatial modeling highlighted 14 areas with the highest relative risk of VL and 12 of them are concentrated in the northern region of the city. Conclusions The spatial analysis used in this study is useful for the identification of small-areas according to risk of human VL and presents operational applicability in control and surveillance program in an urban environment with an unequal spatial distribution of the disease. Thus the frequent monitoring of relative risk of human VL in small-areas is important to direct and prioritize the actions of the control program in urban environment, especially in big cities. PMID:24244776

  2. Lung cancer risk prediction: a tool for early detection.

    PubMed

    Cassidy, Adrian; Duffy, Stephen W; Myles, Jonathan P; Liloglou, Triantafillos; Field, John K

    2007-01-01

    Although 45% of men and 39% of women will be diagnosed with cancer in their lifetime, it is difficult to predict which individuals will be affected. For some cancers, substantial progress in individual risk estimation has already been made. However, relatively few models have been developed to predict lung cancer risk beyond effects of age and smoking. This paper reviews published models for lung cancer risk prediction, discusses their potential contribution to clinical and research settings and suggests improvements to the risk modeling strategy for lung cancer. The sensitivity and specificity of existing cancer risk models is less than optimal. Improvement in individual risk prediction is important for selection of individuals for prevention or early detection interventions. In addition to smoking, factors related to occupational exposure, personal medical history and family history of cancer can add to the predictive power. A good risk prediction model is one that can identify a small fraction of the population in which a large proportion of the disease cases will occur. In the future, genetic and other biological markers are likely to be useful, although they will require rigorous evaluation. Validation is essential to establish the predictive effect and for ongoing monitoring of the model's continued relevance.

  3. Risk Factor Fusion for Predicting Multifactorial Diseases

    DTIC Science & Technology

    2007-11-02

    validity of method is demonstrated by applying it to predict the occur- rence of gout in patients. 1. INTRODUCTION The goal in this paper is to...and parametric classifier design. In order to demonstrate the validity of the approach, the prediction of gout , which is a multifactorial disease...is considered. The goal is to classify a patient into one of two classes: gout or non- gout . The approach for gout classification is summarized in

  4. Predicting the risk of sudden cardiac death.

    PubMed

    Lerma, Claudia; Glass, Leon

    2016-05-01

    Sudden cardiac death (SCD) is the result of a change of cardiac activity from normal (typically sinus) rhythm to a rhythm that does not pump adequate blood to the brain. The most common rhythms leading to SCD are ventricular tachycardia (VT) or ventricular fibrillation (VF). These result from an accelerated ventricular pacemaker or ventricular reentrant waves. Despite significant efforts to develop accurate predictors for the risk of SCD, current methods for risk stratification still need to be improved. In this article we briefly review current approaches to risk stratification. Then we discuss the mathematical basis for dynamical transitions (called bifurcations) that may lead to VT and VF. One mechanism for transition to VT or VF involves a perturbation by a premature ventricular complex (PVC) during sinus rhythm. We describe the main mechanisms of PVCs (reentry, independent pacemakers and abnormal depolarizations). An emerging approach to risk stratification for SCD involves the development of individualized dynamical models of a patient based on measured anatomy and physiology. Careful analysis and modelling of dynamics of ventricular arrhythmia on an individual basis will be essential in order to improve risk stratification for SCD and to lay a foundation for personalized (precision) medicine in cardiology.

  5. Predicting Risk Sensitivity in Humans and Lower Animals: Risk as Variance or Coefficient of Variation

    ERIC Educational Resources Information Center

    Weber, Elke U.; Shafir, Sharoni; Blais, Ann-Renee

    2004-01-01

    This article examines the statistical determinants of risk preference. In a meta-analysis of animal risk preference (foraging birds and insects), the coefficient of variation (CV), a measure of risk per unit of return, predicts choices far better than outcome variance, the risk measure of normative models. In a meta-analysis of human risk…

  6. Updating Risk Prediction Tools: A Case Study in Prostate Cancer

    PubMed Central

    Ankerst, Donna P.; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J.; Feng, Ziding; Sanda, Martin G.; Partin, Alan W.; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M.

    2013-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [−2]proPSA measured on an external case control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. PMID:22095849

  7. Submission Form for Peer-Reviewed Cancer Risk Prediction Models

    Cancer.gov

    If you have information about a peer-reviewd cancer risk prediction model that you would like to be considered for inclusion on this list, submit as much information as possible through the form on this page.

  8. Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis.

    PubMed

    Nieto, Prixia; Malone, John B; Bavia, Maria E

    2006-11-01

    Two predictive models were developed within a geographic information system using Genetic Algorithm Rule-Set Prediction (GARP) and the growing degree day (GDD)-water budget (WB) concept to predict the distribution and potential risk of visceral leishmaniasis (VL) in the State of Bahia, Brazil. The objective was to define the environmental suitability of the disease as well as to obtain a deeper understanding of the eco-epidemiology of VL by associating environmental and climatic variables with disease prevalence. Both the GARP model and the GDDWB model, using different analysis approaches and with the same human prevalence database, predicted similar distribution and abundance patterns for the Lutzomyia longipalpis-Leishmania chagasi system in Bahia. High and moderate prevalence sites for VL were significantly related to areas of high and moderate risk prediction by: (i) the area predicted by the GARP model, depending on the number of pixels that overlapped among eleven annual model years, and (ii) the number of potential generations per year that could be completed by the Lu. longipalpis-L. chagasi system by GDD-WB analysis. When applied to the ecological zones of Bahia, both the GARP and the GDD-WB prediction models suggest that the highest VL risk is in the interior region of the state, characterized by a semi-arid and hot climate known as Caatinga, while the risk in the Bahia interior forest and the Cerrado ecological regions is lower. The Bahia coastal forest was predicted to be a low-risk area due to the unsuitable conditions for the vector and VL transmission.

  9. Detection and risk assessment of diarrheagenic E. coli in recreational beaches of Brazil.

    PubMed

    Rodrigues, Vanessa F V; Rivera, Irma N G; Lim, Keah-Ying; Jiang, Sunny C

    2016-08-15

    Marine beaches are important recreational and economic resources in Brazil, but the beaches' water quality is negatively impacted by the discharge of domestic sewage effluent. The occurrence of diarrheagenic Escherichiacoli among the E. coli isolated from three Brazilian marine beaches was investigated. Multiplex and single step PCR were used to screen 99 E. coli isolates for ten target toxin genes. Six toxin genes, stx1, eae, estp, esth, astA, and bfpA, were identified in 1% to 35% of the isolates. A quantitative microbial risk assessment (QMRA) of human exposure to diarrheagenic E. coli during marine recreation was carried out. The results indicated that the diarrheagenic E. coli risk is well below the U.S. EPA's recommended daily recreational risk benchmark. However, the overall recreational health risk due to all pathogens in the water could be much higher and exceeded the U.S. EPA's benchmark.

  10. HIV risk behaviors among outpatients with severe mental illness in Rio de Janeiro, Brazil

    PubMed Central

    WAINBERG, MILTON L.; MCKINNON, KAREN; ELKINGTON, KATHERINE; MATTOS, PAULO E.; GRUBER MANN, CLAUDIO; DE SOUZA PINTO, DIANA; OTTO-SALAJ, LAURA; COURNOS, FRANCINE; AND THE INVESTIGATORS OF PRISSMA

    2008-01-01

    We conducted the first study to examine rates of sexual activity, sexual risk behaviors, sexual protective behaviors, injection drug use (IDU), needle sharing, and knowledge about HIV/AIDS among outpatients with severe mental illness (SMI) in Rio de Janeiro, Brazil. Using a measure with demonstrated reliability, we found that 42% of 98 patients engaged in vaginal or anal sex within the past three months. Comorbid substance use disorder was significantly associated with sexual activity. Only 22% of sexually active patients used condoms consistently, despite having better HIV knowledge than those who were sexually abstinent. Overall, 45% of patients reported not engaging in any HIV protective behaviors. There were no reports of drug injection. Adults with SMI in Brazil are in need of efficacious HIV prevention programs and policies that can sustain these programs within mental health treatment settings. PMID:18836542

  11. Risk, medicine and women: a case study on prenatal genetic counselling in Brazil.

    PubMed

    Guilam, Maria Cristina R; Corrêa, Marilena C D V

    2007-08-01

    Genetic counselling is an important aspect of prenatal care in many developed countries. This tendency has also begun to emerge in Brazil, although few medical centres offer this service. Genetic counselling provides prenatal risk control through a process of individual decision-making based on medical information, in a context where diagnostic and therapeutic possibilities overlap. Detection of severe foetal anomalies can lead to a decision involving possible termination of pregnancy. This paper focuses on medical and legal consequences of the detection of severe foetal anomalies, mainly anencephaly and Down syndrome, and in light of the fact that abortion is illegal in Brazil. The discussion is based on the literature and empirical research at a high-complexity public hospital in Rio de Janeiro.

  12. Risk avoidance in sympatric large carnivores: reactive or predictive?

    PubMed

    Broekhuis, Femke; Cozzi, Gabriele; Valeix, Marion; McNutt, John W; Macdonald, David W

    2013-09-01

    1. Risks of predation or interference competition are major factors shaping the distribution of species. An animal's response to risk can either be reactive, to an immediate risk, or predictive, based on preceding risk or past experiences. The manner in which animals respond to risk is key in understanding avoidance, and hence coexistence, between interacting species. 2. We investigated whether cheetahs (Acinonyx jubatus), known to be affected by predation and competition by lions (Panthera leo) and spotted hyaenas (Crocuta crocuta), respond reactively or predictively to the risks posed by these larger carnivores. 3. We used simultaneous spatial data from Global Positioning System (GPS) radiocollars deployed on all known social groups of cheetahs, lions and spotted hyaenas within a 2700 km(2) study area on the periphery of the Okavango Delta in northern Botswana. The response to risk of encountering lions and spotted hyaenas was explored on three levels: short-term or immediate risk, calculated as the distance to the nearest (contemporaneous) lion or spotted hyaena, long-term risk, calculated as the likelihood of encountering lions and spotted hyaenas based on their cumulative distributions over a 6-month period and habitat-associated risk, quantified by the habitat used by each of the three species. 4. We showed that space and habitat use by cheetahs was similar to that of lions and, to a lesser extent, spotted hyaenas. However, cheetahs avoided immediate risks by positioning themselves further from lions and spotted hyaenas than predicted by a random distribution. 5. Our results suggest that cheetah spatial distribution is a hierarchical process, first driven by resource acquisition and thereafter fine-tuned by predator avoidance; thus suggesting a reactive, rather than a predictive, response to risk.

  13. Prediction of Psychosis in Youth at High Clinical Risk

    PubMed Central

    Cannon, Tyrone D.; Cadenhead, Kristin; Cornblatt, Barbara; Woods, Scott W.; Addington, Jean; Walker, Elaine; Seidman, Larry J.; Perkins, Diana; Tsuang, Ming; McGlashan, Thomas; Heinssen, Robert

    2011-01-01

    Context Early detection and prospective evaluation of individuals who will develop schizophrenia or other psychotic disorders are critical to efforts to isolate mechanisms underlying psychosis onset and to the testing of preventive interventions, but existing risk prediction approaches have achieved only modest predictive accuracy. Objectives To determine the risk of conversion to psychosis and to evaluate a set of prediction algorithms maximizing positive predictive power in a clinical high-risk sample. Design, Setting, and Participants Longitudinal study with a 2½-year follow-up of 291 prospectively identified treatment-seeking patients meeting Structured Interview for Prodromal Syndromes criteria. The patients were recruited and underwent evaluation across 8 clinical research centers as part of the North American Prodrome Longitudinal Study. Main Outcome Measure Time to conversion to a fully psychotic form of mental illness. Results The risk of conversion to psychosis was 35%, with a decelerating rate of transition during the 2½-year follow-up. Five features assessed at baseline contributed uniquely to the prediction of psychosis: a genetic risk for schizophrenia with recent deterioration in functioning, higher levels of unusual thought content, higher levels of suspicion/paranoia, greater social impairment, and a history of substance abuse. Prediction algorithms combining 2 or 3 of these variables resulted in dramatic increases in positive predictive power (ie, 68%–80%) compared with the prodromal criteria alone. Conclusions These findings demonstrate that prospective ascertainment of individuals at risk for psychosis is feasible, with a level of predictive accuracy comparable to that in other areas of preventive medicine. They provide a benchmark for the rate and shape of the psychosis risk function against which standardized preventive intervention programs can be compared. PMID:18180426

  14. On the estimation of risk associated with an attenuation prediction

    NASA Technical Reports Server (NTRS)

    Crane, R. K.

    1992-01-01

    Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.

  15. Predicting the risk of coral disease outbreak using satellite SST.

    NASA Astrophysics Data System (ADS)

    Heron, S. F.; Willis, B. L.; Skirving, W. J.; Page, C. A.; Eakin, C. M.; Miller, I. R.; Christensen, T. R.; Gledhill, D. K.; Liu, G.; Morgan, J. A.; Parker, B. A.; Strong, A. E.

    2009-05-01

    Several environmental parameters have been linked to outbreaks of coral disease. Here we describe the influence of remotely-sensed summer and winter temperatures, as well as local observations of coral cover, to predict the risk of White Syndrome disease outbreaks on the Great Barrier Reef, Australia. Coral disease is an emerging risk to coral reef ecosystems that is likely to escalate with ocean warming due to climate change. The aim of this work is to provide reef managers with an expert system for predicting disease risk on coral reefs as far as six months in advance of summer outbreaks.

  16. Predicting relapse risk in childhood acute lymphoblastic leukaemia.

    PubMed

    Teachey, David T; Hunger, Stephen P

    2013-09-01

    Intensive multi-agent chemotherapy regimens and the introduction of risk-stratified therapy have substantially improved cure rates for children with acute lymphoblastic leukaemia (ALL). Current risk allocation schemas are imperfect, as some children are classified as lower-risk and treated with less intensive therapy relapse, while others deemed higher-risk are probably over-treated. Most cooperative groups previously used morphological clearance of blasts in blood and marrow during the initial phases of chemotherapy as a primary factor for risk group allocation; however, this has largely been replaced by the detection of minimal residual disease (MRD). Other than age and white blood cell count (WBC) at presentation, many clinical variables previously used for risk group allocation are no longer prognostic, as MRD and the presence of sentinel genetic lesions are more reliable at predicting outcome. Currently, a number of sentinel genetic lesions are used by most cooperative groups for risk stratification; however, in the near future patients will probably be risk-stratified using genomic signatures and clustering algorithms, rather than individual genetic alterations. This review will describe the clinical, biological, and response-based features known to predict relapse risk in childhood ALL, including those currently used and those likely to be used in the near future to risk-stratify therapy.

  17. Predicting adolescent's cyberbullying behavior: A longitudinal risk analysis.

    PubMed

    Barlett, Christopher P

    2015-06-01

    The current study used the risk factor approach to test the unique and combined influence of several possible risk factors for cyberbullying attitudes and behavior using a four-wave longitudinal design with an adolescent US sample. Participants (N = 96; average age = 15.50 years) completed measures of cyberbullying attitudes, perceptions of anonymity, cyberbullying behavior, and demographics four times throughout the academic school year. Several logistic regression equations were used to test the contribution of these possible risk factors. Results showed that (a) cyberbullying attitudes and previous cyberbullying behavior were important unique risk factors for later cyberbullying behavior, (b) anonymity and previous cyberbullying behavior were valid risk factors for later cyberbullying attitudes, and (c) the likelihood of engaging in later cyberbullying behavior increased with the addition of risk factors. Overall, results show the unique and combined influence of such risk factors for predicting later cyberbullying behavior. Results are discussed in terms of theory.

  18. Seroprevalence and risk factors for Neospora caninum in goats in Santa Catarina state, Brazil.

    PubMed

    Topazio, Josué Pires; Weber, Augusto; Camillo, Giovana; Vogel, Fernanda Flores; Machado, Gustavo; Ribeiro, André; Moura, Anderson Barbosa; Lopes, Leandro Sâmia; Tonin, Alexandre Alberto; Soldá, Natan Marcos; Bräunig, Patrícia; Silva, Aleksandro Schafer da

    2014-01-01

    Neosporosis is an infectious disease caused by the parasite Neospora caninum. Knowledge regarding neosporosis in goats is still quite limited, especially in the state of Santa Catarina (SC), southern Brazil. Therefore, this study aimed to assess the seroprevalence and risk factors for N. caninum in goats in the western and mountain regions of SC. Blood samples were collected from 654 goats in 57 municipalities. The indirect immunofluorescence test was used for antibody detection against N. caninum. Thirty samples (4.58%) were seropositive, with titers ranging from 1:50 to 1:6400. An epidemiological survey was also conducted in order to identify risk factors for neosporosis in goats. It was found that reproductive problems on the farms, as well as the diet and direct contact with dogs were casual risks for neosporosis. These results indicate that N. caninum infects goats in these regions, which may lead to reproductive problems.

  19. Brain structure predicts risk for obesity ☆

    PubMed Central

    Smucny, Jason; Cornier, Marc-Andre; Eichman, Lindsay C.; Thomas, Elizabeth A.; Bechtell, Jamie L.; Tregellas, Jason R.

    2014-01-01

    The neurobiology of obesity is poorly understood. Here we report findings of a study designed to examine the differences in brain regional gray matter volume in adults recruited as either Obese Prone or Obese Resistant based on self-identification, body mass index, and personal/family weight history. Magnetic resonance imaging was performed in 28 Obese Prone (14 male, 14 female) and 25 Obese Resistant (13 male, 12 female) healthy adults. Voxel-based morphometry was used to identify gray matter volume differences between groups. Gray matter volume was found to be lower in the insula, medial orbitofrontal cortex and cerebellum in Obese Prone, as compared to Obese Resistant individuals. Adjusting for body fat mass did not impact these results. Insula gray matter volume was negatively correlated with leptin concentration and measures of hunger. These findings suggest that individuals at risk for weight gain have structural differences in brain regions known to be important in energy intake regulation, and that these differences, particularly in the insula, may be related to leptin. PMID:22963736

  20. Ethical and social aspects of risk predictions.

    PubMed

    Fletcher, J C

    1984-01-01

    This paper reviews past, present and future social and ethical considerations of screening carriers of autosomal disorders and other heterozygotes. A body of ethical and social guidance has evolved in the 1970's and 1980's for screening. The values of voluntaristic participation and informed consent are high. The goal of programs should be to provide couples, families, and individuals with knowledge respecting their reproductive choices. The dangers are coercive strategies, stigmatization, and careless communication of risk information. It is assumed that the number of autosomal carrier states that are screenable will undoubtedly increase as will states of heterozygosity that cause susceptibility to common diseases. Before the end of the century, something approaching a "biopsy of the human genome" will be a practical reality. To balance the potential for harmful psychological and social effects of so much new genetic knowledge, new efforts must be made to find treatments for progeny affected by recessive disorders. Maternal and paternal screening, prenatal diagnosis and treatment will be increasingly linked in the future. This paper will report on a case of fetal therapy for congenital adrenal hyperplasia as a paradigm for the future. The argument will be made that society ought to put a higher priority on prenatal care and prevention of disorders of prematurity than genetic disorders with a low frequency, lest genetic screening be distorted by unfounded concern about eugenics.

  1. Toxoplasmosis screening and risk factors amongst pregnant females in Natal, northeastern Brazil.

    PubMed

    Barbosa, Isabelle Ribeiro; de Carvalho Xavier Holanda, Cecília Maria; de Andrade-Neto, Valter Ferreira

    2009-04-01

    Toxoplasmosis results in systemic disease, and if the mother is infected for the first time during gestation, the fetus may suffer substantial damage. Relatively little is known about the epidemiology of toxoplasmosis in pregnancy in most states of northeastern Brazil. Seroprevalence of toxoplasmosis among pregnant woman was studied in Natal, capital of Rio Grande do Norte State, in northeastern Brazil, from March to December 2007. The sera were tested for IgM and avidity of IgG antibodies to Toxoplasma by a microparticle enzyme immunoassay. The overall seroprevalence was high [126/190 (66.3%)]; prevalence increased with age indicating that in this setting most infections occur in adulthood (third decade of life). Only one pregnant woman was IgM positive and had high-avidity antibodies. The high percentage of pregnant women who are vulnerable to this parasite (33.1%) favors primary infection during pregnancy. Our studies show that direct contact with cats or dogs was highly associated with toxoplasmosis (odds ratio 2.72, P<0.001, 95% CI 1.46-5.02). The number of years in school (P<0.001), precarious socioeconomic status and limited knowledge about the disease (Prisk factors for infection corroborate other studies in Brazil.

  2. Intensification of cattle ranching production systems: socioeconomic and environmental synergies and risks in Brazil.

    PubMed

    Latawiec, A E; Strassburg, B B N; Valentim, J F; Ramos, F; Alves-Pinto, H N

    2014-08-01

    Intensification of Brazilian cattle ranching systems has attracted both national and international attention due to its direct relation with Amazon deforestation on the one hand and increasing demand of the global population for meat on the other. Since Brazilian cattle ranching is predominantly pasture-based, we particularly focus on pasture management. We summarize the most recurrent opportunities and risks associated with pasture intensification that are brought up within scientific and political dialogues, and discuss them within the Brazilian context. We argue that sustainable intensification of pasturelands in Brazil is a viable way to increase agricultural output while simultaneously sparing land for nature. Since environmental degradation is often associated with low-yield extensive systems in Brazil, it is possible to obtain higher yields, while reversing degradation, by adopting practices like rotational grazing, incorporation of legumes and integrated crop-livestock-forestry systems. Technical assistance is however essential, particularly for small- and medium-scale farmers. Sound complementary policies and good governance must accompany these measures so that a 'rebound effect' does not lead to increased deforestation and other adverse social and environmental impacts. It is also important that animal welfare is not compromised. Although the discussion is presented with respect to Brazil, some aspects are relevant to other developing countries.

  3. [Statistical prediction methods in violence risk assessment and its application].

    PubMed

    Liu, Yuan-Yuan; Hu, Jun-Mei; Yang, Min; Li, Xiao-Song

    2013-06-01

    It is an urgent global problem how to improve the violence risk assessment. As a necessary part of risk assessment, statistical methods have remarkable impacts and effects. In this study, the predicted methods in violence risk assessment from the point of statistics are reviewed. The application of Logistic regression as the sample of multivariate statistical model, decision tree model as the sample of data mining technique, and neural networks model as the sample of artificial intelligence technology are all reviewed. This study provides data in order to contribute the further research of violence risk assessment.

  4. Assessing patients' risk of febrile neutropenia: is there a correlation between physician-assessed risk and model-predicted risk?

    PubMed

    Lyman, Gary H; Dale, David C; Legg, Jason C; Abella, Esteban; Morrow, Phuong Khanh; Whittaker, Sadie; Crawford, Jeffrey

    2015-08-01

    This study evaluated the correlation between the risk of febrile neutropenia (FN) estimated by physicians and the risk of severe neutropenia or FN predicted by a validated multivariate model in patients with nonmyeloid malignancies receiving chemotherapy. Before patient enrollment, physician and site characteristics were recorded, and physicians self-reported the FN risk at which they would typically consider granulocyte colony-stimulating factor (G-CSF) primary prophylaxis (FN risk intervention threshold). For each patient, physicians electronically recorded their estimated FN risk, orders for G-CSF primary prophylaxis (yes/no), and patient characteristics for model predictions. Correlations between physician-assessed FN risk and model-predicted risk (primary endpoints) and between physician-assessed FN risk and G-CSF orders were calculated. Overall, 124 community-based oncologists registered; 944 patients initiating chemotherapy with intermediate FN risk enrolled. Median physician-assessed FN risk over all chemotherapy cycles was 20.0%, and median model-predicted risk was 17.9%; the correlation was 0.249 (95% CI, 0.179-0.316). The correlation between physician-assessed FN risk and subsequent orders for G-CSF primary prophylaxis (n = 634) was 0.313 (95% CI, 0.135-0.472). Among patients with a physician-assessed FN risk ≥ 20%, 14% did not receive G-CSF orders. G-CSF was not ordered for 16% of patients at or above their physician's self-reported FN risk intervention threshold (median, 20.0%) and was ordered for 21% below the threshold. Physician-assessed FN risk and model-predicted risk correlated weakly; however, there was moderate correlation between physician-assessed FN risk and orders for G-CSF primary prophylaxis. Further research and education on FN risk factors and appropriate G-CSF use are needed.

  5. [Early pregnancy risk: development and validation of a predictive instrument].

    PubMed

    Burrows, R; Rosales, M E; Díaz, M; Muzzo, S

    1994-06-01

    An early pregnancy risk scale, with scores ranging from 11 to 66 points from lower to higher risk, was constructed using variables associated with teenager's pregnancy. This scale was applied to 3000 female teenagers, coming from Metropolitan Santiago public schools. The sample was divided in three risk groups: group A (high risk) with scores equal or over 35 points, group B (low risk) with scores equal or below 20 points and group B (intermediate risk) with scores between 20.1 and 34.9 points. These girls were followed during 2 years. During this period, 84 girls became pregnant, 24 of 184 (13%) in group A, 60 of 2332 (2.6%) in group C and none of 307 in group B. There were 104 school desertions in group A and 37 in group B. To study associations and analyze risk, the sample was divided in two risk groups: high, with scores over 27 and low, with scores below 27. There was a high association between pregnancy risk score and the occurrence of pregnancy (RR 5.25 p < 0.0001) and school desertion (RR 3.32 p < 0.0001). Pregnancy was predicted with a 78% sensitivity and 55.6% specificity. School desertion was predicted with a 74% sensitivity and 56% specificity. The importance variable weighing using multiple regression models, to improve the predictor's sensitivity and specificity, is discussed.

  6. Risk factors that predict future onset of each DSM-5 eating disorder: Predictive specificity in high-risk adolescent females.

    PubMed

    Stice, Eric; Gau, Jeff M; Rohde, Paul; Shaw, Heather

    2017-01-01

    Because no single report has examined risk factors that predict future onset each type of eating disorder and core symptom dimensions that crosscut disorders, we addressed these aims to advance knowledge regarding risk factor specificity. Data from 3 prevention trials that targeted young women with body dissatisfaction (N = 1,272; Mage = 18.5, SD = 4.2) and collected annual diagnostic interview data over 3-year follow-up were combined to identify predictors of subthreshold/threshold anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and purging disorder (PD). Negative affect and functional impairment predicted onset of all eating disorders. Thin-ideal internalization, body dissatisfaction, dieting, overeating, and mental health care predicted onset of subthreshold/threshold BN, BED, and PD; positive thinness expectations, denial of cost of pursuing the thin ideal, and fasting predicted onset of 2 of these 3 disorders. Similar risk factors predicted core eating disorder symptom onset. Low BMI and dieting specifically predicted onset of subthreshold/threshold AN or low BMI. Only a subset of factors showed unique predictive effects in multivariate models, likely due to moderate correlations between the risk factors (M r = .14). Results provide support for the theory that pursuit of the thin ideal and the resulting body dissatisfaction, dieting, and unhealthy weight control behaviors increase risk for binge/purge spectrum eating disorders, but suggest that youth who are inherently lean, rather than purposely pursuing the thin ideal, are at risk for AN. Impaired interpersonal functioning and negative affect are transdiagnostic risk factors, suggesting these factors should be targeted in prevention programs. (PsycINFO Database Record

  7. The Impact of Covariate Measurement Error on Risk Prediction

    PubMed Central

    Khudyakov, Polyna; Gorfine, Malka; Zucker, David; Spiegelman, Donna

    2015-01-01

    In the development of risk prediction models, predictors are often measured with error. In this paper, we investigate the impact of covariate measurement error on risk prediction. We compare the prediction performance using a costly variable measured without error, along with error-free covariates, to that of a model based on an inexpensive surrogate along with the error-free covariates. We consider continuous error-prone covariates with homoscedastic and heteroscedastic errors, and also a discrete misclassified covariate. Prediction performance is evaluated by the area under the receiver operating characteristic curve (AUC), the Brier score (BS), and the ratio of the observed to the expected number of events (calibration). In an extensive numerical study, we show that (i) the prediction model with the error-prone covariate is very well calibrated, even when it is mis-specified; (ii) using the error-prone covariate instead of the true covariate can reduce the AUC and increase the BS dramatically; (iii) adding an auxiliary variable, which is correlated with the error-prone covariate but conditionally independent of the outcome given all covariates in the true model, can improve the AUC and BS substantially. We conclude that reducing measurement error in covariates will improve the ensuing risk prediction, unless the association between the error-free and error-prone covariates is very high. Finally, we demonstrate how a validation study can be used to assess the effect of mismeasured covariates on risk prediction. These concepts are illustrated in a breast cancer risk prediction model developed in the Nurses’ Health Study. PMID:25865315

  8. Risk Models to Predict Hypertension: A Systematic Review

    PubMed Central

    Echouffo-Tcheugui, Justin B.; Batty, G. David; Kivimäki, Mika; Kengne, Andre P.

    2013-01-01

    Background As well as being a risk factor for cardiovascular disease, hypertension is also a health condition in its own right. Risk prediction models may be of value in identifying those individuals at risk of developing hypertension who are likely to benefit most from interventions. Methods and Findings To synthesize existing evidence on the performance of these models, we searched MEDLINE and EMBASE; examined bibliographies of retrieved articles; contacted experts in the field; and searched our own files. Dual review of identified studies was conducted. Included studies had to report on the development, validation, or impact analysis of a hypertension risk prediction model. For each publication, information was extracted on study design and characteristics, predictors, model discrimination, calibration and reclassification ability, validation and impact analysis. Eleven studies reporting on 15 different hypertension prediction risk models were identified. Age, sex, body mass index, diabetes status, and blood pressure variables were the most common predictor variables included in models. Most risk models had acceptable-to-good discriminatory ability (C-statistic>0.70) in the derivation sample. Calibration was less commonly assessed, but overall acceptable. Two hypertension risk models, the Framingham and Hopkins, have been externally validated, displaying acceptable-to-good discrimination, and C-statistic ranging from 0.71 to 0.81. Lack of individual-level data precluded analyses of the risk models in subgroups. Conclusions The discrimination ability of existing hypertension risk prediction tools is acceptable, but the impact of using these tools on prescriptions and outcomes of hypertension prevention is unclear. PMID:23861760

  9. A new explained-variance based genetic risk score for predictive modeling of disease risk.

    PubMed

    Che, Ronglin; Motsinger-Reif, Alison A

    2012-09-25

    The goal of association mapping is to identify genetic variants that predict disease, and as the field of human genetics matures, the number of successful association studies is increasing. Many such studies have shown that for many diseases, risk is explained by a reasonably large number of variants that each explains a very small amount of disease risk. This is prompting the use of genetic risk scores in building predictive models, where information across several variants is combined for predictive modeling. In the current study, we compare the performance of four previously proposed genetic risk score methods and present a new method for constructing genetic risk score that incorporates explained variance information. The methods compared include: a simple count Genetic Risk Score, an odds ratio weighted Genetic Risk Score, a direct logistic regression Genetic Risk Score, a polygenic Genetic Risk Score, and the new explained variance weighted Genetic Risk Score. We compare the methods using a wide range of simulations in two steps, with a range of the number of deleterious single nucleotide polymorphisms (SNPs) explaining disease risk, genetic modes, baseline penetrances, sample sizes, relative risks (RR) and minor allele frequencies (MAF). Several measures of model performance were compared including overall power, C-statistic and Akaike's Information Criterion. Our results show the relative performance of methods differs significantly, with the new explained variance weighted GRS (EV-GRS) generally performing favorably to the other methods.

  10. Individualized Risk Prediction Model for Lung Cancer in Korean Men

    PubMed Central

    Park, Sohee; Nam, Byung-Ho; Yang, Hye-Ryung; Lee, Ji An; Lim, Hyunsun; Han, Jun Tae; Park, Il Su; Shin, Hai-Rim; Lee, Jin Soo

    2013-01-01

    Purpose Lung cancer is the leading cause of cancer deaths in Korea. The objective of the present study was to develop an individualized risk prediction model for lung cancer in Korean men using population-based cohort data. Methods From a population-based cohort study of 1,324,804 Korean men free of cancer at baseline, the individualized absolute risk of developing lung cancer was estimated using the Cox proportional hazards model. We checked the validity of the model using C statistics and the Hosmer–Lemeshow chi-square test on an external validation dataset. Results The risk prediction model for lung cancer in Korean men included smoking exposure, age at smoking initiation, body mass index, physical activity, and fasting glucose levels. The model showed excellent performance (C statistic = 0.871, 95% CI = 0.867–0.876). Smoking was significantly associated with the risk of lung cancer in Korean men, with a four-fold increased risk in current smokers consuming more than one pack a day relative to non-smokers. Age at smoking initiation was also a significant predictor for developing lung cancer; a younger age at initiation was associated with a higher risk of developing lung cancer. Conclusion This is the first study to provide an individualized risk prediction model for lung cancer in an Asian population with very good model performance. In addition to current smoking status, earlier exposure to smoking was a very important factor for developing lung cancer. Since most of the risk factors are modifiable, this model can be used to identify those who are at a higher risk and who can subsequently modify their lifestyle choices to lower their risk of lung cancer. PMID:23408946

  11. Quantitative risk assessment for human salmonellosis through the consumption of pork sausage in Porto Alegre, Brazil.

    PubMed

    Mürmann, Lisandra; Corbellini, Luis Gustavo; Collor, Alexandre Ávila; Cardoso, Marisa

    2011-04-01

    A quantitative microbiology risk assessment was conducted to evaluate the risk of Salmonella infection to consumers of fresh pork sausages prepared at barbecues in Porto Alegre, Brazil. For the analysis, a prevalence of 24.4% positive pork sausages with a level of contamination between 0.03 and 460 CFU g(-1) was assumed. Data related to frequency and habits of consumption were obtained by a questionnaire survey given to 424 people. A second-order Monte Carlo simulation separating the uncertain parameter of cooking time from the variable parameters was run. Of the people interviewed, 87.5% consumed pork sausage, and 85.4% ate it at barbecues. The average risk of salmonellosis per barbecue at a minimum cooking time of 15.6 min (worst-case scenario) was 6.24 × 10(-4), and the risk assessed per month was 1.61 × 10(-3). Cooking for 19 min would fully inactivate Salmonella in 99.9% of the cases. At this cooking time, the sausage reached a mean internal temperature of 75.7°C. The results of the quantitative microbiology risk assessment revealed that the consumption of fresh pork sausage is safe when cooking time is approximately 19 min, whereas undercooked pork sausage may represent a nonnegligible health risk for consumers.

  12. Risk assessment and life prediction of complex engineering systems

    SciTech Connect

    Garcia, M.D.; Varma, R.; Heger, A.S.

    1996-03-01

    Many complex engineering systems will exceed their design life expectancy within the next 10 to 15 years. It is also expected that these systems must be maintained and operated beyond their design life. This paper presents a integrated approach for managing the risks associated with aging effects and predicting the residually expectancy these systems, The approach unifies risk assessment, enhanced surveillance and testing, and robust computational models to assess the risk, predict age, and develop a life-extension management procedure. It also relies on the state of the art in life-extension and risk assessment methods from the nuclear power industry. Borrowing from the developments in decision analysis, this approach should systematically identify the options available for managing the existing aging systems beyond their intended design life.

  13. Cumulative risk hypothesis: Predicting and preventing child maltreatment recidivism.

    PubMed

    Solomon, David; Åsberg, Kia; Peer, Samuel; Prince, Gwendolyn

    2016-08-01

    Although Child Protective Services (CPS) and other child welfare agencies aim to prevent further maltreatment in cases of child abuse and neglect, recidivism is common. Having a better understanding of recidivism predictors could aid in preventing additional instances of maltreatment. A previous study identified two CPS interventions that predicted recidivism: psychotherapy for the parent, which was related to a reduced risk of recidivism, and temporary removal of the child from the parent's custody, which was related to an increased recidivism risk. However, counter to expectations, this previous study did not identify any other specific risk factors related to maltreatment recidivism. For the current study, it was hypothesized that (a) cumulative risk (i.e., the total number of risk factors) would significantly predict maltreatment recidivism above and beyond intervention variables in a sample of CPS case files and that (b) therapy for the parent would be related to a reduced likelihood of recidivism. Because it was believed that the relation between temporary removal of a child from the parent's custody and maltreatment recidivism is explained by cumulative risk, the study also hypothesized that that the relation between temporary removal of the child from the parent's custody and recidivism would be mediated by cumulative risk. After performing a hierarchical logistic regression analysis, the first two hypotheses were supported, and an additional predictor, psychotherapy for the child, also was related to reduced chances of recidivism. However, Hypothesis 3 was not supported, as risk did not significantly mediate the relation between temporary removal and recidivism.

  14. Identification of the high risk emergency surgical patient: Which risk prediction model should be used?

    PubMed Central

    Stonelake, Stephen; Thomson, Peter; Suggett, Nigel

    2015-01-01

    Introduction National guidance states that all patients having emergency surgery should have a mortality risk assessment calculated on admission so that the ‘high risk’ patient can receive the appropriate seniority and level of care. We aimed to assess if peri-operative risk scoring tools could accurately calculate mortality and morbidity risk. Methods Mortality risk scores for 86 consecutive emergency laparotomies, were calculated using pre-operative (ASA, Lee index) and post-operative (POSSUM, P-POSSUM and CR-POSSUM) risk calculation tools. Morbidity risk scores were calculated using the POSSUM predicted morbidity and compared against actual morbidity according to the Clavien–Dindo classification. Results The actual mortality was 10.5%. The average predicted risk scores for all laparotomies were: ASA 26.5%, Lee Index 2.5%, POSSUM 29.5%, P-POSSUM 18.5%, CR-POSSUM 10.5%. Complications occurred following 67 laparotomies (78%). The majority (51%) of complications were classified as Clavien–Dindo grade 2–3 (non-life-threatening). Patients having a POSSUM morbidity risk of greater than 50% developed significantly more life-threatening complications (CD 4–5) compared with those who predicted less than or equal to 50% morbidity risk (P = 0.01). Discussion Pre-operative risk stratification remains a challenge because the Lee Index under-predicts and ASA over-predicts mortality risk. Post-operative risk scoring using the CR-POSSUM is more accurate and we suggest can be used to identify patients who require intensive care post-operatively. Conclusions In the absence of accurate risk scoring tools that can be used on admission to hospital it is not possible to reliably audit the achievement of national standards of care for the ‘high-risk’ patient. PMID:26468369

  15. [Rural work and health risks: a review into de "safe use" of pesticides in Brazil].

    PubMed

    de Abreu, Pedro Henrique Barbosa; Alonzo, Herling Gregorio Aguilar

    2014-10-01

    The paradigm of the "safe use" of pesticides is based on measures to control risks in the handling of these products. However, studies carried out in various regions of Brazil reveal a situation of widespread exposure and health damages among rural workers, revealing the ineffectiveness of this paradigm. This work presents a critical review of the "safe use" approach for pesticides in scientific papers published in Brazil in the past 15 years. Results indicate that these studies do not address, simultaneously, all the work activities that involve exposure and risk of intoxication (acquisition, transportation, storage, preparation and application, final disposal of empty containers and sanitization of contaminated clothes/ PPEs), nor do they comprehensively address the "safe use" measures recommended in safety manuals, which are mandatory for each activity. A total of 25 studies were selected and analyzed, revealing a high number of results and analyses regarding activities of preparation and application and final disposal of empty containers. The range of the approaches was seen to be timely in the six work activities. For future studies, a broader approach of the "safe use" of pesticides is recommended, seeking to reveal the complete infeasibility of this safety paradigm.

  16. Use of transgenic Aedes aegypti in Brazil: risk perception and assessment.

    PubMed

    Paes de Andrade, Paulo; Aragão, Francisco José Lima; Colli, Walter; Dellagostin, Odir Antônio; Finardi-Filho, Flávio; Hirata, Mario Hiroyuki; Lira-Neto, Amaro de Castro; Almeida de Melo, Marcia; Nepomuceno, Alexandre Lima; Gorgônio da Nóbrega, Francisco; Delfino de Sousa, Gutemberg; Valicente, Fernando Hercos; Zanettini, Maria Helena Bodanese

    2016-10-01

    The OX513A strain of Aedes aegypti, which was developed by the British company Oxitec, expresses a self-limiting transgene that prevents larvae from developing to adulthood. In April 2014, the Brazilian National Technical Commission on Biosafety completed a risk assessment of OX513A and concluded that the strain did not present new biological risks to humans or the environment and could be released in Brazil. At that point, Brazil became the first country to approve the unconstrained release of a genetically modified mosquito. During the assessment, the commission produced a comprehensive list of - and systematically analysed - the perceived hazards. Such hazards included the potential survival to adulthood of immature stages carrying the transgene - should the transgene fail to be expressed or be turned off by exposure to sufficient environmental tetracycline. Other perceived hazards included the potential allergenicity and/or toxicity of the proteins expressed by the gene, the potential for gene flow or increased transmission of human pathogens and the occupation of vacant breeding sites by other vector species. The Zika epidemic both elevated the perceived importance of Ae. aegypti as a vector - among policy-makers and regulators as well as the general public - and increased concerns over the release of males of the OX513A strain. We have therefore reassessed the potential hazards. We found that release of the transgenic mosquitoes would still be both safe and of great potential value in the control of diseases spread by Ae. aegypti, such as chikungunya, dengue and Zika.

  17. Prediction and Informative Risk Factor Selection of Bone Diseases.

    PubMed

    Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong

    2015-01-01

    With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.

  18. HIV infection and risk behaviors among male port workers in Santos, Brazil.

    PubMed Central

    Larcerda, R; Stall, R; Gravato, N; Tellini, R; Hudes, E S; Hearst, N

    1996-01-01

    OBJECTIVES. This paper measured the extent to which human immunodeficiency virus (HIV) infection has spread among the male working-class population of Santos, Brazil. METHODS. Questionnaires on risk behaviors and blood tests were administered to a random sample (n = 395) of male port workers employed by the Santos Port Authority. RESULTS. Although the rate of HIV infection among these men- the working-class male population of Santos-remains low (1.1%), self-reported behavioral risks for HIV infection are common. CONCLUSIONS. There is still time to prevent a widespread outbreak of HIV infection among the hetero-sexual population of Santos and of the transportation corridors emanating from that city. PMID:8712280

  19. Leptospirosis seroprevalence and risk factors for sheep in Maranhão state, Brazil.

    PubMed

    de Carvalho, Sônia Maria; Mineiro, Ana Lys B B; Castro, Vanessa; Genovez, Margareth E; Azevedo, Sérgio Santos; Costa, Francisco A L

    2014-02-01

    This study was conducted to determine leptospirosis seroprevalence in sheep and their spatial distribution as well as identify risk factors associated with seropositivity in sheep from 37 herds and 11 municipalities in the Presidente Dutra microregion, Maranhão state, Brazil. We analyzed 379 blood serum samples using a Microscopic Agglutination Test (MAT). The individual seroprevalence was 32%. Of the 37 herds studied, 30 (81%, 95% CI 69-94%) had at least one seropositive animal. In seven municipalities, we observed infection in 100% of the herds. The serovars recorded were Grippotyphosa (67%), Wollfi with Hardjo (9%), Bratislava (9%), Hardjo (5%), Icterohaemorrhagiae (5%), Pomona (2%), Castellonis (2%) and Copenhageni (0.8%). We concluded that the Leptospira spp. in sheep is widespread in the area of sheep farms in Maranhão state, and a risk factor is the animals' water source.

  20. Variation of surface ozone in Campo Grande, Brazil: meteorological effect analysis and prediction.

    PubMed

    Pires, J C M; Souza, A; Pavão, H G; Martins, F G

    2014-09-01

    The effect of meteorological variables on surface ozone (O3) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O3 concentration, relative humidity and solar radiation. The threshold model that considers two O3 regimes was the one that correctly describes the effect of important meteorological variables in O3 behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O3 regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O3 concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O3 behaviour, being useful to define policy strategies for human health protection regarding air pollution.

  1. Clustering of Risk Factors for Non-Communicable Diseases among Adolescents from Southern Brazil

    PubMed Central

    2016-01-01

    Introduction The aim of this study was to investigate the simultaneous presence of risk factors for non-communicable diseases and the association of these risk factors with demographic and economic factors among adolescents from southern Brazil. Methods The study included 916 students (14–19 years old) enrolled in the 2014 school year at state schools in São José, Santa Catarina, Brazil. Risk factors related to lifestyle (i.e., physical inactivity, excessive alcohol consumption, smoking, sedentary behaviour and unhealthy diet), demographic variables (sex, age and skin colour) and economic variables (school shift and economic level) were assessed through a questionnaire. Simultaneous behaviours were assessed by the ratio between observed and expected prevalences of risk factors for non-communicable diseases. The clustering of risk factors was analysed by multinomial logistic regression. The clusters of risk factors that showed a higher prevalence were analysed by binary logistic regression. Results The clustering of two, three, four, and five risk factors were found in 22.2%, 49.3%, 21.7% and 3.1% of adolescents, respectively. Subgroups that were more likely to have both behaviours of physical inactivity and unhealthy diet simultaneously were mostly composed of girls (OR = 3.03, 95% CI = 1.57–5.85) and those with lower socioeconomic status (OR = 1.83, 95% CI = 1.05–3.21); simultaneous physical inactivity, excessive alcohol consumption, sedentary behaviour and unhealthy diet were mainly observed among older adolescents (OR = 1.49, 95% CI = 1.05–2.12). Subgroups less likely to have both behaviours of sedentary behaviour and unhealthy diet were mostly composed of girls (OR = 0.58, 95% CI = 0.38–0.89); simultaneous physical inactivity, sedentary behaviour and unhealthy diet were mainly observed among older individuals (OR = 0.66, 95% CI = 0.49–0.87) and those of the night shift (OR = 0.59, 95% CI = 0.43–0.82). Conclusion Adolescents had a high prevalence

  2. Predicting operative risk for coronary artery surgery in the United Kingdom: a comparison of various risk prediction algorithms

    PubMed Central

    Bridgewater, B; Neve, H; Moat, N; Hooper, T; Jones, M

    1998-01-01

    Objective—To compare the ability of four risk models to predict operative mortality after coronary artery bypass graft surgery (CABG) in the United Kingdom.
Design—Prospective study.
Setting—Two cardiothoracic centres in the United Kingdom.
Subjects—1774 patients having CABG.
Main outcome measures—Risk factors were recorded for all patients, along with in-hospital mortality. Predicted mortality was derived from the American Society of Thoracic Surgeons (STS) risk program, Ontario Province risk score (PACCN), Parsonnet score, and the UK Society of Cardiothoracic Surgeons risk algorithm.
Results—There were significant differences (p < 0.05) between the British and American populations from which the STS risk algorithm was derived with respect to most variables. The observed mortality in the British population was 3.7% (65 of 1774). The mean pre- dicted mortality by STS score, PACCN, Parsonnet score, and UK algorithms were 1.1%, 1.6%, 4.6%, and 4.7% respectively. The overall predictive ability of the models as measured by the area under the receiver operating characteristic curve were 0.64, 0.60, 0.73, and 0.75, respectively.
Conclusions—There are differences between the British and American populations for CABG and the North American algorithms are not useful for predicting mortality in the United Kingdom. The UK Society of Cardiothoracic Surgeons algorithm is the best of the models tested but still only has limited predictive ability. Great care must be exercised when using methods of this type for comparisons of units and surgeons.

 Keywords: cardiac surgery;  risk stratification;  audit PMID:9616341

  3. Risk Perception and Occupational Accidents: A Study of Gas Station Workers in Southern Brazil

    PubMed Central

    Cezar-Vaz, Marta Regina; Rocha, Laurelize Pereira; Bonow, Clarice Alves; da Silva, Mara Regina Santos; Vaz, Joana Cezar; Cardoso, Letícia Silveira

    2012-01-01

    The present study aimed to identify the perceptions of gas station workers about physical, chemical, biological and physiological risk factors to which they are exposed in their work environment; identify types of occupational accidents involving gas station workers and; report the development of a socioenvironmental intervention as a tool for risk communication to gas station workers. A quantitative study was performed with 221 gas station workers in southern Brazil between October and December 2010. Data collection was performed between October to December 2010 via structured interviews. The data were analyzed using SPSS 19.0. The participants identified the following risk types: chemical (93.7%), physical (88.2%), physiological (64.3%) and biological (62.4%). In this sample, 94.1% of gas station workers reported occupational accidents, and 74.2% reported fuel contact with the eyes (p < 0.05). It is concluded that workers perceive risks, and that they tend to relate risks with the occurrence of occupational accidents as an indicator of the dangerous nature of their work environment. PMID:22851948

  4. Risk Communication Concerning Welding Fumes for the Primary Preventive Care of Welding Apprentices in Southern Brazil

    PubMed Central

    Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; Cezar Vaz, Joana

    2015-01-01

    This study’s aim was to assess the perceptions of welding apprentices concerning welding fumes being associated with respiratory and cardiovascular disorders and assess the implementation of risk communication as a primary prevention tool in the welding training process. This quasi-experimental, non-randomized study with before-and-after design was conducted with 84 welding apprentices in Southern Brazil. Poisson Regression analysis was used. Relative Risk was the measure used with a 95% confidence interval and 5% (p ≤ 0.05) significance level. Significant association was found between perceptions of worsened symptoms of respiratory disorders caused by welding fumes and educational level (p = 0.049), the use of goggles to protect against ultraviolet rays (p = 0.023), and access to services in private health facilities without insurance coverage (p = 0.001). Apprentices younger than 25 years old were 4.9 times more likely to perceive worsened cardiovascular symptoms caused by welding fumes after risk communication (RR = 4.91; CI 95%: 1.09 to 22.2). The conclusion is that risk communication as a primary preventive measure in continuing education processes implemented among apprentices, who are future welders, was efficacious. Thus, this study confirms that risk communication can be implemented as a primary prevention tool in welding apprenticeships. PMID:25607606

  5. Risk communication concerning welding fumes for the primary preventive care of welding apprentices in southern Brazil.

    PubMed

    Cezar-Vaz, Marta Regina; Bonow, Clarice Alves; Vaz, Joana Cezar

    2015-01-19

    This study's aim was to assess the perceptions of welding apprentices concerning welding fumes being associated with respiratory and cardiovascular disorders and assess the implementation of risk communication as a primary prevention tool in the welding training process. This quasi-experimental, non-randomized study with before-and-after design was conducted with 84 welding apprentices in Southern Brazil. Poisson Regression analysis was used. Relative Risk was the measure used with a 95% confidence interval and 5% (p ≤ 0.05) significance level. Significant association was found between perceptions of worsened symptoms of respiratory disorders caused by welding fumes and educational level (p = 0.049), the use of goggles to protect against ultraviolet rays (p = 0.023), and access to services in private health facilities without insurance coverage (p = 0.001). Apprentices younger than 25 years old were 4.9 times more likely to perceive worsened cardiovascular symptoms caused by welding fumes after risk communication (RR = 4.91; CI 95%: 1.09 to 22.2). The conclusion is that risk communication as a primary preventive measure in continuing education processes implemented among apprentices, who are future welders, was efficacious. Thus, this study confirms that risk communication can be implemented as a primary prevention tool in welding apprenticeships.

  6. Protective and risk factors for toxocariasis in children from two different social classes of Brazil.

    PubMed

    Santarém, Vamilton Alvares; Leli, Flávia Noris Chagas; Rubinsky-Elefant, Guita; Giuffrida, Rogério

    2011-01-01

    The aim of this study was to analyze the prevalence of Toxocara spp. antibodies in children from two different socioeconomic classes in the Presidente Prudente municipality, São Paulo State, Brazil, and the protective and risk factors associated with toxocariasis. One hundred and twenty-six middle-class (MC) and 126 disadvantaged children (DC) were included in this study. Anti-Toxocara ELISA test was performed in order to evaluate seroprevalence. A survey was applied to the children's guardians/parents in order to analyze the protective and risk factors. The overall prevalence was 11.1%, and of 9.5% (12/126) and 12.7% (16/126) for MC and DC subgroups, respectively. Toxocara seropositivity was inversely proportional to the family income. A high household income was considered a protective factor for toxocariasis in the total population and in both MC and DC subgroups. Being a girl was considered a protective factor for the total population and for both subgroups. Whilst being an owner of cat was a risk factor for children belonging to the total and for both MC and DC subgroups, having dog was considered as a risk factor for only the MC. Epidemiologic protective/factor risks can be distinct depending on the strata of the same population. Thus, it is relevant to evaluate these factors independently for different socioeconomic classes in order to design future investigations and programs for preventing the infection of human beings by Toxocara spp. and other geohelminths.

  7. Cumulative Family Risk Predicts Sibling Adjustment to Childhood Cancer

    PubMed Central

    Long, Kristin A.; Marsland, Anna L.; Alderfer, Melissa A.

    2013-01-01

    Background Prolonged, intensive treatment regimens often disrupt families of children with cancer. Siblings are at increased risk for distress, but factors underlying this risk have received limited empirical attention. This study examined associations between the family context and sibling distress. Methods Siblings of children with cancer (ages 8–18, N=209) and parents (186 mothers, 70 fathers) completed measures of sibling distress, family functioning, parenting, and parent posttraumatic stress. Associations between sibling distress and each family risk factor were evaluated. Then, family risks were considered simultaneously by calculating cumulative family risk index scores. Results After controlling for socio-demographic covariates, greater sibling distress was associated with more sibling-reported problems with family functioning and parental psychological control, lower sibling-reported maternal acceptance, and lower paternal self-reported acceptance. When risk factors were considered together, results supported a quadratic model in which associations between family risk and sibling distress were stronger at higher levels of risk. Conclusions Findings support a contextual model of sibling adjustment to childhood cancer in which elevated distress is predicted by family risk factors, alone and in combination. PMID:23576115

  8. Risk Prediction for Adverse Pregnancy Outcomes in a Medicaid Population

    PubMed Central

    Hall, Eric S.; Greenberg, James M.; Kelly, Elizabeth A.

    2015-01-01

    Abstract Background: Despite prior efforts to develop pregnancy risk prediction models, there remains a lack of evidence to guide implementation in clinical practice. The current aim was to develop and validate a risk tool grounded in social determinants theory for use among at-risk Medicaid patients. Methods: This was a retrospective cohort study of 409 women across 17 Cincinnati health centers between September 2013 and April 2014. The primary outcomes included preterm birth, low birth weight, intrauterine fetal demise, and neonatal death. After random allocation into derivation and validation samples, a multivariable model was developed, and a risk scoring system was assessed and validated using area under the receiver operating characteristic curve (AUROC) values. Results: The derived multivariable model (n=263) included: prior preterm birth, interpregnancy interval, late prenatal care, comorbid conditions, history of childhood abuse, substance use, tobacco use, body mass index, race, twin gestation, and short cervical length. Using a weighted risk score, each additional point was associated with an odds ratio of 1.57 for adverse outcomes, p<0.001, AUROC=0.79. In the validation sample (n=146), each additional point conferred an odds ratio of 1.20, p=0.03, AUROC=0.63. Using a cutoff of 20% probability for the outcome, sensitivity was 29%, with specificity 82%. Positive and negative predictive values were 22% and 85%, respectively. Conclusions: Risk scoring based on social determinants can discriminate pregnancy risk within a Medicaid population; however, performance is modest and consistent with prior prediction models. Future research is needed to evaluate whether implementation of risk scoring in Medicaid prenatal care programs improves clinical outcomes. PMID:26102375

  9. Risk Factors Predictive of the Problem Behavior of Children at Risk for Emotional and Behavioral Disorders

    ERIC Educational Resources Information Center

    Nelson, J. Ron; Stage, Scott; Duppong-Hurley, Kristin; Synhorst, Lori; Epstein, Michael H.

    2007-01-01

    Logistic regression analyses were used to establish the most robust set of risk factors that would best predict borderline/clinical levels of problem behavior (i.e., a t score at or above 60 on the Child Behavior Checklist Total Problem scale) of kindergarten and first-grade children at risk for emotional and behavioral disorders. Results showed…

  10. Use of a predictive model for food insecurity estimates in Brazil.

    PubMed

    Gubert, Muriel Bauermann; Benício, Maria Helena D'Aquino; da Silva, Joseane Padilha; da Costa Rosa, Tereza Etsuko; dos Santos, Soane Mota; dos Santos, Leonor Maria Pacheco

    2010-06-01

    In 2004 the National Household Survey (Pesquisa Nacional por Amostras de Domicilios-PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p = 0.561) and ROC curve (area = 0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

  11. Ensemble Streamflow Predictions in the Três Marias Basin, Brazil

    NASA Astrophysics Data System (ADS)

    Mainardi Fan, Fernando; Schwanenberg, Dirk; Kuwajima, Julio; Assis dos Reis, Alberto; Collischonn, Walter

    2014-05-01

    Hydropower is the main electricity source of Brazil. The related hydropower reservoirs are multi-purpose thus besides efficient and reliable energy production, they are relevant for flood control. In this context, the present study shows results of an Ensemble Streamflow Prediction (ESP) for supporting the operational decision making implemented at Três Marias hydroelectric power project located in the São Francisco River basin in Brazil. It is a large tropical river basin with approximately 55,000km² up to the Três Marias dam. The hydrological model used in the study is the MGB-IPH (Modelo de Grandes Bacias from Instituto de Pesquisas Hidráulicas), a large scale distributed hydrological model. Applied in an operational forecasting mode, it uses an empirical data assimilation method to take into account real time streamflow observations to update its state variables. We present results of a hindcast experiment with observed precipitation and streamflow data from the local energy utility, CEMIG (Companhia Energética de Minas Gerais), and from the Brazilian water agency, ANA (Agencia Nacional de Água),. Probabilistic Numerical Weather Predictions (NWP) from CPTEC (Centro de Previsão de Tempo e Estudos Climáticos), ECMWF (European Centre for Medium-Range Weather Forecast) and NOAA (National Oceanic and Atmospheric Administration) are used to generate the ESP. The data products and the MGB-IPH model are integrated into an open shell forecasting platform based on the software package Delft-FEWS. Inside the forecasting platform a hindcast mode over a forecast lead time of 10-16 days in recent rainfall periods is applied in. The ESP results are compared to deterministic forecasts of the Três Marias reservoir inflow. The results assessment verifies the added value of the ESP in general in comparison to the use of deterministic forecasts by means of different performance indicators. The ESP derived from the ECMWP ensemble shows the best performance. A future

  12. Gastrointestinal and ectoparasites from urban stray dogs in Fortaleza (Brazil): high infection risk for humans?

    PubMed

    Klimpel, Sven; Heukelbach, Jörg; Pothmann, David; Rückert, Sonja

    2010-08-01

    Dogs are important definite or reservoir hosts for zoonotic parasites. However, only few studies on the prevalence of intestinal parasites in urban areas in Brazil are available. We performed a comprehensive study on parasites of stray dogs in a Brazilian metropolitan area. We included 46 stray dogs caught in the urban areas of Fortaleza (northeast Brazil). After euthanization, dogs were autopsied. Ectoparasites were collected, and the intestinal content of dogs were examined for the presence of parasites. Faecal samples were collected and analysed using merthiolate iodine formaldehyde concentration method. A total of nine different parasite species were found, including five endoparasite (one protozoan, one cestode and three nematode species) and four ectoparasite species (two flea, one louse and one tick species). In the intestinal content, 3,162 specimens of four helminth species were found: Ancylostoma caninum (prevalence, 95.7%), Dipylidium caninum (45.7%), Toxocara canis (8.7%) and Trichuris vulpis (4.3%). A total of 394 ectoparasite specimens were identified, including Rhipicephalus sanguineus (prevalence, 100.0%), Heterodoxus spiniger (67.4%), Ctenocephalides canis (39.1%) and Ctenocephalides felis (17.4%). In the faeces, intestinal parasites were detected in 38 stray dogs (82.6%), including oocysts of Giardia sp. (2.2%) and eggs of the nematode A. caninum (82.6%). Neither eggs nor larval stages of D. caninum, T. canis or T. vulpis were detected in dog faeces. Sensitivity of faecal examination for A. caninum was 86.4% (95% confidence interval, 72.0-94.3) but zero percentage for the other intestinal helminth species. Our data show that stray dogs in northeast Brazil carry a multitude of zoonotic ecto- and endoparasites, posing a considerable risk for humans. With the exception of A. caninum, sensitivity of faecal examination was negligible.

  13. Predicting impacts of climate change on Fasciola hepatica risk.

    PubMed

    Fox, Naomi J; White, Piran C L; McClean, Colin J; Marion, Glenn; Evans, Andy; Hutchings, Michael R

    2011-01-10

    Fasciola hepatica (liver fluke) is a physically and economically devastating parasitic trematode whose rise in recent years has been attributed to climate change. Climate has an impact on the free-living stages of the parasite and its intermediate host Lymnaea truncatula, with the interactions between rainfall and temperature having the greatest influence on transmission efficacy. There have been a number of short term climate driven forecasts developed to predict the following season's infection risk, with the Ollerenshaw index being the most widely used. Through the synthesis of a modified Ollerenshaw index with the UKCP09 fine scale climate projection data we have developed long term seasonal risk forecasts up to 2070 at a 25 km square resolution. Additionally UKCIP gridded datasets at 5 km square resolution from 1970-2006 were used to highlight the climate-driven increase to date. The maps show unprecedented levels of future fasciolosis risk in parts of the UK, with risk of serious epidemics in Wales by 2050. The seasonal risk maps demonstrate the possible change in the timing of disease outbreaks due to increased risk from overwintering larvae. Despite an overall long term increase in all regions of the UK, spatio-temporal variation in risk levels is expected. Infection risk will reduce in some areas and fluctuate greatly in others with a predicted decrease in summer infection for parts of the UK due to restricted water availability. This forecast is the first approximation of the potential impacts of climate change on fasciolosis risk in the UK. It can be used as a basis for indicating where active disease surveillance should be targeted and where the development of improved mitigation or adaptation measures is likely to bring the greatest benefits.

  14. The Reliability and Predictive Validity of the Stalking Risk Profile.

    PubMed

    McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

    2016-06-14

    This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period (Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

  15. Risk factors for Toxoplasma gondii infection in sheep and cattle from Fernando de Noronha Island, Brazil.

    PubMed

    Magalhães, Fernando Jorge Rodrigues; Ribeiro-Andrade, Müller; Alcântara, Adrianne Mota de; Pinheiro, José Wilton; Sena, Maria José de; Porto, Wagnner José Nascimento; Vieira, Rafael Felipe da Costa; Mota, Rinaldo Aparecido

    2016-01-01

    Toxoplasmosis is a zoonotic disease of global distribution that affects all warm-blooded animals. The purpose of this investigation was to determine the prevalence of T. gondii infection and identify the risk factors associated with its occurrence in domestic ruminants raised on the island of Fernando de Noronha, Brazil, and to confirm that cattle and sheep raised in Fernando de Noronha Island present statistically different T. gondii prevalence rates. Serum samples were collected from sheep (n=240) and cattle (n=140) for the detection of antibodies by indirect immunofluorescence. Samples were collected from all the animals on all the farms. Risk factors were analyzed by univariate analysis and logistic regression. The prevalence rate of positive sheep was 85.0% while that of cattle was 10.7%. A multivariate analysis revealed that the site of contact of sheep with felines was a risk factor. For cattle, the risk factors identified in this study were: extensive farming system, water source, more than three cats per farm, and the presence of rats in feed storage locations. The findings revealed a significant difference in the prevalence rates in sheep and cattle raised in this insular environment.

  16. Patterns of Migration and Risks Associated with Leprosy among Migrants in Maranhão, Brazil

    PubMed Central

    Murto, Christine; Chammartin, Frédérique; Schwarz, Karolin; da Costa, Lea Marcia Melo; Kaplan, Charles; Heukelbach, Jorg

    2013-01-01

    Leprosy remains a public health problem in Brazil with new case incidence exceeding World Health Organization (WHO) goals in endemic clusters throughout the country. Migration can facilitate movement of disease between endemic and non-endemic areas, and has been considered a possible factor in continued leprosy incidence in Brazil. A study was conducted to investigate migration as a risk factor for leprosy. The study had three aims: (1) examine past five year migration as a risk factor for leprosy, (2) describe and compare geographic and temporal patterns of migration among past 5-year migrants with leprosy and a control group, and (3) examine social determinants of health associated with leprosy among past 5-year migrants. The study implemented a matched case-control design and analysis comparing individuals newly diagnosed with leprosy (n = 340) and a clinically unapparent control group (n = 340) without clinical signs of leprosy, matched for age, sex and location in four endemic municipalities in the state of Maranhão, northeastern Brazil. Fishers exact test was used to conduct bivariate analyses. A multivariate logistic regression analysis was employed to control for possible confounding variables. Eighty cases (23.5%) migrated 5-years prior to diagnosis, and 55 controls (16.2%) migrated 5-years prior to the corresponding case diagnosis. Past 5 year migration was found to be associated with leprosy (OR: 1.59; 95% CI 1.07–2.38; p = 0.02), and remained significantly associated with leprosy after controlling for leprosy contact in the family, household, and family/household contact. Poverty, as well as leprosy contact in the family, household and other leprosy contact, was associated with leprosy among past 5-year migrants in the bivariate analysis. Alcohol consumption was also associated with leprosy, a relevant risk factor in susceptibility to infection that should be explored in future research. Our findings provide insight into patterns of

  17. Common polygenic variation enhances risk prediction for Alzheimer's disease.

    PubMed

    Escott-Price, Valentina; Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D; Amouyel, Philippe; Williams, Julie

    2015-12-01

    The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

  18. Tuberculosis prevalence and risk factors for water buffalo in Pará, Brazil.

    PubMed

    Barbosa, José D; da Silva, Jenevaldo B; Rangel, Charles P; da Fonseca, Adivaldo H; Silva, Natália S; Bomjardim, Henrique A; Freitas, Nayra F Q R

    2014-03-01

    The prevalence of and possible risk factors for tuberculosis were studied in water buffalo from Pará, Brazil. In this study, 3,917 pregnant and nonpregnant female Murrah and Mediterranean buffaloes were studied; 2,089 originated from Marajó Island, and 1,108 were from the mainland. The comparative cervical tuberculin test was used as a diagnostic test for tuberculosis in these animals. The prevalence of positive buffaloes was 3.5 % (100/2,809) on Marajó Island and 7.2 % (80/1,108) on the mainland. The municipalities with the highest tuberculosis prevalence rates in animals were Ipixuna do Pará (10.1 %), Marapanim (9.8 %), Chaves (9.4 %), Paragominas (8.6 %), and Cachoeira do Arari (6.7 %). The tuberculosis prevalence was not significantly different between the Murrah (4.3 %) and Mediterranean (4.8 %) breeds or between pregnant (5 %) and nonpregnant (4.3 %) buffaloes. Tuberculosis was detected in water buffaloes from Pará, Brazil; the mainland buffalo exhibited the highest tuberculosis prevalence. These results indicate that this disease is dangerous to public health and buffalo farming in Pará.

  19. RISK FACTORS ASSOCIATED WITH AMERICAN CUTANEOUS LEISHMANIASIS IN AN ENDEMIC AREA OF BRAZIL

    PubMed Central

    de ARAUJO, Alberon Ribeiro; PORTELA, Nairomberg Cavalcanti; FEITOSA, Ana Paula Sampaio; da SILVA, Otamires Alves; XIMENES, Ricardo Andrade Arraes; ALVES, Luiz Carlos; BRAYNER, Fábio André

    2016-01-01

    SUMMARY Brazil is among the top five countries worldwide regarding the number of cases of leishmaniasis, which are present in all of the regions of the country. The northeastern region continues to have higher numbers of cases every year and in the state of Pernambuco, 34% of the municipalities are endemic for this disease. The diversity of vectors, reservoirs and etiological agents, in association with socioeconomic and environmental conditions, gives rise to factors that can modify the behavior of American cutaneous leishmaniasis. Consequently, the aim of the present study was to determine the risk factors associated with American cutaneous leishmaniasis in the municipality of Timbaúba, Brazil. A case-control study was conducted. A validated questionnaire was used for data collection. The study included 58 cases and 174 controls, and they were serologically diagnosed at the Oswaldo Cruz Foundation (FIOCRUZ). Our results showed that some factors were associated with American cutaneous leishmaniasis: biological (gender), economic (work activity, hours spent away from home and water supply) and peridomestic (presence of animals). In our study, the associations of these variables with leishmaniasis were linked to precarious housing conditions and poverty, which are parameters that can be managed in order to prevent the disease in this region. PMID:27982352

  20. Effective Genetic-Risk Prediction Using Mixed Models

    PubMed Central

    Golan, David; Rosset, Saharon

    2014-01-01

    For predicting genetic risk, we propose a statistical approach that is specifically adapted to dealing with the challenges imposed by disease phenotypes and case-control sampling. Our approach (termed Genetic Risk Scores Inference [GeRSI]), combines the power of fixed-effects models (which estimate and aggregate the effects of single SNPs) and random-effects models (which rely primarily on whole-genome similarities between individuals) within the framework of the widely used liability-threshold model. We demonstrate in extensive simulation that GeRSI produces predictions that are consistently superior to current state-of-the-art approaches. When applying GeRSI to seven phenotypes from the Wellcome Trust Case Control Consortium (WTCCC) study, we confirm that the use of random effects is most beneficial for diseases that are known to be highly polygenic: hypertension (HT) and bipolar disorder (BD). For HT, there are no significant associations in the WTCCC data. The fixed-effects model yields an area under the ROC curve (AUC) of 54%, whereas GeRSI improves it to 59%. For BD, using GeRSI improves the AUC from 55% to 62%. For individuals ranked at the top 10% of BD risk predictions, using GeRSI substantially increases the BD relative risk from 1.4 to 2.5. PMID:25279982

  1. A risk scoring system for prediction of haemorrhagic stroke.

    PubMed

    Zodpey, S P; Tiwari, R R

    2005-01-01

    The present pair-matched case control study was carried out at Government Medical College Hospital, Nagpur, India, a tertiary care hospital with the objective to devise and validate a risk scoring system for prediction of hemorrhagic stroke. The study consisted of 166 hospitalized CT scan proved cases of hemorrhagic stroke (ICD 9, 431-432), and a age and sex matched control per case. The controls were selected from patients who attended the study hospital for conditions other than stroke. On conditional multiple logistic regression five risk factors- hypertension (OR = 1.9. 95% Cl = 1.5-2.5). raised scrum total cholesterol (OR = 2.3, 95% Cl = 1.1-4.9). use of anticoagulants and antiplatelet agents (OR = 3.4, 95% Cl =1.1-10.4). past history of transient ischaemic attack (OR = 8.4, 95% Cl = 2.1- 33.6) and alcohol intake (OR = 2.1, 95% Cl = 1.3-3.6) were significant. These factors were ascribed statistical weights (based on regression coefficients) of 6, 8, 12, 21 and 8 respectively. The nonsignificant factors (diabetes mellitus, physical inactivity, obesity, smoking, type A personality, history of claudication, family history of stroke, history of cardiac diseases and oral contraceptive use in females) were not included in the development of scoring system. ROC curve suggested a total score of 21 to be the best cut-off for predicting haemorrhag stroke. At this cut-off the sensitivity, specificity, positive predictivity and Cohen's kappa were 0.74, 0.74, 0.74 and 0.48 respectively. The overall predictive accuracy of this additive risk scoring system (area under ROC curve by Wilcoxon statistic) was 0.79 (95% Cl = 0.73-0.84). Thus to conclude, if substantiated by further validation, this scorincy system can be used to predict haemorrhagic stroke, thereby helping to devise effective risk factor intervention strategy.

  2. Risk reversals in predictive testing for Huntington disease.

    PubMed Central

    Almqvist, E; Adam, S; Bloch, M; Fuller, A; Welch, P; Eisenberg, D; Whelan, D; Macgregor, D; Meschino, W; Hayden, M R

    1997-01-01

    The first predictive testing for Huntington disease (HD) was based on analysis of linked polymorphic DNA markers to estimate the likelihood of inheriting the mutation for HD. Limits to accuracy included recombination between the DNA markers and the mutation, pedigree structure, and whether DNA samples were available from family members. With direct tests for the HD mutation, we have assessed the accuracy of results obtained by linkage approaches when requested to do so by the test individuals. For six such individuals, there was significant disparity between the tests. Three went from a decreased risk to an increased risk, while in another three the risk was decreased. Knowledge of the potential reasons for these changes in results and impact of these risk reversals on both patients and the counseling team can assist in the development of strategies for the prevention and, where necessary, management of a risk reversal in any predictive testing program. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:9382108

  3. Prediction of cardiac risk in patients undergoing vascular surgery

    SciTech Connect

    Morise, A.P.; McDowell, D.E.; Savrin, R.A.; Goodwin, C.A.; Gabrielle, O.F.; Oliver, F.N.; Nullet, F.R.; Bekheit, S.; Jain, A.C.

    1987-03-01

    In an attempt to determine whether noninvasive cardiac testing could be used to assess cardiac risk in patients undergoing surgery for vascular disease, the authors studied 96 patients. Seventy-seven patients eventually underwent major vascular surgery with 11 (14%) experiencing a significant cardiac complication. Thallium imaging was much more likely to be positive (p less than 0.01) in patients with a cardiac complication; however, there was a significant number of patients with cardiac complications who had a positive history or electrocardiogram for myocardial infarction. When grouped by complication and history of infarction, thallium imaging, if negative, correctly predicted low cardiac risk in the group with a history of infarction. Thallium imaging, however, did not provide a clear separation of risk in those without a history of infarction. Age and coronary angiography, on the other hand, did reveal significant differences within the group without a history of infarction. The resting radionuclide ejection fraction followed a similar pattern to thallium imaging. It is concluded that a positive history of myocardial infarction at any time in the past is the strongest risk predictor in this population and that the predictive value of noninvasive testing is dependent on this factor. Considering these findings, a proposed scheme for assessing risk that will require further validation is presented.

  4. Transfer of sampling methods for studies on most-at-risk populations (MARPs) in Brazil.

    PubMed

    Barbosa Júnior, Aristides; Pascom, Ana Roberta Pati; Szwarcwald, Célia Landmann; Kendall, Carl; McFarland, Willi

    2011-01-01

    The objective of this paper was to describe the process of transferring two methods for sampling most-at-risk populations: respondent-driven sampling (RDS) and time-space sampling (TSS). The article describes steps in the process, the methods used in the 10 pilot studies, and lessons learned. The process was conducted in six steps, from a state-of-the-art seminar to a workshop on writing articles with the results of the pilot studies. The principal investigators reported difficulties in the fieldwork and data analysis, independently of the pilot sampling method. One of the most important results of the transfer process is that Brazil now has more than 100 researchers able to sample MARPs using RDS or TSS. The process also enabled the construction of baselines for MARPS, thus providing a broader understanding of the dynamics of HIV infection in the country and the use of evidence to plan the national response to the epidemic in these groups.

  5. Use of Chronic Kidney Disease to Enhance Prediction of Cardiovascular Risk in Those at Medium Risk.

    PubMed

    Chia, Yook Chin; Lim, Hooi Min; Ching, Siew Mooi

    2015-01-01

    Based on global cardiovascular (CV) risk assessment for example using the Framingham risk score, it is recommended that those with high risk should be treated and those with low risk should not be treated. The recommendation for those of medium risk is less clear and uncertain. We aimed to determine whether factoring in chronic kidney disease (CKD) will improve CV risk prediction in those with medium risk. This is a 10-year retrospective cohort study of 905 subjects in a primary care clinic setting. Baseline CV risk profile and serum creatinine in 1998 were captured from patients record. Framingham general cardiovascular disease risk score (FRS) for each patient was computed. All cardiovascular disease (CVD) events from 1998-2007 were captured. Overall, patients with CKD had higher FRS risk score (25.9% vs 20%, p = 0.001) and more CVD events (22.3% vs 11.9%, p = 0.002) over a 10-year period compared to patients without CKD. In patients with medium CV risk, there was no significant difference in the FRS score among those with and without CKD (14.4% vs 14.6%, p = 0.84) However, in this same medium risk group, patients with CKD had more CV events compared to those without CKD (26.7% vs 6.6%, p = 0.005). This is in contrast to patients in the low and high risk group where there was no difference in CVD events whether these patients had or did not have CKD. There were more CV events in the Framingham medium risk group when they also had CKD compared those in the same risk group without CKD. Hence factoring in CKD for those with medium risk helps to further stratify and identify those who are actually at greater risk, when treatment may be more likely to be indicated.

  6. Mapping risk of bovine fasciolosis in the south of Brazil using Geographic Information Systems.

    PubMed

    Dutra, L H; Molento, M B; Naumann, C R C; Biondo, A W; Fortes, F S; Savio, D; Malone, J B

    2010-04-19

    Fasciolosis, caused by Fasciola hepatica, is an endemic disease of ruminants that occurs in several countries of South America where it can lead to decreased production and fertility and, in severe cases, animal death. Although very prevalent, information on the epidemiology of the disease is incomplete in Brazil. The objective of the present study was to define the prevalence of F. hepatica in the livers of cattle from slaughterhouses and correlate the data with the animal's origin (climate and altitude) using a Geographic Information System (GIS). The data was used to create an epidemiological map of fasciolosis by state (Rio Grande do Sul, Santa Catarina, Paraná), by municipality (n=530) and by year (2003-2008). Information was analyzed using a databank from slaughterhouses with Federal Inspection Services of the Ministry of Agriculture. The highest cattle infection rate was found in the two most Southern states of Rio Grande do Sul (18.7%) and Santa Catarina (10.1%). Animals from the Campanha region of Rio Grande do Sul and from the central coast area of Santa Catarina had prevalences of greater than 40%. Cattle from low altitudes municipalities were significantly more likely to have the disease (p<0.05). No significant differences were found between high or low prevalence and ambient temperatures. Risk maps resulting from this study provide information on the epidemiology and transmission of F. hepatica in Southern Brazil needed for design of appropriate control measures to control economic impacts. F. hepatica may represent an important source of zoonotic infection of humans as well; therefore these findings may be complemented by future studies on human infections in high risk areas.

  7. Use of transgenic Aedes aegypti in Brazil: risk perception and assessment

    PubMed Central

    Aragão, Francisco José Lima; Colli, Walter; Dellagostin, Odir Antônio; Finardi-Filho, Flávio; Hirata, Mario Hiroyuki; Lira-Neto, Amaro de Castro; Almeida de Melo, Marcia; Nepomuceno, Alexandre Lima; Gorgônio da Nóbrega, Francisco; Delfino de Sousa, Gutemberg; Valicente, Fernando Hercos; Zanettini, Maria Helena Bodanese

    2016-01-01

    Abstract The OX513A strain of Aedes aegypti, which was developed by the British company Oxitec, expresses a self-limiting transgene that prevents larvae from developing to adulthood. In April 2014, the Brazilian National Technical Commission on Biosafety completed a risk assessment of OX513A and concluded that the strain did not present new biological risks to humans or the environment and could be released in Brazil. At that point, Brazil became the first country to approve the unconstrained release of a genetically modified mosquito. During the assessment, the commission produced a comprehensive list of – and systematically analysed – the perceived hazards. Such hazards included the potential survival to adulthood of immature stages carrying the transgene – should the transgene fail to be expressed or be turned off by exposure to sufficient environmental tetracycline. Other perceived hazards included the potential allergenicity and/or toxicity of the proteins expressed by the gene, the potential for gene flow or increased transmission of human pathogens and the occupation of vacant breeding sites by other vector species. The Zika epidemic both elevated the perceived importance of Ae. aegypti as a vector – among policy-makers and regulators as well as the general public – and increased concerns over the release of males of the OX513A strain. We have therefore reassessed the potential hazards. We found that release of the transgenic mosquitoes would still be both safe and of great potential value in the control of diseases spread by Ae. aegypti, such as chikungunya, dengue and Zika. PMID:27843167

  8. Ecological risk analysis of pesticides used on irrigated rice crops in southern Brazil.

    PubMed

    Vieira, Danielle Cristina; Noldin, José Alberto; Deschamps, Francisco C; Resgalla, Charrid

    2016-11-01

    Based on studies conducted in the past decade in the southern region of Brazil to determine residue levels of the pesticides normally used on irrigated rice crops, changes can be observed in relation to the presence of pesticides in the waters of the main river basins in Santa Catarina State. In previous harvests, the presence of residues of 7 pesticides was determined, with the herbicide bentazon and the insecticide carbofuran being the products showing highest frequency. Following toxicological tests conducted with 8 different test organisms, deterministic and probabilistic risk analysis was performed to assess the situation of the river basins in areas used for the production of irrigated rice. Of the species tested, the herbicide bentazon showed greatest toxicity toward plants, but did not present an ecological risk because in the worst-case scenario the highest concentration of this pesticide in the environment is 37 times lower than the lowest EC50/LC50 value obtained in the tests. The insecticide carbofuran, which had the highest toxicity toward the organisms used in the tests, presented an ecological risk in the deterministic analysis, but without any associated probability. The results highlight the need for increased efforts in training farmers in crop management practices and for the continual monitor of water bodies for the presence of pesticide residues.

  9. Cadmium and lead in seafood from the Aratu Bay, Brazil and the human health risk assessment.

    PubMed

    Silva da Araújo, Cecilia Freitas; Lopes, Mariângela Vieira; Vaz Ribeiro, Mirian Rocha; Porcino, Thiago Santos; Vaz Ribeiro, Amanda Santos; Rodrigues, Juliana Lima Gomes; do Prado Oliveira, Sérgio Soares; Menezes-Filho, José Antonio

    2016-04-01

    This study aimed to evaluate cadmium (Cd) and lead (Pb) levels in seafood and perform a risk assessment based on individual food consumption frequency of inhabitants of the Aratu Bay, Brazil. From December 2013 to November 2014, ready-to-market seafood, including fish [pititinga (Lile piquitinga) and small green eel (Gobionellus oceanicus)], mollusks [mussel (Mytella guyanensis) and oyster (Crassostrea rhizophorae)], and crustaceans [white shrimp (Litopenaeus schmitti) and blue crab (Callinectes exasperatus)], were purchased bimonthly from a local artisanal shellfish harvester. Metal levels were analyzed by graphite furnace atomic absorption spectrometry (GFAAS). Based on the volunteer’ seafood consumption, estimates of the non-carcinogenic target hazard quotients (THQs) were calculated. The annual concentrations (μg/g, w/w) of Cd were 0.007 (±0.001) in crustaceans, 0.001 (±0.0003) in fish, and 0.446 (±0.034) in mollusks. Lead levels were risk; however, 9.1 % presented THQs between ≥1 and <9.9. These data are important to inform the community of the imminent exposure risk through communication strategies, with the purpose of minimizing exposure and, consequently, the health effects associated with it.

  10. Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk

    PubMed Central

    Jarmul, Jamie A.; Pignone, Michael; Pletcher, Mark J.

    2015-01-01

    Background Hemoglobin A1C (HbA1C) is associated with increased risk of cardiovascular events, but its use for prediction of cardiovascular disease (CVD) events in combination with conventional risk factors has not been well defined. Methods and Results To understand the effect of HbA1C on CVD risk in the context of other CVD risk factors, we analyzed HbA1C and other CVD risk factor measurements in 2000 individuals aged 40-79 years old without pre-existing diabetes or cardiovascular disease from the 2011-2012 NHANES survey. The resulting regression model was used to predict the HbA1C distribution based on individual patient characteristics. We then calculated post-test 10-year atherosclerotic cardiovascular disease (ASCVD) risk incorporating the actual versus predicted HbA1C, according to established methods, for a set of example scenarios. Age, gender, race/ethnicity and traditional cardiovascular risk factors were significant predictors of HbA1C in our model, with the expected HbA1C distribution being significantly higher in non-Hispanic black, non-Hispanic Asian and Hispanic individuals than non-Hispanic white/other individuals. Incorporating the expected HbA1C distribution into pretest ASCVD risk has a modest effect on post-test ASCVD risk. In the patient examples we assessed, having an HbA1C < 5.7% reduced post-test risk by 0.4%-2.0% points, whereas having an HbA1C ≥ 6.5% increased post-test risk by 1.0%-2.5% points, depending on the scenario. The post-test risk increase from having an HbA1C ≥ 6.5 % tends to approximate the risk increase from being five years older in age. Conclusions HbA1C has modest effects on predicted ASCVD risk when considered in the context of conventional risk factors. PMID:26349840

  11. Risk prediction with machine learning and regression methods.

    PubMed

    Steyerberg, Ewout W; van der Ploeg, Tjeerd; Van Calster, Ben

    2014-07-01

    This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.

  12. Improving default risk prediction using Bayesian model uncertainty techniques.

    PubMed

    Kazemi, Reza; Mosleh, Ali

    2012-11-01

    Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis.

  13. The Impact of Dietary and Metabolic Risk Factors on Cardiovascular Diseases and Type 2 Diabetes Mortality in Brazil

    PubMed Central

    de Oliveira Otto, Marcia C.; Afshin, Ashkan; Micha, Renata; Khatibzadeh, Shahab; Fahimi, Saman; Singh, Gitanjali; Danaei, Goodarz; Sichieri, Rosely; Monteiro, Carlos A; Louzada, Maria L. C.; Ezzati, Majid; Mozaffarian, Dariush

    2016-01-01

    Background Trends in food availability and metabolic risk factors in Brazil suggest a shift toward unhealthy dietary patterns and increased cardiometabolic disease risk, yet little is known about the impact of dietary and metabolic risk factors on cardiometabolic mortality in Brazil. Methods Based on data from Global Burden of Disease (GBD) Study, we used comparative risk assessment to estimate the burden of 11 dietary and 4 metabolic risk factors on mortality due to cardiovascular diseases and diabetes in Brazil in 2010. Information on national diets and metabolic risks were obtained from the Brazilian Household Budget Survey, the Food and Agriculture Organization database, and large observational studies including Brazilian adults. Relative risks for each risk factor were obtained from meta-analyses of randomized trials or prospective cohort studies; and disease-specific mortality from the GBD 2010 database. We quantified uncertainty using probabilistic simulation analyses, incorporating uncertainty in dietary and metabolic data and relative risks by age and sex. Robustness of findings was evaluated by sensitivity to varying feasible optimal levels of each risk factor. Results In 2010, high systolic blood pressure (SBP) and suboptimal diet were the largest contributors to cardiometabolic deaths in Brazil, responsible for 214,263 deaths (95% uncertainty interval [UI]: 195,073 to 233,936) and 202,949 deaths (95% UI: 194,322 to 211,747), respectively. Among individual dietary factors, low intakes of fruits and whole grains and high intakes of sodium were the largest contributors to cardiometabolic deaths. For premature cardiometabolic deaths (before age 70 years, representing 40% of cardiometabolic deaths), the leading risk factors were suboptimal diet (104,169 deaths; 95% UI: 99,964 to 108,002), high SBP (98,923 deaths; 95%UI: 92,912 to 104,609) and high body-mass index (BMI) (42,643 deaths; 95%UI: 40,161 to 45,111). Conclusion suboptimal diet, high SBP, and high

  14. Risk Prediction Models for Lung Cancer: A Systematic Review.

    PubMed

    Gray, Eoin P; Teare, M Dawn; Stevens, John; Archer, Rachel

    2016-03-01

    Many lung cancer risk prediction models have been published but there has been no systematic review or comprehensive assessment of these models to assess how they could be used in screening. We performed a systematic review of lung cancer prediction models and identified 31 articles that related to 25 distinct models, of which 11 considered epidemiological factors only and did not require a clinical input. Another 11 articles focused on models that required a clinical assessment such as a blood test or scan, and 8 articles considered the 2-stage clonal expansion model. More of the epidemiological models had been externally validated than the more recent clinical assessment models. There was varying discrimination, the ability of a model to distinguish between cases and controls, with an area under the curve between 0.57 and 0.879 and calibration, the model's ability to assign an accurate probability to an individual. In our review we found that further validation studies need to be considered; especially for the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial 2012 Model Version (PLCOM2012) and Hoggart models, which recorded the best overall performance. Future studies will need to focus on prediction rules, such as optimal risk thresholds, for models for selective screening trials. Only 3 validation studies considered prediction rules when validating the models and overall the models were validated using varied tests in distinct populations, which made direct comparisons difficult. To improve this, multiple models need to be tested on the same data set with considerations for sensitivity, specificity, model accuracy, and positive predictive values at the optimal risk thresholds.

  15. Body Mass Index, Waist Circumference, Body Adiposity Index, and Risk for Type 2 Diabetes in Two Populations in Brazil: General and Amerindian

    PubMed Central

    Alvim, Rafael de Oliveira; Mourao-Junior, Carlos Alberto; de Oliveira, Camila Maciel; Krieger, José E.; Mill, José G.; Pereira, Alexandre C.

    2014-01-01

    Objective The use of the anthropometric indices of adiposity, especially body mass index and waist circumference in the prediction of diabetes mellitus has been widely explored. Recently, a new body composition index, the body adiposity index was proposed. The aim of this study was to compare the effectiveness of body mass index, waist circumference, and body adiposity index in the risk assessment for type 2 diabetes mellitus. Design and methods A total of 1,572 individuals from the general population of Vitoria City, Brazil and 620 Amerindians from the Aracruz Indian Reserve, Brazil were randomly selected. BMI, waist circumference, and BAI were determined according to a standard protocol. Type 2 diabetes mellitus was diagnosed by the presence of fasting glucose ≥126 mg/dL or by the use of antidiabetic drugs. Results The area under the curve was similar for all anthropometric indices tested in the Amerindian population, but with very different sensitivities or specificities. In women from the general population, the area under the curve of waist circumference was significantly higher than that of the body adiposity index. Regarding risk assessment for type 2 diabetes mellitus, the body adiposity index was a better risk predictor than body mass index and waist circumference in the Amerindian population and was the index with highest odds ratio for type 2 diabetes mellitus in men from the general population, while in women from the general population waist circumference was the best risk predictor. Conclusion Body adiposity index was the best risk predictor for type 2 diabetes mellitus in the Amerindian population and men from the general population. Our data suggest that the body adiposity index is a useful tool for the risk assessment of type 2 diabetes mellitus in admixture populations. PMID:24937307

  16. Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

    PubMed Central

    2014-01-01

    Background To date, our ability to accurately identify patients at high risk from suicidal behaviour, and thus to target interventions, has been fairly limited. This study examined a large pool of factors that are potentially associated with suicide risk from the comprehensive electronic medical record (EMR) and to derive a predictive model for 1–6 month risk. Methods 7,399 patients undergoing suicide risk assessment were followed up for 180 days. The dataset was divided into a derivation and validation cohorts of 4,911 and 2,488 respectively. Clinicians used an 18-point checklist of known risk factors to divide patients into low, medium, or high risk. Their predictive ability was compared with a risk stratification model derived from the EMR data. The model was based on the continuation-ratio ordinal regression method coupled with lasso (which stands for least absolute shrinkage and selection operator). Results In the year prior to suicide assessment, 66.8% of patients attended the emergency department (ED) and 41.8% had at least one hospital admission. Administrative and demographic data, along with information on prior self-harm episodes, as well as mental and physical health diagnoses were predictive of high-risk suicidal behaviour. Clinicians using the 18-point checklist were relatively poor in predicting patients at high-risk in 3 months (AUC 0.58, 95% CIs: 0.50 – 0.66). The model derived EMR was superior (AUC 0.79, 95% CIs: 0.72 – 0.84). At specificity of 0.72 (95% CIs: 0.70-0.73) the EMR model had sensitivity of 0.70 (95% CIs: 0.56-0.83). Conclusion Predictive models applied to data from the EMR could improve risk stratification of patients presenting with potential suicidal behaviour. The predictive factors include known risks for suicide, but also other information relating to general health and health service utilisation. PMID:24628849

  17. Osteoporosis risk prediction using machine learning and conventional methods.

    PubMed

    Kim, Sung Kean; Yoo, Tae Keun; Oh, Ein; Kim, Deok Won

    2013-01-01

    A number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women, and compared with the ability of a conventional clinical decision tool, osteoporosis self-assessment tool (OST). We collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Surveys (KNHANES V-1). The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and logistic regression (LR) based on various predictors associated with low bone density. The learning models were compared with OST. SVM had significantly better area under the curve (AUC) of the receiver operating characteristic (ROC) than ANN, LR, and OST. Validation on the test set showed that SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0%. We were the first to perform comparisons of the performance of osteoporosis prediction between the machine learning and conventional methods using population-based epidemiological data. The machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

  18. Methods and Techniques for Risk Prediction of Space Shuttle Upgrades

    NASA Technical Reports Server (NTRS)

    Hoffman, Chad R.; Pugh, Rich; Safie, Fayssal

    1998-01-01

    Since the Space Shuttle Accident in 1986, NASA has been trying to incorporate probabilistic risk assessment (PRA) in decisions concerning the Space Shuttle and other NASA projects. One major study NASA is currently conducting is in the PRA area in establishing an overall risk model for the Space Shuttle System. The model is intended to provide a tool to predict the Shuttle risk and to perform sensitivity analyses and trade studies including evaluation of upgrades. Marshall Space Flight Center (MSFC) and its prime contractors including Pratt and Whitney (P&W) are part of the NASA team conducting the PRA study. MSFC responsibility involves modeling the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). A major challenge that faced the PRA team is modeling the shuttle upgrades. This mainly includes the P&W High Pressure Fuel Turbopump (HPFTP) and the High Pressure Oxidizer Turbopump (HPOTP). The purpose of this paper is to discuss the various methods and techniques used for predicting the risk of the P&W redesigned HPFTP and HPOTP.

  19. Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models.

    PubMed

    Stevenson, Jennifer M; Williams, Josceline L; Burnham, Thomas G; Prevost, A Toby; Schiff, Rebekah; Erskine, S David; Davies, J Graham

    2014-01-01

    Adverse drug reaction (ADR) risk-prediction models for use in older adults have been developed, but it is not clear if they are suitable for use in clinical practice. This systematic review aimed to identify and investigate the quality of validated ADR risk-prediction models for use in older adults. Standard computerized databases, the gray literature, bibliographies, and citations were searched (2012) to identify relevant peer-reviewed studies. Studies that developed and validated an ADR prediction model for use in patients over 65 years old, using a multivariable approach in the design and analysis, were included. Data were extracted and their quality assessed by independent reviewers using a standard approach. Of the 13,423 titles identified, only 549 were associated with adverse outcomes of medicines use. Four met the inclusion criteria. All were conducted in inpatient cohorts in Western Europe. None of the models satisfied the four key stages in the creation of a quality risk prediction model; development and validation were completed, but impact and implementation were not assessed. Model performance was modest; area under the receiver operator curve ranged from 0.623 to 0.73. Study quality was difficult to assess due to poor reporting, but inappropriate methods were apparent. Further work needs to be conducted concerning the existing models to enable the development of a robust ADR risk-prediction model that is externally validated, with practical design and good performance. Only then can implementation and impact be assessed with the aim of generating a model of high enough quality to be considered for use in clinical care to prioritize older people at high risk of suffering an ADR.

  20. Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models

    PubMed Central

    Stevenson, Jennifer M; Williams, Josceline L; Burnham, Thomas G; Prevost, A Toby; Schiff, Rebekah; Erskine, S David; Davies, J Graham

    2014-01-01

    Adverse drug reaction (ADR) risk-prediction models for use in older adults have been developed, but it is not clear if they are suitable for use in clinical practice. This systematic review aimed to identify and investigate the quality of validated ADR risk-prediction models for use in older adults. Standard computerized databases, the gray literature, bibliographies, and citations were searched (2012) to identify relevant peer-reviewed studies. Studies that developed and validated an ADR prediction model for use in patients over 65 years old, using a multivariable approach in the design and analysis, were included. Data were extracted and their quality assessed by independent reviewers using a standard approach. Of the 13,423 titles identified, only 549 were associated with adverse outcomes of medicines use. Four met the inclusion criteria. All were conducted in inpatient cohorts in Western Europe. None of the models satisfied the four key stages in the creation of a quality risk prediction model; development and validation were completed, but impact and implementation were not assessed. Model performance was modest; area under the receiver operator curve ranged from 0.623 to 0.73. Study quality was difficult to assess due to poor reporting, but inappropriate methods were apparent. Further work needs to be conducted concerning the existing models to enable the development of a robust ADR risk-prediction model that is externally validated, with practical design and good performance. Only then can implementation and impact be assessed with the aim of generating a model of high enough quality to be considered for use in clinical care to prioritize older people at high risk of suffering an ADR. PMID:25278750

  1. Risk prediction models for contrast induced nephropathy: systematic review

    PubMed Central

    Silver, Samuel A; Shah, Prakesh M; Chertow, Glenn M; Wald, Ron

    2015-01-01

    Objectives To look at the available literature on validated prediction models for contrast induced nephropathy and describe their characteristics. Design Systematic review. Data sources Medline, Embase, and CINAHL (cumulative index to nursing and allied health literature) databases. Review methods Databases searched from inception to 2015, and the retrieved reference lists hand searched. Dual reviews were conducted to identify studies published in the English language of prediction models tested with patients that included derivation and validation cohorts. Data were extracted on baseline patient characteristics, procedural characteristics, modelling methods, metrics of model performance, risk of bias, and clinical usefulness. Eligible studies evaluated characteristics of predictive models that identified patients at risk of contrast induced nephropathy among adults undergoing a diagnostic or interventional procedure using conventional radiocontrast media (media used for computed tomography or angiography, and not gadolinium based contrast). Results 16 studies were identified, describing 12 prediction models. Substantial interstudy heterogeneity was identified, as a result of different clinical settings, cointerventions, and the timing of creatinine measurement to define contrast induced nephropathy. Ten models were validated internally and six were validated externally. Discrimination varied in studies that were validated internally (C statistic 0.61-0.95) and externally (0.57-0.86). Only one study presented reclassification indices. The majority of higher performing models included measures of pre-existing chronic kidney disease, age, diabetes, heart failure or impaired ejection fraction, and hypotension or shock. No prediction model evaluated its effect on clinical decision making or patient outcomes. Conclusions Most predictive models for contrast induced nephropathy in clinical use have modest ability, and are only relevant to patients receiving contrast for

  2. Meta-Prediction of MTHFR Gene Polymorphism Mutations and Associated Risk for Colorectal Cancer

    PubMed Central

    Yu, C. H.

    2016-01-01

    The methylenetetrahydrofolate reductase (MTHFR) gene is one of the most investigated of the genes associated with chronic human diseases because of its associations with hyperhomocysteinemia and toxicity. It has been proposed as a prototype gene for the prevention of colorectal cancer (CRC). The major objectives of this meta-analysis were to examine the polymorphism-mutation patterns of MTHFR and their associations with risk for CRC as well as potential contributing factors for mutations and disease risks. This analysis included 33,626 CRC cases and 48,688 controls across 92 studies for MTHFR 677 and 16,367 cases and 24,874 controls across 54 studies for MTHFR 1298, comprising data for various racial and ethnic groups, both genders, and multiple cancer sites. MTHFR 677 homozygous TT genotype was protective (p < .05) for CRC for all included populations; however, with heterogeneity across various racial–ethnic groups and opposing findings, it was a risk genotype for the subgroup of Hispanics (p < .01). Additional countries for which subgroup analyses resulted in 677 TT as a risk genotype included Turkey, Romania, Croatia, Hungary, Portugal, Mexico, Brazil, U.S. Hawai’i, Taiwan, India, and Egypt. Countries with the highest mutation rates and risks for both MTHFR 677 and 1298 genotypes are presented using global maps to visualize the grouping patterns. Meta-predictive analyses revealed that air pollution levels were associated with gene polymorphisms for both genotypes. Future nursing research should be conducted to develop proactive measures to protect populations in cities where air pollution causes more deaths. PMID:26858257

  3. Landmark risk prediction of residual life for breast cancer survival.

    PubMed

    Parast, Layla; Cai, Tianxi

    2013-09-10

    The importance of developing personalized risk prediction estimates has become increasingly evident in recent years. In general, patient populations may be heterogenous and represent a mixture of different unknown subtypes of disease. When the source of this heterogeneity and resulting subtypes of disease are unknown, accurate prediction of survival may be difficult. However, in certain disease settings, the onset time of an observable short-term event may be highly associated with these unknown subtypes of disease and thus may be useful in predicting long-term survival. One approach to incorporate short-term event information along with baseline markers for the prediction of long-term survival is through a landmark Cox model, which assumes a proportional hazards model for the residual life at a given landmark point. In this paper, we use this modeling framework to develop procedures to assess how a patient's long-term survival trajectory may change over time given good short-term outcome indications along with prognosis on the basis of baseline markers. We first propose time-varying accuracy measures to quantify the predictive performance of landmark prediction rules for residual life and provide resampling-based procedures to make inference about such accuracy measures. Simulation studies show that the proposed procedures perform well in finite samples. Throughout, we illustrate our proposed procedures by using a breast cancer dataset with information on time to metastasis and time to death. In addition to baseline clinical markers available for each patient, a chromosome instability genetic score, denoted by CIN25, is also available for each patient and has been shown to be predictive of survival for various types of cancer. We provide procedures to evaluate the incremental value of CIN25 for the prediction of residual life and examine how the residual life profile changes over time. This allows us to identify an informative landmark point, t(0) , such that

  4. Childhood BMI Trajectories Predicting Cardiovascular Risk in Adolescence

    PubMed Central

    Boyer, Brittany P.; Nelson, Jackie A.; Holub, Shayla C.

    2015-01-01

    Objective The current study compared growth parameters of girls’ and boys’ BMI trajectories from infancy to middle childhood, and evaluated these parameters as predictors of cardiovascular disease (CVD) risk in adolescence. Methods Using 657 children from the NICHD Study of Early Child Care and Youth Development (SECCYD), quadratic growth curve analyses were conducted to establish growth parameters (intercept, slope, quadratic term) for girls and boys from 15 months to age 10 ½. Parameters were compared across gender and evaluated as predictors of a CVD risk index at age 15, controlling for characteristics of the adiposity rebound (AR) including age at which it occurred and children’s BMI at the rebound. Results Boys had more extreme trajectories of growth compared to girls with higher initial BMI at 15 months (intercept), more rapid declines in BMI before the AR (slope), and sharper rebound growth in BMI after the rebound (quadratic term). For boys and girls, higher intercept, slope, and quadratic term values predicted higher CVD risk at age 15, controlling for characteristics of the AR. Conclusions Findings suggest that individuals at risk for developing CVD later in life may be identified before the AR by elevated BMI at 15 months and slow BMI declines. Due to the importance of early intervention in altering lifelong health trajectories, consistent BMI monitoring is essential in identifying high-risk children. PMID:25746172

  5. Seroprevalence and risk factors associated with ovine toxoplasmosis in Northeast Brazil

    PubMed Central

    Andrade, Milena M. Clementino; Carneiro, Mariangela; Medeiros, Andrea D.; Neto, Valter Andrade; Vitor, Ricardo W.A.

    2013-01-01

    Serum samples of 930 sheep were tested by ELISA to assess the prevalence of anti-Toxoplasma gondii antibodies and to identify risk factors associated with the presence of toxoplasmosis in two regions of Rio Grande do Norte (Northeast Brazil), with different climatic conditions. The overall estimated prevalence was 22.1%, with 26.3% and 17.8% positive sheep in Leste Potiguar and Central Potiguar regions, respectively. Among the positive sheep, 18.1% had low-avidity IgG antibodies, suggesting the occurrence of recent toxoplasmosis. The risk factors for toxoplasmosis in sheep were: presence of cats (odds ratio (OR) = 1.55; confidence interval (CI) 95% = 1.11–2.16), age of the animals, with adults presenting a greater chance of infection (OR = 2.44; CI 95% = 1.58–3.75), and the use of running water (OR = 1.61; CI 95% = 1.25–2.09), characterizing the existence of transmission by sporulated oocysts of T. gondii in the environment. PMID:23707895

  6. Health risks due to pre-harvesting sugarcane burning in São Paulo State, Brazil.

    PubMed

    Paraiso, Maria Leticia de Souza; Gouveia, Nelson

    2015-01-01

    After 2003, a new period of expansion of the sugarcane culture began in Brazil. Pre-harvesting burning of sugarcane straw is an agricultural practice that, despite the nuisance for the population and pollution generated, still persisted in over 70% of the municipalities of São Paulo State in 2010. In order to study the distribution of this risk factor, an ecological epidemiological study was conducted associating the rates of deaths and hospital admissions for respiratory diseases, for each municipality in the State, with the exposure to the pre-harvesting burning of sugarcane straw. A Bayesian multivariate regression model, controlled for the possible effects of socioeconomic and climate (temperature, humidity, and rainfall) variations, has been used. The effect on health was measured by the standardized mortality and morbidity ratio. The measures of exposure to the pre-harvesting burning used were: percentage of the area of sugarcane harvested with burning, average levels of aerosol, and number of outbreaks of burning. The autocorrelation between data was controlled using a neighborhood matrix. It was observed that the increase in the number of outbreaks of burning was significantly associated with higher rates of hospital admissions for respiratory disease in children under five years old. Pre-harvesting burning of sugarcane effectively imposes risk to population health and therefore it should be eliminated.

  7. Risk factors for Toxoplasma gondii and Neospora caninum seropositivity in buffaloes in Paraiba State, Brazil.

    PubMed

    Brasil, Arthur Willian de Lima; Parentoni, Roberta Nunes; Feitosa, Thais Ferreira; Bezerra, Camila de Sousa; Vilela, Vinicius Longo Ribeiro; Pena, Hilda Fátima de Jesus; de Azevedo, Sergio Santos

    2015-01-01

    The aims of this survey were to determine the frequency of anti-Toxoplasma gondii and anti-Neospora caninum antibodies and to identify the risk factors associated with seropositivity among buffaloes in the state of Paraíba, Brazil. This survey included 136 buffaloes belonging to 14 herds. To detect anti-T. gondii and anti-N. caninum antibodies, the indirect fluorescent antibody test (IFAT) was used. Among the 136 samples analyzed, 17 (12.5%) were positive for anti-T. gondii antibodies with titers ranging from 64 to 1,024, and 26 (19.1%) for anti-N. caninum with titers from 200 to 1,600. Animals seropositive for both T. gondii and N. caninum were found in 10 of the 14 herds (71.4%). Semi-intensive management systems (odds ratio = 2.99) and presence of pigs (odds ratio = 4.33) were identified as risk factors for T. gondii and N. caninum, respectively. It can be suggested that T. gondii and N. caninum are widespread in buffaloes in Paraíba, and that additional surveys are needed in order to ascertain the importance of these agents for this species and for pigs, and the influence of the farming type on occurrences of seropositive animals.

  8. Trichomonas vaginalis PREVALENCE AND RISK FACTORS FOR WOMEN IN SOUTHERN BRAZIL

    PubMed Central

    AMBROZIO, Cíntia Lima; NAGEL, Andréia Saggin; JESKE, Sabrina; BRAGANÇA, Guilherme Cassão Marques; BORSUK, Sibele; VILLELA, Marcos Marreiro

    2016-01-01

    SUMMARY Trichomonas vaginalis infections have been associated with other diseases so that epidemiological studies of the parasite are important and help to prevent the spread of the disease. This study aimed to determine the prevalence of T. vaginalis in female patients of 19 counties in southwestern Rio Grande do Sul, Brazil. For diagnosis, was used direct examination, followed by applying a socio-epidemiological questionnaire. We analyzed 300 women and 9% were infected by Trichomonas vaginalis. The highest frequency occurred in women between 18 and 39 years old, single/divorced/widowed, whose family income was at one minimum wage or less, and they had not completed the primary school. Statistically significant risk factors were: women reporting two or more sexual partners in the last year were 3.3 times more likely to acquire the parasite, and those in use of oral contraceptives were 2.7 times more likely to have T. vaginalis. Importantly, 33% of the asymptomatic women were infected, and most of the negative results were from women presenting symptoms consistent with the infection. The findings emphasize that it is necessary to expand the knowledge of individuals about the disease, especially among women with the above mentioned risk factors and also to include the regular screening of Trichomonas vaginalis infections in health centers. PMID:27680166

  9. Potential risks of the residue from Samarco's mine dam burst (Bento Rodrigues, Brazil).

    PubMed

    Segura, Fabiana Roberta; Nunes, Emilene Arusievicz; Paniz, Fernanda Pollo; Paulelli, Ana Carolina Cavalheiro; Rodrigues, Gabriela Braga; Braga, Gilberto Úbida Leite; Dos Reis Pedreira Filho, Walter; Barbosa, Fernando; Cerchiaro, Giselle; Silva, Fábio Ferreira; Batista, Bruno Lemos

    2016-11-01

    On November 5th, 2015, Samarco's iron mine dam - called Fundão - spilled 50-60 million m(3) of mud into Gualaxo do Norte, a river that belongs to Rio Doce Basin. Approximately 15 km(2) were flooded along the rivers Gualaxo do Norte, Carmo and Doce, reaching the Atlantic Ocean on November 22nd, 2015. Six days after, our group collected mud, soil and water samples in Bento Rodrigues (Minas Gerais, Brazil), which was the first impacted area. Overall, the results, water samples - potable and surface water from river - presented chemical elements concentration according to Brazilian environmental legislations, except silver concentration in surface water that ranged from 1.5 to 1087 μg L(-1). In addition, water mud-containing presented Fe and Mn concentrations approximately 4-fold higher than the maximum limit for water bodies quality assessment, according to Brazilian laws. Mud particle size ranged from 1 to 200 μm. SEM-EDS spot provided us some semi quantitative data. Leaching/extraction tests suggested that Ba, Pb, As, Sr, Fe, Mn and Al have high potential mobilization from mud to water. Low microbial diversity in mud samples compared to background soil samples. Toxicological bioassays (HepG2 and Allium cepa) indicated potential risks of cytotoxicity and DNA damage in mud and soil samples used in both assays. The present study provides preliminary information aiming to collaborate to the development of future works for monitoring and risk assessment.

  10. The ARIC predictive model reliably predicted risk of type II diabetes in Asian populations

    PubMed Central

    2012-01-01

    Background Identification of high-risk individuals is crucial for effective implementation of type 2 diabetes mellitus prevention programs. Several studies have shown that multivariable predictive functions perform as well as the 2-hour post-challenge glucose in identifying these high-risk individuals. The performance of these functions in Asian populations, where the rise in prevalence of type 2 diabetes mellitus is expected to be the greatest in the next several decades, is relatively unknown. Methods Using data from three Asian populations in Singapore, we compared the performance of three multivariate predictive models in terms of their discriminatory power and calibration quality: the San Antonio Health Study model, Atherosclerosis Risk in Communities model and the Framingham model. Results The San Antonio Health Study and Atherosclerosis Risk in Communities models had better discriminative powers than using only fasting plasma glucose or the 2-hour post-challenge glucose. However, the Framingham model did not perform significantly better than fasting glucose or the 2-hour post-challenge glucose. All published models suffered from poor calibration. After recalibration, the Atherosclerosis Risk in Communities model achieved good calibration, the San Antonio Health Study model showed a significant lack of fit in females and the Framingham model showed a significant lack of fit in both females and males. Conclusions We conclude that adoption of the ARIC model for Asian populations is feasible and highly recommended when local prospective data is unavailable. PMID:22497781

  11. Predicting risk of adverse drug reactions in older adults

    PubMed Central

    Lavan, Amanda Hanora; Gallagher, Paul

    2016-01-01

    Adverse drug reactions (ADRs) are common in older adults, with falls, orthostatic hypotension, delirium, renal failure, gastrointestinal and intracranial bleeding being amongst the most common clinical manifestations. ADR risk increases with age-related changes in pharmacokinetics and pharmacodynamics, increasing burden of comorbidity, polypharmacy, inappropriate prescribing and suboptimal monitoring of drugs. ADRs are a preventable cause of harm to patients and an unnecessary waste of healthcare resources. Several ADR risk tools exist but none has sufficient predictive value for clinical practice. Good clinical practice for detecting and predicting ADRs in vulnerable patients includes detailed documentation and regular review of prescribed and over-the-counter medications through standardized medication reconciliation. New medications should be prescribed cautiously with clear therapeutic goals and recognition of the impact a drug can have on multiple organ systems. Prescribers should regularly review medication efficacy and be vigilant for ADRs and their contributory risk factors. Deprescribing should occur at an individual level when drugs are no longer efficacious or beneficial or when safer alternatives exist. Inappropriate prescribing and unnecessary polypharmacy should be minimized. Comprehensive geriatric assessment and the use of explicit prescribing criteria can be useful in this regard. PMID:26834959

  12. The development of an early warning system for climate-sensitive disease risk with a focus on dengue epidemics in Southeast Brazil.

    PubMed

    Lowe, Rachel; Bailey, Trevor C; Stephenson, David B; Jupp, Tim E; Graham, Richard J; Barcellos, Christovam; Carvalho, Marilia Sá

    2013-02-28

    Previous studies demonstrate statistically significant associations between disease and climate variations, highlighting the potential for developing climate-based epidemic early warning systems. However, limitations include failure to allow for non-climatic confounding factors, limited geographical/temporal resolution, or lack of evaluation of predictive validity. Here, we consider such issues for dengue in Southeast Brazil using a spatio-temporal generalised linear mixed model with parameters estimated in a Bayesian framework, allowing posterior predictive distributions to be derived in time and space. This paper builds upon a preliminary study by Lowe et al. but uses extended, more recent data and a refined model formulation, which, amongst other adjustments, incorporates past dengue risk to improve model predictions. For the first time, a thorough evaluation and validation of model performance is conducted using out-of-sample predictions and demonstrates considerable improvement over a model that mirrors current surveillance practice. Using the model, we can issue probabilistic dengue early warnings for pre-defined 'alert' thresholds. With the use of the criterion 'greater than a 50% chance of exceeding 300 cases per 100,000 inhabitants', there would have been successful epidemic alerts issued for 81% of the 54 regions that experienced epidemic dengue incidence rates in February-April 2008, with a corresponding false alarm rate of 25%. We propose a novel visualisation technique to map ternary probabilistic forecasts of dengue risk. This technique allows decision makers to identify areas where the model predicts with certainty a particular dengue risk category, to effectively target limited resources to those districts most at risk for a given season.

  13. Recent Enhancements to the Genetic Risk Prediction Model BRCAPRO

    PubMed Central

    Mazzola, Emanuele; Blackford, Amanda; Parmigiani, Giovanni; Biswas, Swati

    2015-01-01

    BRCAPRO is a widely used model for genetic risk prediction of breast cancer. It is a function within the R package BayesMendel and is used to calculate the probabilities of being a carrier of a deleterious mutation in one or both of the BRCA genes, as well as the probability of being affected with breast and ovarian cancer within a defined time window. Both predictions are based on information contained in the counselee’s family history of cancer. During the last decade, BRCAPRO has undergone several rounds of successive refinements: the current version is part of release 2.1 of BayesMendel. In this review, we showcase some of the most notable features of the software resulting from these recent changes. We provide examples highlighting each feature, using artificial pedigrees motivated by complex clinical examples. We illustrate how BRCAPRO is a comprehensive software for genetic risk prediction with many useful features that allow users the flexibility to incorporate varying amounts of available information. PMID:25983549

  14. Next-generation ecological risk assessment: Predicting risk from molecular initiation to ecosystem service delivery.

    PubMed

    Forbes, Valery E; Galic, Nika

    2016-05-01

    Ecological risk assessment is the process of evaluating how likely it is that the environment may be impacted as the result of exposure to one or more chemicals and/or other stressors. It is not playing as large a role in environmental management decisions as it should be. A core challenge is that risk assessments often do not relate directly or transparently to protection goals. There have been exciting developments in in vitro testing and high-throughput systems that measure responses to chemicals at molecular and biochemical levels of organization, but the linkage between such responses and impacts of regulatory significance - whole organisms, populations, communities, and ecosystems - are not easily predictable. This article describes some recent developments that are directed at bridging this gap and providing more predictive models that can make robust links between what we typically measure in risk assessments and what we aim to protect.

  15. Peak Pc Prediction in Conjunction Analysis: Conjunction Assessment Risk Analysis. Pc Behavior Prediction Models

    NASA Technical Reports Server (NTRS)

    Vallejo, J.J.; Hejduk, M.D.; Stamey, J. D.

    2015-01-01

    Satellite conjunction risk typically evaluated through the probability of collision (Pc). Considers both conjunction geometry and uncertainties in both state estimates. Conjunction events initially discovered through Joint Space Operations Center (JSpOC) screenings, usually seven days before Time of Closest Approach (TCA). However, JSpOC continues to track objects and issue conjunction updates. Changes in state estimate and reduced propagation time cause Pc to change as event develops. These changes a combination of potentially predictable development and unpredictable changes in state estimate covariance. Operationally useful datum: the peak Pc. If it can reasonably be inferred that the peak Pc value has passed, then risk assessment can be conducted against this peak value. If this value is below remediation level, then event intensity can be relaxed. Can the peak Pc location be reasonably predicted?

  16. Risk Factors for Bartonella species Infection in Blood Donors from Southeast Brazil

    PubMed Central

    Diniz, Pedro Paulo Vissotto de Paiva; Velho, Paulo Eduardo Neves Ferreira; Pitassi, Luiza Helena Urso; Drummond, Marina Rovani; Lania, Bruno Grosselli; Barjas-Castro, Maria Lourdes; Sowy, Stanley; Breitschwerdt, Edward B.; Scorpio, Diana Gerardi

    2016-01-01

    Bacteria from the genus Bartonella are emerging blood-borne bacteria, capable of causing long-lasting infection in marine and terrestrial mammals, including humans. Bartonella are generally well adapted to their main host, causing persistent infection without clinical manifestation. However, these organisms may cause severe disease in natural or accidental hosts. In humans, Bartonella species have been detected from sick patients presented with diverse disease manifestations, including cat scratch disease, trench fever, bacillary angiomatosis, endocarditis, polyarthritis, or granulomatous inflammatory disease. However, with the advances in diagnostic methods, subclinical bloodstream infection in humans has been reported, with the potential for transmission through blood transfusion been recently investigated by our group. The objective of this study was to determine the risk factors associated with Bartonella species infection in asymptomatic blood donors presented at a major blood bank in Southeastern Brazil. Five hundred blood donors were randomly enrolled and tested for Bartonella species infection by specialized blood cultured coupled with high-sensitive PCR assays. Epidemiological questionnaires were designed to cover major potential risk factors, such as age, gender, ethnicity, contact with companion animals, livestock, or wild animals, bites from insects or animal, economical status, among other factors. Based on multivariate logistic regression, bloodstream infection with B. henselae or B. clarridgeiae was associated with cat contact (adjusted OR: 3.4, 95% CI: 1.1–9.6) or history of tick bite (adjusted OR: 3.7, 95% CI: 1.3–13.4). These risk factors should be considered during donor screening, as bacteremia by these Bartonella species may not be detected by traditional laboratory screening methods, and it may be transmitted by blood transfusion. PMID:26999057

  17. Risk Prediction for Early CKD in Type 2 Diabetes

    PubMed Central

    Gao, Peggy; Lee, Shun Fu; Heinze, Georg; Clase, Catherine M.; Tobe, Sheldon; Teo, Koon K.; Gerstein, Hertzel; Mann, Johannes F.E.

    2015-01-01

    Background and objectives Quantitative data for prediction of incidence and progression of early CKD are scarce in individuals with type 2 diabetes. Therefore, two risk prediction models were developed for incidence and progression of CKD after 5.5 years and the relative effect of predictors were ascertained. Design, setting, participants, & measurements Baseline and prospective follow-up data of two randomized clinical trials, ONgoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial (ONTARGET) and Outcome Reduction with Initial Glargine Intervention (ORIGIN), were used as development and independent validation cohorts, respectively. Individuals aged ≥55 years with type 2 diabetes and normo- or microalbuminuria at baseline were included. Incidence or progression of CKD after 5.5 years was defined as new micro- or macroalbuminuria, doubling of creatinine, or ESRD. The competing risk of death was considered as an additional outcome state in the multinomial logistic models. Results Of the 6766 ONTARGET participants with diabetes, 1079 (15.9%) experienced incidence or progression of CKD, and 1032 (15.3%) died. The well calibrated, parsimonious laboratory prediction model incorporating only baseline albuminuria, eGFR, sex, and age exhibited an externally validated c-statistic of 0.68 and an R2 value of 10.6%. Albuminuria, modeled to depict the difference between baseline urinary albumin/creatinine ratio and the threshold for micro- or macroalbuminuria, was mostly responsible for the predictive performance. Inclusion of clinical predictors, such as glucose control, diabetes duration, number of prescribed antihypertensive drugs, previous vascular events, or vascular comorbidities, increased the externally validated c-statistic and R2 value only to 0.69 and 12.1%, respectively. Explained variation was largely driven by renal and not clinical predictors. Conclusions Albuminuria and eGFR were the most important factors to predict onset and

  18. Predicting the use of Individualized Risk Assessment for Breast Cancer

    PubMed Central

    Bartle-Haring, Suzanne; Toviessi, Paula; Katafiasz, Heather

    2008-01-01

    Purpose The purpose of this study was to investigate the decision to obtain individualized risk assessment after a breast cancer education session. Methods A sample of both African American and Caucasian women was used to determine if there were differences by race/ethnicity in uptake of the assessment and differences in the variables that were most predictive of uptake. The sample included 166 women between the ages of 18 and 80. Sixty-two percent of the sample were African American women. Key Findings The results suggested that African American women and Caucasian women used different factors and used other factors differently to decide whether or not to obtain an individualized risk assessment. Conclusions and Implications These results are discussed within the context of health disparities among ethnic minority and Caucasian women with implications for breast cancer control programs. The results of this study would suggest that knowledge alone does not lead to opting for a personalized risk assessment, and that African American and Caucasian women use different pieces of information, or information differently to make decision about getting more personalized information about risk. PMID:18319147

  19. [Severe intimate partner violence risk prediction scale-revised].

    PubMed

    Echeburúa, Enrique; Amor, Pedro Javier; Loinaz, Ismael; de Corral, Paz

    2010-11-01

    The aim of this study was to describe the psychometric properties of the Severe Intimate Partner Violence Risk Prediction Scale and to revise it in order to ponderate the 20 items according to their discriminant capacity and to solve the missing item problem. The sample for this study consisted of 450 male batterers who were reported to the police station. The victims were classified as high-risk (18.2%), moderate-risk (45.8%) and low-risk (36%), depending on the cutoff scores in the original scale. Internal consistency (Cronbach's alpha=.72) and interrater reliability (r=.73) were acceptable. The point biserial correlation coefficient between each item and the corrected total score of the 20-item scale was calculated to determine the most discriminative items, which were associated with the context of intimate partner violence in the last month, with the male batterer's profile and with the victim's vulnerability. A revised scale (EPV-R) with new cutoff scores and indications on how to deal with the missing items were proposed in accordance with these results. This easy-to-use tool appears to be suitable to the requirements of criminal justice professionals and is intended for use in safety planning. Implications of these results for further research are discussed.

  20. Towards malaria risk prediction in Afghanistan using remote sensing

    PubMed Central

    2010-01-01

    Background Malaria is a significant public health concern in Afghanistan. Currently, approximately 60% of the population, or nearly 14 million people, live in a malaria-endemic area. Afghanistan's diverse landscape and terrain contributes to the heterogeneous malaria prevalence across the country. Understanding the role of environmental variables on malaria transmission can further the effort for malaria control programme. Methods Provincial malaria epidemiological data (2004-2007) collected by the health posts in 23 provinces were used in conjunction with space-borne observations from NASA satellites. Specifically, the environmental variables, including precipitation, temperature and vegetation index measured by the Tropical Rainfall Measuring Mission and the Moderate Resolution Imaging Spectoradiometer, were used. Regression techniques were employed to model malaria cases as a function of environmental predictors. The resulting model was used for predicting malaria risks in Afghanistan. The entire time series except the last 6 months is used for training, and the last 6-month data is used for prediction and validation. Results Vegetation index, in general, is the strongest predictor, reflecting the fact that irrigation is the main factor that promotes malaria transmission in Afghanistan. Surface temperature is the second strongest predictor. Precipitation is not shown as a significant predictor, as it may not directly lead to higher larval population. Autoregressiveness of the malaria epidemiological data is apparent from the analysis. The malaria time series are modelled well, with provincial average R2 of 0.845. Although the R2 for prediction has larger variation, the total 6-month cases prediction is only 8.9% higher than the actual cases. Conclusions The provincial monthly malaria cases can be modelled and predicted using satellite-measured environmental parameters with reasonable accuracy. The Third Strategic Approach of the WHO EMRO Malaria Control and

  1. Risk Factors and Prediction Models for Retinopathy of Prematurity

    PubMed Central

    Senthil, Mallika Prem; Salowi, Mohamad Aziz; Bujang, Mohamad Adam; Kueh, Adeline; Siew, Chong Min; Sumugam, Kala; Gaik, Chan Lee; Kah, Tan Aik

    2015-01-01

    Objectives To develop a simple prediction model for the pre-screening of Retinopathy of Prematurity (ROP) among preterm babies. Methods This was a prospective study. The test dataset (January 2007 until December 2010) was used to construct risk prediction models, and the validation dataset (January 2011 until March 2012) was used to validate the models developed from the test dataset. Two prediction models were produced using the test dataset based on logistic regression equations in which the development of ROP was used as the outcome. Results The sensitivity and specificity for model 1 [gestational age (GA), birth weight (BW), intraventricular haemorrhage (IVH) and respiratory distress syndrome (RDS)] was 82 % and 81.7%, respectively; for model 2, (GA and BW) the sensitivity and specificity were 80.5% and 80.3%, respectively. Conclusion Model 2 was preferable, as it only required two predictors (GA and BW). Our prediction model can be used for early detection of ROP to avoid poor outcomes. PMID:28239269

  2. Design and prospective evaluation of a risk-based surveillance system for shrimp grow-out farms in northeast Brazil.

    PubMed

    Marques, Ana Rita; Pereira, Marcelo; Ferreira Neto, Jose Soares; Ferreira, Fernando

    2015-12-01

    The farming of Pacific white shrimp Litopennaeus vannamei in northeast Brazil, has proven to be a promising sector. However, the farming of Pacific white shrimp in Brazil has been affected negatively by the occurrence of viral diseases, threatening this sector's expansion and sustainability. For this reason, the drafting of a surveillance system for early detection and definition of freedom from viral diseases, whose occurrence could result in high economic loses, is of the utmost importance. The stochastic model AquaVigil was implemented to prospectively evaluate different surveillance strategies to determine freedom from disease and identify the strategy with the lowest sampling efforts, making the best use of available resources through risk-based surveillance. The worked example presented was designed for regional application for the state of Ceará and can easily be applied to other Brazilian states. The AquaVigil model can analyse any risk-based surveillance system that considers a similar outline to the strategy here presented.

  3. Supplementation with Brazil nuts and green tea extract regulates targeted biomarkers related to colorectal cancer risk in humans.

    PubMed

    Hu, Ying; McIntosh, Graeme H; Le Leu, Richard K; Somashekar, Roshini; Meng, Xing Q; Gopalsamy, Geetha; Bambaca, Libby; McKinnon, Ross A; Young, Graeme P

    2016-12-01

    Se and green tea have been shown in epidemiological, observational and preclinical studies to be inversely related to the risk of developing colorectal cancer (CRC). However, there are limited studies to evaluate their regulatory effects on genes/proteins that relate to CRC oncogenesis in human subjects, such as selenoproteins, WNT signalling pathway, inflammation and methylation. This study examined the effects of supplementation of Se using Brazil nuts and green tea extract (GTE) capsules, alone and in combination, on targeted biomarkers. In total, thirty-two volunteers (>50 years of age) with plasma Se≤1·36 µmol/l were randomised to one of three treatment groups: nine to Se (approximately 48 µg/d) as six Brazil nuts, eleven to four GTE capsules (800 mg (-)-epigallocatechin-3-gallate) and twelve to a combination of Brazil nuts and GTE. Blood and rectal biopsies were obtained before and after each intervention. Plasma Se levels, rectal selenoprotein P (SePP) and β-catenin mRNA increased significantly in subjects consuming Brazil nuts alone or in combination, whereas rectal DNA methyltransferase (DNMT1) and NF-κB mRNA were reduced significantly in subjects consuming GTE alone or in combination. None of the interventions significantly affected rectal acetylated histone H3 or Ki-67 expression at the protein level or plasma C-reactive protein. Effects of the combination of Brazil nuts and GTE did not differ from what would be expected from either agent alone. In conclusion, supplementation of Brazil nuts and/or GTE regulates targeted biomarkers related to CRC oncogenesis, specifically genes associated with selenoproteins (SePP), WNT signalling (β-catenin), inflammation (NF-κB) and methylation (DNMT1). Their combination does not appear to provide additional effects compared with either agent alone.

  4. Injury risk prediction from computational simulations of ocular blast loading.

    PubMed

    Weaver, Ashley A; Stitzel, Sarah M; Stitzel, Joel D

    2017-04-01

    A predictive Lagrangian-Eulerian finite element eye model was used to analyze 2.27 and 0.45 kg trinitrotoluene equivalent blasts detonated from 24 different locations. Free air and ground level blasts were simulated directly in front of the eye and at lateral offset locations with box, average, less protective, and more protective orbital anthropometries, resulting in 96 simulations. Injury risk curves were developed for hyphema, lens dislocation, retinal damage, and globe rupture from experimental and computational data to compute risk from corneoscleral stress and intra-ocular pressure computational outputs. Corneoscleral stress, intra-ocular pressure, and injury risks increased when the blast size was larger and located nearer to the eye. Risks ranged from 20-100 % for hyphema, 1-100 % for lens dislocation, 2-100 % for retinal damage, and 0-98 % for globe rupture depending on the blast condition. Orbital geometry affected the stresses, pressures, and associated ocular injury risks of the blast conditions simulated. Orbital geometries that more fully surrounded the eye such as the more protective orbit tended to produce higher corneoscleral stresses and compression of the eye against the surrounding rigid orbit contributing to high stresses as the blast wave propagated. However, the more protective orbit tended to produce lower intra-ocular pressures in comparison with the other three orbital geometries which may indicate that the more protective orbit inhibits propagation of the blast wave and reduces ocular loading. Results of this parametric computational study of ocular blast loading are valuable to the design of eye protection equipment and the mitigation of blast-related eye injuries.

  5. Value-at-risk prediction using context modeling

    NASA Astrophysics Data System (ADS)

    Denecker, K.; van Assche, S.; Crombez, J.; Vander Vennet, R.; Lemahieu, I.

    2001-04-01

    In financial market risk measurement, Value-at-Risk (VaR) techniques have proven to be a very useful and popular tool. Unfortunately, most VaR estimation models suffer from major drawbacks: the lognormal (Gaussian) modeling of the returns does not take into account the observed fat tail distribution and the non-stationarity of the financial instruments severely limits the efficiency of the VaR predictions. In this paper, we present a new approach to VaR estimation which is based on ideas from the field of information theory and lossless data compression. More specifically, the technique of context modeling is applied to estimate the VaR by conditioning the probability density function on the present context. Tree-structured vector quantization is applied to partition the multi-dimensional state space of both macroeconomic and microeconomic priors into an increasing but limited number of context classes. Each class can be interpreted as a state of aggregation with its own statistical and dynamic behavior, or as a random walk with its own drift and step size. Results on the US S&P500 index, obtained using several evaluation methods, show the strong potential of this approach and prove that it can be applied successfully for, amongst other useful applications, VaR and volatility prediction. The October 1997 crash is indicated in time.

  6. Tryptophan Predicts the Risk for Future Type 2 Diabetes

    PubMed Central

    Chen, Tianlu; Zheng, Xiaojiao; Ma, Xiaojing; Bao, Yuqian; Ni, Yan; Hu, Cheng; Rajani, Cynthia; Huang, Fengjie; Zhao, Aihua; Jia, Weiping; Jia, Wei

    2016-01-01

    Recently, 5 amino acids were identified and verified as important metabolites highly associated with type 2 diabetes (T2D) development. This report aims to assess the association of tryptophan with the development of T2D and to evaluate its performance with existing amino acid markers. A total of 213 participants selected from a ten-year longitudinal Shanghai Diabetes Study (SHDS) were examined in two ways: 1) 51 subjects who developed diabetes and 162 individuals who remained metabolically healthy in 10 years; 2) the same 51 future diabetes and 23 strictly matched ones selected from the 162 healthy individuals. Baseline fasting serum tryptophan concentrations were quantitatively measured using ultra-performance liquid chromatography triple quadruple mass spectrometry. First, serum tryptophan level was found significantly higher in future T2D and was positively and independently associated with diabetes onset risk. Patients with higher tryptophan level tended to present higher degree of insulin resistance and secretion, triglyceride and blood pressure. Second, the prediction potential of tryptophan is non-inferior to the 5 existing amino acids. The predictive performance of the combined score improved after taking tryptophan into account. Our findings unveiled the potential of tryptophan as a new marker associated with diabetes risk in Chinese populations. The addition of tryptophan provided complementary value to the existing amino acid predictors. PMID:27598004

  7. Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

    NASA Astrophysics Data System (ADS)

    Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam

    2011-03-01

    This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

  8. Toxoplasma gondii in goats from Curitiba, Paraná, Brazil: risks factors and epidemiology.

    PubMed

    Garcia, Guilherme; Sotomaior, Cristina; do Nascimento, Aguinaldo José; Navarro, Italmar Teodorico; Soccol, Vanete Thomaz

    2012-01-01

    Toxoplasmosis is a zoonosis caused by Toxoplasma gondii, a protozoan with wide geographical distribution and minimal parasitic specificity that affects many species of wild and domestic animals. In livestock, especially in small ruminants like goats, toxoplasmosis can cause abortion and the birth of weak animals, leading to economic losses to farmers, and is a major source of human infection. This is a seroepidemiological study of toxoplasmosis in goats in the state of Paraná, Brazil. Sera from 405 goats from the metropolitan mesoregion of Curitiba, eastern state, were tested by the enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence antibody test (IFAT). Information on properties and goat characteristics was also collected using questionnaires. The prevalence of toxoplasmosis was 39.41 and 35.96% by ELISA and IFAT, respectively. T. gondii antibody prevalence increased with age. The risk factors for T. gondii infection in goats were: age over one year; exposure to cats, type of management and purpose of breeding. Other epidemiological factors and relevant control measures are discussed in the current study.

  9. Maternal Alcohol Consumption during Pregnancy and Early Age Leukemia Risk in Brazil

    PubMed Central

    Ferreira, Jeniffer Dantas; Couto, Arnaldo Cézar; Pombo-de-Oliveira, Maria S.; Koifman, Sergio

    2015-01-01

    Objectives. To investigate the association between the maternal alcohol consumption during pregnancy and early age leukemia (EAL) in offspring. Methods. Datasets were analyzed from a case-control study carried out in Brazil during 1999–2007. Data were obtained by maternal interviews using a standardized questionnaire. The present study included 675 children (193 acute lymphoid leukemia (ALL), 59 acute myeloid leukemia (AML), and 423 controls). Unconditional logistic regression was performed, and adjusted odds ratios (adj. OR) on the association between alcohol consumption and EAL were ascertained. Results. Alcohol consumption was reported by 43% of ALL and 39% of AML case mothers and 35.5% of controls'. Beer consumption before and during pregnancy was associated with ALL in crude analysis (OR = 1.54, 95% CI, 1.08–2.19), although in adjusted analysis no statistical significance was found. For weekly intake of ≤1 glass (adj. OR = 1.30, 95% CI, 0.71–2.36) and ≥1 glass/week (adj. OR = 1.47, 95% CI, 0.88–2.46) a potential dose-response was observed (P trend < 0.03). Conclusion. This study failed to support the hypothesis of an increased risk of EAL associated with maternal alcohol intake during pregnancy, neither with the interaction with tobacco nor with alcohol consumption. PMID:26090439

  10. Respiratory syncytial virus seasonality in Brazil: implications for the immunisation policy for at-risk populations

    PubMed Central

    Freitas, André Ricardo Ribas; Donalisio, Maria Rita

    2016-01-01

    Respiratory syncytial virus (RSV) infection is the leading cause of hospitalisation for respiratory diseases among children under 5 years old. The aim of this study was to analyse RSV seasonality in the five distinct regions of Brazil using time series analysis (wavelet and Fourier series) of the following indicators: monthly positivity of the immunofluorescence reaction for RSV identified by virologic surveillance system, and rate of hospitalisations per bronchiolitis and pneumonia due to RSV in children under 5 years old (codes CID-10 J12.1, J20.5, J21.0 and J21.9). A total of 12,501 samples with 11.6% positivity for RSV (95% confidence interval 11 - 12.2), varying between 7.1 and 21.4% in the five Brazilian regions, was analysed. A strong trend for annual cycles with a stable stationary pattern in the five regions was identified through wavelet analysis of the indicators. The timing of RSV activity by Fourier analysis was similar between the two indicators analysed and showed regional differences. This study reinforces the importance of adjusting the immunisation period for high risk population with the monoclonal antibody palivizumab taking into account regional differences in seasonality of RSV. PMID:27120006

  11. Predictive model of avian electrocution risk on overhead power lines.

    PubMed

    Dwyer, J F; Harness, R E; Donohue, K

    2014-02-01

    Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤ 33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red-tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution-risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high-risk poles for retrofitting.

  12. Predicting Low-Risk Prostate Cancer from Transperineal Saturation Biopsies

    PubMed Central

    van Leeuwen, Pim J.; Siriwardana, Amila; Roobol, Monique; Ting, Francis; Nieboer, Daan; Thompson, James; Delprado, Warick; Haynes, Anne-Marie; Brenner, Phillip; Stricker, Phillip

    2016-01-01

    Introduction. To assess the performance of five previously described clinicopathological definitions of low-risk prostate cancer (PC). Materials and Methods. Men who underwent radical prostatectomy (RP) for clinical stage ≤T2, PSA <10 ng/mL, Gleason score <8 PC, diagnosed by transperineal template-guided saturation biopsy were included. The performance of five previously described criteria (i.e., criteria 1–5, criterion 1 stringent (Gleason score 6 + ≤5 mm total max core length PC + ≤3 mm max per core length PC) up to criterion 5 less stringent (Gleason score 6-7 with ≤5% Gleason grade 4) was analysed to assess ability of each to predict insignificant disease in RP specimens (defined as Gleason score ≤6 and total tumour volume <2.5 mL, or Gleason score 7 with ≤5% grade 4 and total tumour volume <0.7 mL). Results. 994 men who underwent RP were included. Criterion 4 (Gleason score 6) performed best with area under the curve of receiver operating characteristics 0.792. At decision curve analysis, criterion 4 was deemed clinically the best performing transperineal saturation biopsy-based definition for low-risk PC. Conclusions. Gleason score 6 disease demonstrated a superior trade-off between sensitivity and specificity for clarifying low-risk PC that can guide treatment and be used as reference test in diagnostic studies. PMID:27148459

  13. Spatial clustering and local risk of leprosy in São Paulo, Brazil

    PubMed Central

    Yamamura, Mellina; Arroyo, Luiz Henrique; Popolin, Marcela Paschoal; Chiaravalloti Neto, Francisco; Palha, Pedro Fredemir; Uchoa, Severina Alice da Costa; Pieri, Flávia Meneguetti; Pinto, Ione Carvalho; Fiorati, Regina Célia; de Queiroz, Ana Angélica Rêgo; Belchior, Aylana de Souza; dos Santos, Danielle Talita; Garcia, Maria Concebida da Cunha; Crispim, Juliane de Almeida; Alves, Luana Seles; Berra, Thaís Zamboni; Arcêncio, Ricardo Alexandre

    2017-01-01

    Background Although the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D) is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method. Methods Data were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk—RR) of leprosy. Maps considering these risks and their confidence intervals were constructed. Results A total of 434 cases were identified, including 188 (43.31%) borderline leprosy and 101 (23.28%) lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75%) presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000) contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721–4.267). Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133–52.984) and 15.24 (95%CI = 10.114–22.919). Conclusion These findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting. PMID:28241038

  14. Carnival or football, is there a real risk for acquiring dengue fever in Brazil during holidays seasons?

    PubMed

    Aguiar, Maíra; Rocha, Filipe; Pessanha, José Eduardo Marques; Mateus, Luis; Stollenwerk, Nico

    2015-02-16

    More than 600,000 football fans, coming from all over the world, were expected to visit Brazil during the FIFA World Cup 2014. International travel can become a public health problem when the visitors start to become sick, needing medical intervention and eventually hospitalization. The occurrence of dengue fever infections in Brazil is persistent and has been increasing since the 1980s, and the health authorities were expected to take preventive measures and to warn the visitors about the risks during the tournament period. Before the World Cup started, studies have been published stating that dengue could be a significant problem in some of the Brazilian cities hosting the games. These conclusions were taken after a brief observation of the available data, analyzing its mean and standard deviation only, or based on seasonal climate forecasts, causing alarm for the world cup in Brazil. Here, with a more careful data analysis, we show that the seasonality of the disease plays a major role in dengue transmission. The density of dengue cases in Brazil is residual during winter in the Southern hemisphere (mid June to mid September) and the fans of football were not likely to get dengue during the tournament period.

  15. Carnival or football, is there a real risk for acquiring dengue fever in Brazil during holidays seasons?

    PubMed Central

    Aguiar, Maíra; Rocha, Filipe; Pessanha, José Eduardo Marques; Mateus, Luis; Stollenwerk, Nico

    2015-01-01

    More than 600,000 football fans, coming from all over the world, were expected to visit Brazil during the FIFA World Cup 2014. International travel can become a public health problem when the visitors start to become sick, needing medical intervention and eventually hospitalization. The occurrence of dengue fever infections in Brazil is persistent and has been increasing since the 1980s, and the health authorities were expected to take preventive measures and to warn the visitors about the risks during the tournament period. Before the World Cup started, studies have been published stating that dengue could be a significant problem in some of the Brazilian cities hosting the games. These conclusions were taken after a brief observation of the available data, analyzing its mean and standard deviation only, or based on seasonal climate forecasts, causing alarm for the world cup in Brazil. Here, with a more careful data analysis, we show that the seasonality of the disease plays a major role in dengue transmission. The density of dengue cases in Brazil is residual during winter in the Southern hemisphere (mid June to mid September) and the fans of football were not likely to get dengue during the tournament period. PMID:25684648

  16. Carnival or football, is there a real risk for acquiring dengue fever in Brazil during holidays seasons?

    NASA Astrophysics Data System (ADS)

    Aguiar, Maíra; Rocha, Filipe; Pessanha, José Eduardo Marques; Mateus, Luis; Stollenwerk, Nico

    2015-02-01

    More than 600,000 football fans, coming from all over the world, were expected to visit Brazil during the FIFA World Cup 2014. International travel can become a public health problem when the visitors start to become sick, needing medical intervention and eventually hospitalization. The occurrence of dengue fever infections in Brazil is persistent and has been increasing since the 1980s, and the health authorities were expected to take preventive measures and to warn the visitors about the risks during the tournament period. Before the World Cup started, studies have been published stating that dengue could be a significant problem in some of the Brazilian cities hosting the games. These conclusions were taken after a brief observation of the available data, analyzing its mean and standard deviation only, or based on seasonal climate forecasts, causing alarm for the world cup in Brazil. Here, with a more careful data analysis, we show that the seasonality of the disease plays a major role in dengue transmission. The density of dengue cases in Brazil is residual during winter in the Southern hemisphere (mid June to mid September) and the fans of football were not likely to get dengue during the tournament period.

  17. A quantitative risk assessment model for Vibrio parahaemolyticus in raw oysters in Sao Paulo State, Brazil.

    PubMed

    Sobrinho, Paulo de S Costa; Destro, Maria T; Franco, Bernadette D G M; Landgraf, Mariza

    2014-06-16

    A risk assessment of Vibrio parahaemolyticus associated with raw oysters produced and consumed in São Paulo State was developed. The model was built according to the United States Food and Drug Administration framework for risk assessment. The outcome of the exposure assessment estimated the prevalence and density of pathogenic V. parahaemolyticus in raw oysters from harvest to consumption. The result of the exposure step was combined with a Beta-Poisson dose-response model to estimate the probability of illness. The model predicted that the average risks per serving of raw oysters were 4.7×10(-4), 6.0×10(-4), 4.7×10(-4) and 3.1×10(-4) for spring, summer, fall and winter, respectively. Sensitivity analyses indicated that the most influential variables on the risk of illness were the total density of V. parahaemolyticus at harvest, transport temperature, relative prevalence of pathogenic strains and storage time at retail. Only storage time under refrigeration at retail showed negative correlation with the risk of illness.

  18. Assessing the Relative Ecological Importance and Deforestation Risks of Unprotected Areas in Western Brazil Using Landsat, CBERS and Quantum GIS

    NASA Astrophysics Data System (ADS)

    Smith, A.; Sevilla, C.; Lanclos, A.; Carson, C.; Larson, J.; Sankaran, M.; Saad, M.

    2012-12-01

    In addition to understanding Brazilian policies and currently utilized methodologies, the measurement of the impacts of deforestation is essential for enhancing techniques to reduce deforestation in the future. Adverse impacts of deforestation include biodiversity loss, increased carbon dioxide emissions, and a reduced rate of evapotranspiration, all of which contribute directly or indirectly to global warming. With the continual growth in population in developing countries such as Brazil, increased demands are placed on infrastructural development and food production. As a result, forested areas are cleared for agricultural production. Recently, exploration for hydrocarbons in Western Brazil has also intensified as a means to stimulate the economy, as abundant oil and gas is believed to be found in these regions. Unfortunately, hydrocarbon-rich regions of Western Brazil are also home to thousands of species. Many of these regions are as of yet untapped but are at risk of ecological disruption as a result of impending human activity. This project utilized Landsat 5 TM to monitor deforestation in a subsection of the Brazilian states of Rondônia and Amazonas. A risk map identifying areas susceptible to future deforestation, based on factors such as proximity to roads, bodies of water, cities, and proposed hydrocarbon activities such as pipeline construction, was created. Areas at higher risk of clearance were recommended to be a target for enhanced monitoring and law enforcement. In addition, an importance map was created based on biodiversity and location of endangered species. This map was used to identify potential areas for future protection. A Chinese-Brazilian satellite, CBERS 2B CCD was also utilized for comparison. The NDVI model was additionally replicated in Quantum GIS, an open source software, so that local communities and policymakers could benefit without having to pay for expensive ArcGIS software. The capabilities of VIIRS were also investigated to

  19. A Genetics-based Biomarker Risk Algorithm for Predicting Risk of Alzheimer’s Disease

    PubMed Central

    Lutz, Michael W.; Sundseth, Scott S.; Burns, Daniel K.; Saunders, Ann M.; Hayden, Kathleen M.; Burke, James R.; Welsh-Bohmer, Kathleen A.; Roses, Allen D.

    2016-01-01

    Background A straightforward, reproducible blood-based test that predicts age dependent risk of Alzheimer’s disease (AD) could be used as an enrichment tool for clinical development of therapies. This study evaluated the prognostic performance of a genetics-based biomarker risk algorithm (GBRA) established on a combination of Apolipoprotein E (APOE)/Translocase of outer mitochondrial membrane 40 homolog (TOMM40) genotypes and age, then compare it to cerebrospinal fluid (CSF) biomarkers, neuroimaging and neurocognitive tests using data from two independent AD cohorts. Methods The GBRA was developed using data from the prospective Bryan-ADRC study (n=407; 86 conversion events (mild cognitive impairment (MCI) or late onset Alzheimer’s disease (LOAD)). The performance of the algorithm was tested using data from the ADNI study (n=660; 457 individuals categorized as MCI or LOAD). Results The positive predictive values (PPV) and negative predictive values (NPV) of the GBRA are in the range of 70–80%. The relatively high odds ratio (approximately 3–5) and significant net reclassification index (NRI) scores comparing the GBRA to a version based on APOE and age alone support the value of the GBRA in risk prediction for MCI due to LOAD. Performance of the GBRA compares favorably with CSF and imaging (fMRI) biomarkers. In addition, the GBRA “high” and “low” AD-risk categorizations correlated well with pathological CSF biomarker levels, PET amyloid burden and neurocognitive scores. Conclusions Unlike dynamic markers (i.e., imaging, protein or lipid markers) that may be influenced by factors unrelated to disease, genomic DNA is easily collected, stable, and the technical methods for measurement are robust, inexpensive, and widely available. The performance characteristics of the GBRA support its use as a pharmacogenetic enrichment tool for LOAD delay of onset clinical trials, and merits further evaluation for its clinical utility in evaluating therapeutic

  20. Cardiovascular risk factors in children and adolescents living in an urban area of Southeast of Brazil: Ouro Preto Study.

    PubMed

    Cândido, Ana Paula C; Benedetto, Raquel; Castro, Ana Paula P; Carmo, Joseane S; Nicolato, Roney L C; Nascimento-Neto, Raimundo M; Freitas, Renata N; Freitas, Sílvia N; Caiaffa, Waleska T; Machado-Coelho, George L L

    2009-11-01

    This study aims to identify risk factors for cardiovascular disorders in schoolchildren living in Ouro Preto City, Brazil. A cross-sectional study was carried out in a population-based sampling of schoolchildren (6-14 years old), randomly selected and stratified by the proportion of students according to age and gender in each schools of the city. Biochemical, clinical and anthropometric variables as well as physical activity and family history were used in a logistic regression model for obesity or arterial hypertension. Out of 780 schoolchildren sampled, the risk of obesity was greater in subjects presenting high triglyceride and low high density lipoprotein-cholesterol levels, and those whose parents were obese, while the risk of hypertension was high in obese subjects and those who presented low birth weight. It was observed that 44.4% of the schoolchildren were exposed to two or three cardiovascular disease (CVD) risk factors and 8.2% were exposed to four or six factors. These findings should be considered in preventive measures to reduce the future risk for CVD among schoolchildren in Brazil.

  1. Predicting Pneumonitis Risk: A Dosimetric Alternative to Mean Lung Dose

    SciTech Connect

    Tucker, Susan L.; Mohan, Radhe; Liengsawangwong, Raweewan; Martel, Mary K.; Liao Zhongxing

    2013-02-01

    Purpose: To determine whether the association between mean lung dose (MLD) and risk of severe (grade {>=}3) radiation pneumonitis (RP) depends on the dose distribution pattern to normal lung among patients receiving 3-dimensional conformal radiation therapy for non-small-cell lung cancer. Methods and Materials: Three cohorts treated with different beam arrangements were identified. One cohort (2-field boost [2FB]) received 2 parallel-opposed (anteroposterior-posteroanterior) fields per fraction initially, followed by a sequential boost delivered using 2 oblique beams. The other 2 cohorts received 3 or 4 straight fields (3FS and 4FS, respectively), ie, all fields were irradiated every day. The incidence of severe RP was plotted against MLD in each cohort, and data were analyzed using the Lyman-Kutcher-Burman (LKB) model. Results: The incidence of grade {>=}3 RP rose more steeply as a function of MLD in the 2FB cohort (N=120) than in the 4FS cohort (N=138), with an intermediate slope for the 3FS group (N=99). The estimated volume parameter from the LKB model was n=0.41 (95% confidence interval, 0.15-1.0) and led to a significant improvement in fit (P=.05) compared to a fit with volume parameter fixed at n=1 (the MLD model). Unlike the MLD model, the LKB model with n=0.41 provided a consistent description of the risk of severe RP in all three cohorts (2FB, 3FS, 4FS) simultaneously. Conclusions: When predicting risk of grade {>=}3 RP, the mean lung dose does not adequately take into account the effects of high doses. Instead, the effective dose, computed from the LKB model using volume parameter n=0.41, may provide a better dosimetric parameter for predicting RP risk. If confirmed, these findings support the conclusion that for the same MLD, high doses to small lung volumes ('a lot to a little') are worse than low doses to large volumes ('a little to a lot').

  2. Short-range ensemble predictions based on convection perturbations in the Eta Model for the Serra do Mar region in Brazil

    NASA Astrophysics Data System (ADS)

    Bustamante, J. F. F.; Chou, S. C.; Gomes, J. L.

    2009-04-01

    The Southeast Brazil, in the coastal and mountain region called Serra do Mar, between Sao Paulo and Rio de Janeiro, is subject to frequent events of landslides and floods. The Eta Model has been producing good quality forecasts over South America at about 40-km horizontal resolution. For that type of hazards, however, more detailed and probabilistic information on the risks should be provided with the forecasts. Thus, a short-range ensemble prediction system (SREPS) based on the Eta Model is being constructed. Ensemble members derived from perturbed initial and lateral boundary conditions did not provide enough spread for the forecasts. Members with model physics perturbation are being included and tested. The objective of this work is to construct more members for the Eta SREPS by adding physics perturbed members. The Eta Model is configured at 10-km resolution and 38 layers in the vertical. The domain covered is most of Southeast Brazil, centered over the Serra do Mar region. The constructed members comprise variations of the cumulus parameterization Betts-Miller-Janjic (BMJ) and Kain-Fritsch (KF) schemes. Three members were constructed from the BMJ scheme by varying the deficit of saturation pressure profile over land and sea, and 2 members of the KF scheme were included using the standard KF and a momentum flux added to KF scheme version. One of the runs with BMJ scheme is the control run as it was used for the initial condition perturbation SREPS. The forecasts were tested for 6 cases of South America Convergence Zone (SACZ) events. The SACZ is a common summer season feature of Southern Hemisphere that causes persistent rain for a few days over the Southeast Brazil and it frequently organizes over Serra do Mar region. These events are particularly interesting because of the persistent rains that can accumulate large amounts and cause generalized landslides and death. With respect to precipitation, the KF scheme versions have shown to be able to reach the

  3. Is More Better? Combining Actuarial Risk Scales to Predict Recidivism among Adult Sex Offenders

    ERIC Educational Resources Information Center

    Seto, Michael C.

    2005-01-01

    The present study was conducted to determine whether combining the results of multiple actuarial risk scales increases accuracy in predicting sex offender recidivism. Multiple methods of combining 4 validated actuarial risk scales--the Violence Risk Appraisal Guide, the Sex Offender Risk Appraisal Guide, the Rapid Risk Assessment for Sexual…

  4. Prediction of ground-level ozone concentration in São Paulo, Brazil: Deterministic versus statistic models

    NASA Astrophysics Data System (ADS)

    Hoshyaripour, G.; Brasseur, G.; Andrade, M. F.; Gavidia-Calderón, M.; Bouarar, I.; Ynoue, R. Y.

    2016-11-01

    Two state-of-the-art models (deterministic: Weather Research and Forecast model with Chemistry (WRF-Chem) and statistic: Artificial Neural Networks: (ANN)) are implemented to predict the ground-level ozone concentration in São Paulo (SP), Brazil. Two domains are set up for WRF-Chem simulations: a coarse domain (with 50 km horizontal resolution) including whole South America (D1) and a nested domain (with horizontal resolution of 10 km) including South Eastern Brazil (D2). To evaluate the spatial distribution of the chemical species, model results are compared to the Measurements of Pollution in The Troposphere (MOPITT) data, showing that the model satisfactorily predicts the CO concentrations in both D1 and D2. The model also reproduces the measurements made at three air quality monitoring stations in SP with the correlation coefficients of 0.74, 0.70, and 0.77 for O3 and 0.51, 0.48, and 0.57 for NOx. The input selection for ANN model is carried out using Forward Selection (FS) method. FS-ANN is then trained and validated using the data from two air quality monitoring stations, showing correlation coefficients of 0.84 and 0.75 for daily mean and 0.64 and 0.67 for daily peak ozone during the test stage. Then, both WRF-Chem and FS-ANN are deployed to forecast the daily mean and peak concentrations of ozone in two stations during 5-20 August 2012. Results show that WRF-Chem preforms better in predicting mean and peak ozone concentrations as well as in conducting mechanistic and sensitivity analysis. FS-ANN is only advantageous in predicting mean daily ozone concentrations considering its significantly lower computational costs and ease of development and implementation, compared to that of WRF-Chem.

  5. Machine learning for risk prediction of acute coronary syndrome.

    PubMed

    VanHouten, Jacob P; Starmer, John M; Lorenzi, Nancy M; Maron, David J; Lasko, Thomas A

    2014-01-01

    Acute coronary syndrome (ACS) accounts for 1.36 million hospitalizations and billions of dollars in costs in the United States alone. A major challenge to diagnosing and treating patients with suspected ACS is the significant symptom overlap between patients with and without ACS. There is a high cost to over- and under-treatment. Guidelines recommend early risk stratification of patients, but many tools lack sufficient accuracy for use in clinical practice. Prognostic indices often misrepresent clinical populations and rely on curated data. We used random forest and elastic net on 20,078 deidentified records with significant missing and noisy values to develop models that outperform existing ACS risk prediction tools. We found that the random forest (AUC = 0.848) significantly outperformed elastic net (AUC=0.818), ridge regression (AUC = 0.810), and the TIMI (AUC = 0.745) and GRACE (AUC = 0.623) scores. Our findings show that random forest applied to noisy and sparse data can perform on par with previously developed scoring metrics.

  6. Rural tourism as risk factor for the transmission of schistosomiasis in Minas Gerais, Brazil.

    PubMed

    Enk, Martin J; Caldeira, Roberta L; Carvalho, Omar S; Schall, Virginia T

    2004-01-01

    Recently, the booming rural tourism in endemic areas of the state of Minas Gerais was identified as a contributing factor in the dissemination of the infection with Schistosoma mansoni. This article presents data from six holiday resorts in a rural district approximately 100 km distant from Belo Horizonte, MG, Brazil, where a possibly new and until now unperceived way of transmission was observed. The infection takes place in swimming pools and little ponds, which are offered to tourists and the local population for fishing and leisure activities. The health authorities of the district reported cases of schistosomiasis among the local population after visiting these sites. As individuals of the non-immune middle class parts of the society of big urban centers also frequent these resorts, infection of these persons cannot be excluded. A malacological survey revealed the presence of molluscs of the species Biomphalaria glabrata and Biomphalaria straminea at the resorts. The snails (B. glabrata) of one resort tested positive for S. mansoni. In order to resolve this complex problem a multidisciplinary approach including health education, sanitation measures, assistance to the local health services, and evolvement of the local political authorities, the local community, the tourism association, and the owners of the leisure resorts is necessary. This evidence emphasizes the urgent need for a participative strategic plan to develop the local tourism in an organized and well-administered way. Only so this important source of income for the region can be ensured on the long term without disseminating the disease and putting the health of the visitors at risk.

  7. Predicting Risk of Endovascular Device Infection in Patients with Staphylococcus aureus Bacteremia (PREDICT-SAB)

    PubMed Central

    Sohail, M. Rizwan; Palraj, Bharath Raj; Khalid, Sana; Uslan, Daniel Z.; Al-Saffar, Farah; Friedman, Paul A.; Hayes, David L.; Lohse, Christine M.; Wilson, Walter R.; Steckelberg, James M.; Baddour, Larry M.

    2014-01-01

    Background Prompt recognition of underlying cardiovascular implantable electronic device (CIED) infection in patients presenting with S. aureus bacteremia (SAB) is critical for optimal management of these cases. The goal of this study was to identify clinical predictors of CIED infection in patients presenting with SAB and no signs of pocket infection. Methods and Results All cases of SAB in CIED recipients at Mayo Clinic from 2001 to 2011 were retrospectively reviewed. We identified 131 patients with CIED who presented with SAB and had no clinical signs of device pocket infection. Forty-five (34%) of these patients had underlying CIED infection based on clinical and/or echocardiographic criteria. The presence of a permanent pacemaker rather than an implantable cardioverter-defibrillator (OR 3.90, 95% CI 1.65–9.23), P=0.002), >1 device-related procedure (OR 3.30, 95% CI 1.23–8.86, P=0.018), and duration of SAB ≥4 days (OR 5.54, 95% CI 3.32–13.23, P<0.001) were independently associated with an increased risk of CIED infection in a multivariable model. The area under the receiver operating characteristics curve (AUC) for the multivariable model was 0.79, indicating a good discriminatory capacity to distinguish SAB patients with and without CIED infection. Conclusions Among patients presenting with SAB and no signs of pocket infection, the risk of underlying CIED infection can be calculated based on the type of device, number of device-related procedures, and duration of SAB. We propose that patients without any of these high-risk features have a very low risk of underlying CIED infection and may be monitored closely without immediate device extraction. Prospective studies are needed to validate this risk prediction model. PMID:25504648

  8. Genetic risk prediction and neurobiological understanding of alcoholism.

    PubMed

    Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefer, F; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B

    2014-05-20

    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress

  9. Novelty seeking is related to individual risk preference and brain activation associated with risk prediction during decision making

    PubMed Central

    Wang, Ying; Liu, Ying; Yang, Lizhuang; Gu, Feng; Li, Xiaoming; Zha, Rujing; Wei, Zhengde; Pei, Yakun; Zhang, Peng; Zhou, Yifeng; Zhang, Xiaochu

    2015-01-01

    Novelty seeking (NS) is a personality trait reflecting excitement in response to novel stimuli. High NS is usually a predictor of risky behaviour such as drug abuse. However, the relationships between NS and risk-related cognitive processes, including individual risk preference and the brain activation associated with risk prediction, remain elusive. In this fMRI study, participants completed the Tridimensional Personality Questionnaire to measure NS and performed a probabilistic decision making task. Using a mathematical model, we estimated individual risk preference. Brain regions associated with risk prediction were determined via fMRI. The NS score showed a positive correlation with risk preference and a negative correlation with the activation elicited by risk prediction in the right posterior insula (r-PI), left anterior insula (l-AI), right striatum (r-striatum) and supplementary motor area (SMA). Within these brain regions, only the activation associated with risk prediction in the r-PI showed a correlation with NS after controlling for the effect of risk preference. Resting-state functional connectivity between the r-PI and r-striatum/l-AI was negatively correlated with NS. Our results suggest that high NS may be associated with less aversion to risk and that the r-PI plays an important role in relating risk prediction to NS. PMID:26065910

  10. Risk assessment tools used to predict outcomes of total hip and total knee arthroplasty.

    PubMed

    Konopka, Joseph F; Hansen, Viktor J; Rubash, Harry E; Freiberg, Andrew A

    2015-07-01

    This article reviews recently proposed clinical tools for predicting risks and outcomes in total hip arthroplasty and total knee arthroplasty patients. Additionally, we share the Massachusetts General Hospital experience with using the Risk Assessment and Prediction Tool to predict the need for an extended care facility after total joint arthroplasty.

  11. Risk prediction of pulmonary tuberculosis using genetic and conventional risk factors in adult Korean population

    PubMed Central

    Hong, Eun Pyo; Go, Min Jin; Kim, Hyung-Lae

    2017-01-01

    A complex interplay among host, pathogen, and environmental factors is believed to contribute to the risk of developing pulmonary tuberculosis (PTB). The lack of replication of published genome-wide association study (GWAS) findings limits the clinical utility of reported single nucleotide polymorphisms (SNPs). We conducted a GWAS using 467 PTB cases and 1,313 healthy controls obtained from two community-based cohorts in Korea. We evaluated the performance of PTB risk models based on different combinations of genetic and nongenetic factors and validated the results in an independent Korean population comprised of 179 PTB cases and 500 healthy controls. We demonstrated the polygenic nature of PTB and nongenetic factors such as age, sex, and body mass index (BMI) were strongly associated with PTB risk. None of the SNPs achieved genome-wide significance; instead, we were able to replicate the associations between PTB and ten SNPs near or in the genes, CDCA7, GBE1, GADL1, SPATA16, C6orf118, KIAA1432, DMRT2, CTR9, CCDC67, and CDH13, which may play roles in the immune and inflammatory pathways. Among the replicated SNPs, an intergenic SNP, rs9365798, located downstream of the C6orf118 gene showed the most significant association under the dominant model (OR = 1.59, 95% CI 1.32–1.92, P = 2.1×10−6). The performance of a risk model combining the effects of ten replicated SNPs and six nongenetic factors (i.e., age, sex, BMI, cigarette smoking, systolic blood pressure, and hemoglobin) were validated in the replication set (AUC = 0.80, 95% CI 0.76–0.84). The strategy of combining genetic and nongenetic risk factors ultimately resulted in better risk prediction for PTB in the adult Korean population. PMID:28355295

  12. Beyond sensation seeking: affect regulation as a framework for predicting risk-taking behaviors in high-risk sport.

    PubMed

    Castanier, Carole; Le Scanff, Christine; Woodman, Tim

    2010-10-01

    Sensation seeking has been widely studied when investigating individual differences in the propensity for taking risks. However, risk taking can serve many different goals beyond the simple management of physiological arousal. The present study is an investigation of affect self-regulation as a predictor of risk-taking behaviors in high-risk sport. Risk-taking behaviors, negative affectivity, escape self-awareness strategy, and sensation seeking data were obtained from 265 high-risk sportsmen. Moderated hierarchical regression analysis revealed significant main and interaction effects of negative affectivity and escape self-awareness strategy in predicting risk-taking behaviors: high-risk sportsmen's negative affectivity leads them to adopt risk-taking behaviors only if they also use escape self-awareness strategy. Furthermore, the affective model remained significant when controlling for sensation seeking. The present study contributes to an in-depth understanding of risk taking in high-risk sport.

  13. Presence of high-risk clones of OXA-23-producing Acinetobacter baumannii (ST79) and SPM-1-producing Pseudomonas aeruginosa (ST277) in environmental water samples in Brazil.

    PubMed

    Turano, Helena; Gomes, Fernando; Medeiros, Micheli; Oliveira, Silvane; Fontes, Lívia C; Sato, Maria I Z; Lincopan, Nilton

    2016-09-01

    This study reports the presence of hospital-associated high-risk lineages of OXA-23-producing ST79 Acinetobacter baumannii and SPM-1-producing ST277 Pseudomonas aeruginosa in urban rivers in Brazil. These findings indicate that urban rivers can act as reservoirs of clinically important multidrug-resistant bacteria, which constitute a potential risk to human and animal health.

  14. Development and validation of a cardiovascular risk prediction model for Japanese: the Hisayama study.

    PubMed

    Arima, Hisatomi; Yonemoto, Koji; Doi, Yasufumi; Ninomiya, Toshiharu; Hata, Jun; Tanizaki, Yumihiro; Fukuhara, Masayo; Matsumura, Kiyoshi; Iida, Mitsuo; Kiyohara, Yutaka

    2009-12-01

    The objective of this paper is to develop a new risk prediction model of cardiovascular disease and to validate its performance in a general population of Japanese. The Hisayama study is a population-based prospective cohort study. A total of 2634 participants aged 40 years or older were followed up for 14 years for incident cardiovascular disease (stroke and coronary heart disease (myocardial infarction, coronary revascularization and sudden cardiac death)). We used data among a random two-thirds (the derivation cohort, n=1756) to develop a new risk prediction model that was then tested to compare observed and predicted outcomes in the remaining one-third (the validation cohort, n=878). A multivariable cardiovascular risk prediction model was developed that incorporated age, sex, systolic blood pressure, diabetes, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and smoking. We assessed the performance of the model for predicting individual cardiovascular event among the validation cohort. The risk prediction model demonstrated good discrimination (c-statistic=0.81; 95% confidence interval, 0.77 to 0.86) and calibration (Hosmer-Lemeshow chi(2)-statistic=6.46; P=0.60). A simple risk score sheet based on the cardiovascular risk prediction model was also presented. We developed and validated a new cardiovascular risk prediction model in a general population of Japanese. The risk prediction model would provide a useful guide to estimate absolute risk of cardiovascular disease and to treat individual risk factors.

  15. Serological markers and risk factors related to hepatitis B virus in dentists in the Central West region of Brazil

    PubMed Central

    de Paiva, Enilza Maria Mendonça; Tiplle, Anaclara Ferreira Veiga; de Paiva Silva, Eliane; de Paula Cardoso, Divina das Dores

    2008-01-01

    The hepatitis B virus (HBV) has been considered the major occupational risk agent for dentists. The Central West region of Brazil is considered an intermediate endemic pattern area, but currently there is no information about the HBV prevalence in dentists of Goiânia, Goiás. This study aimed at the detection of the HBV infection rate and risk factors for dentists of Goiânia and the comparison of the obtained data with the general population and other groups. A randomized sample of 680 professionals participated in this study. All dentists gave written consent for the procedure and filled out a questionnaire about risk factors. The HBV serological markers were analyzed using ELISA test and the presence of anti-HBc was observed in 41 (6.0%) of the dentists. None of them was HBsAg positive. Significant relationships with HBV positivity were observed with gender, the time working as a dentist and the use of incomplete personal protective equipment (PPE). The HBV prevalence found in this group of dentists was lower than the endemic pattern of the general population, other health care workers of the region and the dentists from other regions in Brazil. These results may indicate a positive impact of vaccination considering the high adherence of the dentists to the immunization program (98.4%). Finally, the use of complete PPE by the majority as well as other standard precautions recommended for health care workers could be responsible for the low HBV seroprevalence. PMID:24031211

  16. [Triatominae and Cactaceae: a risk for the transmission of the American trypanosomiasis in the peridomicilary space (Northeast Brazil)].

    PubMed

    Emperaire, L; Romaña, C A

    2006-06-01

    Field observations carried in semi-arid Brazil Northeast point out the frequent association, in the peridomiciliary space, between a cactus, Cereus jamacaru, the occurrence of nests in its branches and the occurrence of two species of insects vectors of Trypanosoma cruzi, pathogenic agent of Chagas disease: Rhodnius neglectus and Triatoma pseudomaculata. The analysis of the architectural variables of this Cactaceae shows that the presence of nests, and thus of insects, depends on the traditional practices of management of this cactus. This study underlines the relevance of an integrated approach of the ecology of Triatominae for the identification of factors of risk.

  17. Maternal Gene Polymorphisms Involved in Folate Metabolism as Risk Factors for Down Syndrome Offspring in Southern Brazil

    PubMed Central

    Brandalize, Ana Paula Carneiro; Bandinelli, Eliane; Santos, Pollyanna Almeida Dos; Schüler-Faccini, Lavínia

    2010-01-01

    This study aimed to investigate the role of maternal polymorphisms, as well as their risk genotypes combinations of MTR A2756G, MTRR A66G, CBS 844ins68, and RFC A80G, involved in folate/homocysteine metabolism, as possible risk factors for Down syndrome (DS) in Southern Brazil. A case-control study was conducted with 239~mothers of DS children and 197 control mothers. The investigation of polymorphisms was performed by PCR and PCR-RFLP. The distribution of genotypic variants was similar in both groups when they were analyzed separately. An investigation of combined risk genotypes showed that the risk of having a DS child for one, two or three risk genotypes was 6.23, 6.96 and 5.84 (95%CI 1.48–26.26; 1.69–28.66; 1.37–24.86), respectively. The combined MTRR 66G and MTHFR 677T alleles were significantly more common among mothers of children with DS than among control mothers (OR 1.55; IC 95% 1.03–2.35). The results show that individual polymorphisms studied in this work are not associated with DS; however, the effects of the combined risk genotypes among MTR, MTRR, CBS and RFC genes are considered maternal risk factors for DS offspring in our population. PMID:21045269

  18. Risk prediction for myocardial infarction via generalized functional regression models.

    PubMed

    Ieva, Francesca; Paganoni, Anna M

    2016-08-01

    In this paper, we propose a generalized functional linear regression model for a binary outcome indicating the presence/absence of a cardiac disease with multivariate functional data among the relevant predictors. In particular, the motivating aim is the analysis of electrocardiographic traces of patients whose pre-hospital electrocardiogram (ECG) has been sent to 118 Dispatch Center of Milan (the Italian free-toll number for emergencies) by life support personnel of the basic rescue units. The statistical analysis starts with a preprocessing of ECGs treated as multivariate functional data. The signals are reconstructed from noisy observations. The biological variability is then removed by a nonlinear registration procedure based on landmarks. Thus, in order to perform a data-driven dimensional reduction, a multivariate functional principal component analysis is carried out on the variance-covariance matrix of the reconstructed and registered ECGs and their first derivatives. We use the scores of the Principal Components decomposition as covariates in a generalized linear model to predict the presence of the disease in a new patient. Hence, a new semi-automatic diagnostic procedure is proposed to estimate the risk of infarction (in the case of interest, the probability of being affected by Left Bundle Brunch Block). The performance of this classification method is evaluated and compared with other methods proposed in literature. Finally, the robustness of the procedure is checked via leave-j-out techniques.

  19. Interpreting incremental value of markers added to risk prediction models.

    PubMed

    Pencina, Michael J; D'Agostino, Ralph B; Pencina, Karol M; Janssens, A Cecile J W; Greenland, Philip

    2012-09-15

    The discrimination of a risk prediction model measures that model's ability to distinguish between subjects with and without events. The area under the receiver operating characteristic curve (AUC) is a popular measure of discrimination. However, the AUC has recently been criticized for its insensitivity in model comparisons in which the baseline model has performed well. Thus, 2 other measures have been proposed to capture improvement in discrimination for nested models: the integrated discrimination improvement and the continuous net reclassification improvement. In the present study, the authors use mathematical relations and numerical simulations to quantify the improvement in discrimination offered by candidate markers of different strengths as measured by their effect sizes. They demonstrate that the increase in the AUC depends on the strength of the baseline model, which is true to a lesser degree for the integrated discrimination improvement. On the other hand, the continuous net reclassification improvement depends only on the effect size of the candidate variable and its correlation with other predictors. These measures are illustrated using the Framingham model for incident atrial fibrillation. The authors conclude that the increase in the AUC, integrated discrimination improvement, and net reclassification improvement offer complementary information and thus recommend reporting all 3 alongside measures characterizing the performance of the final model.

  20. Variability, Predictability, and Risk in the Alaskan Arctic Waters

    NASA Astrophysics Data System (ADS)

    Arbetter, T. E.; Goldstein, M. A.; Lynch, A. H.

    2015-12-01

    Summer sea ice extent in the Arctic has been in decline since 1996, but after successive record September minimums in 2005, 2007, and 2012, the possibility of developing the high Arctic has rapidly changed from something decades away to an imminent opportunity. The Obama administration permitted Royal Dutch Shell to conduct exploratory oil drilling in the Chukchi Sea in summer 2015. If successful, further development will follow. The Bering Strait, as the exit of the Northern Sea Route, has already seen increased ship traffic, and this will likely continue if the sea ice remains reliably low. While not the only factor, predictability of sea ice extent, particularly on seasonal scales (3-12 months), is essential; a wrong decision will be costly if not catastrophic (e.g, Kulluk 2012). Using a reduced form model, we investigate geophysical processes which govern the advance and retreat of the sea ice edge at key points (e.g., Nome, Kotzebue, Barrow, Prudhoe Bay). Using the Black-Scholes Option Pricing formula, we estimate costs and risks associated with the ice edge variability.

  1. AN APPROACH TO PREDICT RISKS TO WILDLIFE POPULATIONS FROM MERCURY AND OTHER STRESSORS

    EPA Science Inventory

    The U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory (NHEERL) is developing tools for predicting risks of multiple stressors to wildlife populations, which support the development of risk-based protective criteria. NHEERL's res...

  2. Heart Rate Change When Standing Up Might Predict Older Adult's Death Risk

    MedlinePlus

    ... Change When Standing Up Might Predict Older Adult's Death Risk People with slower heart rate recovery had ... they stand up might reveal their risk of death over the next several years, a new study ...

  3. Decision-making competence predicts domain-specific risk attitudes

    PubMed Central

    Weller, Joshua A.; Ceschi, Andrea; Randolph, Caleb

    2015-01-01

    Decision-making competence (DMC) reflects individual differences in rational responding across several classic behavioral decision-making tasks. Although it has been associated with real-world risk behavior, less is known about the degree to which DMC contributes to specific components of risk attitudes. Utilizing a psychological risk-return framework, we examined the associations between risk attitudes and DMC. Italian community residents (n = 804) completed an online DMC measure, using a subset of the original Adult-DMC battery. Participants also completed a self-reported risk attitude measure for three components of risk attitudes (risk-taking, risk perceptions, and expected benefits) across six risk domains. Overall, greater performance on the DMC component scales were inversely, albeit modestly, associated with risk-taking tendencies. Structural equation modeling results revealed that DMC was associated with lower perceived expected benefits for all domains. In contrast, its association with perceived risks was more domain-specific. These analyses also revealed stronger indirect effects for the DMC → expected benefits → risk-taking path than the DMC → perceived riskrisk-taking path, especially for behaviors that may be considered more maladaptive in nature. These results suggest that DMC performance differentially impacts specific components of risk attitudes, and may be more strongly related to the evaluation of expected value of a specific behavior. PMID:26029128

  4. Causes of death and associated risk factors among climacteric women from Southern Brazil: a population based-study

    PubMed Central

    2014-01-01

    Background Aging and menopause are particular cardiovascular risk factors for women, due to estrogen deprivation at the time of menopause. Studies show that diabetes mellitus (DM), smoking, hypertension, high body mass index (BMI), and serum lipids are associated with increased risk of cardiovascular disease (CVD), the main cause of female mortality in Brazil. The aim of this study was to assess the mortality rate, causes of death and associated risk factors in a cohort of women from Brazil. Methods A longitudinal population-based study of menopausal status is currently underway in a city in South Brazil. In 2010, a third follow-up of this population was performed to assess cardiovascular risk and mortality rate between 1995 and 2011. For this analysis, 358 participants were studied. At baseline, participants had completed a standardized questionnaire including demographic, lifestyle, medical and reproductive characteristics. In addition to the contacts with relatives, mortality data were obtained through review of medical records in all city hospitals and the Center for Health Information (NIS/RS-SES). Multivariate-adjusted hazard risk (HR) and 95% confidence intervals (CI95%) were estimated using Cox proportional hazards regression. Survival curves were estimated using the Kaplan-Meier curve. Results There were 17 (4.7%) deaths from all causes during the study period. Seven (41.2%) deaths were caused by CVD, including four cases of stroke and three cases of myocardial infarction. Six (35.3%) deaths were due to cancer, and four (23.5%) were due to other reasons. In the age and smoking-adjusted multivariate models, diabetes (HR 6.645, 95% CI: 1.938–22.79, p = 0.003), alcohol intake (HR 1.228, 95% CI: 1.014-1.487, p = 0.035) and postmenopausal status (HR = 6.216, 95% CI: 0.963–40.143, p = 0.055) were associated with all-cause mortality. A significant association was found between abdominal obesity (WHR ≥ 0.85) and mortality even after the adjustment for BMI

  5. Does albuminuria predict renal risk and/or cardiovascular risk in obese type 2 diabetic patients?

    PubMed Central

    Bentata, Yassamine; Abouqal, Redouane

    2014-01-01

    Increased urinary albumin excretion (UAE) is a marker of renal and cardiovascular risk in patients with type 2 diabetes (DT2). What about the obese patient with DT2? Does albuminuria predict the progression of renal disease and/or cardiovascular disease? The objective of this study is to determine the link between albuminuria, renal risk and cardiovascular risk in a cohort of obese DT2 patients. This is a prospective study begun in September 2006. It included DT2 patients presenting obesity defined by a body mass index (BMI)>30 Kg/m2. Three groups of patients were defined: normo-albuminuria (Urinary Albumin Excretion UAE<30 mg/day or Albumin Creatinine Ratio ACR<30 mg/g), micro-albuminuria (UAE=30-300 mg/day or ACR=30-300 mg/g) and macro-albuminuria (UAE>300 mg/day or ACR>300 mg/g). Data on 144 obese DT2 patients were compiled: The mean age of our patients was 59 ± 9 years and the sex ratio 0.26. The incidence of ESRD was higher in the macro-albuminuria group than in the two other groups (26.5% vs. 1.2%, p<0.001). The incidence of cardiovascular events was 15.4%, 14.3% and 23.5% in the normo, micro and macro-albuminuria groups (p=0.48). A history of cardiovascular comorbidities was the main cardiovascular risk in multivariate analysis (0R=15.07; 95% CI=5.30-42.82; p<0.001) and the low admission GFR (0R=5.67; 95% CI=1.23-9.77; p=0.008) was the main factor for progression of kidney disease in multivariate analysis. Albuminuria may be a better marker of kidney disease progression than of cardiovascular risk in the obese DT2 patient, according to our results. However, to accurately demonstrate the link albuminuria - renal risk and albuminuria - cardiovascular risk in the obese DT2 patient, additional studies using very strict criteria of selection and judgment are needed. PMID:24551483

  6. Distribution of Short-Term and Lifetime Predicted Risks of Cardiovascular Diseases in Peruvian Adults

    PubMed Central

    Quispe, Renato; Bazo-Alvarez, Juan Carlos; Burroughs Peña, Melissa S; Poterico, Julio A; Gilman, Robert H; Checkley, William; Bernabé-Ortiz, Antonio; Huffman, Mark D; Miranda, J Jaime

    2015-01-01

    Background Short-term risk assessment tools for prediction of cardiovascular disease events are widely recommended in clinical practice and are used largely for single time-point estimations; however, persons with low predicted short-term risk may have higher risks across longer time horizons. Methods and Results We estimated short-term and lifetime cardiovascular disease risk in a pooled population from 2 studies of Peruvian populations. Short-term risk was estimated using the atherosclerotic cardiovascular disease Pooled Cohort Risk Equations. Lifetime risk was evaluated using the algorithm derived from the Framingham Heart Study cohort. Using previously published thresholds, participants were classified into 3 categories: low short-term and low lifetime risk, low short-term and high lifetime risk, and high short-term predicted risk. We also compared the distribution of these risk profiles across educational level, wealth index, and place of residence. We included 2844 participants (50% men, mean age 55.9 years [SD 10.2 years]) in the analysis. Approximately 1 of every 3 participants (34% [95% CI 33 to 36]) had a high short-term estimated cardiovascular disease risk. Among those with a low short-term predicted risk, more than half (54% [95% CI 52 to 56]) had a high lifetime predicted risk. Short-term and lifetime predicted risks were higher for participants with lower versus higher wealth indexes and educational levels and for those living in urban versus rural areas (P<0.01). These results were consistent by sex. Conclusions These findings highlight potential shortcomings of using short-term risk tools for primary prevention strategies because a substantial proportion of Peruvian adults were classified as low short-term risk but high lifetime risk. Vulnerable adults, such as those from low socioeconomic status and those living in urban areas, may need greater attention regarding cardiovascular preventive strategies. PMID:26254303

  7. Risk factors for hepatitis C virus infection among blood donors in southern Brazil: a case-control study

    PubMed Central

    Brandão, Ajacio BM; Costa Fuchs, Sandra

    2002-01-01

    Background In Brazil, it is estimated that between 2.5 and 4.9% of the general population present anti-hepatitis C virus (HCV) antibodies, which corresponds to as many as 3.9 to 7.6 million chronic carriers. Chronic liver disease is associated with HCV infection in 20% to 58% of the Brazilian patients. The objective of this case-control study was to investigate the risk factors for presence of anti-HCV antibody in blood donors in southern Brazil. Methods One hundred and seventy eight blood donors with two positive ELISA results for anti-HCV were cases, and 356 controls tested negative. A standardized questionnaire was used to collect data concerning demographic and socioeconomic aspects, history of previous hepatitis infection, social and sexual behaviors, and number of donations. Variables were grouped into sets of hierarchical categories. Cases and controls were compared using logistic regression, odds ratios, and 95% confidence intervals. The statistical significance of the associations was assessed through likelihood ratio tests based on a P value < 0.05. Results The prevalence of anti-HCV among blood donors was 1.1%. Most of the donors were white and males. In the multivariate analysis, independent predictors of anti-HCV positivity were: intravenous drug use, blood transfusion >10 years earlier, having had two to four sexually transmitted diseases, incarceration, tattooing, sex with a hepatitis B or C virus carrier or with intravenous drug users. Conclusion Intravenous drug use, blood transfusion, and tattooing were the main risk factors for anti-HCV positivity among blood donors from southern Brazil, but sexual HCV transmission should also be considered. PMID:12169200

  8. Population-based genetic risk prediction and stratification for ovarian cancer: views from women at high risk.

    PubMed

    Rahman, Belinda; Meisel, Susanne F; Fraser, Lindsay; Side, Lucy; Gessler, Sue; Wardle, Jane; Lanceley, Anne

    2015-03-01

    There is an opportunity to improve outcomes for ovarian cancer (OC) through advances in risk stratification, early detection and diagnosis. A population-based OC genetic risk prediction and stratification program is being developed. A previous focus group study with individuals from the general population showed support for the proposed program. This qualitative interview study explores the attitudes of women at high risk of OC. Eight women participated in one-on-one, in-depth, semi-structured interviews to explore: experiences of learning of OC risk, risk perceptions, OC knowledge and awareness, and opinions on risk stratification approach. There was evidence of strong support for the proposed program. Benefits were seen as providing reassurance to women at low risk, and reducing worry in women at high risk through appropriate clinical management. Stratification into 'low' and 'high' risk groups was well-received. Participants were more hesitant about stratification to the 'intermediate' risk group. The data suggest formats to effectively communicate OC risk estimates will require careful thought. Interactions with GPs were highlighted as a barrier to OC risk assessment and diagnosis. These results are encouraging for the possible introduction and uptake of a risk prediction and stratification program for OC in the general population.

  9. Perceived Mental Illness Stigma and HIV Risk Behaviors Among Adult Psychiatric Outpatients in Rio de Janeiro, Brazil

    PubMed Central

    Elkington, Katherine S.; McKinnon, Karen; Mann, Claudio Gruber; Collins, Pamela Y.; Leu, Cheng-Shiun; Wainberg, Milton L.

    2009-01-01

    We examined the associations between perceived mental illness stigma and HIV risk and protective behaviors among adults with severe mental illness (SMI) in Rio de Janeiro, Brazil. We measured mental illness stigma across three domains (“Personal Experiences,” “Perceived Attractiveness,” and “Relationship Discrimination”), and examined the relationship between experiences of stigma in each domain and HIV risk and protective behaviors over the past three months in 98 outpatients with SMI. Those who reported greater “Relationship Discrimination” stigma were significantly more likely to be sexually active and to have unprotected sex; they were significantly less likely to report deliberately having fewer partners as a way to protect themselves from HIV. The role of stigma in unprotected sexual behavior should be examined further and considered in any HIV prevention intervention for people with SMI. PMID:19543974

  10. Case-control study evaluating the sow's risk factors associated with stillbirth piglets in Midwestern in Brazil.

    PubMed

    Silva, Gustavo Sousa; da Costa Lana, Marconni Victor; Dias, Geovanny Bruno Gonçalves; da Cruz, Raquel Aparecida Sales; Lopes, Leticya Lerner; Machado, Gustavo; Corbellini, Luis Gustavo; Gava, Danielle; Souza, Marcos Almeida; Pescador, Caroline Argenta

    2015-02-01

    Reproductive failure in swine herds is often difficult to diagnose and is important to swine production. The present study aims to identify the potential risk factors (infectious/noninfectious) for stillborn piglets in two commercial swine farms situated in midwestern region of Brazil. The potential risk factors were included in a multivariable logistic model, and the dependent variable was defined as the presence of at least one stillborn piglet in a given litter (yes or no). In the best fit model, two variables from the multivariable analysis, total litter size (p = 0.01), and average birth weight (p = 0.03) were significantly associated with the presence of stillborn piglets at the farms examined in this study. Porcine circovirus type 2 (PCV2) was detected in 29.1 % of the litters. Neither parvovirus (PPV) nor leptospirosis infections were identified in this study, suggesting that they have a minor impact on reproductive disease.

  11. Antibodies to Leptospira interrogans in goats and risk factors of the disease in Santa Catarina (West side), Brazil.

    PubMed

    Topazio, Josué; Tonin, Alexandre A; Machado, Gustavo; Noll, Jessica C G; Ribeiro, André; Moura, Anderson B; Carmo, Guilherme M; Grosskopf, Hyolanda M; Martins, Jorge L R; Badke, Manoel R T; Stefani, Lenita M; Lopes, Leandro S; Da Silva, Aleksandro S

    2015-04-01

    Leptospirosis is an infectious disease caused by the bacterium Leptospira spp. In goats, the productive impact of leptospirosis is not well known and totally unknown in Santa Catarina (SC), Brazil. This study aimed to investigate leptospirosis seroprevalence and its risk factors in goats in the west side of SC. A total of 654 blood samples were analyzed using the microscopic agglutination technique and 35.47% (232) of the animals were seropositives. Except for serogroup Autumnalis, positive samples for all other serogroups were found as follows: Sejroe (Hardjo, Wolffi), Grippotyphosa (Grippotyphosa), Canicola (Canicola), Icterohaemorrhagiae (Icterohaemorrhagiae, Copenhageni), Australis (Australis, Bratislava) and Pomona (Pomona). The contact among sheep and goats, and the addition of concentrate as food supplement were found to be risk factors for leptospirosis. Based on these results, we conclude that there is a high occurrence of anti-Leptospira antibodies in goats in the Western part of Santa Catarina State.

  12. Prevalence and risk factors for Cysticercus tenuicollis in goats and sheep in Paraíba, northeastern Brazil.

    PubMed

    Morais, Dayana Firmino de; Vilela, Vinícius Longo Ribeiro; Feitosa, Thais Ferreira; Santos, Vinícius Mamede Dos; Gouveia, Vitória Régia; Athayde, Ana Célia Rodrigues; Azevêdo, Sérgio Santos de

    2017-01-26

    This study aimed to determine the prevalence and risk factors for C. tenuicollis among goats and sheep in slaughterhouses in Paraíba. 390 animals (195 goats and 195 sheep) in the municipalities of Patos and Esperança, Paraíba, Brazil, were inspected between February and May 2014. The prevalence of C. tenuicollis was 39% (76/195) in goats and 17.4% (34/195) in sheep. In both species, most of the cysticerci vesicles were located at the omentum and mesentery. The only risk factor found was extensive sheep farming. It can be concluded that C. tenuicollis is highly prevalent in small ruminants in Paraíba, being more prevalent in goats than in sheep. Extensively-reared sheep were twice as likely to develop infection by this parasite.

  13. [FIBRA-RJ Network: frailty and risk of hospitalization in the elderly in Rio de Janeiro, Brazil].

    PubMed

    Perez, Mariangela; Lourenço, Roberto Alves

    2013-07-01

    The objective of this study was to determine the risk profile and factors associated with frailty in elderly community residents. The population consisted of individuals 65 years or older living in the northern districts of the city of Rio de Janeiro, Brazil, and who held private health insurance policies. The cross-sectional study was done at baseline in a cohort with a sample (N = 764) stratified by gender and age. Risk stratification used probability of repeated admissions (PRA) as the screening instrument. Following bivariate analyses, logistic regression analyses were performed to study associations between probability of repeated admissions and socio-demographic, health-status, functional, and cognitive variables. Of the total sample, 6.7% were classified as high risk. Cancer, falls, chronic obstructive pulmonary disease, use of medication, receiving a visit from a health professional, being bedridden at home, living alone, and level of activities of daily living were statistically associated with risk of hospitalization. The instrument appeared to be useful for stratifying risk in the elderly.

  14. [Temporary workers' perceptions of occupational risks in the port of Rio Grande, Rio Grande do Sul State, Brazil].

    PubMed

    Soares, Jorgana Fernanda de Souza; Cezar-Vaz, Marta Regina; Mendoza-Sassi, Raul Andrés; Almeida, Tabajara Lucas de; Muccillo-Baisch, Ana Luiza; Soares, Maria Cristina Flores; Costa, Valdecir Zavarese da

    2008-06-01

    This was a cross-sectional, descriptive, quantitative study in the port of Rio Grande, Rio Grande do Sul, Brazil, aimed at identifying occupational risk perceptions in a sample of 306 temporary dockworkers. Most temporary dockworkers (93.46%) acknowledged the existence of health risks on the job, independently of schooling (p = 0.44) and job activity (p = 0.47). Risks identified by temporary workers as a whole included falling of suspended objects (8.43 +/- 2.47), noise (8.06 +/- 2.32), and bad weather conditions (8.05 +/- 2.48). Risks that varied significantly between jobs were: noise (p = 0.00), lifting loads manually (p = 0.00), work tools (p = 0,00), insufficient number of work team members (p = 0.03), extra wages based on productivity (p = 0.00), work pace (p = 0.01), working on scaffolding and other high areas (p = 0.00), workers moving on top of cargo (p = 0.00), and ship's ladders and gangways (p = 0.00). The study corroborated that temporary dock work is unhealthy and hazardous, and that the risks affect workers according to the specific jobs they perform.

  15. Reproductive risk factors differ among breast cancer patients and controls in a public hospital of Paraiba, northeast Brazil.

    PubMed

    Sarmento de Almeida, Gibran; Leal Almeida, Layze Amanda; Rodrigues Araujo, Gilmara Marques; Weller, Mathias

    2015-01-01

    The incidence and mortality rates of breast cancer in Northeast Brazil are increasing and little is known about prevailing reproductive factors contributing to this increase. A case-control study was conducted in a public hospital of Campina Grande, state of Paraiba, including 81 women with diagnosed invasive breast cancer and 162 age matched (±5 years) controls. Binominal logistic regression analysis was applied to estimate odds ratio (OR) and confidence intervals (CI) of risk factors. In this model, age at menarche≤12 (OR=2.120; CI: 1.043-4.308; p=0.038), single parity (OR=3.748; CI: 1.459- 9.627; p=0.06) and reproductive period>10 years (OR=3.042; CI: 1.421- 6.512; p=0.04) were identified as independent variables that significantly increased breast cancer risk of parous women. Compared to parous women who never practised breastfeeding, total breastfeeding time>24 months decreased the risk of breast cancer (OR=0.258; CI: 0.084- 0.787; p=0.017). The results indicated that modifiable reproductive factors contribute to breast cancer risk in women included in the present study. Women's knowledge about factors such as the protective effect of breastfeeding could reduce the risk of breast cancer.

  16. The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

    ERIC Educational Resources Information Center

    Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

    2010-01-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

  17. The potential of large studies for building genetic risk prediction models

    Cancer.gov

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  18. Developing Risk Prediction Models for Postoperative Pancreatic Fistula: a Systematic Review of Methodology and Reporting Quality.

    PubMed

    Wen, Zhang; Guo, Ya; Xu, Banghao; Xiao, Kaiyin; Peng, Tao; Peng, Minhao

    2016-04-01

    Postoperative pancreatic fistula is still a major complication after pancreatic surgery, despite improvements of surgical technique and perioperative management. We sought to systematically review and critically access the conduct and reporting of methods used to develop risk prediction models for predicting postoperative pancreatic fistula. We conducted a systematic search of PubMed and EMBASE databases to identify articles published before January 1, 2015, which described the development of models to predict the risk of postoperative pancreatic fistula. We extracted information of developing a prediction model including study design, sample size and number of events, definition of postoperative pancreatic fistula, risk predictor selection, missing data, model-building strategies, and model performance. Seven studies of developing seven risk prediction models were included. In three studies (42 %), the number of events per variable was less than 10. The number of candidate risk predictors ranged from 9 to 32. Five studies (71 %) reported using univariate screening, which was not recommended in building a multivariate model, to reduce the number of risk predictors. Six risk prediction models (86 %) were developed by categorizing all continuous risk predictors. The treatment and handling of missing data were not mentioned in all studies. We found use of inappropriate methods that could endanger the development of model, including univariate pre-screening of variables, categorization of continuous risk predictors, and model validation. The use of inappropriate methods affects the reliability and the accuracy of the probability estimates of predicting postoperative pancreatic fistula.

  19. Which Part of a Short, Global Risk Assessment, the Risk Instrument for Screening in the Community, Predicts Adverse Healthcare Outcomes?

    PubMed Central

    O'Caoimh, Rónán; FitzGerald, Carol; Cronin, Una; Svendrovski, Anton; Gao, Yang; Healy, Elizabeth; O'Connell, Elizabeth; O'Keeffe, Gabrielle; O'Herlihy, Eileen; Weathers, Elizabeth; Cornally, Nicola; Leahy-Warren, Patricia; Orfila, Francesc; Paúl, Constança; Clarnette, Roger; Molloy, D. William

    2015-01-01

    The Risk Instrument for Screening in the Community (RISC) is a short, global risk assessment to identify community-dwelling older adults' one-year risk of institutionalisation, hospitalisation, and death. We investigated the contribution that the three components of the RISC (concern, its severity, and the ability of the caregiver network to manage concern) make to the accuracy of the instrument, across its three domains (mental state, activities of daily living (ADL), and medical state), by comparing their accuracy to other assessment instruments in the prospective Community Assessment of Risk and Treatment Strategies study. RISC scores were available for 782 patients. Across all three domains each subtest more accurately predicted institutionalisation compared to hospitalisation or death. The caregiver network's ability to manage ADL more accurately predicted institutionalisation (AUC 0.68) compared to hospitalisation (AUC 0.57, P = 0.01) or death (AUC 0.59, P = 0.046), comparing favourably with the Barthel Index (AUC 0.67). The severity of ADL (AUC 0.63), medical state (AUC 0.62), Clinical Frailty Scale (AUC 0.67), and Charlson Comorbidity Index (AUC 0.66) scores had similar accuracy in predicting mortality. Risk of hospitalisation was difficult to predict. Thus, each component, and particularly the caregiver network, had reasonable accuracy in predicting institutionalisation. No subtest or assessment instrument accurately predicted risk of hospitalisation. PMID:26346934

  20. Predicting bioaccumulation of PAHs in the trophic chain in the estuary region of Paranagua, Brazil.

    PubMed

    Froehner, Sandro; Maceno, Marcell; Machado, Karina Scurupa

    2011-03-01

    The presence of polycyclic aromatic hydrocarbon (PAH) compounds in sediment and water samples collected in the estuary area of Paranagua, southern Brazil, was investigated. There is a lot of port activity in the region. Recreational fishing is widespread; thus, there is concern about possible contamination by PAHs. The 16 priority PAHs were investigated, and only eight were found. The total concentration of PAHs ranged from 40.8 to 406.8 ng/g. High molecular weight were the most abundant, while PAHs with a low molecular weight were absent. There are suspicions that the main source of PAHs is combustion, but some uncertainties exist, and there may even be the presence of PAHs resulting from accidental spills of crude oil. Although the sediments contain PAHs, the amount is below the maximum concentrations allowed by the Brazilian environmental legislation, as well as the maximum levels at which adverse effects are observed. From the analytical results, a probable bioaccumulation was assessed in the local trophic chain using a mathematical model (Arnot and Gobas, Environ Toxicol Chem 23(10):2343-2355, 2004). The model showed that there is a possibility of biomagnification along the food chain selected. Three fishes with high local consumption were selected, and the concentration of some PAHs could be found in those fishes.

  1. Climatic Variables Do Not Directly Predict Spider Richness and Abundance in Semiarid Caatinga Vegetation, Brazil.

    PubMed

    Carvalho, Leonardo S; Sebastian, Nicholas; Araújo, Helder F P; Dias, Sidclay C; Venticinque, Eduardo; Brescovit, Antonio D; Vasconcellos, Alexandre

    2015-02-01

    Spiders are abundant in tropical ecosystems and exert predatory pressure on a wide variety of invertebrate populations and also serve as prey for many others organisms, being part of complex interrelationships influenced directly and indirectly by a myriad of factors. We examined the influence of biotic (i.e., prey availability) and abiotic (i.e., temperature, precipitation, relative humidity, real evapotranspiration) factors on species richness and abundance during a two-year period in the semiarid Caatinga vegetation in northeastern Brazil. Data were analyzed through partial autocorrelation functions, cross correlations, and a path analysis. A total of 2522 spiders were collected with beating tray, pit-fall traps, and malaise traps, comprising 91 species and 34 families. Spider abundance peaked in the rainy season. Our results suggest that total invertebrate abundance has a direct influence on spider richness and abundance, whereas the effects of precipitation were mainly indirectly related to most spider assemblage parameters. The increase in vegetation cover with the rainy season in the Caatinga provides more breeding and foraging sites for spiders and stimulates their activities. Additionally, rainfall in arid and semiarid ecosystems stimulated the activity and reproduction of many herbivore and detritivore invertebrates dependent on plant biomass and necromass consumption, leading to an increase in spider prey availability.

  2. Predicting urban outdoor thermal comfort by the Universal Thermal Climate Index UTCI--a case study in Southern Brazil.

    PubMed

    Bröde, Peter; Krüger, Eduardo L; Rossi, Francine A; Fiala, Dusan

    2012-05-01

    Recognising that modifications to the physical attributes of urban space are able to promote improved thermal outdoor conditions and thus positively influence the use of open spaces, a survey to define optimal thermal comfort ranges for passers-by in pedestrian streets was conducted in Curitiba, Brazil. We applied general additive models to study the impact of temperature, humidity, and wind, as well as long-wave and short-wave radiant heat fluxes as summarised by the recently developed Universal Thermal Climate Index (UTCI) on the choice of clothing insulation by fitting LOESS smoothers to observations from 944 males and 710 females aged from 13 to 91 years. We further analysed votes of thermal sensation compared to predictions of UTCI. The results showed that females chose less insulating clothing in warm conditions compared to males and that observed values of clothing insulation depended on temperature, but also on season and potentially on solar radiation. The overall pattern of clothing choice was well reflected by UTCI, which also provided for good predictions of thermal sensation votes depending on the meteorological conditions. Analysing subgroups indicated that the goodness-of-fit of the UTCI was independent of gender and age, and with only limited influence of season and body composition as assessed by body mass index. This suggests that UTCI can serve as a suitable planning tool for urban thermal comfort in sub-tropical regions.

  3. Childhood trauma and suicide risk in a sample of young individuals aged 14-35 years in southern Brazil.

    PubMed

    Barbosa, Luana Porto; Quevedo, Luciana; da Silva, Giovanna Del Grande; Jansen, Karen; Pinheiro, Ricardo Tavares; Branco, Jerônimo; Lara, Diogo; Oses, Jean; da Silva, Ricardo Azevedo

    2014-07-01

    Suicide is among the main causes of death of people aged between 15 and 44 years old. Childhood trauma is an important risk factor for suicide. Hence, the objective of this study was to verify the relationship between childhood trauma and current suicide risk (suicidal behavior and ideation) in individuals aged 14-35 years, in the city of Pelotas, Brazil. This is a cross-sectional, population-based study. Sample selection was performed by clusters. Suicide risk was evaluated using the Mini International Neuropsychiatric Interview (MINI) and Childhood trauma was assessed with the Childhood Trauma Questionnaire (CTQ). Moreover, the participants responded to a questionnaire concerning socioeconomic status, work, and substance use. The sample was composed of 1,380 individuals. The prevalence of suicide risk was 11.5%. The prevalence figures of childhood trauma were 15.2% (emotional neglect), 13.5% (physical neglect), 7.6% (sexual abuse), 10.1% (physical abuse), and 13.8% (emotional abuse). Suicide risk was associated (p<.001) with gender, work, alcohol abuse, tobacco use, and all types of childhood trauma. The odds of suicide risk were higher in women (OR=1.8), people who were not currently working (OR=2.3), individuals who presented alcohol abuse (OR=2.6), and among tobacco smokers (OR=3.4). Moreover, suicide risk was increased in all types of trauma: emotional neglect (OR=3.7), physical neglect (OR=2.8), sexual abuse (OR=3.4), physical abuse (OR=3.1), and emotional abuse (OR=6.6). Thus, preventing early trauma may reduce suicide risk in young individuals.

  4. Predicting extinction risk of Brazilian Atlantic forest angiosperms.

    PubMed

    Leão, Tarciso C C; Fonseca, Carlos R; Peres, Carlos A; Tabarelli, Marcelo

    2014-10-01

    Understanding how plant life history affects species vulnerability to anthropogenic disturbances and environmental change is a major ecological challenge. We examined how vegetation type, growth form, and geographic range size relate to extinction risk throughout the Brazilian Atlantic Forest domain. We used a database containing species-level information of 6,929 angiosperms within 112 families and a molecular-based working phylogeny. We used decision trees, standard regression, and phylogenetic regression to explore the relationships between species attributes and extinction risk. We found a significant phylogenetic signal in extinction risk. Vegetation type, growth form, and geographic range size were related to species extinction risk, but the effect of growth form was not evident after phylogeny was controlled for. Species restricted to either rocky outcrops or scrub vegetation on sandy coastal plains exhibited the highest extinction risk among vegetation types, a finding that supports the hypothesis that species adapted to resource-limited environments are more vulnerable to extinction. Among growth forms, epiphytes were associated with the highest extinction risk in non-phylogenetic regression models, followed by trees, whereas shrubs and climbers were associated with lower extinction risk. However, the higher extinction risk of epiphytes was not significant after correcting for phylogenetic relatedness. Our findings provide new indicators of extinction risk and insights into the mechanisms governing plant vulnerability to extinction in a highly diverse flora where human disturbances are both frequent and widespread.

  5. Which Risk Factors Predict the Basic Reading Skills of Children at Risk for Emotional and Behavioral Disorders?

    ERIC Educational Resources Information Center

    Nelson, J. Ron; Stage, Scott; Trout, Alex; Duppong-Hurley, Kristin; Epstein, Michael H.

    2008-01-01

    Multinomial stepwise logistic regression analyses were used to establish the most robust set of risk factors that would best predict low basic reading skills (i.e., a standard score less than 85 on the Woodcock Reading Mastery Test-Revised Basic Reading Skills cluster) of kindergarten and first-grade children at risk for emotional and behavioral…

  6. The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer.

    PubMed

    Hawken, Steven J; Greenwood, Celia M T; Hudson, Thomas J; Kustra, Rafal; McLaughlin, John; Yang, Quanhe; Zanke, Brent W; Little, Julian

    2010-07-01

    Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., approximately 140-160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual's CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci

  7. Evaluation of the predictability of real-time crash risk models.

    PubMed

    Xu, Chengcheng; Liu, Pan; Wang, Wei

    2016-09-01

    The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the predictability of a real-time crash risk model. The predictability is defined as the crash probability given the crash precursor identified by the crash risk model. An equation was derived based on the Bayes' theorem for estimating approximately the predictability of crash risk models. The estimated predictability was then used to quantitatively evaluate the effects of the threshold of crash precursors, the matched and unmatched case-control design, and the control-to-case ratio on the predictability of crash risk models. It was found that: (a) the predictability of a crash risk model can be measured as the product of prior crash probability and the ratio between sensitivity and false alarm rate; (b) there is a trade-off between the predictability and sensitivity of a real-time crash risk model; (c) for a given level of sensitivity, the predictability of the crash risk model that is developed using the unmatched case-controlled sample is always better than that of the model developed using the matched case-controlled sample; and (d) when the control-to-case ratio is beyond 4:1, the increase in control-to-case ratio does not lead to clear improvements in predictability.

  8. Risk Prediction Models for Other Cancers or Multiple Sites

    Cancer.gov

    Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Risk tools for the prediction of violence: 'VRAG, HCR-20, PCL-R'.

    PubMed

    Jaber, F S; Mahmoud, K F

    2015-03-01

    Many instruments have been introduced as measures of violence risk prediction. Studies on risk assessment displayed two major approaches - clinical risk evaluation and actuarial measures - and three tools were mostly used: (1) Violence Risk Appraisal Guide, (2) Historical-Clinical-Risk-20 item scale and (3) Psychopathy Checklist-Revised. Although these tools are commonly used in clinical practice, they differ in their uses, benefits and limitations, and their ability to predict future violence. Subsequently, this paper aim to provide the readers an in-depth description that specifies these aspects, as well as a comparison of these tools in order to help readers decide which tool to use.

  10. Simplified risk score models accurately predict the risk of major in-hospital complications following percutaneous coronary intervention.

    PubMed

    Resnic, F S; Ohno-Machado, L; Selwyn, A; Simon, D I; Popma, J J

    2001-07-01

    The objectives of this analysis were to develop and validate simplified risk score models for predicting the risk of major in-hospital complications after percutaneous coronary intervention (PCI) in the era of widespread stenting and use of glycoprotein IIb/IIIa antagonists. We then sought to compare the performance of these simplified models with those of full logistic regression and neural network models. From January 1, 1997 to December 31, 1999, data were collected on 4,264 consecutive interventional procedures at a single center. Risk score models were derived from multiple logistic regression models using the first 2,804 cases and then validated on the final 1,460 cases. The area under the receiver operating characteristic (ROC) curve for the risk score model that predicted death was 0.86 compared with 0.85 for the multiple logistic model and 0.83 for the neural network model (validation set). For the combined end points of death, myocardial infarction, or bypass surgery, the corresponding areas under the ROC curves were 0.74, 0.78, and 0.81, respectively. Previously identified risk factors were confirmed in this analysis. The use of stents was associated with a decreased risk of in-hospital complications. Thus, risk score models can accurately predict the risk of major in-hospital complications after PCI. Their discriminatory power is comparable to those of logistic models and neural network models. Accurate bedside risk stratification may be achieved with these simple models.

  11. A Comparative Study of Adolescent Risk Assessment Instruments: Predictive and Incremental Validity

    ERIC Educational Resources Information Center

    Welsh, Jennifer L.; Schmidt, Fred; McKinnon, Lauren; Chattha, H. K.; Meyers, Joanna R.

    2008-01-01

    Promising new adolescent risk assessment tools are being incorporated into clinical practice but currently possess limited evidence of predictive validity regarding their individual and/or combined use in risk assessments. The current study compares three structured adolescent risk instruments, Youth Level of Service/Case Management Inventory…

  12. Age and regional differences in clinical presentation and risk of hospitalization for dengue in Brazil, 2000-2014

    PubMed Central

    Burattini, Marcelo N.; Lopez, Luis F.; Coutinho, Francisco A.B.; Siqueira, João B.; Homsani, Sheila; Sarti, Elsa; Massad, Eduardo

    2016-01-01

    OBJECTIVES: Dengue cases range from asymptomatic to severe, eventually leading to hospitalization and death. Timely and appropriate management is critical to reduce morbidity. Since 1980, dengue has spread throughout Brazil, affecting an increasing number of individuals. This paper describes age and regional differences in dengue’s clinical presentation and associated risk of hospitalization based on more than 5 million cases reported to the Brazilian Ministry of Health from 2000-2014. METHODS: We performed a retrospective analysis of ∼5,450,000 dengue cases, relating clinical manifestations and the risk of hospitalization to age, gender, previous infection by dengue, dengue virus serotype, years of formal education, delay to first attendance and the occurrence of dengue during outbreaks and in different Brazilian regions. RESULTS: Complicated forms of dengue occurred more frequently among those younger than 10 years (3.12% vs 1.92%) and those with dengue virus 2 infection (7.65% vs 2.42%), with a delay to first attendance >2 days (3.18% vs 0.82%) and with ≤4 years of formal education (2.02% vs 1.46%). The risk of hospitalization was higher among those aged 6-10 years old (OR 4.57; 95% CI 1.43-29.96) and those who were infected by dengue virus 2 (OR 6.36; 95% CI 2.52-16.06), who lived in the Northeast region (OR 1.38; 95% CI 1.11-2.10) and who delayed first attendance by >5 days (composite OR 3.15; 95% CI 1.33-8.9). CONCLUSIONS: In Brazil, the occurrence of severe dengue and related hospitalization is associated with being younger than 10 years old, being infected by dengue virus 2 or 3, living in the Northeast region (the poorest and the second most populated) and delaying first attendance for more than 2 days. PMID:27626476

  13. Narrative review: Assessment of C-reactive protein in risk prediction for cardiovascular disease.

    PubMed

    Lloyd-Jones, Donald M; Liu, Kiang; Tian, Lu; Greenland, Philip

    2006-07-04

    Some experts propose C-reactive protein (CRP) as a screening tool for prediction of cardiovascular disease (CVD). Many epidemiologic studies show positive associations between elevated CRP levels and incident CVD. Assessment of the value of new prognostic tests, however, must rely on understanding of test characteristics rather than on associations measured by relative risks. In the case of CRP, test characteristics must be judged in the context of currently available CVD risk prediction algorithms. In this review of literature published before January 2006, the authors describe what is known about the additional utility of CRP in risk prediction. They find no definitive evidence that, for most individuals, CRP adds substantial predictive value above that provided by risk estimation using traditional risk factors for CVD. Use of CRP may add to risk estimation in a limited subset of individuals who are at intermediate predicted risk according to the Framingham risk score. The authors propose that many questions still must be addressed before CRP is incorporated into risk prediction algorithms and before universal screening with CRP can be recommended.

  14. Ryegrass cv. Lema and guava cv. Paluma biomonitoring suitability for estimating nutritional contamination risks under seasonal climate in Southeastern Brazil.

    PubMed

    Bulbovas, Patricia; Camargo, Carla Z S; Domingos, Marisa

    2015-08-01

    The risks posed by nutrient deposition due to air pollution on ecosystems and their respective services to human beings can be appropriately estimated by bioindicator plants when they are well acclimated to the study region environmental conditions. This assumption encouraged us to comparatively evaluate the accumulation potential of ryegrass cv. Lema and guava cv. Paluma macro and micronutrients. We also indicated the most appropriate species for biomonitoring nutrient contamination risks in tropical areas of Southeastern Brazil, which are characterized by marked dry and wet seasons and complex mixtures of air pollutants from different sources (industries, vehicle traffic and agriculture). The study was conducted in 14 sites with different neighboring land uses, within the Metropolitan Region of Campinas, central-eastern region of São Paulo State. The exposure experiments with ryegrass and guava were consecutively repeated 40 (28 days each) and 12 (84 days each) times, respectively, from Oct/2010 to Sept/2013. Macro and micronutrients were analyzed and background concentrations and enrichment ratios (ER) were estimated to classify the contamination risk within the study region. Significantly higher ER suggested that ryegrass were the most appropriate accumulator species for N, S, Mg, Fe, Mn, Cu and Zn deposition and guava for K, Ca, P and B deposition. Based on these biomonitoring adjustments, we concluded that the nutrient deposition was spatially homogeneous in the study area, but clear seasonality in the contamination risk by nutritional inputs was evidenced. Significantly higher contamination risk by S, Fe, K and B occurred during the dry season and enhanced contamination risk by Mn, Cu and Zn were highlighted during the wet season. Distinctly high contamination risk was estimated for S, Fe and Mn in several exposure experiments.

  15. Risk factors and prevalence of newborn hearing loss in a private health care system of Porto Velho, Northern Brazil

    PubMed Central

    de Oliveira, Juliana Santos; Rodrigues, Liliane Barbosa; Aurélio, Fernanda Soares; da Silva, Virgínia Braz

    2013-01-01

    OBJECTIVE: To determine the prevalence of hearing loss and to analyze the results of newborn hearing screening and audiological diagnosis in private health care systems. METHODS Cross-sectional and retrospective study in a database of newborn hearing screening performed by a private clinic in neonates born in private hospitals of Porto Velho, Rondônia, Northern Brazil. The screening results, the risk for hearing loss, the risk indicators for hearing loss and the diagnosis were descriptively analyzed. Newborns cared in rooming in with their mothers were compared to those admitted to the Intensive Care Unit regarding risk factors for hearing loss. RESULTS: Among 1,146 (100%) enrolled newborns, 1,064 (92.8%) passed and 82 (7.2%) failed the hearing screening. Among all screened neonates, 1,063 (92.8%) were cared in rooming and 83 (7.2%) needed intensive care; 986 (86.0%) were considered at low risk and 160 (14.0%) at high risk for hearing problems. Of the 160 patients identified as having high risk for hearing loss, 83 (37.7%) were admitted to an hospitalized in the Intensive Care Unit, 76 (34.5%) used ototoxic drugs and 38 (17.2%) had a family history of hearing loss in childhood. Hearing loss was diagnosed in two patients (0.2% of the screened sample). CONCLUSIONS: The prevalence of hearing loss in newborns from private hospitals was two cases per 1,000 evaluated patients. The use of ototoxic drugs, admission to Intensive Care Unit and family history of hearing loss were the most common risk factors for hearing loss in the studied population. PMID:24142311

  16. Predicting carbon dynamics in integrated production systems in Brazil using the CQESTR model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Process-based carbon models are research tools to predict management impact on soil organic carbon (SOC) and options to increase SOC stocks and reduce CO2. The CQESTR model was used to examine the effect of soil management practices, including integrated crop-livestock system (iCLS), and various sc...

  17. Social deprivation index and lymphatic filariasis: a tool for mapping urban areas at risk in northeastern Brazil.

    PubMed

    Bonfim, Cristine; Aguiar-Santos, Ana Maria; Pedroza, Dinilson; Costa, Tadeu Rodrigues; Portugal, José Luiz; Oliveira, Conceição; Medeiros, Zulma

    2009-09-01

    This paper describes the construction and application of a social deprivation index that was created to explore the relationship between lymphatic filariasis and socioenvironmental variables in the municipality of Jaboatão dos Guararapes, Pernambuco, Brazil, thereby contributing towards identifying priority areas for interventions. This indicator was obtained from principal-component factor analysis. Variables available from the national census representing socioenvironmental conditions, household characteristics and urban services were used. Epidemiological data came from a parasitological survey on lymphatic filariasis. 23 673 individuals were examined and 323 were positive (1.4%). Two factors that together explained 80.61% of the total variance were selected. The social deprivation strata were capable of indicating a risk gradient, with 74.9% of the microfilaremia cases situated in the high-risk stratum. Principal-component factor analysis was shown to be sensitive for selecting indicators associated with the risk of lymphatic filariasis transmission and for detecting areas potentially at risk. The capacity of the social deprivation index for picking up social inequalities qualifies it as a new tool for use in planning interventions aimed at controlling lymphatic filariasis in urban spaces.

  18. A coffee can, factor analysis, and prediction of antisocial behavior: the structure of criminal risk.

    PubMed

    Kroner, Daryl G; Mills, Jeremy F; Reddon, John R

    2005-01-01

    The predictive accuracy of the Psychopathy Checklist-Revised, Level of Service Inventory-Revised, Violence Risk Appraisal Guide, and the General Statistical Information on Recidivism were compared to four instruments randomly generated from the total pool of original items. None of the four original instruments better predicted post-release failure than the four randomly generated instruments. These results suggest two conclusions: (a) the instruments are only measuring criminal risk, and (b) no single instrument has captured sufficient risk assessment theory to result in better prediction than randomly derived instruments measuring criminal risk. A two-stage factor analysis was completed on 1614 cases. This analysis of the risk items indicated a 4-factor solution and all 4 factors were equal to the original instruments in predicting post-release failure. Thus, the original instruments did not improve prediction over randomly structured scales, nor did the restructuring of items improve risk assessment, suggesting substantial deficiencies in the conceptualization of risk assessment and instrumentation. We argue that developing a risk-based construct, which involves hypothesis testing and an explanation of behavior, is the optimal method to advance risk assessment within the criminal justice and mental health systems. Such an approach would provide targeted areas for clinical intervention that are salient to risk.

  19. A New Method to Predict the Epidemiology of Fungal Keratitis by Monitoring the Sales Distribution of Antifungal Eye Drops in Brazil

    PubMed Central

    Ibrahim, Marlon Moraes; de Angelis, Rafael; Lima, Acacio Souza; Viana de Carvalho, Glauco Dreyer; Ibrahim, Fuad Moraes; Malki, Leonardo Tannus; de Paula Bichuete, Marina; de Paula Martins, Wellington; Rocha, Eduardo Melani

    2012-01-01

    Purpose Fungi are a major cause of keratitis, although few medications are licensed for their treatment. The aim of this study is to observe the variation in commercialisation of antifungal eye drops, and to predict the seasonal distribution of fungal keratitis in Brazil. Methods Data from a retrospective study of antifungal eye drops sales from the only pharmaceutical ophthalmologic laboratory, authorized to dispense them in Brazil (Opthalmos) were gathered. These data were correlated with geographic and seasonal distribution of fungal keratitis in Brazil between July 2002 and June 2008. Results A total of 26,087 antifungal eye drop units were sold, with a mean of 2.3 per patient. There was significant variation in antifungal sales during the year (p<0.01). A linear regression model displayed a significant association between reduced relative humidity and antifungal drug sales (R2 = 0.17,p<0.01). Conclusions Antifungal eye drops sales suggest that there is a seasonal distribution of fungal keratitis. A possible interpretation is that the third quarter of the year (a period when the climate is drier), when agricultural activity is more intense in Brazil, suggests a correlation with a higher incidence of fungal keratitis. A similar model could be applied to other diseases, that are managed with unique, or few, and monitorable medications to predict epidemiological aspects. PMID:22457787

  20. Multimethod prediction of child abuse risk in an at-risk sample of male intimate partner violence offenders.

    PubMed

    Rodriguez, Christina M; Gracia, Enrique; Lila, Marisol

    2016-10-01

    The vast majority of research on child abuse potential has concentrated on women demonstrating varying levels of risk of perpetrating physical child abuse. In contrast, the current study considered factors predictive of physical child abuse potential in a group of 70 male intimate partner violence offenders, a group that would represent a likely high risk group. Elements of Social Information Processing theory were evaluated, including pre-existing schemas of empathy, anger, and attitudes approving of parent-child aggression considered as potential moderators of negative attributions of child behavior. To lend methodological rigor, the study also utilized multiple measures and multiple methods, including analog tasks, to predict child abuse risk. Contrary to expectations, findings did not support the role of anger independently predicting child abuse risk in this sample of men. However, preexisting beliefs approving of parent-child aggression, lower empathy, and more negative child behavior attributions independently predicted abuse potential; in addition, greater anger, poorer empathy, and more favorable attitudes toward parent-child aggression also exacerbated men's negative child attributions to further elevate their child abuse risk. Future work is encouraged to consider how factors commonly considered in women parallel or diverge from those observed to elevate child abuse risk in men of varying levels of risk.

  1. Development and Validation of a Lung Cancer Risk Prediction Model for African-Americans

    PubMed Central

    Etzel, Carol J.; Kachroo, Sumesh; Liu, Mei; D'Amelio, Anthony; Dong, Qiong; Cote, Michele L.; Wenzlaff, Angela S.; Hong, Waun Ki; Greisinger, Anthony J.; Schwartz, Ann G.; Spitz, Margaret R.

    2009-01-01

    Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self- reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67−0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57−0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction

  2. Modifiable risk factors for overweight and obesity in children and adolescents from São Paulo, Brazil

    PubMed Central

    2011-01-01

    Background Brazil is currently experiencing a nutrition transition: the displacement of traditional diets with foods high in saturated fat, sodium, and cholesterol and an increase in sedentary lifestyles. Despite these trends, our understanding of child obesity in Brazil is limited. Thus, the aims of this study were (1) to investigate the current prevalence of overweight and obesity in a large sample of children and adolescents living in São Paulo, Brazil, and (2) to identify the lifestyle behaviors associated with an increased risk of obesity in young Brazilians. Methods A total of 3,397 children and adolescents (1,596 male) aged 7-18 years were randomly selected from 22 schools in São Paulo, Brazil. Participants were classified as normal weight, overweight, or obese based on international age- and sex-specific body mass index thresholds. Selected sociodemographic, physical activity, and nutrition behaviors were assessed via questionnaire. Results Overall, 19.4% of boys and 16.1% of girls were overweight while 8.9% and 4.3% were obese. Two-way analysis of variance revealed that the prevalence of overweight and obesity was significantly higher in boys and in younger children when compared to girls and older children, respectively (P < 0.05 for both). Logistic regression analysis revealed that overweight was associated with more computer usage, parental encouragement to be active, and light soft drink consumption after controlling for differences in sex, age, and parental education (P < 0.05 for all). Conversely, overweight was associated with less active transport to school, eating before sleep, and consumption of breakfast, full-sugar soft drinks, fried food and confectionery (P < 0.05 for all). Conclusions Our results show that obesity in São Paulo children and adolescents has reached a level equivalent to that seen in many developed countries. We have also identified three key modifiable factors related to obesity that may be appropriate targets for future

  3. Genetic risk profiling for prediction of type 2 diabetes

    PubMed Central

    Mihaescu, Raluca; Meigs, James; Sijbrands, Eric; Janssens, A. Cecile

    2011-01-01

    Type 2 diabetes (T2D) is a common disease caused by a complex interplay between many genetic and environmental factors. Candidate gene studies and recent collaborative genome-wide association efforts revealed at least 38 common single nucleotide polymorphisms (SNPs) associated with increased risk of T2D. Genetic testing of multiple SNPs is considered a potentially useful tool for early detection of individuals at high diabetes risk leading to improved targeting of preventive interventions. PMID:21278902

  4. Predictive Malaria Risk and Uncertainty Mapping in Nchelenge District, Zambia: Evidence of Widespread, Persistent Risk and Implications for Targeted Interventions

    PubMed Central

    Pinchoff, Jessie; Chaponda, Mike; Shields, Timothy; Lupiya, James; Kobayashi, Tamaki; Mulenga, Modest; Moss, William J.; Curriero, Frank C.

    2015-01-01

    Malaria risk maps may be used to guide policy decisions on whether vector control interventions should be targeted and, if so, where. Active surveillance for malaria was conducted through household surveys in Nchelenge District, Zambia from April 2012 through December 2014. Households were enumerated based on satellite imagery and randomly selected for study enrollment. At each visit, participants were administered a questionnaire and a malaria rapid diagnostic test (RDT). Logistic regression models were used to construct spatial prediction risk maps and maps of risk uncertainty. A total of 461 households were visited, comprising 1,725 participants, of whom 48% were RDT positive. Several environmental features were associated with increased household malaria risk in a multivariable logistic regression model adjusting for seasonal variation. The model was validated using both internal and external evaluation measures to generate and assess root mean square error, as well as sensitivity and specificity for predicted risk. The final, validated model was used to predict and map malaria risk including a measure of risk uncertainty. Malaria risk in a high, perennial transmission setting is widespread but heterogeneous at a local scale, with seasonal variation. Targeting malaria control interventions may not be appropriate in this epidemiological setting. PMID:26416106

  5. The link between childhood undernutrition and risk of chronic diseases in adulthood: a case study of Brazil.

    PubMed

    Sawaya, Ana L; Martins, Paula; Hoffman, Daniel; Roberts, Susan B

    2003-05-01

    Obesity, cardiovascular disease, and type 2 diabetes mellitus are now prevalent among adults living in developing countries; these chronic diseases affect socioeconomically disadvantaged adults living in impoverished families with undernourished children. This review summarizes data from Brazil--a developing country undergoing the nutrition transition--suggesting an association between childhood undernutrition and obesity and chronic degenerative disease. Potential mechanisms for the association include long-term effects of childhood undernutrition on energy expenditure, fat oxidation, regulation of food intake, susceptibility to the effects of high-fat diets, and altered insulin sensitivity. The combination of childhood undernutrition and adult chronic degenerative disease results in enormous social and economic burdens for developing countries. Further research is urgently needed to examine the effect of childhood undernutrition on risk of obesity and chronic degenerative diseases; one goal of such research would be to determine and provide low-cost methods for prevention and treatment.

  6. Prevalence and risk factors for cannabis use in low-income pregnant women in São Paulo, Brazil.

    PubMed

    Shu, Janet E; Huang, Hsiang; Menezes, Paulo R; Faisal-Cury, Alexandre

    2016-02-01

    Cannabis is the most commonly used illicit drug during the perinatal period and has potential risks to the fetus. The purpose of this study is to estimate the 1-year prevalence of cannabis use and identify associated factors for a population of low-income pregnant women in Brazil. We performed a cross-sectional analysis of 831 women surveyed using a structured questionnaire to collect sociodemographic, clinical, and substance use history. The 1-year prevalence of antenatal cannabis use was 4.2 %; reported lifetime use was 9.6 %. The presence of a common mental disorder and active tobacco smoking were independently associated with cannabis use, OR = 3.3 (95 % CI 1.65-6.59) and OR = 6.89 (95 % CI 3.45-13.8), respectively.

  7. Predicting Risk of Suicide Attempt Using History of Physical Illnesses From Electronic Medical Records

    PubMed Central

    Luo, Wei; Tran, Truyen; Berk, Michael; Venkatesh, Svetha

    2016-01-01

    Background Although physical illnesses, routinely documented in electronic medical records (EMR), have been found to be a contributing factor to suicides, no automated systems use this information to predict suicide risk. Objective The aim of this study is to quantify the impact of physical illnesses on suicide risk, and develop a predictive model that captures this relationship using EMR data. Methods We used history of physical illnesses (except chapter V: Mental and behavioral disorders) from EMR data over different time-periods to build a lookup table that contains the probability of suicide risk for each chapter of the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes. The lookup table was then used to predict the probability of suicide risk for any new assessment. Based on the different lengths of history of physical illnesses, we developed six different models to predict suicide risk. We tested the performance of developed models to predict 90-day risk using historical data over differing time-periods ranging from 3 to 48 months. A total of 16,858 assessments from 7399 mental health patients with at least one risk assessment was used for the validation of the developed model. The performance was measured using area under the receiver operating characteristic curve (AUC). Results The best predictive results were derived (AUC=0.71) using combined data across all time-periods, which significantly outperformed the clinical baseline derived from routine risk assessment (AUC=0.56). The proposed approach thus shows potential to be incorporated in the broader risk assessment processes used by clinicians. Conclusions This study provides a novel approach to exploit the history of physical illnesses extracted from EMR (ICD-10 codes without chapter V-mental and behavioral disorders) to predict suicide risk, and this model outperforms existing clinical assessments of suicide risk. PMID:27400764

  8. icuARM-II: improving the reliability of personalized risk prediction in pediatric intensive care units

    PubMed Central

    Cheng, Chih-Wen; Chanani, Nikhil; Maher, Kevin; Wang

    2016-01-01

    Clinicians in intensive care units (ICUs) rely on standardized scores as risk prediction models to predict a patient’s vulnerability to life-threatening events. Conventional Current scales calculate scores from a fixed set of conditions collected within a specific time window. However, modern monitoring technologies generate complex, temporal, and multimodal patient data that conventional prediction models scales cannot fully utilize. Thus, a more sophisticated model is needed to tailor individual characteristics and incorporate multiple temporal modalities for a personalized risk prediction. Furthermore, most scales models focus on adult patients. To address this needdeficiency, we propose a newly designed ICU risk prediction system, called icuARM-II, using a large-scaled pediatric ICU database from Children’s Healthcare of Atlanta. This novel database contains clinical data collected in 5,739 ICU visits from 4,975 patients. We propose a temporal association rule mining framework giving clinicians a potential to perform predict risks prediction based on all available patient conditions without being restricted by a fixed observation window. We also develop a new metric that can rigidly assesses the reliability of all all generated association rules. In addition, the icuARM-II features an interactive user interface. Using the icuARM-II, our results demonstrated showed a use case of short-term mortality prediction using lab testing results, which demonstrated a potential new solution for reliable ICU risk prediction using personalized clinical data in a previously neglected population. PMID:27532061

  9. Predicting reading disability: early cognitive risk and protective factors.

    PubMed

    Eklund, Kenneth Mikael; Torppa, Minna; Lyytinen, Heikki

    2013-02-01

    This longitudinal study examined early cognitive risk and protective factors for Grade 2 reading disability (RD). We first examined the reading outcome of 198 children in four developmental cognitive subgroups that were identified in our previous analysis: dysfluent trajectory, declining trajectory, unexpected trajectory and typical trajectory. We found that RD was unevenly distributed among the subgroups, although children with RD were found in all subgroups. A majority of the children with RD had familial risk for dyslexia. Second, we examined in what respect children with similar early cognitive development but different RD outcome differ from each other in cognitive skills, task-focused behaviour and print exposure. The comparison of the groups with high cognitive risk but different RD outcome showed significant differences in phonological skills, in the amount of shared reading and in task-focused behaviour. Children who ended up with RD despite low early cognitive risk had poorer cognitive skills, more task avoidance and they were reading less than children without RD and low cognitive risk. In summary, lack of task avoidance seemed to act as a protective factor, which underlines the importance of keeping children interested in school work and reading.

  10. Predicting Parkinson disease in the community using a nonmotor risk score.

    PubMed

    Darweesh, Sirwan K L; Koudstaal, Peter J; Stricker, Bruno H; Hofman, Albert; Steyerberg, Ewout W; Ikram, M Arfan

    2016-07-01

    At present, there are no validated methods to identify persons who are at increased risk for Parkinson Disease (PD) from the general population. We investigated the clinical usefulness of a recently proposed non-motor risk score for PD (the PREDICT-PD risk score) in the population-based Rotterdam Study. At baseline (1990), we constructed a weighted risk score based on 10 early nonmotor features and risk factors in 6492 persons free of parkinsonism and dementia. We followed these persons for up to 20 years (median 16.1 years) for the onset of PD until 2011. We studied the association between the PREDICT-PD risk score and incident PD using competing risk regression models with adjustment for age and sex. In addition, we assessed whether the PREDICT-PD risk score improved discrimination (C-statistics) and risk classification (net reclassification improvement) of incident PD beyond age and sex. During follow-up, 110 persons were diagnosed with incident PD. The PREDICT-PD risk score was associated with incident PD (hazard ratio [HR] = 1.30; 95 % confidence interval [1.06; 1.59]) and yielded a small, non-significant improvement in overall discrimination (ΔC-statistic = 0.018[-0.005; 0.041]) and risk classification (net reclassification improvement = 0.172[-0.017; 0.360]) of incident PD. In conclusion, the PREDICT-PD risk score only slightly improves long-term prediction of PD in the community.

  11. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    PubMed Central

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  12. Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

    PubMed Central

    2011-01-01

    Background The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults. Methods We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance. Results Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in

  13. Cardiorespiratory fitness is a stronger indicator of cardiometabolic risk factors and risk prediction than self-reported physical activity levels.

    PubMed

    Gray, Benjamin J; Stephens, Jeffrey W; Williams, Sally P; Davies, Christine A; Turner, Daniel; Bracken, Richard M

    2015-11-01

    This study investigated the relationships of self-reported physical activity levels and cardiorespiratory fitness in 81 males to assess which measurement is the greatest indicator of cardiometabolic risk. Physical activity levels were determined by the General Practice Physical Activity Questionnaire tool and cardiorespiratory fitness assessed using the Chester Step Test. Cardiovascular disease risk was estimated using the QRISK2, Framingham Lipids, Framingham body mass index and Joint British Societies' Guidelines-2 equations, and type 2 diabetes mellitus risk calculated using QDiabetes, Leicester Risk Assessment, Finnish Diabetes Risk Score and Cambridge Risk Score models. Categorising employees by cardiorespiratory fitness categories ('Excellent/Good' vs 'Average/Below Average') identified more differences in cardiometabolic risk factor (body mass index, waist circumference, total cholesterol, total cholesterol:high-density lipoprotein ratio, high-density lipoprotein cholesterol, triglycerides, HbA(1c)) scores than physical activity (waist circumference only). Cardiorespiratory fitness levels also demonstrated differences in all four type 2 diabetes mellitus risk prediction models and both the QRISK2 and Joint British Societies' Guidelines-2 cardiovascular disease equations. Furthermore, significant negative correlations (p < 0.001) were observed between individual cardiorespiratory fitness values and estimated risk in all prediction models. In conclusion, from this preliminary observational study, cardiorespiratory fitness levels reveal a greater number of associations with markers of cardiovascular disease or type 2 diabetes mellitus compared to physical activity determined by the General Practice Physical Activity Questionnaire tool.

  14. Is Food Insecurity Associated with HIV Risk? Cross-Sectional Evidence from Sexually Active Women in Brazil

    PubMed Central

    Tsai, Alexander C.; Hung, Kristin J.; Weiser, Sheri D.

    2012-01-01

    Background Understanding how food insecurity among women gives rise to differential patterning in HIV risks is critical for policy and programming in resource-limited settings. This is particularly the case in Brazil, which has undergone successive changes in the gender and socio-geographic composition of its complex epidemic over the past three decades. We used data from a national survey of Brazilian women to estimate the relationship between food insecurity and HIV risk. Methods and Findings We used data on 12,684 sexually active women from a national survey conducted in Brazil in 2006–2007. Self-reported outcomes were (a) consistent condom use, defined as using a condom at each occasion of sexual intercourse in the previous 12 mo; (b) recent condom use, less stringently defined as using a condom with the most recent sexual partner; and (c) itchy vaginal discharge in the previous 30 d, possibly indicating presence of a sexually transmitted infection. The primary explanatory variable of interest was food insecurity, measured using the culturally adapted and validated Escala Brasiliera de Segurança Alimentar. In multivariable logistic regression models, severe food insecurity with hunger was associated with a reduced odds of consistent condom use in the past 12 mo (adjusted odds ratio [AOR] = 0.67; 95% CI, 0.48–0.92) and condom use at last sexual intercourse (AOR = 0.75; 95% CI, 0.57–0.98). Self-reported itchy vaginal discharge was associated with all categories of food insecurity (with AORs ranging from 1.46 to 1.94). In absolute terms, the effect sizes were large in magnitude across all outcomes. Underweight and/or lack of control in sexual relations did not appear to mediate the observed associations. Conclusions Severe food insecurity with hunger was associated with reduced odds of condom use and increased odds of itchy vaginal discharge, which is potentially indicative of sexually transmitted infection, among sexually active women in Brazil

  15. Risk and return: evaluating Reverse Tracing of Precursors earthquake predictions

    NASA Astrophysics Data System (ADS)

    Zechar, J. Douglas; Zhuang, Jiancang

    2010-09-01

    In 2003, the Reverse Tracing of Precursors (RTP) algorithm attracted the attention of seismologists and international news agencies when researchers claimed two successful predictions of large earthquakes. These researchers had begun applying RTP to seismicity in Japan, California, the eastern Mediterranean and Italy; they have since applied it to seismicity in the northern Pacific, Oregon and Nevada. RTP is a pattern recognition algorithm that uses earthquake catalogue data to declare alarms, and these alarms indicate that RTP expects a moderate to large earthquake in the following months. The spatial extent of alarms is highly variable and each alarm typically lasts 9 months, although the algorithm may extend alarms in time and space. We examined the record of alarms and outcomes since the prospective application of RTP began, and in this paper we report on the performance of RTP to date. To analyse these predictions, we used a recently developed approach based on a gambling score, and we used a simple reference model to estimate the prior probability of target earthquakes for each alarm. Formally, we believe that RTP investigators did not rigorously specify the first two `successful' predictions in advance of the relevant earthquakes; because this issue is contentious, we consider analyses with and without these alarms. When we included contentious alarms, RTP predictions demonstrate statistically significant skill. Under a stricter interpretation, the predictions are marginally unsuccessful.

  16. Predictions of Leukemia Risks to Astronauts from Solar Particle Events

    NASA Technical Reports Server (NTRS)

    Cucinotta, F. A.; Atwell, W.; Kim, M. Y.; George, K. A.; Ponomarev, A.; Nikjoo, H.; Wilson, J. W.

    2006-01-01

    Leukemias consisting of acute and chronic myeloid leukemia and acute lymphatic lymphomas represent the earliest cancers that appear after radiation exposure, have a high lethality fraction, and make up a significant fraction of the overall fatal cancer risk from radiation for adults. Several considerations impact the recommendation of a preferred model for the estimation of leukemia risks from solar particle events (SPE's): The BEIR VII report recommends several changes to the method of calculation of leukemia risk compared to the methods recommended by the NCRP Report No. 132 including the preference of a mixture model with additive and multiplicative components in BEIR VII compared to the additive transfer model recommended by NCRP Report No. 132. Proton fluences and doses vary considerably across marrow regions because of the characteristic spectra of primary solar protons making the use of an average dose suspect. Previous estimates of bone marrow doses from SPE's have used an average body-shielding distribution for marrow based on the computerized anatomical man model (CAM). We have developed an 82-point body-shielding distribution that faithfully reproduces the mean and variance of SPE doses in the active marrow regions (head and neck, chest, abdomen, pelvis and thighs) allowing for more accurate estimation of linear- and quadratic-dose components of the marrow response. SPE's have differential dose-rates and a pseudo-quadratic dose response term is possible in the peak-flux period of an event. Also, the mechanistic basis for leukemia risk continues to improve allowing for improved strategies in choosing dose-rate modulation factors and radiation quality descriptors. We make comparisons of the various choices of the components in leukemia risk estimates in formulating our preferred model. A major finding is that leukemia could be the dominant risk to astronauts for a major solar particle event.

  17. Landscape risk factors for attacks of vampire bats on cattle in Sao Paulo, Brazil.

    PubMed

    Gomes, Murilo Novaes; Monteiro, Antonio Miguel Vieira; Lewis, Nicola; Gonçalves, Celso Alberto; Filho, Vladimir de Souza Nogueira

    2010-02-01

    Vampire-bat (Desmodus rotundus) attacks on cattle are a major concern for cattle-raising area. Blood loss and paralytic rabies due to bat bites can impose severe losses on the livestock. We took four municipalities inside the Sao Joao da Boa Vista veterinary district (Sao Paulo, Brazil) as a study area and tested a set of landscape features for spatial correlation with distance to areas in which vampire-bat attacks on cattle were documented. Bat- and cattle-related data from the Sao Paulo State Rabies Control Program were used. Landscape data (first-order rivers and their tributaries, main roads, railways and urban areas) were obtained from official cartographic agencies; forest, sugarcane and pasture data were acquired from remote-sensing mappings. The study area was taken as a grid split into 178 cells. Each 4kmx4km cell was filled with bat, cattle and landscape data. Our analysis detected that grid cells that were closer to areas of bat attacks on cattle had higher cattle density and a greater percentage of the land committed to sugarcane cropping, and were close to forest fragments. These results shed light on the need for rethink the Rabies Control Program strategies for defining the surveillance of vampire-bat populations and rabies control in the state of Sao Paulo, Brazil.

  18. Risk estimation to human health caused by the mercury content of Sushi and Sashimi sold in Japanese restaurants in Brazil.

    PubMed

    Alves, Jeanne Clécia; Lima de Paiva, Esther; Milani, Raquel Fernanda; Bearzoti, Eduardo; Morgano, Marcelo Antonio; Diego Quintaes, Késia

    2017-03-08

    Although fish is a healthy alternative for meat, it can be a vehicle for mercury (Hg), including in its most toxic organic form, methylmercury (MeHg). The objective of the present study was to estimate the risk to human health caused by the consumption of sushi and sashimi as commercialized by Japanese food restaurants in the city of Campinas (SP, Brazil). The total Hg content was determined by atomic absorption spectrometry with thermal decomposition and amalgamation, and the MeHg content calculated considering that 90% of the total Hg is in the organic form. The health risk was estimated from the values for the provisional tolerable weekly ingestion (PTWI) by both adults and children. The mean concentrations for total Hg were: 147.99, 6.13, and 3.42 µg kg(-1) in the tuna, kani, and salmon sushi samples, respectively, and 589.09, 85.09, and 11.38 µg kg(-1) in the tuna, octopus and salmon sashimi samples, respectively. The tuna samples showed the highest Hg concentrations. One portion of tuna sashimi exceeded the PTWI value for MeHg established for children and adults. The estimate of risk for human health indicated that the level of toxicity depended on the type of fish and size of the portion consumed.

  19. Longitudinal prediction of disruptive behavior disorders in adolescent males from multiple risk domains.

    PubMed

    Trentacosta, Christopher J; Hyde, Luke W; Goodlett, Benjamin D; Shaw, Daniel S

    2013-08-01

    The disruptive behavior disorders are among the most prevalent youth psychiatric disorders, and they predict numerous problematic outcomes in adulthood. This study examined multiple domains of risk during early childhood and early adolescence as longitudinal predictors of disruptive behavior disorder diagnoses among adolescent males. Early adolescent risks in the domains of sociodemographic factors, the caregiving context, and youth attributes were examined as mediators of associations between early childhood risks and disruptive behavior disorder diagnoses. Participants were 309 males from a longitudinal study of low-income mothers and their sons. Caregiving and youth risk during early adolescence each predicted the likelihood of receiving a disruptive behavior disorder diagnosis. Furthermore, sociodemographic and caregiving risk during early childhood were indirectly associated with disruptive behavior disorder diagnoses via their association with early adolescent risk. The findings suggest that preventive interventions targeting risk across domains may reduce the prevalence of disruptive behavior disorders.

  20. Risk factors for intestinal parasitic infections in preschoolers in a low socio-economic area, Diamantina, Brazil

    PubMed Central

    Nobre, Luciana N; Silva, Renata V; Macedo, Mariana S; Teixeira, Romero A; Lamounier, Joel A; Franceschini, Sylvia C C

    2013-01-01

    Objective To verify the prevalence of intestinal parasitic infections among preschoolers and to identify the associated risk factors. Methods The study is a cross-sectional study nested in a cohort of children who were born and resident in Diamantina, Minas Gerais, Brazil. At the time of the study, all children were aged 60 months ± five months. They were recruited after written informed consent was obtained from parents or guardians. The study was carried out between July 2009 and July 2010. In total 214 children provided a stool sample for examination on intestinal parasitic infections. Information on potential risk factors for parasitosis was obtained from parents and guardians of the children by a questionnaire. Logistic regression was used for analysis. Results Intestinal parasitic infections were found in 27.5% (n = 59) of children. The boys' infection prevalence (26.1%, n = 36) was slightly lower than the infection prevalence of the girls (30.3%, n = 23), but not statistically different (p = 0.51). Fourteen children, (23.7%) were infected with two or more parasite species and forty-five (76.3%) with single parasites. A low per capita income of family was strongly associated with an increased risk for an infection (OR = 2.89; P = 0.003). Preschoolers whose mothers did not work outside home had a significantly lower risk for infection (OR = 0.41; p = 0.01). Conclusion Intestinal parasite infection is a health problem among Diamantina preschoolers. Poverty was implicated as an important risk factor for infection, while the presence of the mother at home full-time was a protective factor. PMID:23683337

  1. Prediction of infection risk of hop by Pseudoperonspora humuli

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Downy mildew, caused by Pseudoperonospora humuli, is one of the most destructive diseases of hop. Weather factors associated with infection risk by P. humuli in the maritime region of western Oregon were examined for 24 and 48-h periods and quadratic discriminant function models were developed to c...

  2. Predicting Reading Disability: Early Cognitive Risk and Protective Factors

    ERIC Educational Resources Information Center

    Eklund, Kenneth Mikael; Torppa, Minna; Lyytinen, Heikki

    2013-01-01

    This longitudinal study examined early cognitive risk and protective factors for Grade 2 reading disability (RD). We first examined the reading outcome of 198 children in four developmental cognitive subgroups that were identified in our previous analysis: dysfluent trajectory, declining trajectory, unexpected trajectory and typical trajectory. We…

  3. Optimization of agricultural field workability predictions for improved risk management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Risks introduced by weather variability are key considerations in agricultural production. The sensitivity of agriculture to weather variability is of special concern in the face of climate change. In particular, the availability of workable days is an important consideration in agricultural practic...

  4. Self-Esteem and Future Orientation Predict Adolescents' Risk Engagement

    ERIC Educational Resources Information Center

    Jackman, Danielle M.; MacPhee, David

    2017-01-01

    This study's purpose was to examine the relations among future orientation, self-esteem, and later adolescent risk behaviors, and to compare two mediational models involving self-esteem versus future orientation as mediators. An ethnically diverse sample of 12- to 14-year-olds (N = 862, 54% female, 53% ethnic minority) was assessed longitudinally.…

  5. Use of Demographics to Predict High Risk Individuals for Suicide

    DTIC Science & Technology

    2013-06-01

    24 Measures of Stress...Figure 2: Suicide and Suicide Related Behaviors (Berman, 2010) .................................. 12 Figure 3: Developing Comprehensive Suicide...2010). The emphasis placed on suicide prevention within the DoD has led to the development of numerous initiatives to reduce the risk of suicide

  6. Androidal fat dominates in predicting cardiometabolic risk in postmenopausal women

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We hypothesized that soy isoflavones would attenuate the anticipated increase in androidal fat mass in postmenopausal women during the 36-month treatment, and thereby favorably modify the circulating cardiometabolic risk factors: triacylglycerol, LDLC, HDL-C, glucose, insulin, uric acid, C-reactive ...

  7. PREDICTING RISKS TO WILDLIFE FROM THE OFFTARGET MOVEMENT OF HERBICIDES

    EPA Science Inventory

    While insecticide applications are generally thought of as the greatest pesticide risk to wildlife, the recent literature would suggest the indirect effects of herbicides on wildlife are much greater. The resulting alteration of habitat and decrease in food sources from the off ...

  8. Predicting Disease Risk, Identifying Stakeholders, and Informing Control Strategies: A Case Study of Anthrax in Montana.

    PubMed

    Morris, Lillian R; Blackburn, Jason K

    2016-06-01

    Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs.

  9. A comparison of the predictive properties of nine sex offender risk assessment instruments.

    PubMed

    Smid, Wineke J; Kamphuis, Jan H; Wever, Edwin C; Van Beek, Daniël J

    2014-09-01

    Sex offender treatment is most effective when tailored to risk-need-responsivity principles, which dictate that treatment levels should match risk levels as assessed by structured risk assessment instruments. The predictive properties, missing values, and interrater agreement of the scores of 9 structured risk assessment instruments were compared in a national sample of 397 Dutch convicted sex offenders. The instruments included the Rapid Risk Assessment for Sexual Offense Recidivism, Static-99, Static-99R, a slightly modified version of Static-2002 and Static-2002R, Structured Anchored Clinical Judgments Minimum, Risk Matrix 2000, Sexual Violence Risk 20, and a modified version of the Sex Offender Risk Appraisal Guide; sexual and violent (including sexual) recidivism was assessed over 5- and 10-year fixed and variable follow-up periods. In general, the instrument scores showed moderate to large predictive accuracy for the occurrence of reoffending and the number of reoffenses in this sample. Predictive accuracy regarding latency showed more variability across instrument scores. Static-2002R and Static-99R scores showed a slight but consistent advantage in predictive properties over the other instrument scores across outcome measures and follow-up periods in this sample. The results of Sexual Violence Risk 20 and Rapid Risk Assessment for Sexual Offense Recidivism scores were the least positive. A positive association between predictive accuracy and interrater agreement at the item level was found for both sexual recidivism (r = .28, p = .01) and violent (including sexual) recidivism (r = .45, p < .001); no significant association was found between predictive accuracy and missing values at the item level. Results underscore the feasibility and utility of these instruments for informing treatment selection according to the risk-need-responsivity principles.

  10. Enhancement of Mammographic Density Measures in Breast Cancer Risk Prediction

    PubMed Central

    Cheddad, Abbas; Czene, Kamila; Shepherd, John A.; Li, Jingmei; Hall, Per; Humphreys, Keith

    2016-01-01

    Background Mammographic density is a strong risk factor for breast cancer. Methods We present a novel approach to enhance area density measures that takes advantage of the relative density of the pectoral muscle that appears in lateral mammographic views. We hypothesized that the grey scale of film mammograms is normalized to volume breast density but not pectoral density and thus pectoral density becomes an independent marker of volumetric density. Results From analysis of data from a Swedish case–control study (1,286 breast cancer cases and 1,391 control subjects, ages 50–75 years), we found that the mean intensity of the pectoral muscle (MIP) was highly associated with breast cancer risk [per SD: OR = 0.82; 95% confidence interval (CI), 0.75–0.88; P = 6 × 10−7] after adjusting for a validated computer-assisted measure of percent density (PD), Cumulus. The area under curve (AUC) changed from 0.600 to 0.618 due to using PD with the pectoral muscle as reference instead of a standard area-based PD measure. We showed that MIP is associated with a genetic variant known to be associated with mammographic density and breast cancer risk, rs10995190, in a subset of women with genetic data. We further replicated the association between MIP and rs10995190 in an additional cohort of 2,655 breast cancer cases (combined P = 0.0002). Conclusions MIP is a marker of volumetric density that can be used to complement area PD in mammographic density studies and breast cancer risk assessment. Impact Inclusion of MIP in risk models should be considered for studies using area PD from analog films. PMID:24722754

  11. Cross-sectional study to assess the association of population density with predicted breast cancer risk.

    PubMed

    Lee, Jeannette Y; Klimberg, Suzanne; Bondurant, Kristina L; Phillips, Martha M; Kadlubar, Susan A

    2014-01-01

    The Gail and CARE models estimate breast cancer risk for white and African-American (AA) women, respectively. The aims of this study were to compare metropolitan and nonmetropolitan women with respect to predicted breast cancer risks based on known risk factors, and to determine if population density was an independent risk factor for breast cancer risk. A cross-sectional survey was completed by 15,582 women between 35 and 85 years of age with no history of breast cancer. Metropolitan and nonmetropolitan women were compared with respect to risk factors, and breast cancer risk estimates, using general linear models adjusted for age. For both white and AA women, tisk factors used to estimate breast cancer risk included age at menarche, history of breast biopsies, and family history. For white women, age at first childbirth was an additional risk factor. In comparison to their nonmetropolitan counterparts, metropolitan white women were more likely to report having a breast biopsy, have family history of breast cancer, and delay childbirth. Among white metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.44% and 1.32% (p < 0.001), and lifetime risks of breast cancer were 10.81% and 10.01% (p < 0.001), respectively. AA metropolitan residents were more likely than those from nonmetropolitan areas to have had a breast biopsy. Among AA metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.16% and 1.12% (p = 0.039) and lifetime risks were 8.94%, and 8.85% (p = 0.344). Metropolitan residence was associated with higher predicted breast cancer risks for white women. Among AA women, metropolitan residence was associated with a higher predicted breast cancer risk at 5 years, but not over a lifetime. Population density was not an independent risk factor for breast cancer.

  12. Indoor tanning and the MC1R genotype: risk prediction for basal cell carcinoma risk in young people.

    PubMed

    Molinaro, Annette M; Ferrucci, Leah M; Cartmel, Brenda; Loftfield, Erikka; Leffell, David J; Bale, Allen E; Mayne, Susan T

    2015-06-01

    Basal cell carcinoma (BCC) incidence is increasing, particularly in young people, and can be associated with significant morbidity and treatment costs. To identify young individuals at risk of BCC, we assessed existing melanoma or overall skin cancer risk prediction models and built a novel risk prediction model, with a focus on indoor tanning and the melanocortin 1 receptor gene, MC1R. We evaluated logistic regression models among 759 non-Hispanic whites from a case-control study of patients seen between 2006 and 2010 in New Haven, Connecticut. In our data, the adjusted area under the receiver operating characteristic curve (AUC) for a model by Han et al. (Int J Cancer. 2006;119(8):1976-1984) with 7 MC1R variants was 0.72 (95% confidence interval (CI): 0.66, 0.78), while that by Smith et al. (J Clin Oncol. 2012;30(15 suppl):8574) with MC1R and indoor tanning had an AUC of 0.69 (95% CI: 0.63, 0.75). Our base model had greater predictive ability than existing models and was significantly improved when we added ever-indoor tanning, burns from indoor tanning, and MC1R (AUC = 0.77, 95% CI: 0.74, 0.81). Our early-onset BCC risk prediction model incorporating MC1R and indoor tanning extends the work of other skin cancer risk prediction models, emphasizes the value of both genotype and indoor tanning in skin cancer risk prediction in young people, and should be validated with an independent cohort.

  13. Development and Validation of a Risk Model for Prediction of Hazardous Alcohol Consumption in General Practice Attendees: The PredictAL Study

    PubMed Central

    King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I.; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

    2011-01-01

    Background Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. Results 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse. PMID:21853028

  14. Early Brain changes May Help Predict Autism Among High-Risk Infants

    MedlinePlus

    ... Media Resources Interviews & Selected Staff Profiles Multimedia Early brain changes may help predict autism among high-risk ... Share this: Page Content NIH-funded researchers link brain changes at 6 and 12 months of age ...

  15. Blood test could predict risk of heart attack and subsequent death.

    PubMed

    2017-01-18

    A high-sensitivity blood test, known as a troponin test, could predict the risk of heart attack and death and patients' response to statins, say researchers from the Universities of Edinburgh and Glasgow.

  16. Comparison of Risk Predicted by Multiple Norovirus Dose-Response Models and Implications for Quantitative Microbial Risk Assessment.

    PubMed

    Van Abel, Nicole; Schoen, Mary E; Kissel, John C; Meschke, J Scott

    2016-06-10

    The application of quantitative microbial risk assessments (QMRAs) to understand and mitigate risks associated with norovirus is increasingly common as there is a high frequency of outbreaks worldwide. A key component of QMRA is the dose-response analysis, which is the mathematical characterization of the association between dose and outcome. For Norovirus, multiple dose-response models are available that assume either a disaggregated or an aggregated intake dose. This work reviewed the dose-response models currently used in QMRA, and compared predicted risks from waterborne exposures (recreational and drinking) using all available dose-response models. The results found that the majority of published QMRAs of norovirus use the 1 F1 hypergeometric dose-response model with α = 0.04, β = 0.055. This dose-response model predicted relatively high risk estimates compared to other dose-response models for doses in the range of 1-1,000 genomic equivalent copies. The difference in predicted risk among dose-response models was largest for small doses, which has implications for drinking water QMRAs where the concentration of norovirus is low. Based on the review, a set of best practices was proposed to encourage the careful consideration and reporting of important assumptions in the selection and use of dose-response models in QMRA of norovirus. Finally, in the absence of one best norovirus dose-response model, multiple models should be used to provide a range of predicted outcomes for probability of infection.

  17. Mechanical risks prediction on Francis runner by Spatial Harmonic Decomposition

    NASA Astrophysics Data System (ADS)

    Bouloc, F.; Guillozet, J.; Duparchy, F.; Lowys, P. Y.; Duparchy, A.

    2016-11-01

    Extending the operating zone of Francis turbines toward low load is a major stake to allow the optimization of the electrical grid. The dynamic phenomena encountered at low load are potential sources of pressure fluctuations, power instability and runner fatigue. Traditionally, the peak to peak value of pressure fluctuations is used to assess these risks. However, this estimator is not sufficient to analyse separately the various dynamic phenomena and their impact on the stability of the turbine. In this paper the recent Spatial Harmonic Decomposition (SHD) method is used to analyse the pressure fluctuations through more relevant indicators. The evolution of these indicators along a load variation is compared with the associated runner strain measured with on-board gauges. It is shown that the use of the Spatial Harmonic Decomposition is a powerful tool to evaluate the risks for the industrial turbine and thus improve its behaviour and its reliability.

  18. Radiation risk predictions for Space Station Freedom orbits

    NASA Technical Reports Server (NTRS)

    Cucinotta, Francis A.; Atwell, William; Weyland, Mark; Hardy, Alva C.; Wilson, John W.; Townsend, Lawrence W.; Shinn, Judy L.; Katz, Robert

    1991-01-01

    Risk assessment calculations are presented for the preliminary proposed solar minimum and solar maximum orbits for Space Station Freedom (SSF). Integral linear energy transfer (LET) fluence spectra are calculated for the trapped proton and GCR environments. Organ dose calculations are discussed using the computerized anatomical man model. The cellular track model of Katz is applied to calculate cell survival, transformation, and mutation rates for various aluminum shields. Comparisons between relative biological effectiveness (RBE) and quality factor (QF) values for SSF orbits are made.

  19. Benign Breast Disease: Toward Molecular Prediction of Breast Cancer Risk

    DTIC Science & Technology

    2006-06-01

    fibroadenoma , or columnar changes were consid- ered nonproliferative unless they also contained one of the lesions denoted above. statistical analysis...Cancer 1989;64: 1977-83. 16. Dupont WD, Page DL, Parl FF, et al. Long-term risk of breast cancer in women with fibroadenoma . N Engl J Med 1994;331...PDWA), and AH. NP fibrocystic changes included cyst formation, stromal fibrosis, apocrine metaplasia, and noncomplex fibroadenoma . Proliferative

  20. A utility/cost analysis of breast cancer risk prediction algorithms

    NASA Astrophysics Data System (ADS)

    Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

    2016-03-01

    Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening.

  1. A Utility/Cost Analysis of Breast Cancer Risk Prediction Algorithms

    PubMed Central

    Abbey, Craig K.; Wu, Yirong; Burnside, Elizabeth S.; Wunderlich, Adam; Samuelson, Frank W.; Boone, John M.

    2016-01-01

    Breast cancer risk prediction algorithms are used to identify subpopulations that are at increased risk for developing breast cancer. They can be based on many different sources of data such as demographics, relatives with cancer, gene expression, and various phenotypic features such as breast density. Women who are identified as high risk may undergo a more extensive (and expensive) screening process that includes MRI or ultrasound imaging in addition to the standard full-field digital mammography (FFDM) exam. Given that there are many ways that risk prediction may be accomplished, it is of interest to evaluate them in terms of expected cost, which includes the costs of diagnostic outcomes. In this work we perform an expected-cost analysis of risk prediction algorithms that is based on a published model that includes the costs associated with diagnostic outcomes (true-positive, false-positive, etc.). We assume the existence of a standard screening method and an enhanced screening method with higher scan cost, higher sensitivity, and lower specificity. We then assess expected cost of using a risk prediction algorithm to determine who gets the enhanced screening method under the strong assumption that risk and diagnostic performance are independent. We find that if risk prediction leads to a high enough positive predictive value, it will be cost-effective regardless of the size of the subpopulation. Furthermore, in terms of the hit-rate and false-alarm rate of the of the risk-prediction algorithm, iso-cost contours are lines with slope determined by properties of the available diagnostic systems for screening. PMID:27335532

  2. Risk assessment prediction from genome sequences: promises and dreams.

    PubMed

    Wassenaar, Trudy M

    2004-09-01

    The application of bacterial genomics opens new avenues of research on foodborne pathogens. Foodborne pathogens must be able to colonize their hosts and survive transmission from host to host. Different groups of genes are involved in the processes of survival, colonization, and virulence, and such genes are potential targets for risk assessment and intervention strategies. Filtering from genome sequences the genes relevant to these processes is a major challenge, and although many tools are already available for analyses, this type of data mining is just beginning. For the simplest application, gene comparison, it is important to know how gene function, for instance in virulence, is being defined and tested. In other genomic applications, reserachers look for specific properties or characteristics of (virulence) genes to identify novel gene candidates. Each approach has pitfalls, and gene candidates must be tested in the lab to confirm their function. Models for colonization and virulence are available for most although not all pathogens. Models for survival and stress responses are needed to increase the utilization of genomic approaches to risk assessment. Here, I discuss how genome sequences are likely to help in microbial risk assessment of foodborne pathogens and how dreams may become promises.

  3. Predicting women's alcohol risk-taking while abroad.

    PubMed

    Smith, Gabie; Klein, Sarah

    2010-05-01

    Numerous studies have examined risk factors that are associated with heavy alcohol use; however, much of this research has not addressed factors that specifically relate to women's alcohol use. The current study has extended the previous literature on women's alcohol-use behavior by examining factors associated with risky drinking in young women traveling abroad (n = 55). Using a pretest-posttest design, we examined the influence of disinhibition sensation-seeking and endorsement of social enhancement alcohol expectancies in relation to participation in risky alcohol use while abroad for three weeks. Analyses confirmed that disinhibition sensation-seeking and social enhancement alcohol expectancies were associated with participation in risky alcohol-use behaviors while abroad (controlling for alcohol-use at the pretest). Analysis of qualitative data reinforced the importance of social facilitation in women's alcohol risk-taking. Participants' qualitative data also emphasized characteristics of situational disinhibition relating to travel as well as culturally-specific motivations for alcohol-use behaviors. Further research examining women's personal need for disinhibition and the role of situational disinhibition in motivating alcohol risk-taking is warranted. In addition, the current findings suggest that interventions focusing on the connections between alcohol use and enhancement of social relationships and the potential isolating effects of non-use are necessary.

  4. A comprehensive genetic approach for improving prediction of skin cancer risk in humans.

    PubMed

    Vazquez, Ana I; de los Campos, Gustavo; Klimentidis, Yann C; Rosa, Guilherme J M; Gianola, Daniel; Yi, Nengjun; Allison, David B

    2012-12-01

    Prediction of genetic risk for disease is needed for preventive and personalized medicine. Genome-wide association studies have found unprecedented numbers of variants associated with complex human traits and diseases. However, these variants explain only a small proportion of genetic risk. Mounting evidence suggests that many traits, relevant to public health, are affected by large numbers of small-effect genes and that prediction of genetic risk to those traits and diseases could be improved by incorporating large numbers of markers into whole-genome prediction (WGP) models. We developed a WGP model incorporating thousands of markers for prediction of skin cancer risk in humans. We also considered other ways of incorporating genetic information into prediction models, such as family history or ancestry (using principal components, PCs, of informative markers). Prediction accuracy was evaluated using the area under the receiver operating characteristic curve (AUC) estimated in a cross-validation. Incorporation of genetic information (i.e., familial relationships, PCs, or WGP) yielded a significant increase in prediction accuracy: from an AUC of 0.53 for a baseline model that accounted for nongenetic covariates to AUCs of 0.58 (pedigree), 0.62 (PCs), and 0.64 (WGP). In summary, prediction of skin cancer risk could be improved by considering genetic information and using a large number of single-nucleotide polymorphisms (SNPs) in a WGP model, which allows for the detection of patterns of genetic risk that are above and beyond those that can be captured using family history. We discuss avenues for improving prediction accuracy and speculate on the possible use of WGP to prospectively identify individuals at high risk.

  5. Occurrence and risk factors associated to Toxoplasma gondii infection in sheep from Rio de Janeiro, Brazil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Toxoplasmosis is an important cause of abortion in sheep and a zoonotic risk to humans, leading to significant hazards to health and to economic losses. This study examined the soroprevalence and associated risk factors for infection with Toxoplama gondii in 379 sheep from 12 flocks in Rio de Janeir...

  6. A Risk Score to Predict Type 2 Diabetes Mellitus in an Elderly Spanish Mediterranean Population at High Cardiovascular Risk

    PubMed Central

    Guasch-Ferré, Marta; Bulló, Mònica; Costa, Bernardo; Martínez-Gonzalez, Miguel Ángel; Ibarrola-Jurado, Núria; Estruch, Ramon; Barrio, Francisco; Salas-Salvadó, Jordi

    2012-01-01

    Introduction To develop and test a diabetes risk score to predict incident diabetes in an elderly Spanish Mediterranean population at high cardiovascular risk. Materials and Methods A diabetes risk score was derived from a subset of 1381 nondiabetic individuals from three centres of the PREDIMED study (derivation sample). Multivariate Cox regression model ß-coefficients were used to weigh each risk factor. PREDIMED-personal Score included body-mass-index, smoking status, family history of type 2 diabetes, alcohol consumption and hypertension as categorical variables; PREDIMED-clinical Score included also high blood glucose. We tested the predictive capability of these scores in the DE-PLAN-CAT cohort (validation sample). The discrimination of Finnish Diabetes Risk Score (FINDRISC), German Diabetes Risk Score (GDRS) and our scores was assessed with the area under curve (AUC). Results The PREDIMED-clinical Score varied from 0 to 14 points. In the subset of the PREDIMED study, 155 individuals developed diabetes during the 4.75-years follow-up. The PREDIMED-clinical score at a cutoff of ≥6 had sensitivity of 72.2%, and specificity of 72.5%, whereas AUC was 0.78. The AUC of the PREDIMED-clinical Score was 0.66 in the validation sample (sensitivity = 85.4%; specificity = 26.6%), and was significantly higher than the FINDRISC and the GDRS in both the derivation and validation samples. Discussion We identified classical risk factors for diabetes and developed the PREDIMED-clinical Score to determine those individuals at high risk of developing diabetes in elderly individuals at high cardiovascular risk. The predictive capability of the PREDIMED-clinical Score was significantly higher than the FINDRISC and GDRS, and also used fewer items in the questionnaire. PMID:22442692

  7. The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer

    PubMed Central

    Hawken, Steven J.; Greenwood, Celia M. T.; Hudson, Thomas J.; Kustra, Rafal; McLaughlin, John; Yang, Quanhe; Zanke, Brent W.

    2010-01-01

    Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., ~140–160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual’s CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with

  8. Fluoride concentrations in the water of Maringá, Brazil, considering the benefit/risk balance of caries and fluorosis.

    PubMed

    Bergamo, Edmara Tatiely Pedroso; Barbana, Marlon; Terada, Raquel Sano Suga; Cury, Jaime Aparecido; Fujimaki, Mitsue

    2015-01-01

    Current Brazilian law regarding water fluoridation classification is dichotomous with respect to the risks of and benefits for oral diseases, and fluoride (F) concentrations less than 0.6 or above 0.8 mg F/L are considered outside the normal limits. Thus, the law does not consider that both caries and fluorosis are dependent on the dosage and duration of fluoride exposure because they are both chronic diseases. Therefore, this study evaluated the quality of water fluoridation in Maringá, PR, Brazil, considering a new classification for the concentration of F in water the supply, based on the anticaries benefit and risk of fluorosis (CECOL/USP, 2011). Water samples (n = 325) were collected monthly over one year from 28 distribution water networks: 20 from treatment plants and 8 from artesian wells. F concentrations were determined using a specific ion electrode. The average F concentration was 0.77 mg F/L (ppm F), ranging from 0.44 to 1.22 mg F/L. Considering all of the water samples analyzed, 83.7% of them presented from 0.55 to 0.84 mg F/L, and according to the new classification used, they would provide maximum anticaries benefit with a low risk of fluorosis. This percentage was lower (75.4%) in the water samples supplied from artesian wells than from those distributed by the treatment plant (86%). In conclusion, based on the new classification of water F concentrations, the quality of water fluoridation in Maringá is adequate and is within the range of the best balance between risk and benefit.

  9. Multi-locus genetic risk score predicts risk for Crohn’s disease in Slovenian population

    PubMed Central

    Zupančič, Katarina; Skok, Kristijan; Repnik, Katja; Weersma, Rinse K; Potočnik, Uroš; Skok, Pavel

    2016-01-01

    AIM: To develop a risk model for Crohn’s disease (CD) based on homogeneous population. METHODS: In our study were included 160 CD patients and 209 healthy individuals from Slovenia. The association study was performed for 112 single nucleotide polymorphisms (SNPs). We generated genetic risk scores (GRS) based on the number of risk alleles using weighted additive model. Discriminatory accuracy was measured by area under ROC curve (AUC). For risk evaluation, we divided individuals according to positive and negative likelihood ratios (LR) of a test, with LR > 5 for high risk group and LR < 0.20 for low risk group. RESULTS: The highest accuracy, AUC of 0.78 was achieved with GRS combining 33 SNPs with optimal sensitivity and specificity of 75.0% and 72.7%, respectively. Individuals with the highest risk (GRS > 5.54) showed significantly increased odds of developing CD (OR = 26.65, 95%CI: 11.25-63.15) compared to the individuals with the lowest risk (GRS < 4.57) which is a considerably greater risk captured than in one SNP with the highest effect size (OR = 3.24). When more than 33 SNPs were included in GRS, discriminatory ability was not improved significantly; AUC of all 74 SNPs was 0.76. CONCLUSION: The authors proved the possibility of building accurate genetic risk score based on 33 risk variants on Slovenian CD patients which may serve as a screening tool in the targeted population. PMID:27076762

  10. Failure mode and effects analysis based risk profile assessment for stereotactic radiosurgery programs at three cancer centers in Brazil

    SciTech Connect

    Teixeira, Flavia C.

    2016-01-15

    Purpose: The goal of this study was to evaluate the safety and quality management program for stereotactic radiosurgery (SRS) treatment processes at three radiotherapy centers in Brazil by using three industrial engineering tools (1) process mapping, (2) failure modes and effects analysis (FMEA), and (3) fault tree analysis. Methods: The recommendations of Task Group 100 of American Association of Physicists in Medicine were followed to apply the three tools described above to create a process tree for SRS procedure for each radiotherapy center and then FMEA was performed. Failure modes were identified for all process steps and values of risk priority number (RPN) were calculated from O, S, and D (RPN = O × S × D) values assigned by a professional team responsible for patient care. Results: The subprocess treatment planning was presented with the highest number of failure modes for all centers. The total number of failure modes were 135, 104, and 131 for centers I, II, and III, respectively. The highest RPN value for each center is as follows: center I (204), center II (372), and center III (370). Failure modes with RPN ≥ 100: center I (22), center II (115), and center III (110). Failure modes characterized by S ≥ 7, represented 68% of the failure modes for center III, 62% for center II, and 45% for center I. Failure modes with RPNs values ≥100 and S ≥ 7, D ≥ 5, and O ≥ 5 were considered as high priority in this study. Conclusions: The results of the present study show that the safety risk profiles for the same stereotactic radiotherapy process are different at three radiotherapy centers in Brazil. Although this is the same treatment process, this present study showed that the risk priority is different and it will lead to implementation of different safety interventions among the centers. Therefore, the current practice of applying universal device-centric QA is not adequate to address all possible failures in clinical processes at different

  11. A Novel Risk Score to the Prediction of 10-year Risk for Coronary Artery Disease Among the Elderly in Beijing Based on Competing Risk Model

    PubMed Central

    Liu, Long; Tang, Zhe; Li, Xia; Luo, Yanxia; Guo, Jin; Li, Haibin; Liu, Xiangtong; Tao, Lixin; Yan, Aoshuang; Guo, Xiuhua

    2016-01-01

    Abstract The study aimed to construct a risk prediction model for coronary artery disease (CAD) based on competing risk model among the elderly in Beijing and develop a user-friendly CAD risk score tool. We used competing risk model to evaluate the risk of developing a first CAD event. On the basis of the risk factors that were included in the competing risk model, we constructed the CAD risk prediction model with Cox proportional hazard model. Time-dependent receiver operating characteristic (ROC) curve and time-dependent area under the ROC curve (AUC) were used to evaluate the discrimination ability of the both methods. Calibration plots were applied to assess the calibration ability and adjusted for the competing risk of non-CAD death. Net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to quantify the improvement contributed by the new risk factors. Internal validation of predictive accuracy was performed using 1000 times of bootstrap re-sampling. Of the 1775 participants without CAD at baseline, 473 incident cases of CAD were documented for a 20-year follow-up. Time-dependent AUCs for men and women at t = 10 years were 0.841 [95% confidence interval (95% CI): 0.806–0.877], 0.804 (95% CI: 0.768–0.839) in Fine and Gray model, 0.784 (95% CI: 0.738–0.830), 0.733 (95% CI: 0.692–0.775) in Cox proportional hazard model. The competing risk model was significantly superior to Cox proportional hazard model on discrimination and calibration. The cut-off values of the risk score that marked the difference between low-risk and high-risk patients were 34 points for men and 30 points for women, which have good sensitivity and specificity. A sex-specific multivariable risk factor algorithm-based competing risk model has been developed on the basis of an elderly Chinese cohort, which could be applied to predict an individual's risk and provide a useful guide to identify the groups at a high risk for CAD among the Chinese

  12. A Novel Risk Score to the Prediction of 10-year Risk for Coronary Artery Disease Among the Elderly in Beijing Based on Competing Risk Model.

    PubMed

    Liu, Long; Tang, Zhe; Li, Xia; Luo, Yanxia; Guo, Jin; Li, Haibin; Liu, Xiangtong; Tao, Lixin; Yan, Aoshuang; Guo, Xiuhua

    2016-03-01

    The study aimed to construct a risk prediction model for coronary artery disease (CAD) based on competing risk model among the elderly in Beijing and develop a user-friendly CAD risk score tool. We used competing risk model to evaluate the risk of developing a first CAD event. On the basis of the risk factors that were included in the competing risk model, we constructed the CAD risk prediction model with Cox proportional hazard model. Time-dependent receiver operating characteristic (ROC) curve and time-dependent area under the ROC curve (AUC) were used to evaluate the discrimination ability of the both methods. Calibration plots were applied to assess the calibration ability and adjusted for the competing risk of non-CAD death. Net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to quantify the improvement contributed by the new risk factors. Internal validation of predictive accuracy was performed using 1000 times of bootstrap re-sampling. Of the 1775 participants without CAD at baseline, 473 incident cases of CAD were documented for a 20-year follow-up. Time-dependent AUCs for men and women at t = 10 years were 0.841 [95% confidence interval (95% CI): 0.806-0.877], 0.804 (95% CI: 0.768-0.839) in Fine and Gray model, 0.784 (95% CI: 0.738-0.830), 0.733 (95% CI: 0.692-0.775) in Cox proportional hazard model. The competing risk model was significantly superior to Cox proportional hazard model on discrimination and calibration. The cut-off values of the risk score that marked the difference between low-risk and high-risk patients were 34 points for men and 30 points for women, which have good sensitivity and specificity. A sex-specific multivariable risk factor algorithm-based competing risk model has been developed on the basis of an elderly Chinese cohort, which could be applied to predict an individual's risk and provide a useful guide to identify the groups at a high risk for CAD among the Chinese adults over 55

  13. Clinical prediction of fall risk and white matter abnormalities: a diffusion tensor imaging study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective: To test the hypothesis that elderly subjects at risk for falling, as deter...

  14. School Violence in Taiwan: Examining How Western Risk Factors Predict School Violence in an Asian Culture

    ERIC Educational Resources Information Center

    Chen, Ji-Kang; Astor, Ron Avi

    2010-01-01

    The current study explores whether theorized risk factors in Western countries can be used to predict school violence perpetration in an Asian cultural context. The study examines the associations between risk factors and school violence perpetration in Taiwan. Data were obtained from a nationally representative sample of 14,022 students from…

  15. Post-Stroke Depression in Primary Support Persons: Predicting Those at Risk.

    ERIC Educational Resources Information Center

    Tompkins, Connie A.; And Others

    1988-01-01

    Assessed psychosocial impact of stroke on patient's primary support person. Collected three waves of data at six-month intervals. At first wave, identified support persons at risk for depression. At second and third waves, predicted and validated risk with at least 74 percent accuracy. Variables included Time 1 depression, optimism, concern about…

  16. Potential ecological risk assessment and predicting zinc accumulation in soils.

    PubMed

    Baran, Agnieszka; Wieczorek, Jerzy; Mazurek, Ryszard; Urbański, Krzysztof; Klimkowicz-Pawlas, Agnieszka

    2017-02-22

    The aims of this study were to investigate zinc content in the studied soils; evaluate the efficiency of geostatistics in presenting spatial variability of zinc in the soils; assess bioavailable forms of zinc in the soils and to assess soil-zinc binding ability; and to estimate the potential ecological risk of zinc in soils. The study was conducted in southern Poland, in the Malopolska Province. This area is characterized by a great diversity of geological structures and types of land use and intensity of industrial development. The zinc content was affected by soil factors, and the type of land use (arable lands, grasslands, forests, wastelands). A total of 320 soil samples were characterized in terms of physicochemical properties (texture, pH, organic C content, total and available Zn content). Based on the obtained data, assessment of the ecological risk of zinc was conducted using two methods: potential ecological risk index and hazard quotient. Total Zn content in the soils ranged from 8.27 to 7221 mg kg(-1) d.m. Based on the surface semivariograms, the highest variability of zinc in the soils was observed from northwest to southeast. The point sources of Zn contamination were located in the northwestern part of the area, near the mining-metallurgical activity involving processing of zinc and lead ores. These findings were confirmed by the arrangement of semivariogram surfaces and bivariate Moran's correlation coefficients. The content of bioavailable forms of zinc was between 0.05 and 46.19 mg kg(-1) d.m. (0.01 mol dm(-3) CaCl2), and between 0.03 and 71.54 mg kg(-1) d.m. (1 mol dm(-3) NH4NO3). Forest soils had the highest zinc solubility, followed by arable land, grassland and wasteland. PCA showed that organic C was the key factor to control bioavailability of zinc in the soils. The extreme, very high and medium zinc accumulation was found in 69% of studied soils. There is no ecological risk of zinc to living organisms in the study area, and in 90

  17. Benign Breast Disease: Toward Molecular Prediction of Breast Cancer Risk

    DTIC Science & Technology

    2009-06-01

    An Analysis of Breast Cancer Risk in Women With Single, Multiple, and Atypical Papilloma Jason T . Lewis, MD,* Lynn C. Hartmann, MD,t Rober! A...beltavior. From the Divisions of *An3lomic Pathology, t Medical Onoology; and t Biostatisti<:s, Mayo Clinic, Rochester, MN 55905. Repri nts: Dr Jason ...probabilities for brea.<r cancer-susceptibility gertes 13RCAI and BRCA2. Am J ll um Genet: 62:145-58. I �. 19. Berry DA, Iversen Jr ES, Gutfbjartsson

  18. Leishmania infantum: illness, transmission profile and risk factors for asymptomatic infection in an endemic metropolis in Brazil.

    PubMed

    Dos Santos Marques, Letícia Helena; DA Rocha, Iara Caixeta Marques; Reis, Ilka Afonso; DA Cunha, Gisele Macedo Rodrigues; Oliveira, Edward; Pfeilsticker, Thais Ribeiro; DE Araújo, Valdelaine Etelvina Miranda; Morais, Maria Helena Franco; Rabello, Ana; Carneiro, Mariângela

    2017-04-01

    To evaluate the distribution of asymptomatic infection by Leishmania infantum in a metropolis in Brazil with different relative risks (RRs) for disease and risk factors associated with the infection, an ecological study was conducted using a Bayesian approach to estimate the RR of human visceral leishmaniasis (HVL) based on cases between 2008 and 2011. The areas were categorized and selected according to disease incidence: low (area-1), medium (area-2) and high (area-3). Cross-sectional study enrolling 935 children was used to estimate the prevalence of infection by L. infantum. Volunteers from these three areas were tested for L. infantum infection by ELISA (rK39 and soluble antigens). Infection prevalence rates were estimated and compared with the RR of disease. Multilevel logistic regression model evaluated the relationship between infection and the analysed variables. The RR of HVL was distributed heterogeneously in the municipality. The infection prevalence rates were: 34·9% in area-1; 29·3% in area-2; and 33·6% in area-3, with no significant differences between these areas. The variables 'Presence of backyards in the neighbourhood' and 'Younger children' were associated with L. infantum infection. We conclude that infection by L. infantum affects a significant proportion of the infant population regardless of the RR of disease.

  19. Fractionation and potential toxic risk of metals from superficial sediment in Itaipu Lake--boundary between Brazil and Paraguay.

    PubMed

    Kalwa, Miguel; Quináia, Sueli Pércio; Pletsch, Adelmo L; Techy, Laura; Felsner, Maria Lurdes

    2013-01-01

    The objective of this study was to evaluate fractions of metals (labile and pseudo-total) extracted from sediment samples collected in Itaipu Lake (boundary between Brazil and Paraguay) and to assess the dynamics and mobility of these fractions by identifying the same bioavailability and ecological risk to metals in the aquatic environment. The concentrations of metal ions were determined by flame atomic absorption spectrometry. There was a correlation between the metal ions, both in the labile and the pseudo-total, with regard to particle size. To assess metals concentrations in sediment, numerical sediment-quality guidelines were applied. The concentrations of aluminum, cadmium, iron, manganese, lead, and zinc in all sediment samples are lower than the proposed probable effects level (PEL), thus possibly indicating that there are no harmful effects from these metals. In contrast, concentrations of copper, chromium, and nickel exceeded the PEL in some samples, thus indicating that these stations are at potential risk. The level of contamination in sediments of Itaipu Lake for all metals was evaluated using contamination factor, degree of contamination, and sum-of-metals toxic unit.

  20. Wheezing conditions in early childhood: prevalence and risk factors in the city of São Paulo, Brazil.

    PubMed Central

    Benício, Maria Helena D.; Ferreira, Marcelo U.; Cardoso, Maria Regina A.; Konno, Sílvia C.; Monteiro, Carlos A.

    2004-01-01

    OBJECTIVE: To investigate the prevalence and risk factors for wheezing disorders in early childhood in São Paulo, Brazil, the largest metropolitan area of South America. METHODS: A population-based cross-sectional survey of 1132 children aged 6-59 months was carried out between 1995 and 1996 to obtain information on recent wheezing and on independent variables such as demographic, socioeconomic, environmental, maternal and nutritional variables and immunization status. Intestinal parasitic infections were diagnosed using standard techniques. Multiple unconditional logistic regression was used to describe associations between outcome and independent variables. FINDINGS: The prevalence of recent wheezing (one or more reported episodes in the past 12 months) was 12.5%; 93% of children with wheezing were also reported to have a medical diagnosis of asthma. Recent wheezing was associated with low per capita income, poor quality of housing, day-care attendance, low birth weight and infection with intestinal helminths. CONCLUSION: Wheezing in early childhood in São Paulo, although more common than in most developing countries, remains less prevalent than in urban areas of industrialized countries. Low income and conditions associated with poverty (poor housing, low birth weight and parasitic infections) are some of the main risk factors for wheezing disorders among young children in this city. PMID:15508196

  1. Informal Trade of Psychoactive Herbal Products in the City of Diadema, SP, Brazil: Quality and Potential Risks

    PubMed Central

    Soares Neto, Julino Assunção Rodrigues; Kato, Edna Myiake; Galduróz, José Carlos F.; Marques, Luis Carlos; Macrini, Thiago; Rodrigues, Eliana

    2013-01-01

    The present study aimed to assess the quality and risks involved in the consumption of psychoactive herbal products (PHs) that are available through informal commerce in the city of Diadema, SP, Brazil. Methods of ethnography were used to conduct the fieldwork during which four dealers were selected to record the collection, handling, packaging, types of PHs marketed, and their therapeutic purposes. In addition, lots of the PHs selected were purchased from the dealers and analyzed using microbiology and pharmacognosy techniques. 217 PHs were recorded and categorized into two main groups: stimulants (67%) and depressants (27%) of the central nervous system; sixteen of them were selected, and their 52 lots were acquired. The deficiencies observed in handling and packaging these lots by dealers were confirmed by microbiological analysis; 80.8% of them presented risk according to the indicators defined by the Brazilian Pharmacopoeia. The pharmacognostic analysis confirmed the authenticity of only 9 to 16 PHs analyzed. In addition, descriptions of contraindications, adverse reactions, and drug interactions were found in the literature for the PHs. The results of this study allow the observation of the priorities for the sanitary adequacy of the popular trade of herbs. PMID:23818934

  2. Assessing the risk of bovine fasciolosis using linear regression analysis for the state of Rio Grande do Sul, Brazil.

    PubMed

    Silva, Ana Elisa Pereira; Freitas, Corina da Costa; Dutra, Luciano Vieira; Molento, Marcelo Beltrão

    2016-02-15

    Fasciola hepatica is the causative agent of fasciolosis, a disease that triggers a chronic inflammatory process in the liver affecting mainly ruminants and other animals including humans. In Brazil, F. hepatica occurs in larger numbers in the most Southern state of Rio Grande do Sul. The objective of this study was to estimate areas at risk using an eight-year (2002-2010) time series of climatic and environmental variables that best relate to the disease using a linear regression method to municipalities in the state of Rio Grande do Sul. The positivity index of the disease, which is the rate of infected animal per slaughtered animal, was divided into three risk classes: low, medium and high. The accuracy of the known sample classification on the confusion matrix for the low, medium and high rates produced by the estimated model presented values between 39 and 88% depending of the year. The regression analysis showed the importance of the time-based data for the construction of the model, considering the two variables of the previous year of the event (positivity index and maximum temperature). The generated data is important for epidemiological and parasite control studies mainly because F. hepatica is an infection that can last from months to years.

  3. Not all risk taking behavior is bad: Associative sensitivity predicts learning during risk taking among high sensation seekers

    PubMed Central

    Humphreys, Kathryn L.; Lee, Steve S.; Tottenham, Nim

    2013-01-01

    Risk taking behavior can be both adaptive and maladaptive depending on context. The majority of studies of risk taking, however, focus on clinical populations and dangerous or harmful risk taking. Individual differences in learning during risk taking are rarely examined in relation to task performance. The present study examined risk taking and associated outcomes in an exploration-based instrumental learning task (Balloon Emotional Learning Task; BELT), which presented a series of balloons in which participants pump up for points. Consistent with prior work, sensation seeking predicted increased risk taking behavior. Importantly, however, a significant interaction between sensation seeking and associative sensitivity, an attentional construct defined as the frequency and remoteness of automatic cognitive activity, was found. Specifically, among individuals high in sensation seeking, associative sensitivity predicted fewer balloon explosions and an increase in points earned on the balloon condition with the most potential feedback driven learning. Thus, these findings suggest that sensation seekers are a heterogeneous group, and secondary traits such as associative sensitivity moderate behavior such as risk taking and learning according to context. PMID:23935235

  4. Not all risk taking behavior is bad: Associative sensitivity predicts learning during risk taking among high sensation seekers.

    PubMed

    Humphreys, Kathryn L; Lee, Steve S; Tottenham, Nim

    2013-04-01

    Risk taking behavior can be both adaptive and maladaptive depending on context. The majority of studies of risk taking, however, focus on clinical populations and dangerous or harmful risk taking. Individual differences in learning during risk taking are rarely examined in relation to task performance. The present study examined risk taking and associated outcomes in an exploration-based instrumental learning task (Balloon Emotional Learning Task; BELT), which presented a series of balloons in which participants pump up for points. Consistent with prior work, sensation seeking predicted increased risk taking behavior. Importantly, however, a significant interaction between sensation seeking and associative sensitivity, an attentional construct defined as the frequency and remoteness of automatic cognitive activity, was found. Specifically, among individuals high in sensation seeking, associative sensitivity predicted fewer balloon explosions and an increase in points earned on the balloon condition with the most potential feedback driven learning. Thus, these findings suggest that sensation seekers are a heterogeneous group, and secondary traits such as associative sensitivity moderate behavior such as risk taking and learning according to context.

  5. Predicting suicidal behaviours using clinical instruments: systematic review and meta-analysis of positive predictive values for risk scales.

    PubMed

    Carter, Gregory; Milner, Allison; McGill, Katie; Pirkis, Jane; Kapur, Navneet; Spittal, Matthew J

    2017-03-16

    BackgroundPrediction of suicidal behaviour is an aspirational goal for clinicians and policy makers; with patients classified as 'high risk' to be preferentially allocated treatment. Clinical usefulness requires an adequate positive predictive value (PPV).AimsTo identify studies of predictive instruments and to calculate PPV estimates for suicidal behaviours.MethodA systematic review identified studies of predictive instruments. A series of meta-analyses produced pooled estimates of PPV for suicidal behaviours.ResultsFor all scales combined, the pooled PPVs were: suicide 5.5% (95% CI 3.9-7.9%), self-harm 26.3% (95% CI 21.8-31.3%) and self-harm plus suicide 35.9% (95% CI 25.8-47.4%). Subanalyses on self-harm found pooled PPVs of 16.1% (95% CI 11.3-22.3%) for high-quality studies, 32.5% (95% CI 26.1-39.6%) for hospital-treated self-harm and 26.8% (95% CI 19.5-35.6%) for psychiatric in-patients.ConclusionsNo 'high-risk' classification was clinically useful. Prevalence imposes a ceiling on PPV. Treatment should reduce exposure to modifiable risk factors and offer effective interventions for selected subpopulations and unselected clinical populations.

  6. Comparison of Measured and Predicted Bioconcentration Estimates of Pharmaceuticals in Fish Plasma and Prediction of Chronic Risk.

    PubMed

    Nallani, Gopinath; Venables, Barney; Constantine, Lisa; Huggett, Duane

    2016-05-01

    Evaluation of the environmental risk of human pharmaceuticals is now a mandatory component in all new drug applications submitted for approval in EU. With >3000 drugs currently in use, it is not feasible to test each active ingredient, so prioritization is key. A recent review has listed nine prioritization approaches including the fish plasma model (FPM). The present paper focuses on comparison of measured and predicted fish plasma bioconcentration factors (BCFs) of four common over-the-counter/prescribed pharmaceuticals: norethindrone (NET), ibuprofen (IBU), verapamil (VER) and clozapine (CLZ). The measured data were obtained from the earlier published fish BCF studies. The measured BCF estimates of NET, IBU, VER and CLZ were 13.4, 1.4, 0.7 and 31.2, while the corresponding predicted BCFs (based log Kow at pH 7) were 19, 1.0, 7.6 and 30, respectively. These results indicate that the predicted BCFs matched well the measured values. The BCF estimates were used to calculate the human: fish plasma concentration ratios of each drug to predict potential risk to fish. The plasma ratio results show the following order of risk potential for fish: NET > CLZ > VER > IBU. The FPM has value in prioritizing pharmaceutical products for ecotoxicological assessments.

  7. Method of Breast Reconstruction Determines Venous Thromboembolism Risk Better Than Current Prediction Models

    PubMed Central

    Patel, Niyant V.; Wagner, Douglas S.

    2015-01-01

    Background: Venous thromboembolism (VTE) risk models including the Davison risk score and the 2005 Caprini risk assessment model have been validated in plastic surgery patients. However, their utility and predictive value in breast reconstruction has not been well described. We sought to determine the utility of current VTE risk models in this population and the VTE rate observed in various methods of breast reconstruction. Methods: A retrospective review of breast reconstructions by a single surgeon was performed. One hundred consecutive transverse rectus abdominis myocutaneous (TRAM) patients, 100 consecutive implant patients, and 100 consecutive latissimus dorsi patients were identified over a 10-year period. Patient demographics and presence of symptomatic VTE were collected. 2005 Caprini risk scores and Davison risk scores were calculated for each patient. Results: The TRAM reconstruction group was found to have a higher VTE rate (6%) than the implant (0%) and latissimus (0%) reconstruction groups (P < 0.01). Mean Davison risk scores and 2005 Caprini scores were similar across all reconstruction groups (P > 0.1). The vast majority of patients were stratified as high risk (87.3%) by the VTE risk models. However, only TRAM reconstruction patients demonstrated significant VTE risk. Conclusions: TRAM reconstruction appears to have a significantly higher risk of VTE than both implant and latissimus reconstruction. Current risk models do not effectively stratify breast reconstruction patients at risk for VTE. The method of breast reconstruction appears to have a significant role in patients’ VTE risk. PMID:26090287

  8. A novel air quality analysis and prediction system for São Paulo, Brazil to support decision-making

    NASA Astrophysics Data System (ADS)

    Hoshyaripour, Gholam Ali; Brasseur, Guy; Andrade, Maria Fatima; Gavidia-Calderón, Mario; Bouarar, Idir

    2016-04-01

    The extensive economic development and urbanization in southeastern Brazil (SEB) in recent decades have notably degraded the air quality with adverse impacts on human health. Since the Metropolitan Area of São Paulo (MASP) accommodates the majority of the economic growth in SEB, it overwhelmingly suffers from the air pollution. Consequently, there is a strong demand for developing ever-better assessment mechanisms to monitor the air quality and to assist the decision makers to mitigate the air pollution in MASP. Here we present the results of an air quality modeling system designed for SEB with focuses on MASP. The Weather Research and Forecast model with Chemistry (WRF-Chem) is used considering the anthropogenic, biomass-burning and biogenic emissions within a 1000×1500 km domain with resolution of 10 km. FINN and MEGAN are used for the biomass-burning and biogenic emissions, respectively. For the anthropogenic emissions we use a local bottom-up inventory for the transport sector and the HTAPv2 global inventory for all other sectors. The bottom-up inventory accounts for the traffic patterns, vehicle types and their emission factors in the area and thus could be used to evaluate the effect of changes in these parameters on air quality in MASP. The model outputs are compered to the satellite and ground-based observations for O3 and NOx. The results show that using the bottom-up or top-down inventories individually can result in a huge deviation between the predictions and observations. On the other hand, combining the inventories significantly enhances the forecast accuracy. It also provides a powerful tool to quantify the effects of traffic and vehicle emission policies on air quality in MASP.

  9. Prediction of near-term breast cancer risk using a Bayesian belief network

    NASA Astrophysics Data System (ADS)

    Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

    2013-03-01

    Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.

  10. Risk factors in Dupuytren's diathesis: is recurrence after surgery predictable?

    PubMed

    Degreef, Ilse; De Smet, Luc

    2011-02-01

    In order to investigate the prognostic value of possible risk factors for Dupuytren's diathesis, clinical parameters on disease presentation in an operated group of patients were compared with self-reported recurrence after a minimum 2 years follow-up. In order of significance, the following factors were found to be significantly correlated with disease recurrence : age of onset under 50 years (p = 0.01), bilateral disease (p = 0.01), Ledderhose disease (p = 0.01), first ray involvement (p = 0.02), multiple ray involvement (more than 2 digits, p = 0.02), ectopic fibromatosis (p = 0.02), family occurrence (p = 0.04) and male gender (p = 0.05). No correlation of self-reported disease recurrence was seen with diabetes, frozen shoulder syndrome or epilepsy. An insight in the significance of the influence of specific risk factors on recurrence rates, helps in creating a clearer representation of Dupuytren's diathesis. This will help the surgeon to more accurately inform the patient and possibly to reconsider and adjust the choice in treatment options.

  11. Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

    PubMed

    Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David

    2015-12-01

    We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p < 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion

  12. Incorporation of Melcor source term predictions into probabilistic risk assessments

    SciTech Connect

    Summers, R.M.; Helton, J.C.; Leigh, C.D.

    1989-01-01

    The MELCOR code has been developed as an advanced computational tool for performing primary source term analyses that will incorporate current phenomenological understanding into probabilistic risk assessments (PRAs). Although MELCOR is reasonably fast running, it is not feasible to perform a MELCOR calculation for each of the thousands of sets of conditions requiring a source term estimate in an integrated PRA. Therefore, the RELTRAC code is being developed to generate secondary source term estimates for use directly in a PRA for the LaSalle nuclear power plant by appropriately manipulating results from calculations by a primary source term code such as MELCOR. This paper describes the MELCOR and RELTRAC models and the manner in which MELCOR calculations are used to provide input to the RELTRAC model. 26 refs., 2 figs., 1 tab.

  13. Predicting post-vaccination autoimmunity: who might be at risk?

    PubMed

    Soriano, Alessandra; Nesher, Gideon; Shoenfeld, Yehuda

    2015-02-01

    Vaccinations have been used as an essential tool in the fight against infectious diseases, and succeeded in improving public health. However, adverse effects, including autoimmune conditions may occur following vaccinations (autoimmune/inflammatory syndrome induced by adjuvants--ASIA syndrome). It has been postulated that autoimmunity could be triggered or enhanced by the vaccine immunogen contents, as well as by adjuvants, which are used to increase the immune reaction to the immunogen. Fortunately, vaccination-related ASIA is uncommon. Yet, by defining individuals at risk we may further limit the number of individuals developing post-vaccination ASIA. In this perspective we defined four groups of individuals who might be susceptible to develop vaccination-induced ASIA: patients with prior post-vaccination autoimmune phenomena, patients with a medical history of autoimmunity, patients with a history of allergic reactions, and individuals who are prone to develop autoimmunity (having a family history of autoimmune diseases; asymptomatic carriers of autoantibodies; carrying certain genetic profiles, etc.).

  14. Development and Predictive Effects of Eating Disorder Risk Factors during Adolescence: Implications for Prevention Efforts

    PubMed Central

    Rohde, Paul; Stice, Eric; Marti, C. Nathan

    2014-01-01

    Objective Although several prospective studies have identified factors that increase risk for eating disorders, little is known about when these risk factors emerge and escalate, or when they begin to predict future eating disorder onset. The objective of this report was to address these key research gaps. Method Data were examined from a prospective study of 496 community female adolescents (M = 13.5, SD = 0.7 at baseline) who completed eight annual assessments of potential risk factors and eating disorders from preadolescence to young adulthood. Results Three variables exhibited positive linear increases: Perceived pressure to be thin, thin-ideal internalization and body dissatisfaction; three were best characterized as quadratic effects: dieting (essentially little change); negative affectivity (overall decrease), and BMI (overall increase). Elevated body dissatisfaction at ages 13, 14, 15, and 16 predicted DSM-5 eating disorders onset in the 4 year period after each assessment, but the predictive effects of other risk factors were largely confined to age 14; BMI did not predict eating disorders at any age. Discussion The results imply that these risk factors are present by early adolescence, though eating disorders tend to emerge in late adolescence and early adulthood. These findings emphasize the need for efficacious eating disorder prevention programs for early adolescent girls, perhaps targeting 14 year olds, when risk factors appear to be most predictive. In early adolescence, it might be fruitful to target girls with body dissatisfaction, as this was the most consistent predictor of early eating disorder onset in this study. PMID:24599841

  15. Computational strategies for predicting the potential risks associated with nanotechnology.

    PubMed

    Barnard, Amanda S

    2009-10-01

    For the move from nanoscience to nanotechnology to be sustainable, it is important that the issues surrounding possible 'nano-hazards' be addressed before commercialization. The global push for more environmentally friendly, biodegradable products, means the introduction of the nanoparticles contained within these products into the ecosystem is an inevitability. When this happens, it is desirable to know how the hazardous properties may be affected, and what the potential hazards are. In this article, a number of strategies will be discussed, combining the desirable aspects of theory, simulation, experiment and observation, and leading to predictions for incorporation into preventative frameworks. Particular attention will be given to the role of theory and computation, and how it intersects with the participants from complementary fields.

  16. Predictive Factors and Risk Mapping for Rift Valley Fever Epidemics in Kenya

    PubMed Central

    Munyua, Peninah M.; Murithi, R. Mbabu; Ithondeka, Peter; Hightower, Allen; Thumbi, Samuel M.; Anyangu, Samuel A.; Kiplimo, Jusper; Bett, Bernard; Vrieling, Anton; Breiman, Robert F.; Njenga, M. Kariuki

    2016-01-01

    Background To-date, Rift Valley fever (RVF) outbreaks have occurred in 38 of the 69 administrative districts in Kenya. Using surveillance records collected between 1951 and 2007, we determined the risk of exposure and outcome of an RVF outbreak, examined the ecological and climatic factors associated with the outbreaks, and used these data to develop an RVF risk map for Kenya. Methods Exposure to RVF was evaluated as the proportion of the total outbreak years that each district was involved in prior epizootics, whereas risk of outcome was assessed as severity of observed disease in humans and animals for each district. A probability-impact weighted score (1 to 9) of the combined exposure and outcome risks was used to classify a district as high (score ≥ 5) or medium (score ≥2 - <5) risk, a classification that was subsequently subjected to expert group analysis for final risk level determination at the division levels (total = 391 divisions). Divisions that never reported RVF disease (score < 2) were classified as low risk. Using data from the 2006/07 RVF outbreak, the predictive risk factors for an RVF outbreak were identified. The predictive probabilities from the model were further used to develop an RVF risk map for Kenya. Results The final output was a RVF risk map that classified 101 of 391 divisions (26%) located in 21 districts as high risk, and 100 of 391 divisions (26%) located in 35 districts as medium risk and 190 divisions (48%) as low risk, including all 97 divisions in Nyanza and Western provinces. The risk of RVF was positively associated with Normalized Difference Vegetation Index (NDVI), low altitude below 1000m and high precipitation in areas with solonertz, luvisols and vertisols soil types (p <0.05). Conclusion RVF risk map serves as an important tool for developing and deploying prevention and control measures against the disease. PMID:26808021

  17. Biochemical Recurrence Prediction in High-Risk Prostate Cancer Patients, Following Robot-Assisted Radical Prostatectomy

    PubMed Central

    Yamaguchi, Noriya; Yumioka, Tetsuya; Iwamoto, Hideto; Masago, Toshihiko; Morizane, Shuichi; Honda, Masashi; Sejima, Takehiro; Takenaka, Atsushi

    2016-01-01

    Background High-risk prostate cancer treatment has been controversial. Some high-risk prostate cancer patients fail to respond to radical prostatectomy only. Thus, we aimed to investigate the predictive factors for biochemical recurrence (BCR) and identify patients who could achieve sufficient therapeutic effect by radical prostatectomy only. Methods Of 264 medical records reviewed, 141 low-intermediate-risk and 100 high-risk prostate cancer patients, excluding those who had received neoadjuvant hormone therapy, were analyzed. BCR was defined as the first increase in prostate-specific antigen levels (≥ 0.2 ng/mL), with levels not decreasing to undetectable limits, after radical prostatectomy. Log-rank test and Cox proportional hazards regression analyses were performed to determine the prognostic factors. We investigated the perioperative predictive factors for BCR and BCR-free survival rates, with the number of National Comprehensive Cancer Network (NCCN) high-risk factors for high-risk prostate cancer patients who underwent robot-assisted radical prostatectomy. Results Multivariate analyses showed that clinical T3 was significantly associated with BCR [hazard ratio (HR) = 4.052; 95% confidence interval (CI), 1.26–12.99; P = 0.019]. Of the 100 patients, 77 had 1 high-risk factor and 23 had ≥ 2 high-risk factors; the 1-year BCR-free survival rate of patients with 1 high-risk factor and those with ≥ 2 high-risk factors was 94.8% and 69.6%, respectively. Patients with ≥ 2 high-risk factors were significantly associated with BCR (P = 0.002). No difference in BCR rate between patients with 1 high-risk factor and those with low- and intermediate-risk was found. Conclusion High-risk prostate cancer patients with 1 NCCN high-risk factor can be considered for robot-assisted radical prostatectomy treatment only. PMID:28070166

  18. Predictive cytogenetic biomarkers for colorectal neoplasia in medium risk patients

    PubMed Central

    Ionescu, EM; Nicolaie, T; Ionescu, MA; Becheanu, G; Andrei, F; Diculescu, M; Ciocirlan, M

    2015-01-01

    Rationale: DNA damage and chromosomal alterations in peripheral lymphocytes parallels DNA mutations in tumor tissues. Objective: The aim of our study was to predict the presence of neoplastic colorectal lesions by specific biomarkers in “medium risk” individuals (age 50 to 75, with no personal or family of any colorectal neoplasia). Methods and Results: We designed a prospective cohort observational study including patients undergoing diagnostic or opportunistic screening colonoscopy. Specific biomarkers were analyzed for each patient in peripheral lymphocytes - presence of micronuclei (MN), nucleoplasmic bridges (NPB) and the Nuclear Division Index (NDI) by the cytokinesis-blocked micronucleus assay (CBMN). Of 98 patients included, 57 were “medium risk” individuals. MN frequency and NPB presence were not significantly different in patients with neoplastic lesions compared to controls. In “medium risk” individuals, mean NDI was significantly lower for patients with any neoplastic lesions (adenomas and adenocarcinomas, AUROC 0.668, p 00.5), for patients with advanced neoplasia (advanced adenoma and adenocarcinoma, AUROC 0.636 p 0.029) as well as for patients with adenocarcinoma (AUROC 0.650, p 0.048), for each comparison with the rest of the population. For a cut-off of 1.8, in “medium risk” individuals, an NDI inferior to that value may predict any neoplastic lesion with a sensitivity of 97.7%, an advanced neoplastic lesion with a sensitivity of 97% and adenocarcinoma with a sensitivity of 94.4%. Discussion: NDI score may have a role as a colorectal cancer-screening test in “medium risk” individuals. Abbreviations: DNA = deoxyribonucleic acid; CRC = colorectal cancer; EU = European Union; WHO = World Health Organization; FOBT = fecal occult blood test; CBMN = cytokinesis-blocked micronucleus assay; MN = micronuclei; NPB = nucleoplasmic bridges; NDI = Nuclear Division Index; FAP = familial adenomatous polyposis; HNPCC = hereditary non

  19. Predicting Risk of Type 2 Diabetes by Using Data on Easy-to-Measure Risk Factors

    PubMed Central

    Buchner, David M.; Grigsby-Toussaint, Diana S.

    2017-01-01

    Introduction Statistical models for assessing risk of type 2 diabetes are usually additive with linear terms that use non-nationally representative data. The objective of this study was to use nationally representative data on diabetes risk factors and spline regression models to determine the ability of models with nonlinear and interaction terms to assess the risk of type 2 diabetes. Methods We used 4 waves of data (2005–2006 to 2011–2012) on adults aged 20 or older from the National Health and Nutrition Examination Survey (n = 5,471) and multivariate adaptive regression splines (MARS) to build risk models in 2015. MARS allowed for interactions among 17 noninvasively measured risk factors for type 2 diabetes. Results A key risk factor for type 2 diabetes was increasing age, especially for those older than 69, followed by a family history of diabetes, with diminished risk among individuals younger than 45. Above age 69, other risk factors superseded age, including systolic and diastolic blood pressure. The additive MARS model with nonlinear terms had an area under curve (AUC) receiver operating characteristic of 0.847, whereas the 2-way interaction MARS model had an AUC of 0.851, a slight improvement. Both models had an 87% accuracy in classifying diabetes status. Conclusion Statistical models of type 2 diabetes risk should allow for nonlinear associations; incorporation of interaction terms into the MARS model improved its performance slightly. Robust statistical manipulation of risk factors commonly measured noninvasively in clinical settings might provide useful estimates of type 2 diabetes risk. PMID:28278129

  20. A Global Risk Score (GRS) to Simultaneously Predict Early and Late Tumor Recurrence Risk after Resection of Hepatocellular Carcinoma1

    PubMed Central

    Dekervel, Jeroen; Popovic, Dusan; van Malenstein, Hannah; Windmolders, Petra; Heylen, Line; Libbrecht, Louis; Bulle, Ashenafi; De Moor, Bart; Van Cutsem, Eric; Nevens, Frederik; Verslype, Chris; van Pelt, Jos

    2016-01-01

    OBJECTIVES: Recurrence of hepatocellular carcinoma can arise from the primary tumor (“early recurrence”) or de novo from tumor formation in a cirrhotic environment (“late recurrence”). We aimed to develop one simple gene expression score applicable in both the tumor and the surrounding liver that can predict the recurrence risk. METHODS: We determined differentially expressed genes in a cell model of cancer aggressiveness. These genes were first validated in three large published data sets of hepatocellular carcinoma from which we developed a seven-gene risk score. RESULTS: The gene score was applied on two independent large patient cohorts. In the first cohort, with only tumor data available, it could predict the recurrence risk at 3 years after resection (68 ± 10% vs 35 ± 7%, P = .03). In the second cohort, when applied on the tumor, this gene score predicted early recurrence (62 ± 5% vs 37 ± 4%, P < .001), and when applied on the surrounding liver tissue, the same genes also correlated with late recurrence. Four patient classes with each different time patterns and rates of recurrence could be identified based on combining tumor and liver scores. In a multivariate Cox regression analysis, our gene score remained significantly associated with recurrence, independent from other important cofactors such as disease stage (P = .007). CONCLUSIONS: We developed a Global Risk Score that is able to simultaneously predict the risk of early recurrence when applied on the tumor itself, as well as the risk of late recurrence when applied on the surrounding liver tissue. PMID:27084430

  1. Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

    PubMed Central

    Choi, Sungkyoung; Bae, Sunghwan

    2016-01-01

    The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes. PMID:28154504

  2. Cardiovascular risk prediction: a comparative study of Framingham and quantum neural network based approach

    PubMed Central

    Narain, Renu; Saxena, Sanjai; Goyal, Achal Kumar

    2016-01-01

    Purpose Currently cardiovascular diseases (CVDs) are the main cause of death worldwide. Disease risk estimates can be used as prognostic information and support for treating CVDs. The commonly used Framingham risk score (FRS) for CVD prediction is outdated for the modern population, so FRS may not be accurate enough. In this paper, a novel CVD prediction system based on machine learning is proposed. Methods This study has been conducted with the data of 689 patients showing symptoms of CVD. Furthermore, the dataset of 5,209 CVD patients of the famous Framingham study has been used for validation purposes. Each patient’s parameters have been analyzed by physicians in order to make a diagnosis. The proposed system uses the quantum neural network for machine learning. This system learns and recognizes the pattern of CVD. The proposed system has been experimentally evaluated and compared with FRS. Results During testing, patients’ data in combination with the doctors’ diagnosis (predictions) are used for evaluation and validation. The proposed system achieved 98.57% accuracy in predicting the CVD risk. The CVD risk predictions by the proposed system, using the dataset of the Framingham study, confirmed the potential risk of death, deaths which actually occurred and had been recorded as due to myocardial infarction and coronary heart disease in the dataset of the Framingham study. The accuracy of the proposed system is significantly higher than FRS and other existing approaches. Conclusion The proposed system will serve as an excellent tool for a medical practitioner in predicting the risk of CVD. This system will be serving as an aid to medical practitioners for planning better medication and treatment strategies. An early diagnosis may be effectively made by using this system. An overall accuracy of 98.57% has been achieved in predicting the risk level. The accuracy is considerably higher compared to the other existing approaches. Thus, this system must be used

  3. Predicted risks of radiogenic cardiac toxicity in two pediatric patients undergoing photon or proton radiotherapy

    PubMed Central

    2013-01-01

    Background Hodgkin disease (HD) and medulloblastoma (MB) are common malignancies found in children and young adults, and radiotherapy is part of the standard treatment. It was reported that these patients who received radiation therapy have an increased risk of cardiovascular late effects. We compared the predicted risk of developing radiogenic cardiac toxicity after photon versus proton radiotherapies for a pediatric patient with HD and a pediatric patient with MB. Methods In the treatment plans, each patient’s heart was contoured in fine detail, including substructures of the pericardium and myocardium. Risk calculations took into account both therapeutic and stray radiation doses. We calculated the relative risk (RR) of cardiac toxicity using a linear risk model and the normal tissue complication probability (NTCP) values using relative seriality and Lyman models. Uncertainty analyses were also performed. Results The RR values of cardiac toxicity for the HD patient were 7.27 (proton) and 8.37 (photon), respectively; the RR values for the MB patient were 1.28 (proton) and 8.39 (photon), respectively. The predicted NTCP values for the HD patient were 2.17% (proton) and 2.67% (photon) for the myocardium, and were 2.11% (proton) and 1.92% (photon) for the whole heart. The predicted ratios of NTCP values (proton/photon) for the MB patient were much less than unity. Uncertainty analyses revealed that the predicted ratio of risk between proton and photon therapies was sensitive to uncertainties in the NTCP model parameters and the mean radiation weighting factor for neutrons, but was not sensitive to heart structure contours. The qualitative findings of the study were not sensitive to uncertainties in these factors. Conclusions We conclude that proton and photon radiotherapies confer similar predicted risks of cardiac toxicity for the HD patient in this study, and that proton therapy reduced the predicted risk for the MB patient in this study. PMID:23880421

  4. Prediction models for cardiovascular disease risk in the general population: systematic review

    PubMed Central

    Hooft, Lotty; Schuit, Ewoud; Debray, Thomas P A; Collins, Gary S; Tzoulaki, Ioanna; Lassale, Camille M; Siontis, George C M; Chiocchia, Virginia; Roberts, Corran; Schlüssel, Michael Maia; Gerry, Stephen; Black, James A; Heus, Pauline; van der Schouw, Yvonne T; Peelen, Linda M; Moons, Karel G M

    2016-01-01

    Objective To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population. Design Systematic review. Data sources Medline and Embase until June 2013. Eligibility criteria for study selection Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population. Results 9965 references were screened, of which 212 articles were included in the review, describing the development of 363 prediction models and 473 external validations. Most models were developed in Europe (n=167, 46%), predicted risk of fatal or non-fatal coronary heart disease (n=118, 33%) over a 10 year period (n=209, 58%). The most common predictors were smoking (n=325, 90%) and age (n=321, 88%), and most models were sex specific (n=250, 69%). Substantial heterogeneity in predictor and outcome definitions was observed between models, and important clinical and methodological information were often missing. The prediction horizon was not specified for 49 models (13%), and for 92 (25%) crucial information was missing to enable the model to be used for individual risk prediction. Only 132 developed models (36%) were externally validated and only 70 (19%) by independent investigators. Model performance was heterogeneous and measures such as discrimination and calibration were reported for only 65% and 58% of the external validations, respectively. Conclusions There is an excess of models predicting incident CVD in the general population. The usefulness of most of the models remains unclear owing to methodological shortcomings, incomplete presentation, and lack of external validation and model impact studies. Rather than developing yet another similar CVD risk prediction model, in this era of large datasets, future research should focus on externally validating and comparing head-to-head promising CVD risk models that already exist, on tailoring or even combining these models to local

  5. Predicting the Unpredictable? Identifying High-Risk versus Low-Risk Parents with Intellectual Disabilities

    ERIC Educational Resources Information Center

    McGaw, Sue; Scully, Tamara; Pritchard, Colin

    2010-01-01

    Objectives: This study set out to identify risk factors affecting parents with intellectual disabilities (IDs) by determining: (i) whether perception of family support differs between parents with IDs, referring professionals, and a specialist parenting service; (ii) whether multivariate familial and demographic factors differentiates "high-risk"…

  6. Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction

    PubMed Central

    Wu, Yiming; Jing, Runyu; Dong, Yongcheng; Kuang, Qifan; Li, Yan; Huang, Ziyan; Gan, Wei; Xue, Yue; Li, Yizhou; Li, Menglong

    2017-01-01

    Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate for the hundreds of SNPs, most of which reside in non-coding regions. Here we provide a comprehensive annotation of 65 known T2D related SNPs and inspect putative functional SNPs probably causing protein dysfunction, response element disruptions of known transcription factors related to T2D genes and regulatory response element disruption of four histone marks in pancreas and pancreas islet. In new identified risk SNPs, some of them were reported as T2D related SNPs in recent studies. Further, we found that accumulation of modest effects of single sites markedly enhanced the risk prediction based on 1989 T2D samples and 3000 healthy controls. The AROC value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals. PMID:28262806

  7. The Stroke Assessment of Fall Risk (SAFR): predictive validity in inpatient stroke rehabilitation

    PubMed Central

    Breisinger, Terry P; Skidmore, Elizabeth R; Niyonkuru, Christian; Terhorst, Lauren; Campbell, Grace B

    2014-01-01

    Objective To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. Design and setting Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. Participants Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. Interventions Not applicable. Main outcome measure(s) Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales’ classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. Results A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). Conclusions An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted. PMID:24849795

  8. Utilizing Dental Electronic Health Records Data to Predict Risk for Periodontal Disease.

    PubMed

    Thyvalikakath, Thankam P; Padman, Rema; Vyawahare, Karnali; Darade, Pratiksha; Paranjape, Rhucha

    2015-01-01

    Periodontal disease is a major cause for tooth loss and adversely affects individuals' oral health and quality of life. Research shows its potential association with systemic diseases like diabetes and cardiovascular disease, and social habits such as smoking. This study explores mining potential risk factors from dental electronic health records to predict and display patients' contextualized risk for periodontal disease. We retrieved relevant risk factors from structured and unstructured data on 2,370 patients who underwent comprehensive oral examinations at the Indiana University School of Dentistry, Indianapolis, IN, USA. Predicting overall risk and displaying relationships between risk factors and their influence on the patient's oral and general health can be a powerful educational and disease management tool for patients and clinicians at the point of care.

  9. Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues.

    PubMed

    Rapuano, Kristina M; Zieselman, Amanda L; Kelley, William M; Sargent, James D; Heatherton, Todd F; Gilbert-Diamond, Diane

    2017-01-03

    Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9-12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life.

  10. Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues

    PubMed Central

    Rapuano, Kristina M.; Zieselman, Amanda L.; Kelley, William M.; Sargent, James D.; Heatherton, Todd F.

    2017-01-01

    Obesity is a major public health concern that involves an interaction between genetic susceptibility and exposure to environmental cues (e.g., food marketing); however, the mechanisms that link these factors and contribute to unhealthy eating are unclear. Using a well-known obesity risk polymorphism (FTO rs9939609) in a sample of 78 children (ages 9–12 y), we observed that children at risk for obesity exhibited stronger responses to food commercials in the nucleus accumbens (NAcc) than children not at risk. Similarly, children at a higher genetic risk for obesity demonstrated larger NAcc volumes. Although a recessive model of this polymorphism best predicted body mass and adiposity, a dominant model was most predictive of NAcc size and responsivity to food cues. These findings suggest that children genetically at risk for obesity are predisposed to represent reward signals more strongly, which, in turn, may contribute to unhealthy eating behaviors later in life. PMID:27994159

  11. Assessment of the landslide and flood risks in São Paulo City, Brazil

    NASA Astrophysics Data System (ADS)

    Vieira, Bianca; Listo, Fabrízio

    2010-05-01

    In Brazilian cities, especially during summer, the landslides and floods cause disaster and economic losses. Aricanduva basin is one of the most critical in the Metropolitan Region of São Paulo (RMSP), where many types of morphodynamic processes occur. This is the largest river basin in São Paulo City. The current situation is characterized by intense urbanization, soil sealing and consequent reduction of soil infiltration, increasing the frequency of flood events in this area. Thus, the main objective of this paper is to map risk areas of landslides and floods in the sub-basin Limoeiro, located in the head of the Aricanduva basin. For mapping the risk areas, we prepared a record field to floods and landslides, based on several studies. Initially, it were identified the natural indicators (vegetation, topography, surface cover and drainage) and anthropogenic (urban pattern, soil cover, building types, occupation density, road conditions, infrastructure, drainage systems, distance between houses and slope, at the top and base, and the drainage channel). On the second step of this research, we identified the evidences of mass movements (scars, cracks, subsidence, trees, poles and inclined walls). Thus, on the basis of this analysis it was possible to define the risk probability: R1 (low or no risk), R2 (moderate), R3 (high) and, R4 (very high). Subsequently, by means of oblique photographs (taken from helicopter flight) it was possible to define risk areas in the basin. In all the sectors identified, were recorded approximately 903 urban settlements. The results showed that from the 25 sectors of risk, 14 sectors (56%) presented landslide risk and 11 (44%), flood risk. Of the sectors that showed landslide risk areas, 21% have very high probability (R4), 21% high (R3), 29% moderate (R2) and 29% low (R1). The sectors at flood risk presented 45% of very high probability (R4), 10% high (R3), 18% moderate (R2) and 27% low (R1). There is large presence of sediments from

  12. Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

    SciTech Connect

    Nguyen, J.; Moteabbed, M.; Paganetti, H.

    2015-01-15

    Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio

  13. Prediction at First Year of Incident New-Onset Diabetes After Kidney Transplantation by Risk Prediction Models

    PubMed Central

    Rodrigo, Emilio; Santos, Lidia; Piñera, Celestino; Ruiz San Millán, Juan Carlos; Quintela, Maria Estrella; Toyos, Carmen; Allende, Natalia; Gómez-Alamillo, Carlos; Arias, Manuel

    2012-01-01

    OBJECTIVE Our aim was to analyze the performance of two scores developed for predicting diabetes in nontransplant populations for identifying kidney transplant recipients with a higher new-onset diabetes mellitus after transplantation (NODAT) risk beyond the first year after transplantation. RESEARCH DESIGN AND METHODS We analyzed 191 kidney transplants, which had at least 1-year follow-up posttransplant. First-year posttransplant variables were collected to estimate the San Antonio Diabetes Prediction Model (SADPM) and Framingham Offspring Study–Diabetes Mellitus (FOS-DM) algorithm. RESULTS Areas under the receiver operating characteristic curve of FOS-DM and SADPM scores to predict NODAT were 0.756 and 0.807 (P < 0.001), respectively. FOS-DM and SADPM scores over 75 percentile (hazard ratio 5.074 and 8.179, respectively, P < 0.001) were associated with NODAT. CONCLUSIONS Both scores can be used to identify kidney recipients at higher risk for NODAT beyond the first year. SADPM score detects some 25% of kidney transplant patients with an eightfold risk for NODAT. PMID:22279030

  14. Selenium deficiency risk predicted to increase under future climate change.

    PubMed

    Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

    2017-03-14

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

  15. Selenium deficiency risk predicted to increase under future climate change

    PubMed Central

    Jones, Gerrad D.; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P.; Seneviratne, Sonia I.; Smith, Pete; Winkel, Lenny H. E.

    2017-01-01

    Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change. PMID:28223487

  16. Persisting arthralgia due to Mayaro virus infection in a traveler from Brazil: is there a risk for attendants to the 2014 FIFA World Cup?

    PubMed

    Slegers, C A D; Keuter, M; Günther, S; Schmidt-Chanasit, J; van der Ven, A J; de Mast, Q

    2014-07-01

    The 2014 FIFA World Cup and the 2016 Olympic Games will attract large groups of visitors to Brazil. These visitors will be at risk for different arboviral infections, some of which not well known outside endemic areas. We report a case of a 52-year-old Dutch woman who presented with persistent arthralgia due to a Mayaro virus (MAYV) infection which she contracted in the Amazon basin in Brazil. MAYV is a mosquito-borne alphavirus which primarily circulates in humid tropical forests of South America. Infections are rarely reported in travelers and are characterized by an acute febrile illness which is often followed by a prolonged and sometimes incapacitating polyarthralgia. Both travelers and physicians should be aware of the risk of these arboviral infections and the importance of mosquito bite prevention should be stressed.

  17. An agro-climatic approach to determine citrus postbloom fruit drop risk in Southern Brazil

    NASA Astrophysics Data System (ADS)

    Soares-Colletti, Ana R.; Alvares, Clayton A.; Sentelhas, Paulo C.

    2016-06-01

    Postbloom fruit drop (PFD) causes lesions on the petals of citrus flowers and induces fruit abscission causing severe damage to production when the flowering period coincides with intense rainfall. The aims of this study were to develop a phenological-climatological model for citrus PFD occurrence and, together with weather data series from several locations, to determine and map the agro-climatic favorability of PFD occurrence in the state of São Paulo, Southern Brazil. A phenological flowering model was developed to identify when citrus flowering occurs. The flowering starts after when a temperature below 10 °C in the months of June or July is reached followed by cumulative rainfall within 5 days of at least 20 mm, and then 96 °C days. Between the beginning of flowering and its peak, 147 °C days are required, and between the peak and its end, approximately 229 °C days, being 206 °C days from the peak to the moment when flowers remaining are about 50 % of total. The relationship between PFD incidence and accumulated rainfall during the critical period (between flowering peak and 50 % of flowers remaining) was adjusted by the Gompertz model ( R 2 = 0.99, p < 0.05). After its validation, this model was used to estimate PFD incidence for 29 locations in the state, from 1993 to 2013, which allowed to map the PFD climatic favorability for the state through a Geographical Information System using linear models based on latitude, longitude, and altitude. The obtained map showed a trend of PFD incidence increasing from the northwest of the state of São Paulo towards the south and the coastal region, with medium to very high favorability in the center of the state. The results of this study can be used by growers as a guide for disease control planning as well as for defining the regions where the climatic conditions are likely to escape this disease.

  18. Consumption of fruits and vegetables associated with other risk behaviors among adolescents in Northeast Brazil

    PubMed Central

    Silva, Fabiana Medeiros de Almeida; Smith-Menezes, Aldemir; Duarte, Maria de Fátima da Silva

    2016-01-01

    Abstract Objective: To determine the prevalence of consumption of fruits and vegetables and identify the association with low level of physical activity, exposure to sedentary behavior, consumption of soft drinks and overweight/obesity in adolescents. Methods: This is a cross-sectional school-based study with a representative sample of 3992 students aged 14–19 years from the state of Sergipe, Brazil. The outcome was low consumption of fruits and vegetables (<5servings/day). Independent variables were: level of physical activity, sedentary behavior, consumption of soft drinks, and overweight/obesity. Global Student Health Survey questionnaire and body mass and height measurements were used, as well as chi-square test and crude and adjusted binary logistic regression. The significance level adopted was 5%. Results: The prevalence of inadequate consumption of fruits and vegetables was high – 88.6% (95%CI=87.6–89.5). Higher likelihood of low consumption of fruits and vegetables was verified among boys who were exposed to sedentary behavior (OR=1.63; 95%CI=1.18–2.24), who consumed soft drinks (OR=3.04; 95%CI=2.10–4.40), with insufficiently physical activity (OR=1.98; 95%CI=1.43–2.73) and girls who consumed soft drinks (OR=1.88; 95%CI=1.43–2.47) and those with overweight/obesity (OR=1.63; 95%CI=1.19–2.23). Conclusions: There is a need of public policies aimed at encouraging the consumption of healthy foods among adolescents. PMID:27240560

  19. Statistical innovations improve prevalence estimates of nutrient risk populations: applications in São Paulo, Brazil.

    PubMed

    Morimoto, Juliana Masami; Marchioni, Dirce Maria Lobo; Cesar, Chester Luiz Galvão; Fisberg, Regina Mara

    2012-10-01

    The objective of this study was to estimate the prevalence of inadequate micronutrient intake and excess sodium intake among adults age 19 years and older in the city of São Paulo, Brazil. Twenty-four-hour dietary recall and sociodemographic data were collected from each participant (n=1,663) in a cross-sectional study, Inquiry of Health of São Paulo, of a representative sample of the adult population of the city of São Paulo in 2003 (ISA-2003). The variability in intake was measured through two replications of the 24-hour recall in a subsample of this population in 2007 (ISA-2007). Usual intake was estimated by the PC-SIDE program (version 1.0, 2003, Department of Statistics, Iowa State University), which uses an approach developed by Iowa State University. The prevalence of nutrient inadequacy was calculated using the Estimated Average Requirement cut-point method for vitamins A and C, thiamin, riboflavin, niacin, copper, phosphorus, and selenium. For vitamin D, pantothenic acid, manganese, and sodium, the proportion of individuals with usual intake equal to or more than the Adequate Intake value was calculated. The percentage of individuals with intake equal to more than the Tolerable Upper Intake Level was calculated for sodium. The highest prevalence of inadequacy for males and females, respectively, occurred for vitamin A (67% and 58%), vitamin C (52% and 62%), thiamin (41% and 50%), and riboflavin (29% and 19%). The adjustment for the within-person variation presented lower prevalence of inadequacy due to removal of within-person variability. All adult residents of São Paulo had excess sodium intake, and the rates of nutrient inadequacy were high for certain key micronutrients.

  20. Screening-level risk assessment applied to dredging of polluted sediments from Guanabara Bay, Rio de Janeiro, Brazil.

    PubMed

    Silveira, Ana Elisa F; Nascimento, Juliana R; Sabadini-Santos, Elisamara; Bidone, Edison D

    2017-03-16

    Guanabara Bay is characterized by predominant eutrophication and anoxic sediments with a mixture of pollutants. The risk prognosis associated with the dumping of its dredged sediments into the open ocean was addressed by our algorithm. Our algorithm could prioritize areas, characterize major processes related to dredging, measure the potential risk of sediments, and predict the effects of sediment mixing. The estimated risk of dredged sediment was >10-fold than that of ocean sediments. Among metals, mercury represented 50-90% of the total risk. The transfer of dredged material into the ocean or internal dumping in the bay requires a 1:10 dilution to mitigate the risk and bring the risk levels close to that in the EPA criteria, below which there is less likelihood of adverse effects to the biota, and a 1:100 dilution to maintain the original characteristics of the ocean disposal control area. Our algorithm indicator can be used in the design of both aquatic and continental disposal of dredged materials and their management.

  1. The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

    NASA Astrophysics Data System (ADS)

    Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

    2015-08-01

    The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

  2. Predicting coronary heart disease: from Framingham Risk Score to ultrasound bioimaging.

    PubMed

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have been tested and found useful (ie, coronary calcium detection by computed tomography scanning, reduction in ankle-brachial index, and ultrasound scanning of the carotid arteries). This review will focus on the latter technique. Detection of thickened carotid intima-media by ultrasound has been used in many large epidemiological studies, but although it has been found to be associated with increased risk of cardiovascular death, its clinical utility is limited. Detection of carotid plaque has, on the other hand, been found to be associated with a substantial risk of future events. Similarly, detection of plaque in the femoral arteries is associated with increased risk, and plaque in the femoral as well as carotid arteries predicts even higher risk. Furthermore, quantification of plaque size (plaque area), such as quantification of amount of coronary calcium on computed tomography scanning, improves predictability-the larger the plaques, the higher the risk. So far, studies using ultrasound all have been performed with 2-dimensional ultrasound imaging. Recently, 3-dimensional ultrasound imaging has been introduced, which allows for more accurate quantification of atherosclerosis. Small studies pioneering its use have indicated the utility of measuring changes in vessel-wall volume and plaque volume with respect to treatment effect. The High-Risk Plaque Initiative BioImage Study is currently investigating the predictive value of total carotid plaque volume with respect to prediction of future cardiovascular events.

  3. Predictive capacity of risk assessment scales and clinical judgment for pressure ulcers: a meta-analysis.

    PubMed

    García-Fernández, Francisco Pedro; Pancorbo-Hidalgo, Pedro L; Agreda, J Javier Soldevilla

    2014-01-01

    A systematic review with meta-analysis was completed to determine the capacity of risk assessment scales and nurses' clinical judgment to predict pressure ulcer (PU) development. Electronic databases were searched for prospective studies on the validity and predictive capacity of PUs risk assessment scales published between 1962 and 2010 in English, Spanish, Portuguese, Korean, German, and Greek. We excluded gray literature sources, integrative review articles, and retrospective or cross-sectional studies. The methodological quality of the studies was assessed according to the guidelines of the Critical Appraisal Skills Program. Predictive capacity was measured as relative risk (RR) with 95% confidence intervals. When 2 or more valid original studies were found, a meta-analysis was conducted using a random-effect model and sensitivity analysis. We identified 57 studies, including 31 that included a validation study. We also retrieved 4 studies that tested clinical judgment as a risk prediction factor. Meta-analysis produced the following pooled predictive capacity indicators: Braden (RR = 4.26); Norton (RR = 3.69); Waterlow (RR = 2.66); Cubbin-Jackson (RR = 8.63); EMINA (RR = 6.17); Pressure Sore Predictor Scale (RR = 21.4); and clinical judgment (RR = 1.89). Pooled analysis of 11 studies found adequate risk prediction capacity in various clinical settings; the Braden, Norton, EMINA (mEntal state, Mobility, Incontinence, Nutrition, Activity), Waterlow, and Cubbin-Jackson scales showed the highest predictive capacity. The clinical judgment of nurses was found to achieve inadequate predictive capacity when used alone, and should be used in combination with a validated scale.

  4. Diabetes Risk Factors, Diabetes Risk Algorithms, and the Prediction of Future Frailty: The Whitehall II Prospective Cohort Study

    PubMed Central

    Bouillon, Kim; Kivimäki, Mika; Hamer, Mark; Shipley, Martin J.; Akbaraly, Tasnime N.; Tabak, Adam; Singh-Manoux, Archana; Batty, G. David

    2013-01-01

    Objective To examine whether established diabetes risk factors and diabetes risk algorithms are associated with future frailty. Design Prospective cohort study. Risk algorithms at baseline (1997–1999) were the Framingham Offspring, Cambridge, and Finnish diabetes risk scores. Setting Civil service departments in London, United Kingdom. Participants There were 2707 participants (72% men) aged 45 to 69 years at baseline assessment and free of diabetes. Measurements Risk factors (age, sex, family history of diabetes, body mass index, waist circumference, systolic and diastolic blood pressure, antihypertensive and corticosteroid treatments, history of high blood glucose, smoking status, physical activity, consumption of fruits and vegetables, fasting glucose, HDL-cholesterol, and triglycerides) were used to construct the risk algorithms. Frailty, assessed during a resurvey in 2007–2009, was denoted by the presence of 3 or more of the following indicators: self-reported exhaustion, low physical activity, slow walking speed, low grip strength, and weight loss; “prefrailty” was defined as having 2 or fewer of these indicators. Results After a mean follow-up of 10.5 years, 2.8% of the sample was classified as frail and 37.5% as prefrail. Increased age, being female, stopping smoking, low physical activity, and not having a daily consumption of fruits and vegetables were each associated with frailty or prefrailty. The Cambridge and Finnish diabetes risk scores were associated with frailty/prefrailty with odds ratios per 1 SD increase (disadvantage) in score of 1.18 (95% confidence interval: 1.09–1.27) and 1.27 (1.17–1.37), respectively. Conclusion Selected diabetes risk factors and risk scores are associated with subsequent frailty. Risk scores may have utility for frailty prediction in clinical practice. PMID:24103860

  5. A study of multidrug-resistant tuberculosis in risk groups in the city of Santos, São Paulo, Brazil.

    PubMed

    Coelho, Andréa Gobetti Vieira; Zamarioli, Liliana Aparecida; Telles, Maria Alice; Ferrazoli, Lucilaine; Waldman, Eliseu Alves

    2012-09-01

    Monitoring the extent of and trends in multidrug-resistant tuberculosis (MDR-TB) is a priority of the Brazilian National Tuberculosis Control Programme. The current study aimed to estimate the incidence of MDR-TB, describe the profile of TB drug resistance in risk groups and examine whether screening for MDR-TB adhered to the recommended guidelines. A descriptive study that examined diagnosed cases of pulmonary TB was conducted in the city of Santos, Brazil, between 2000-2004. Of the 2,176 pulmonary TB cases studied, 671 (30.8%) met the criteria for drug sensitivity testing and, of these cases, 31.7% (213/671) were tested. Among the tested cases, 9.4% were resistant to one anti-TB drug and 15% were MDR. MDR was observed in 11.6% of 86 new TB cases and 17.3% of 127 previously treated cases. The average annual incidence of MDR-TB was 1.9 per 100,000 inhabitants-years. The extent of known MDR-TB in the city of Santos is high, though likely to be underestimated. Our study therefore indicates an inadequate adherence to the guidelines for MDR-TB screening and suggests the necessity of alternative strategies of MDR-TB surveillance.

  6. Family food insecurity and nutritional risk in adolescents from a low-income area of Rio de Janeiro, Brazil.

    PubMed

    Lopes, Taís S; Sichieri, Rosely; Salles-Costa, Rosana; Veiga, Gloria V; Pereira, Rosangela A

    2013-09-01

    The study objective was to analyse the association between food insecurity and the weight and height status of adolescents from a low-income area in the metropolitan region of Rio de Janeiro, Brazil. The population-based cross-sectional survey included 523 adolescents aged 12-18 years, selected by a three-stage cluster sample. Dietary intake was ascertained with a food frequency questionnaire and family food insecurity was assessed with a validated questionnaire. The analysis estimated weighted means of energy and nutrient intakes by families' socioeconomic characteristics and the association between dietary intake with overweight and stunting. The prevalence of mild family food insecurity was 36%, and 24% of the families reported moderate or severe food insecurity. Overweight prevalence was 24%, and the prevalence of stunting was 9%, with no significant differences between sex or age groups. Family food insecurity was associated with unfavourable socioeconomic characteristics, but there was no association between socioeconomic characteristics (including family food insecurity) and overweight or stunting. Moderate or severe family food insecurity was inversely associated with intake of protein and calcium. In addition, stunting was associated with low calcium and iron intake. The co-existence of family food insecurity with overweight and stunting implies a high nutritional risk for adolescents from poor areas of Rio de Janeiro. Nevertheless, the observed absence of a statistical association between family food insecurity and weight status attests to the complexity of this issue.

  7. Serological survey and risk factors for brucellosis in water buffaloes in the state of Pará, Brazil.

    PubMed

    da Silva, Jenevaldo Barbosa; Rangel, Charles Passos; da Fonseca, Adivaldo Henrique; de Morais, Eziquiel; Vinhote, Wagner Marcelo Souza; da Silva Lima, Danillo Henrique; da Silva e Silva, Natália; Barbosa, José Diomedes

    2014-02-01

    To evaluate the prevalence and possible risk factors for brucellosis caused by Brucella abortus in water buffaloes in the state of Pará, Brazil, 3,917 female buffalo serum samples from pregnant and non-pregnant animals were examined: 2,809 from Marajó Island and 1,108 from the mainland. The buffered acidified plate antigen (BAPA) screening test positively diagnosed 4.8% (188/3,917) of the animals with brucellosis, and the 2-mercaptoethanol (2-ME) confirmatory test affirmed 95.7% (180/188) of the results. The brucellosis prevalence was 4.17 times greater in mainland animals than on Marajó Island, with the highest prevalence in Tailândia (11.30%) and Paragominas (12.38%). Brucellosis seroprevalence was significantly influenced (p < 0.05) by reproductive status, with pregnant females being most vulnerable. These results demonstrate that brucellosis infection is active in the Brazilian region containing the largest buffalo population and that this disease poses a threat to public health and buffalo production in Pará.

  8. INCIDENCE DENSITY, PROPORTIONATE MORTALITY, AND RISK FACTORS OF ASPERGILLOSIS IN MAGELLANIC PENGUINS IN A REHABILITATION CENTER FROM BRAZIL.

    PubMed

    Silva Filho, Rodolfo Pinho da; Xavier, Melissa Orzechowski; Martins, Aryse Moreira; Ruoppolo, Valéria; Mendoza-Sassi, Raúl Andrés; Adornes, Andréa Corrado; Cabana, Ângela Leitzke; Meireles, Mário Carlos Araújo

    2015-12-01

    Aspergillosis, an opportunistic mycosis caused by the Aspergillus genus, affects mainly the respiratory system and is considered one of the most significant causes of mortality in captive penguins. This study aimed to examine a 6-yr period of cases of aspergillosis in penguins at the Centro de Recuperação de Animais Marinhos (CRAM-FURG), Rio Grande, Brazil. A retrospective cohort study was conducted using the institution's records of penguins received from January 2004 to December 2009. Animals were categorized according to the outcome "aspergillosis," and analyzed by age group, sex, oil fouling, origin, prophylactic administration of itraconazole, period in captivity, body mass, hematocrit, and total plasma proteins. A total of 327 Magellanic penguins (Spheniscus magellanicus) was studied, 66 of which died of aspergillosis. Proportionate mortality by aspergillosis was 48.5%, and incidence density was 7.3 lethal aspergillosis cases per 100 penguins/mo. Approximately 75% of the aspergillosis cases occurred in penguins that had been transferred from other rehabilitation centers, and this was considered a significant risk factor for the disease. Significant differences were also observed between the groups in regard to the period of time spent in captivity until death, hematocrit and total plasma proteins upon admission to the center, and body mass gain during the period in captivity. The findings demonstrate the negative impacts of aspergillosis on the rehabilitation of Magellanic penguins, with a high incidence density and substantial mortality.

  9. Assessing risk prediction models using individual participant data from multiple studies.

    PubMed

    Pennells, Lisa; Kaptoge, Stephen; White, Ian R; Thompson, Simon G; Wood, Angela M

    2014-03-01

    Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous.

  10. Evaluation of Major Online Diabetes Risk Calculators and Computerized Predictive Models

    PubMed Central

    Stiglic, Gregor; Pajnkihar, Majda

    2015-01-01

    Classical paper-and-pencil based risk assessment questionnaires are often accompanied by the online versions of the questionnaire to reach a wider population. This study focuses on the loss, especially in risk estimation performance, that can be inflicted by direct transformation from the paper to online versions of risk estimation calculators by ignoring the possibilities of more complex and accurate calculations that can be performed using the online calculators. We empirically compare the risk estimation performance between four major diabetes risk calculators and two, more advanced, predictive models. National Health and Nutrition Examination Survey (NHANES) data from 1999–2012 was used to evaluate the performance of detecting diabetes and pre-diabetes. American Diabetes Association risk test achieved the best predictive performance in category of classical paper-and-pencil based tests with an Area Under the ROC Curve (AUC) of 0.699 for undiagnosed diabetes (0.662 for pre-diabetes) and 47% (47% for pre-diabetes) persons selected for screening. Our results demonstrate a significant difference in performance with additional benefits for a lower number of persons selected for screening when statistical methods are used. The best AUC overall was obtained in diabetes risk prediction using logistic regression with AUC of 0.775 (0.734) and an average 34% (48%) persons selected for screening. However, generalized boosted regression models might be a better option from the economical point of view as the number of selected persons for screening of 30% (47%) lies significantly lower for diabetes risk assessment in comparison to logistic regression (p < 0.001), with a significantly higher AUC (p < 0.001) of 0.774 (0.740) for the pre-diabetes group. Our results demonstrate a serious lack of predictive performance in four major online diabetes risk calculators. Therefore, one should take great care and consider optimizing the online versions of questionnaires that were

  11. Association between vehicular emissions and cardiorespiratory disease risk in Brazil and its variation by spatial clustering of socio-economic factors.

    PubMed

    Requia, Weeberb J; Koutrakis, Petros; Roig, Henrique L; Adams, Matthew D; Santos, Cleide M

    2016-10-01

    Many studies have suggested that socio-economic factors are strong modifiers of human vulnerability to air pollution effects. Most of these studies were performed in developed countries, specifically in the US and Europe. Only a few studies have been performed in developing countries, and analyzed small regions (city level) with no spatial disaggregation. The aim of this study was to assess the association between vehicle emissions and cardiorespiratory disease risk in Brazil and its modification by spatial clustering of socio-economic conditions. We used a quantile regression model to estimate the risk and a geostatistical approach (K means) to execute spatial cluster analysis. We performed the risk analysis in three stages. First, we analyzed the entire study area (primary analysis), and then we conducted a spatial cluster analysis based on various municipal-level socio-economic factors, followed by a sensitivity analysis. We studied 5444 municipalities in Brazil between 2008 and 2012. Our findings showed a significant association between cardiorespiratory disease risk and vehicular emissions. We found that a 15% increase in air pollution is associated with a 6% increase in hospital admissions rates. The results from the spatial cluster analysis revealed two groups of municipalities with distinct sets of socio-economic factors and risk levels of cardiorespiratory disease related to exposure to vehicular emissions. For example, for vehicle emissions of PM in 2008, we found a relative risk of 4.18 (95% CI: 3.66, 4.93) in the primary analysis; in Group 1, the risk was 0.98 (95% CI: 0.10, 2.05) while in Group 2, the risk was 5.56 (95% CI: 4.46, 6.25). The risk in Group 2 was 480% higher than the risk in Group 1, and 35% higher than the risk in the primary analysis. Group 1 had higher values (3rd quartile) for urbanization rate, highway density, and GDP; very high values (≥3rd quartile) for population density; median values for distance from the capital; and lower

  12. Ecological risks of trace metals in Guanabara Bay, Rio de Janeiro, Brazil: An index analysis approach.

    PubMed

    de Carvalho Aguiar, Valquiria Maria; de Lima, Michelle Nunes; Abuchacra, Rodrigo Coutinho; Abuchacra, Paula Ferreira Falheiro; Neto, José Antônio Baptista; Borges, Heloísa Vargas; de Oliveira, Vitor Calôr

    2016-11-01

    Total concentrations of Ni, Cr, Cu, Pb and Zn were determined in surface sediments from 30 stations in Guanabara Bay in 1999 and 2008. An approach using various environmental indices was used to assess contamination status of metals. This approach allowed the comparison with different coastal areas. Background Enrichment Index, Contamination index and Ecological Risk index (Pollution Load Index; Sediment Quality Guideline Quotient and Ecological Risk Index) were calculated for the metals. Results revealed a great load of organic matter and significant increases in Cu and Pb levels between 1999 and 2008. The concentrations of Cr and Zn were of great concern, surpassing the values of Probable Effect Level reference values. In spite of the differences of each index, results effectively revealed the striking contamination in Guanabara Bay concerning trace metals, and also suggested potential risk to local biota. The contamination of the northwest area was notably higher than the rest of the bay. In comparison with some other coastal bays around the world, Guanabara Bay stood out as a remarkably contaminated environment.

  13. Performances of HTLV serological tests in diagnosing HTLV infection in high-risk population of São Paulo, Brazil.

    PubMed

    Jacob, Fabrício; Santos-Fortuna, Elizabeth de los; Azevedo, Raymundo Soares; Caterino-de-Araujo, Adele

    2007-01-01

    Testing problems in diagnosing human T-lymphotropic virus (HTLV) infection, mostly HTLV-II, have been documented in HIV/AIDS patients. Since December 1998, the Immunology Department of Instituto Adolfo Lutz (IAL) offers HTLV-I/II serology to Public Health Units that attend HTLV high-risk individuals. Two thousand, three hundred and twelve serum samples: 1,393 from AIDS Reference Centers (Group I), and 919 from HTLV out-patient clinics (Group II) were sent to IAL for HTLV-I/II antibodies detection. The majority of them were screened by two enzyme immunoassays (EIAs), and confirmed by Western Blot (WB 2.4, Genelabs). Seven different EIA kits were employed during the period, and according to WB results, the best performance was obtained by EIAs that contain HTLV-I and HTLV-II viral lysates and rgp21 as antigens. Neither 1st and 2nd, nor 3rd generation EIA kits were 100% sensitive in detecting truly HTLV-I/II reactive samples. HTLV-I and HTLV-II prevalence rates of 3.3% and 2.5% were detected in Group I, and of 9.6% and 3.6% in Group II, respectively. High percentages of HTLV-seroindeterminate WB sera were detected in both Groups. The algorithm testing to be employed in HTLV high-risk population from São Paulo, Brazil, needs the use of two EIA kits of different formats and compounds as screening, and because of high seroindeterminate WB, may be another confirmatory assay.

  14. Premorbid Multivariate Prediction of Adult Psychosis-Spectrum Disorder: A High-Risk Prospective Investigation

    PubMed Central

    Schiffman, Jason; Kline, Emily; Jameson, Nicole; Sorensen, Holger J.; Dodge, Shana; Tsuji, Thomas; Mortensen, Erik L.; Mednick, Sarnoff

    2015-01-01

    Premorbid prediction of psychosis-spectrum disorders has implications for both understanding etiology and clinical identification. The current study used a longitudinal high-risk for psychosis design that included children of parents with schizophrenia as well as two groups of controls (children whose parents had no mental illness, and children with at least one parent with a non-psychotic psychiatric diagnosis). Premorbid neurological factors and an indication of social function, as measured when participants were 10–13 years of age, were combined to predict psychosis-spectrum disorders in adulthood. Through a combination of childhood predictors, the model correctly classified 82% (27 of 33) of the participants who eventually developed a psychosis-spectrum outcome in adulthood. With replication, multivariate premorbid prediction, including genetic risk, social, and neurological variables, could potentially be a useful complementary approach to identifying individuals at risk for developing psychosis-spectrum disorders. PMID:26213343

  15. Premorbid multivariate prediction of adult psychosis-spectrum disorder: A high-risk prospective investigation.

    PubMed

    Schiffman, Jason; Kline, Emily; Jameson, Nicole D; Sorensen, Holger J; Dodge, Shana; Tsuji, Thomas; Mortensen, Erik L; Mednick, Sarnoff A

    2015-10-01

    Premorbid prediction of psychosis-spectrum disorders has implications for both understanding etiology and clinical identification. The current study used a longitudinal high-risk for psychosis design that included children of parents with schizophrenia as well as two groups of controls (children whose parents had no mental illness, and children with at least one parent with a non-psychotic psychiatric diagnosis). Premorbid neurological factors and an indication of social function, as measured when participants were 10-13years of age, were combined to predict psychosis-spectrum disorders in adulthood. Through a combination of childhood predictors, the model correctly classified 82% (27 of 33) of the participants who eventually developed a psychosis-spectrum outcome in adulthood. With replication, multivariate premorbid prediction, including genetic risk, social, and neurological variables, could potentially be a useful complementary approach to identifying individuals at risk for developing psychosis-spectrum disorders.

  16. Dispositional Optimism and Perceived Risk Interact to Predict Intentions to Learn Genome Sequencing Results

    PubMed Central

    Taber, Jennifer M.; Klein, William M. P.; Ferrer, Rebecca A.; Lewis, Katie L.; Biesecker, Leslie G.; Biesecker, Barbara B.

    2015-01-01

    Objective Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Method Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Results Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. Conclusions The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. PMID:25313897

  17. Dietary Information Improves Model Performance and Predictive Ability of a Noninvasive Type 2 Diabetes Risk Model

    PubMed Central

    Han, Tianshu; Tian, Shuang; Wang, Li; Liang, Xi; Cui, Hongli; Du, Shanshan; Na, Guanqiong; Na, Lixin; Sun, Changhao

    2016-01-01

    There is no diabetes risk model that includes dietary predictors in Asia. We sought to develop a diet-containing noninvasive diabetes risk model in Northern China and to evaluate whether dietary predictors can improve model performance and predictive ability. Cross-sectional data for 9,734 adults aged 20–74 years old were used as the derivation data, and results obtained for a cohort of 4,515 adults with 4.2 years of follow-up were used as the validation data. We used a logistic regression model to develop a diet-containing noninvasive risk model. Akaike’s information criterion (AIC), area under curve (AUC), integrated discrimination improvements (IDI), net classification improvement (NRI) and calibration statistics were calculated to explicitly assess the effect of dietary predictors on a diabetes risk model. A diet-containing type 2 diabetes risk model was developed. The significant dietary predictors including the consumption of staple foods, livestock, eggs, potato, dairy products, fresh fruit and vegetables were included in the risk model. Dietary predictors improved the noninvasive diabetes risk model with a significant increase in the AUC (delta AUC = 0.03, P<0.001), an increase in relative IDI (24.6%, P-value for IDI <0.001), an increase in NRI (category-free NRI = 0.155, P<0.001), an increase in sensitivity of the model with 7.3% and a decrease in AIC (delta AIC = 199.5). The results of the validation data were similar to the derivation data. The calibration of the diet-containing diabetes risk model was better than that of the risk model without dietary predictors in the validation data. Dietary information improves model performance and predictive ability of noninvasive type 2 diabetes risk model based on classic risk factors. Dietary information may be useful for developing a noninvasive diabetes risk model. PMID:27851788

  18. Predictive Validity of Pressure Ulcer Risk Assessment Tools for Elderly: A Meta-Analysis.

    PubMed

    Park, Seong-Hi; Lee, Young-Shin; Kwon, Young-Mi

    2016-04-01

    Preventing pressure ulcers is one of the most challenging goals existing for today's health care provider. Currently used tools which assess risk of pressure ulcer development rarely evaluate the accuracy of predictability, especially in older adults. The current study aimed at providing a systemic review and meta-analysis of 29 studies using three pressure ulcer risk assessment tools: Braden, Norton, and Waterlow Scales. Overall predictive validities of pressure ulcer risks in the pooled sensitivity and specificity indicated a similar range with a moderate accuracy level in all three scales, while heterogeneity showed more than 80% variability among studies. The studies applying the Braden Scale used five different cut-off points representing the primary cause of heterogeneity. Results indicate that commonly used screening tools for pressure ulcer risk have limitations regarding validity and accuracy for use with older adults due to heterogeneity among studies.

  19. Learning to Predict Post-Hospitalization VTE Risk from EHR Data

    PubMed Central

    Kawaler, Emily; Cobian, Alexander; Peissig, Peggy; Cross, Deanna; Yale, Steve; Craven, Mark

    2012-01-01

    We consider the task of predicting which patients are most at risk for post-hospitalization venothromboembolism (VTE) using information automatically elicited from an EHR. Given a set of cases and controls, we use machine-learning methods to induce models for making these predictions. Our empirical evaluation of this approach offers a number of interesting and important conclusions. We identify several risk factors for VTE that were not previously recognized. We show that machine-learning methods are able to induce models that identify high-risk patients with accuracy that exceeds previously developed scoring models for VTE. Additionally, we show that, even without having prior knowledge about relevant risk factors, we are able to learn accurate models for this task. PMID:23304314

  20. Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review

    PubMed Central

    Tang, Eugene Y. H.; Harrison, Stephanie L.; Errington, Linda; Gordon, Mark F.; Visser, Pieter Jelle; Novak, Gerald; Dufouil, Carole; Brayne, Carol; Robinson, Louise; Launer, Lenore J.; Stephan, Blossom C. M.

    2015-01-01

    Background Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance. Methods Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included. Findings In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model. Interpretation There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction

  1. Developing Risk Prediction Models for Kidney Injury and Assessing Incremental Value for Novel Biomarkers

    PubMed Central

    Kerr, Kathleen F.; Meisner, Allison; Thiessen-Philbrook, Heather; Coca, Steven G.

    2014-01-01

    The field of nephrology is actively involved in developing biomarkers and improving models for predicting patients’ risks of AKI and CKD and their outcomes. However, some important aspects of evaluating biomarkers and risk models are not widely appreciated, and statistical methods are still evolving. This review describes some of the most important statistical concepts for this area of research and identifies common pitfalls. Particular attention is paid to metrics proposed within the last 5 years for quantifying the incremental predictive value of a new biomarker. PMID:24855282

  2. Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest.

    PubMed

    Miao, Fen; Cai, Yun-Peng; Zhang, Yu-Xiao; Li, Ye; Zhang, Yuan-Ting

    2015-01-01

    Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH) often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF), a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in the public MIMIC II clinical database were investigated, with 3,452 deaths occurring within 1-year followups. Forty risk factors including demographics and clinical and laboratory information and antiarrhythmic agents were analyzed as potential predictors of all-cause mortality. RSF was adopted to build a comprehensive survival model and a simplified risk model composed of 14 top risk factors. The built comprehensive model achieved a prediction accuracy of 0.81 measured by c-statistic with 10-fold cross validation. The simplified risk model also achieved a good accuracy of 0.799. Both results outperformed traditional CPH (which achieved a c-statistic of 0.733 for the comprehensive model and 0.718 for the simplified model). Moreover, various factors are observed to have nonlinear impact on cardiac arrhythmias prognosis. As a result, RSF based model which took nonlinearity into account significantly outperformed traditional Cox proportional hazard model and has great potential to be a more effective approach for survival analysis.

  3. Prediction of men at high risk of heart attack and its relevance to pilots.

    PubMed

    Pocock, S J; Shaper, A G; Phillips, A N; Walker, M

    1988-05-01

    In this paper we have extrapolated from data on the general population of middle-aged men and made suggestions for risk prediction and prevention policy in aircrew. As suggested previously, it would be helpful in future if data on the risk of heart attack in pilots could be generated from a central recording system covering both current pilots and those who retire for whatever reason. Indefinite follow-up information on ischaemic events would also be particularly helpful.

  4. Performance of different adiposity measures for predicting cardiovascular risk in adolescents

    PubMed Central

    Zhao, Min; Bovet, Pascal; Ma, Chuanwei; Xi, Bo

    2017-01-01

    This study aims to compare the performance of body mass index (BMI), waist circumference (WC), and waist-to-height-ratio (WHtR) to predict the presence of at least 3 main CV risk factors in US adolescents. A total of 3621 adolescents (boys: 49.9%) aged 12–17 years from the US National Health and Nutrition Examination Survey (1999–2012) were included in this study. Measured CV risk factors included systolic/diastolic blood pressure, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and fasting plasma glucose. The AUC of BMI-z score, WC-z score and WHtR-z score to predict at least three CV risk factors were similar (~0.85), irrespective of criteria used to define abnormal levels of CV risk factors. A 1-SD increase in any of three indices to predict CV risk was also similar for the three adiposity scores. For instance, a 1-SD increase risk in BMI-z score, WC-z score and WHtR-z score was 3.32 (95%CI 2.53–4.36), 3.43 (95%CI 2.64–4.46), and 3.45 (95%CI 2.64–4.52), respectively, in the total population using the International Diabetes Federation definition. In addition, the most efficient WHtR cut-off for screening CV risk was ~0.50 in US adolescents. In summary, BMI, WC and WHtR performed similarly well to predict the presence of at least 3 main CV risk factors among US adolescents. PMID:28262726

  5. A stillbirth calculator: Development and internal validation of a clinical prediction model to quantify stillbirth risk

    PubMed Central

    Tuuli, Methodius G.; Colditz, Graham A.; Macones, George A.; Odibo, Anthony O.

    2017-01-01

    Objective To generate a clinical prediction tool for stillbirth that combines maternal risk factors to provide an evidence based approach for the identification of women who will benefit most from antenatal testing for stillbirth prevention. Design Retrospective cohort study Setting Midwestern United States quaternary referral center Population Singleton pregnancies undergoing second trimester anatomic survey from 1999–2009. Pregnancies with incomplete follow-up were excluded. Methods Candidate predictors were identified from the literature and univariate analysis. Backward stepwise logistic regression with statistical comparison of model discrimination, calibration and clinical performance was used to generate final models for the prediction of stillbirth. Internal validation was performed using bootstrapping with 1,000 repetitions. A stillbirth risk calculator and stillbirth risk score were developed for the prediction of stillbirth at or beyond 32 weeks excluding fetal anomalies and aneuploidy. Statistical and clinical cut-points were identified and the tools compared using the Integrated Discrimination Improvement. Main outcome measures Antepartum stillbirth Results 64,173 women met inclusion criteria. The final stillbirth risk calculator and score included maternal age, black race, nulliparity, body mass index, smoking, chronic hypertension and pre-gestational diabetes. The stillbirth calculator and simple risk score demonstrated modest discrimination but clinically significant performance with no difference in overall performance between the tools [(AUC 0.66 95% CI 0.60–0.72) and (AUC 0.64 95% CI 0.58–0.70), (p = 0.25)]. Conclusion A stillbirth risk score was developed incorporating maternal risk factors easily ascertained during prenatal care to determine an individual woman’s risk for stillbirth and provide an evidenced based approach to the initiation of antenatal testing for the prediction and prevention of stillbirth. PMID:28267756

  6. Evaluating the Framingham hypertension risk prediction model in young adults: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

    PubMed

    Carson, April P; Lewis, Cora E; Jacobs, David R; Peralta, Carmen A; Steffen, Lyn M; Bower, Julie K; Person, Sharina D; Muntner, Paul

    2013-12-01

    A prediction model was developed in the Framingham Heart Study (FHS) to evaluate the short-term risk of hypertension. Our goal was to determine the predictive ability of the FHS hypertension model in a cohort of young adults advancing into middle age and compare it with the predictive ability of prehypertension and individual components of the FHS model. We studied 4388 participants, aged 18 to 30 years without hypertension at baseline, enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, who participated in 2 consecutive examinations occurring 5 years apart between the baseline (1985-1986) and year 25 examination (2010-2011). Weibull regression was used to assess the association of the FHS model overall, individual components of the FHS model, and prehypertension with incident hypertension. During the 25-year follow-up period, 1179 participants developed incident hypertension. The FHS hypertension model (c-index=0.84; 95% confidence interval, 0.83-0.85) performed well in discriminating those who did and did not develop hypertension and was better than prehypertension alone (c-index=0.71; 95% confidence interval, 0.70-0.73). The predicted risk from the FHS hypertension model was systematically lower than the observed hypertension incidence initially (χ(2)=249.4; P<0.001) but demonstrated a good fit after recalibration (χ(2)=14.6; P=0.067). In summary, the FHS model performed better than prehypertension and may be a useful tool for identifying young adults with a high risk for developing hypertension.

  7. Predicting crash risk and identifying crash precursors on Korean expressways using loop detector data.

    PubMed

    Kwak, Ho-Chan; Kho, Seungyoung

    2016-03-01

    In order to improve traffic safety on expressways, it is important to develop proactive safety management strategies with consideration for segment types and traffic flow states because crash mechanisms have some differences by each condition. The primary objective of this study is to develop real-time crash risk prediction models for different segment types and traffic flow states on expressways. The mainline of expressways is divided into basic segment and ramp vicinity, and the traffic flow states are classified into uncongested and congested conditions. Also, Korean expressways have irregular intervals between loop detector stations. Therefore, we investigated on the effect and application of the detector stations at irregular intervals for the crash risk prediction on expressways. The most significant traffic variables were selected by conditional logistic regression analysis which could control confounding factors. Based on the selected traffic variables, separate models to predict crash risk were developed using genetic programming technique. The model estimation results showed that the traffic flow characteristics leading to crashes are differed by segment type and traffic flow state. Especially, the variables related to the intervals between detector stations had a significant influence on crash risk prediction under the uncongested condition. Finally, compared with the single model for all crashes and the logistic models used in previous studies, the proposed models showed higher prediction performance. The results of this study can be applied to develop more effective proactive safety management strategies for different segment types and traffic flow states on expressways with loop detector stations at irregular intervals.

  8. Predictive and prognostic factors in definition of risk groups in endometrial carcinoma.

    PubMed

    Sorbe, Bengt

    2012-01-01

    Background. The aim was to evaluate predictive and prognostic factors in a large consecutive series of endometrial carcinomas and to discuss pre- and postoperative risk groups based on these factors. Material and Methods. In a consecutive series of 4,543 endometrial carcinomas predictive and prognostic factors were analyzed with regard to recurrence rate and survival. The patients were treated with primary surgery and adjuvant radiotherapy. Two preoperative and three postoperative risk groups were defined. DNA ploidy was included in the definitions. Eight predictive or prognostic factors were used in multivariate analyses. Results. The overall recurrence rate of the complete series was 11.4%. Median time to relapse was 19.7 months. In a multivariate logistic regression analysis, FIGO grade, myometrial infiltration, and DNA ploidy were independent and statistically predictive factors with regard to recurrence rate. The 5-year overall survival rate was 73%. Tumor stage was the single most important factor with FIGO grade on the second place. DNA ploidy was also a significant prognostic factor. In the preoperative risk group definitions three factors were used: histology, FIGO grade, and DNA ploidy. Conclusions. DNA ploidy was an important and significant predictive and prognostic factor and should be used both in preoperative and postoperative risk group definitions.

  9. Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

    PubMed

    Al-Sakkaf, A; Jones, G

    2014-05-01

    Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic.

  10. Projecting Risk: The Importance of the HCR-20 Risk Management Scale in Predicting Outcomes with Forensic Patients.

    PubMed

    Vitacco, Michael J; Tabernik, Holly E; Zavodny, Denis; Bailey, Karen; Waggoner, Christina

    2016-03-01

    The present study evaluates data from 116 forensic inpatients who underwent violent risk assessments, which included the Historical, Clinical, Risk-20 (HCR-20), from 2006 to 2013 as part of an opportunity to be conditionally discharged from state forensic facilities. Of the 116 inpatients, 58 were never released, 39 were released and returned to a hospital, and 19 were released and never returned. Results from analyses of variance and multinomial logistic regression found the risk management (R) scale of the HCR-20 successfully predicted group membership in that higher scores were associated with a greater likelihood of not being released from a forensic facility or returning to a forensic facility after release. The results of this study indicate that clinicians should consider community-based risk variables when evaluating forensic patients for potential return to the community. This research demonstrates that clinicians failing to fully consider dynamic risk factors associated with community integration jeopardize the quality and thoroughness of their violence risk assessment with regards to readiness for release. Copyright © 2016 John Wiley & Sons, Ltd.

  11. Predicting pesticide environmental risk in intensive agricultural areas. II: Screening level risk assessment of complex mixtures in surface waters.

    PubMed

    Verro, Roberto; Finizio, Antonio; Otto, Stefan; Vighi, Marco

    2009-01-15

    In a previous article, a procedure for assessing pesticide ecotoxicological risk for surface water was applied to all active ingredients in a pilot basin. This data set has been used to assess the composition of pesticide mixtures that are likely to be present in surface waters as a consequence of pesticide emissions from the crops grown within the basin (maize, soybean, sugar beet, and vineyard). Temporal evolution of the mixture composition has been evaluated as a function of the different contamination patterns (drift and runoff). Ecotoxicological risk has been assessed for the mixtures released by individual crops and from all the relevant crops cultivated in the basin. The different role of drift and runoff, as well as the temporal trends of exposure and risk are compared. Daphnia is the most affected among the three indicator organisms considered, particularly from drift mixtures after insecticide application on vineyard. The highest risk for algae occurs during runoff events in spring. In most risk events, one or a few chemicals are usually responsible for more than 80% of the toxic potency of the mixture. The CA model for predicting mixture response is assumed to be a reliable approach for assessing risk for ecologically relevant pesticide mixtures.

  12. Predicting the risk of endometrial cancer in postmenopausal women presenting with vaginal bleeding: the Norwich DEFAB risk assessment tool

    PubMed Central

    Burbos, N; Musonda, P; Giarenis, I; Shiner, A M; Giamougiannis, P; Morris, E P; Nieto, J J

    2010-01-01

    Background: This study aimed to show the longitudinal use of routinely collected clinical data from history and ultrasound evaluation of the endometrium in developing an algorithm to predict the risk of endometrial carcinoma for postmenopausal women presenting with vaginal bleeding. Methods: This prospective study collected data from 3047 women presenting with postmenopausal bleeding. Data regarding the presence of risk factors for endometrial cancer was collected and univariate and multivariate analyses were performed. Results: Age distribution ranged from 35 to 97 years with a median of 59 years. A total of 149 women (5% of total) were diagnosed with endometrial carcinoma. Women in the endometrial cancer group were significantly more likely to be older, have higher BMI, recurrent episodes of bleeding, diabetes, hypertension, or a previous history of breast cancer. An investigator best model selection approach was used to select the best predictors of cancer, and using logistic regression analysis we created a model, ‘Norwich DEFAB', which is a clinical prediction rule for endometrial cancer. The calculated Norwich DEFAB score can vary from a value of 0 to 9. A Norwich DEFAB value equal to or greater than 3 has a positive predictive value (PPV) of 7.78% and negative predictive value (NPV) of 98.2%, whereas a score equal to or greater than 5 has a PPV of 11.9% and NPV of 97.8%. Conclusion: The combination of clinical information with our investigation tool for women with postmenopausal vaginal bleeding allows the clinician to calculate a predicted risk of endometrial malignancy and prioritise subsequent clinical investigations. PMID:20354525

  13. Trends in risk factors chronic diseases, according of health insurance, Brazil, 2008-2013.

    PubMed

    Malta, Deborah Carvalho; Bernal, Regina Tomie Ivata; Oliveira, Martha

    2015-04-01

    This article aims to compare the trends for risk and protective factors for NCD in the population with and without health insurance. Analysis of temporal trends of the Vigitel phone survey, collected annually in adult population. Were used analyzed the temporal series of variables referent to risk and protective factors for NCD, from 2008 to 2013. Variables were compared according to the possession or not of health insurance using simple linear regression model. There was a reduction in the prevalence of smoking in the population with and without health insurance, in 0.72% and 0,69% per year respectively. The consumption of fruits and vegetables grew 0,8% and 0.72% per year respectively among the population with and without health insurance. Physical activity in leisure time increased 1.17% and 1.01% per year among population with and without health insurance. Excess weight increased in 1.03% and obesity in 0.74% p.y in the population with health insurance and 1.53% and 0.95% p.y without health insurance. Mammography increased 2.4% in the population without health insurance. Vigitel monitoring showed improvement in the indicators in the population with and without health insurance.

  14. Schistosomiasis in a low prevalence area: incomplete urbanization increasing risk of infection in Paracambi, RJ, Brazil.

    PubMed

    Soares, M S; Barreto, M G; da Silva, C L; Pereira, J B; Moza, P G; Rey, L; Calçado, M S; Lustoza, A; Maspero, R

    1995-01-01

    The risk of schistosomiasis infection and heavy infection in the locality of Sabugo was evaluated in relation to housing in areas with different urbanization development and to residential supply with snail-infested water. Critical sanitary conditions were found in areas of incomplete urbanization, where healthy water supply sources were scarce, and draining of sewage, without previous treatment, was made directly to the water-bodies used for domestic and leisure activities, despite being Biomphalaria tenagophila snail breeding-places. Stool examinations (Kato-Katz and Lutz methods) showed prevalence of 2.9% mean intensity of 79 eggs per gram of stool and 47% of positive cases presenting intense infection. The use of snail-contaminated water for domestic purposes was considered a risk factor for infection. It is concluded that incomplete urbanization would facilitate transmission, probably enhancing the intensity of infection and that a low prevalence could hide a highly focal transmission. The relevance of these facts upon the efficiency of epidemiologic study methods and disease control planning are then discussed.

  15. Predictive risk mapping of West Nile virus (WNV) infection in Saskatchewan horses.

    PubMed

    Epp, Tasha Y; Waldner, Cheryl; Berke, Olaf

    2011-07-01

    The objective of this study was to develop a model using equine data from geographically limited surveillance locations to predict risk categories for West Nile virus (WNV) infection in horses in all geographic locations across the province of Saskatchewan. The province was divided geographically into low-, medium-, or high-risk categories for WNV, based on available serology information from 923 horses obtained through 4 studies of WNV infection in horse populations in Saskatchewan. Discriminant analysis was used to build models using the observed risk of WNV in horses and geographic division-specific environmental data as well as to predict the risk category for all areas, including those beyond the surveillance zones. High-risk areas were indicated by relatively lower rainfall, higher temperatures, and a lower percentage of area covered in trees, water, and wetland. These conditions were most often identified in the southwest corner of the province. Environmental conditions can be used to identify those areas that are at highest risk for WNV. Public health managers could use prediction maps, which are based on animal or human information and developed from annual early season meteorological information, to guide ongoing decisions about when and where to focus intervention strategies for WNV.

  16. Battered Women's Perceptions of Risk Versus Risk Factors and Instruments in Predicting Repeat Reassault

    ERIC Educational Resources Information Center

    Heckert, D. Alex; Gondolf, Edward W.

    2004-01-01

    This study partially replicates and expands on a previous study that showed women's perceptions of risk to be a strong predictor of reassault among batterers. The current study employed a larger and multisite sample, a longer follow-up period of 15 months, and multiple outcomes including "repeated reassault" (n = 499). According to the multinomial…

  17. PREDICTING RISKS OF UNCHARACTERISTIC WILDFIRES: APPLICATION OF THE RISK ASSESSMENT PROCESS

    EPA Science Inventory

    The U.S. Forest Service is struggling with a legacy of over 100 years of fire suppression on the country's national forest lands and an increasing occurrence of uncharacteristically large, intense wildfires. This paper reviews the risk assessment process and describes how it can...

  18. Retinopathy of prematurity: A comprehensive risk analysis for prevention and prediction of disease

    PubMed Central

    Owen, Leah A.; Morrison, Margaux A.; Hoffman, Robert O.; Yoder, Bradley A.; DeAngelis, Margaret M.

    2017-01-01

    Background Retinopathy of prematurity (ROP) is a blinding morbidity of preterm infants. Our current screening criteria have remained unchanged since their inception and lack the ability to identify those at greatest risk. Objectives We sought to comprehensively analyze numerous proposed maternal, infant, and environmental ROP risk variables in a robustly phenotyped population using logistic regression to determine the most predictive model for ROP development and severity. We further sought to determine the statistical interaction between significant ROP risk variables, which has not previously been done in the field of ROP. We hypothesize that our comprehensive analysis will allow for better identification of risk variables that independently correlate with ROP disease. Going forward, this may allow for improved infant risk stratification along a time continuum from prenatal to postnatal development, making prevention more feasible. Methods We performed a retrospective cohort analysis of preterm infants referred for ROP screening in one neonatal intensive care unit from 2010–2015. The primary outcome measure was presence of ROP. Secondary outcome measures were ROP requiring treatment and severe ROP not clearly meeting current treatment criteria. Univariate, stepwise regression and statistical interaction analyses of 57 proposed ROP risk variables was performed to identify variables which were significantly associated with each outcome measure. Results We identified 457 infants meeting our inclusion criteria. Within this cohort, numerous factors showed a significant individual association with our ROP outcome measures; however, stepwise regression analysis found the most predictive model for overall ROP risk included estimated gestational age, birth weight, the need for any surgery, and maternal magnesium prophylaxis. The corresponding Area Under the Curve (AUC) for this model was 0.8641, while the traditional model of gestational age and birth weight predicted

  19. Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria

    PubMed Central

    Ekpo, Uwem F; Mafiana, Chiedu F; Adeofun, Clement O; Solarin, Adewale RT; Idowu, Adewumi B

    2008-01-01

    Background The control of urinary schistosomiasis in Ogun State, Nigeria remains inert due to lack of reliable data on the geographical distribution of the disease and the population at risk. To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria. Methods Infection data used were derived from carefully validated morbidity questionnaires among primary school children in 2001–2002, in which school children were asked among other questions if they have experienced "blood in urine" or urinary schistosomiasis. The infection data from 1,092 schools together with remotely sensed environmental data such as rainfall, vegetation, temperature, soil-types, altitude and land cover were analysis using binary logistic regression models to identify environmental features that influence the spatial distribution of the disease. The final regression equations were then used in Arc View 3.2a GIS software to generate predictive risk maps of the distribution of the disease and population at risk in the state. Results Logistic regression analysis shows that the only significant environmental variable in predicting the presence and absence of urinary schistosomiasis in any area of the State was Land Surface Temperature (LST) (B = 0.308, p = 0.013). While LST (B = -0.478, p = 0.035), rainfall (B = -0.006, p = 0.0005), ferric luvisols (B = 0.539, p = 0.274), dystric nitosols (B = 0.133, p = 0.769) and pellic vertisols (B = 1.386, p = 0.008) soils types were the final variables in the model for predicting the probability of an area having an infection prevalence equivalent to or more than 50%. The two predictive risk maps suggest that urinary schistosomiasis is widely distributed and occurring in all the Local Government Areas (LGAs) in State. The high-risk

  20. Fracture risk prediction using BMD and clinical risk factors in early postmenopausal women: sensitivity of the WHO FRAX tool.

    PubMed

    Trémollieres, Florence A; Pouillès, Jean-Michel; Drewniak, Nicolas; Laparra, Jacques; Ribot, Claude A; Dargent-Molina, Patricia

    2010-05-01

    The aim of this prospective study was (1) to identify significant and independent clinical risk factors (CRFs) for major osteoporotic (OP) fracture among peri- and early postmenopausal women, (2) to assess, in this population, the discriminatory capacity of FRAX and bone mineral density (BMD) for the identification of women at high risk of fracture, and (3) to assess whether adding risk factors to either FRAX or BMD would improve discriminatory capacity. The study population included 2651 peri- and early postmenopausal women [mean age (+/- SD): 54 +/- 4 years] with a mean follow-up period of 13.4 years (+/-1.4 years). At baseline, a large set of CRFs was recorded, and vertebral BMD was measured (Lunar, DPX) in all women. Femoral neck BMD also was measured in 1399 women in addition to spine BMD. Women with current or past OP treatment for more than 3 months at baseline (n = 454) were excluded from the analyses. Over the follow-up period, 415 women sustained a first low-energy fracture, including 145 major OP fractures (108 wrist, 44 spine, 20 proximal humerus, and 13 hip). In Cox multivariate regression models, only 3 CRFs were significant predictors of a major OP fracture independent of BMD and age: a personal history of fracture, three or more pregnancies, and current postmenopausal hormone therapy. In the subsample of women who had a hip BMD measurement and who were not receiving OP therapy (including hormone-replacement therapy) at baseline, mean FRAX value was 3.8% (+/-2.4%). The overall discriminative value for fracture, as measured by the area under the Receiver Operating Characteristic (ROC) curve (AUC), was equal to 0.63 [95% confidence interval (CI) 0.56-0.69] and 0.66 (95% CI 0.60-0.73), respectively, for FRAX and hip BMD. Sensitivity of both tools was low (ie, around 50% for 30% of the women classified as the highest risk). Adding parity to the predictive model including FRAX or using a simple risk score based on the best predictive model in our

  1. Space Weather Influence on Power Systems: Prediction, Risk Analysis, and Modeling

    NASA Astrophysics Data System (ADS)

    Yatsenko, Vitaliy

    2016-04-01

    This report concentrates on dynamic probabilistic risk analysis of optical elements for complex characterization of damages using physical model of solid state lasers and predictable level of ionizing radiation and space weather. The following main subjects will be covered by our report: (a) solid-state laser model; (b) mathematical models for dynamic probabilistic risk assessment; and (c) software for modeling and prediction of ionizing radiation. A probabilistic risk assessment method for solid-state lasers is presented with consideration of some deterministic and stochastic factors. Probabilistic risk assessment is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in solid-state lasers for the purpose of cost-e®ectively improving their safety and performance. This method based on the Conditional Value-at-Risk measure (CVaR) and the expected loss exceeding Value-at-Risk (VaR). We propose to use a new dynamical-information approach for radiation damage risk assessment of laser elements by cosmic radiation. Our approach includes the following steps: laser modeling, modeling of ionizing radiation in°uences on laser elements, probabilistic risk assessment methods, and risk minimization. For computer simulation of damage processes at microscopic and macroscopic levels the following methods are used: () statistical; (b) dynamical; (c) optimization; (d) acceleration modeling, and (e) mathematical modeling of laser functioning. Mathematical models of space ionizing radiation in°uence on laser elements were developed for risk assessment in laser safety analysis. This is a so-called `black box' or `input-output' models, which seeks only to reproduce the behaviour of the system's output in response to changes in its inputs. The model inputs are radiation in°uences on laser systems and output parameters are dynamical characteristics of the solid laser. Algorithms and software for optimal structure and parameters of

  2. EVALUATING RISK-PREDICTION MODELS USING DATA FROM ELECTRONIC HEALTH RECORDS

    PubMed Central

    WANG, LE; SHAW, PAMELA A.; MATHELIER, HANSIE M.; KIMMEL, STEPHEN E.; FRENCH, BENJAMIN

    2016-01-01

    The availability of data from electronic health records facilitates the development and evaluation of risk-prediction models, but estimation of prediction accuracy could be limited by outcome misclassification, which can arise if events are not captured. We evaluate the robustness of prediction accuracy summaries, obtained from receiver operating characteristic curves and risk-reclassification methods, if events are not captured (i.e., “false negatives”). We derive estimators for sensitivity and specificity if misclassification is independent of marker values. In simulation studies, we quantify the potential for bias in prediction accuracy summaries if misclassification depends on marker values. We compare the accuracy of alternative prognostic models for 30-day all-cause hospital readmission among 4548 patients discharged from the University of Pennsylvania Health System with a primary diagnosis of heart failure. Simulation studies indicate that if misclassification depends on marker values, then the estimated accuracy improvement is also biased, but the direction of the bias depends on the direction of the association between markers and the probability of misclassification. In our application, 29% of the 1143 readmitted patients were readmitted to a hospital elsewhere in Pennsylvania, which reduced prediction accuracy. Outcome misclassification can result in erroneous conclusions regarding the accuracy of risk-prediction models. PMID:27158296

  3. Predicting Risk-Mitigating Behaviors From Indecisiveness and Trait Anxiety: Two Cognitive Pathways to Task Avoidance.

    PubMed

    McNeill, Ilona M; Dunlop, Patrick D; Skinner, Timothy C; Morrison, David L

    2016-02-01

    Past research suggests that indecisiveness and trait anxiety may both decrease the likelihood of performing risk-mitigating preparatory behaviors (e.g., preparing for natural hazards) and suggests two cognitive processes (perceived control and worrying) as potential mediators. However, no single study to date has examined the influence of these traits and processes together. Examining them simultaneously is necessary to gain an integrated understanding of their relationship with risk-mitigating behaviors. We therefore examined these traits and mediators in relation to wildfire preparedness in a two-wave field study among residents of wildfire-prone areas in Western Australia (total N = 223). Structural equation modeling results showed that indecisiveness uniquely predicted preparedness, with higher indecisiveness predicting lower preparedness. This relationship was fully mediated by perceived control over wildfire-related outcomes. Trait anxiety did not uniquely predict preparedness or perceived control, but it did uniquely predict worry, with higher trait anxiety predicting more worrying. Also, worry trended toward uniquely predicting preparedness, albeit in an unpredicted positive direction. This shows how the lack of performing risk-mitigating behaviors can result from distinct cognitive processes that are linked to distinct personality traits. It also highlights how simultaneous examination of multiple pathways to behavior creates a fuller understanding of its antecedents.

  4. Predicting fractures in an international cohort using risk factor algorithms without BMD.

    PubMed

    Sambrook, Philip N; Flahive, Julie; Hooven, Fred H; Boonen, Steven; Chapurlat, Roland; Lindsay, Robert; Nguyen, Tuan V; Díez-Perez, Adolfo; Pfeilschifter, Johannes; Greenspan, Susan L; Hosmer, David; Netelenbos, J Coen; Adachi, Jonathan D; Watts, Nelson B; Cooper, Cyrus; Roux, Christian; Rossini, Maurizio; Siris, Ethel S; Silverman, Stuart; Saag, Kenneth G; Compston, Juliet E; LaCroix, Andrea; Gehlbach, Stephen

    2011-11-01

    Clinical risk factors are associated with increased probability of fracture in postmenopausal women. We sought to compare prediction models using self-reported clinical risk factors, excluding BMD, to predict incident fracture among postmenopausal women. The GLOW study enrolled women aged 55 years or older from 723 primary-care practices in 10 countries. The population comprised 19,586 women aged 60 years or older who were not receiving antiosteoporosis medication and were followed annually for 2 years. Self-administered questionnaires were used to collect data on characteristics, fracture risk factors, previous fractures, and health status. The main outcome measure compares the C index for models using the WHO Fracture Risk (FRAX), the Garvan Fracture Risk Calculator (FRC), and a simple model using age and prior fracture. Over 2 years, 880 women reported incident fractures including 69 hip fractures, 468 "major fractures" (as defined by FRAX), and 583 "osteoporotic fractures" (as defined by FRC). Using baseline clinical risk factors, both FRAX and FRC showed a moderate ability to correctly order hip fracture times (C index for hip fracture 0.78 and 0.76, respectively). C indices for "major" and "osteoporotic" fractures showed lower values, at 0.61 and 0.64. Neither algorithm was better than the model based on age + fracture history alone (C index for hip fracture 0.78). In conclusion, estimation of fracture risk in an international primary-care population of postmenopausal women can be made using clinical risk factors alone without BMD. However, more sophisticated models incorporating multiple clinical risk factors including falls were not superior to more parsimonious models in predicting future fracture in this population.

  5. Factors Predicting Adherence to Risk Management Behaviors of Women at Increased Risk for Developing Lymphedema

    PubMed Central

    Sherman, Kerry A.; Miller, Suzanne M.; Roussi, Pagona; Taylor, Alan

    2014-01-01

    Purpose Lymphedema affects 20-30% of women following breast cancer treatment. However, even when women are informed, they do not necessarily adhere to recommended lymphedema self-management regimens. Utilizing the Cognitive-Social Health Information Processing framework, we assessed cognitive and emotional factors influencing adherence to lymphedema risk management. Methods Women with breast cancer who had undergone breast and lymph node surgery were recruited through the Fox Chase Cancer Centre breast clinic. Participants (N=103) completed measures of lymphedema-related perceived risk, beliefs and expectancies, distress, self-regulatory ability to manage distress, knowledge, and adherence to risk management behaviors. They then received the American Cancer Society publication “Lymphedema: What Every Woman with Breast Cancer Should Know”. Cognitive and affective variables were reassessed at 6- and 12-months post-baseline. Results Maximum likelihood multilevel model analyses indicated that overall adherence increased over time, with significant differences between baseline and 6- and 12- month assessments. Adherence to wearing gloves was significantly lower than that for all other behaviors except electric razor use. Distress significantly decreased, and knowledge significantly increased, over time. Greater knowledge, higher self-efficacy to enact behaviors, lower distress, and higher self-regulatory ability to manage distress were associated with increased adherence. Conclusions Women who understand lymphedema risk management and feel confident in managing this risk are more likely to adhere to recommended strategies. These factors should be rigorously assessed as part of routine care to ensure that women have the self-efficacy to seek treatment and the self-regulatory skills to manage distress, which may undermine attempts to seek medical assistance. PMID:24970542

  6. Incidence, risk factors and risk prediction of hospital-acquired suspected adverse drug reactions: a prospective cohort of Ugandan inpatients

    PubMed Central

    Kiguba, Ronald; Karamagi, Charles; Bird, Sheila M

    2017-01-01

    Objectives To determine the incidence and risk factors of hospital-acquired suspected adverse drug reactions (ADRs) among Ugandan inpatients. We also constructed risk scores to predict and qualitatively assess for peculiarities between low-risk and high-risk ADR patients. Methods Prospective cohort of consented adults admitted on medical and gynaecological wards of the 1790-bed Mulago National Referral Hospital. Hospital-acquired suspected ADRs were dichotomised as possible (possible/probable/definite) or not and probable (probable/definite) or not, using the Naranjo scale. Risk scores were generated from coefficients of ADR risk-factor logistic regression models. Results The incidence of possible hospital-acquired suspected ADRs was 25% (194/762, 95% CI: 22% to 29%): 44% (85/194) experienced serious possible ADRs. The risk of probable ADRs was 11% (87/762, 95% CI 9% to 14%): 46% (40/87) had serious probable ADRs. Antibacterials-only (51/194), uterotonics-only (21/194), cardiovascular drugs-only (16/194), antimalarials-only (12/194) and analgesics-only (10/194) were the most frequently implicated. Treatment with six or more conventional medicines during hospitalisation (OR=2.31, 95% CI 1.29 to 4.15) and self-reported herbal medicine use during the 4 weeks preadmission (OR=1.96, 95% CI 1.22 to 3.13) were the risk factors for probable hospital-acquired ADRs. Risk factors for possible hospital-acquired ADRs were: treatment with six or more conventional medicines (OR=2.72, 95% CI 1.79 to 4.13), herbal medicine use during the 4 weeks preadmission (OR=1.68, 95% CI 1.16 to 2.43), prior 3 months hospitalisation (OR=1.57, 95% CI 1.09 to 2.26) and being on gynaecological ward (OR=2.16, 95% CI 1.36 to 3.44). More drug classes were implicated among high-risk ADR-patients, with cardiovascular drugs being the most frequently linked to possible ADRs. Conclusions The risk of hospital-acquired suspected ADRs was higher with preadmission herbal medicine use and treatment with

  7. Admission Risk Score to Predict Inpatient Pediatric Mortality at Four Public Hospitals in Uganda

    PubMed Central

    Mpimbaza, Arthur; Sears, David; Sserwanga, Asadu; Kigozi, Ruth; Rubahika, Denis; Nadler, Adam; Yeka, Adoke; Dorsey, Grant

    2015-01-01

    Mortality rates among hospitalized children in many government hospitals in sub-Saharan Africa are high. Pediatric emergency services in these hospitals are often sub-optimal. Timely recognition of critically ill children on arrival is key to improving service delivery. We present a simple risk score to predict inpatient mortality among hospitalized children. Between April 2010 and June 2011, the Uganda Malaria Surveillance Project (UMSP), in collaboration with the National Malaria Control Program (NMCP), set up an enhanced sentinel site malaria surveillance program for children hospitalized at four public hospitals in different districts: Tororo, Apac, Jinja and Mubende. Clinical data collected through March 2013, representing 50249 admissions were used to develop a mortality risk score (derivation data set). One year of data collected subsequently from the same hospitals, representing 20406 admissions, were used to prospectively validate the performance of the risk score (validation data set). Using a backward selection approach, 13 out of 25 clinical parameters recognizable on initial presentation, were selected for inclusion in a final logistic regression prediction model. The presence of individual parameters was awarded a score of either 1 or 2 based on regression coefficients. For each individual patient, a composite risk score was generated. The risk score was further categorized into three categories; low, medium, and high. Patient characteristics were comparable in both data sets. Measures of performance for the risk score included the receiver operating characteristics curves and the area under the curve (AUC), both demonstrating good and comparable ability to predict deathusing both the derivation (AUC =0.76) and validation dataset (AUC =0.74). Using the derivation and validation datasets, the mortality rates in each risk category were as follows: low risk (0.8% vs. 0.7%), moderate risk (3.5% vs. 3.2%), and high risk (16.5% vs. 12.6%), respectively. Our

  8. Deficits in Top-Down Sensory Prediction in Infants At Risk due to Premature Birth.

    PubMed

    Emberson, Lauren L; Boldin, Alex M; Riccio, Julie E; Guillet, Ronnie; Aslin, Richard N

    2017-02-06

    A prominent theoretical view is that the brain is inherently predictive [1, 2] and that prediction helps drive the engine of development [3, 4]. Although infants exhibit neural signatures of top-down sensory prediction [5, 6], in order to establish that prediction supports development, it must be established that deficits in early prediction abilities alter trajectories. We investigated prediction in infants born prematurely, a leading cause of neuro-cognitive impairment worldwide [7]. Prematurity, independent of medical complications, leads to developmental disturbances [8-12] and a broad range of developmental delays [13-17]. Is an alteration in early prediction abilities the common cause? Using functional near-infrared spectroscopy (fNIRS), we measured top-down sensory prediction in preterm infants (born <33 weeks gestation) before infants exhibited clinically identifiable developmental delays (6 months corrected age). Whereas preterm infants had typical neural responses to presented visual stimuli, they exhibited altered neural responses to predicted visual stimuli. Importantly, a separate behavioral control confirmed that preterm infants detect pattern violations at the same rate as full-terms, establishing selectivity of this response to top-down predictions (e.g., not in learning an audiovisual association). These findings suggest that top-down sensory prediction plays a crucial role in development and that deficits in this ability may be the reason why preterm infants experience altered developmental trajectories and are at risk for poor developmental outcomes. Moreover, this work presents an opportunity for establishing a neuro-biomarker for early identification of infants at risk and could guide early intervention regimens.

  9. A Comprehensive Index for Predicting Risk of Anemia from Patients' Diagnoses.

    PubMed

    Tuck, Matthew G; Alemi, Farrokh; Shortle, John F; Avramovic, Sanj; Hesdorffer, Charles

    2017-03-01

    This article demonstrates how time-dependent, interacting, and repeating risk factors can be used to create more accurate predictive medicine. In particular, we show how emergence of anemia can be predicted from medical history within electronic health records. We used the Veterans Affairs Informatics and Computing Infrastructure database to examine a retrospective cohort of 9,738,838 veterans over an 11-year period. Using International Clinical Diagnoses Version 9 codes organized into 25 major diagnostic categories, we measured progression of disease by examining changes in risk over time, interactions in risk of combination of diseases, and elevated risk associated with repeated hospitalization for the same diagnostic category. The maximum risk associated with each diagnostic category was used to predict anemia. The accuracy of the model was assessed using a validation cohort. Age and several diagnostic categories significantly contributed to the prediction of anemia. The largest contributors were health status ([Formula: see text] = -1075, t = -92, p < 0.000), diseases of the endocrine ([Formula: see text] = -1046, t = -87, p < 0.000), hepatobiliary ([Formula: see text] = -1043, t = -72, p < 0.000), kidney ([Formula: see text] = -1125, t = -111, p < 0.000), and respiratory systems ([Formula: see text] = -1151, t = -89, p < 0.000). The AUC for the additive model was 0.751 (confidence interval 74.95%-75.26%). The magnitude of AUC suggests that the model may assist clinicians in determining which patients are likely to develop anemia. The procedures used for examining changes in risk factors over time may also be helpful in other predictive medicine projects.

  10. Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.

    PubMed

    Green, Andrew R; Soria, D; Powe, D G; Nolan, C C; Aleskandarany, M; Szász, M A; Tőkés, A M; Ball, G R; Garibaldi, J M; Rakha, E A; Kulka, J; Ellis, I O

    2016-05-01

    The Nottingham prognostic index plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification for breast cancer superior to the traditional NPI. This study aimed to determine prognostic capability of the NPI+ in predicting risk of development of distant disease. A well-characterised series of 1073 primary early-stage BC cases treated in Nottingham and 251 cases from Budapest were immunohistochemically assessed for cytokeratin (Ck)5/6, Ck18, EGFR, oestrogen receptor (ER), progesterone receptor, HER2, HER3, HER4, Mucin 1 and p53 expression. NPI+ biological class and prognostic scores were assigned using individual algorithms for each biological class incorporating clinicopathologic parameters and investigated in terms of prediction of distant metastases-free survival (MFS). The NPI+ identified distinct prognostic groups (PG) within each molecular class which were predictive of MFS providing improved patient outcome stratification superior to the traditional NPI. NPI+ PGs, between series, were comparable in predicting patient outcome between series in luminal A, basal p53 altered and HER2+/ER+ (p > 0.01) tumours. The low-risk groups were similarly validated in luminal B, luminal N, basal p53 normal tumours (p > 0.01). Due to small patient numbers the remaining PGs could not be validated. NPI+ was additionally able to predict a higher risk of metastases at certain distant sites. This study may indicate the NPI+ as a useful tool in predicting the risk of metastases. The NPI+ provides accurate risk stratification allowing improved individualised clinical decision making for breast cancer.

  11. High Susceptibility to Cry1Ac and Low Resistance Allele Frequency Reduce the Risk of Resistance of Helicoverpa armigera to Bt Soybean in Brazil

    PubMed Central

    Bacalhau, Fabiana B.; Amado, Douglas; Carvalho, Renato A.; Martinelli, Samuel; Head, Graham P.; Omoto, Celso

    2016-01-01

    The Old World bollworm, Helicoverpa armigera (Hübner), was recently introduced into Brazil, where it has caused extensive damage to cotton and soybean crops. MON 87701 × MON 89788 soybean, which expresses the Bt protein Cry1Ac, was recently deployed in Brazil, providing high levels of control against H. armigera. To assess the risk of resistance to the Cry1Ac protein expressed by MON 87701 × MON 89788 soybean in Brazil, we conducted studies to evaluate the baseline susceptibility of H. armigera to Cry1Ac, in planta efficacy including the assessment of the high-dose criterion, and the initial resistance allele frequency based on an F2 screen. The mean Cry1Ac lethal concentration (LC50) ranged from 0.11 to 1.82 μg·mL−1 of diet among all H. armigera field populations collected from crop seasons 2013/14 to 2014/15, which indicated about 16.5-fold variation. MON 87701 × MON 89788 soybean exhibited a high level of efficacy against H. armigera and most likely met the high dose criterion against this target species in leaf tissue dilution bioassays up to 50 times. A total of 212 F2 family lines of H. armigera were established from field collections sampled from seven locations across Brazil and were screened for the presence of MON 87701 × MON 89788 soybean resistance alleles. None of the 212 families survived on MON 87701 × MON 89788 soybean leaf tissue (estimated allele frequency = 0.0011). The responses of H. armigera to Cry1Ac protein, high susceptibility to MON 87701 × MON 89788 soybean, and low frequency of resistance alleles across the main soybean-producing regions support the assumptions of a high-dose/refuge strategy. However, maintenance of reasonable compliance with the refuge recommendation will be essential to delay the evolution of resistance in H. armigera to MON 87701 × MON 89788 soybean in Brazil. PMID:27532632

  12. High Susceptibility to Cry1Ac and Low Resistance Allele Frequency Reduce the Risk of Resistance of Helicoverpa armigers to Bt Soybean in Brazil.

    PubMed

    Dourado, Patrick M; Bacalhau, Fabiana B; Amado, Douglas; Carvalho, Renato A; Martinelli, Samuel; Head, Graham P; Omoto, Celso

    2016-01-01

    The Old World bollworm, Helicoverpa armigera (Hübner), was recently introduced into Brazil, where it has caused extensive damage to cotton and soybean crops. MON 87701 × MON 89788 soybean, which expresses the Bt protein Cry1Ac, was recently deployed in Brazil, providing high levels of control against H. armigera. To assess the risk of resistance to the Cry1Ac protein expressed by MON 87701 × MON 89788 soybean in Brazil, we conducted studies to evaluate the baseline susceptibility of H. armigera to Cry1Ac, in planta efficacy including the assessment of the high-dose criterion, and the initial resistance allele frequency based on an F2 screen. The mean Cry1Ac lethal concentration (LC50) ranged from 0.11 to 1.82 μg·mL-1 of diet among all H. armigera field populations collected from crop seasons 2013/14 to 2014/15, which indicated about 16.5-fold variation. MON 87701 × MON 89788 soybean exhibited a high level of efficacy against H. armigera and most likely met the high dose criterion against this target species in leaf tissue dilution bioassays up to 50 times. A total of 212 F2 family lines of H. armigera were established from field collections sampled from seven locations across Brazil and were screened for the presence of MON 87701 × MON 89788 soybean resistance alleles. None of the 212 families survived on MON 87701 × MON 89788 soybean leaf tissue (estimated allele frequency = 0.0011). The responses of H. armigera to Cry1Ac protein, high susceptibility to MON 87701 × MON 89788 soybean, and low frequency of resistance alleles across the main soybean-producing regions support the assumptions of a high-dose/refuge strategy. However, maintenance of reasonable compliance with the refuge recommendation will be essential to delay the evolution of resistance in H. armigera to MON 87701 × MON 89788 soybean in Brazil.

  13. The Predictive Properties of Dynamic Sex Offender Risk Assessment Instruments: A Meta-Analysis.

    PubMed

    van den Berg, Jan Willem; Smid, Wineke; Schepers, Klaartje; Wever, Edwin; van Beek, Daan; Janssen, Erick; Gijs, Luk

    2017-04-03

    This meta-analysis is the first to our knowledge to evaluate the predictive properties of dynamic sex offender risk assessment instruments, which are designed to assess factors associated with recidivism that are amenable to change. Based on 52 studies (N = 13,446), we found that dynamic risk assessment instruments have small-to-moderate predictive properties, with Cohen's d ranging between 0.71 for sexual recidivism (41 studies, 22 unique samples, N = 5,699) and 0.43 for violent (including sexual) recidivism (27 studies, 14 unique samples, N = 10,368). Incremental predictive validity of dynamic over static risk assessment instruments was significant but modest; Cox hazard ratios varied between 1.08 for sexual recidivism (19 studies, 13 unique samples, N = 3,747) and 1.05 for any recidivism (11 studies, 8 unique samples, N = 2,511). Cox hazard ratios for the predictive validity of change scores on dynamic risk assessment instruments, controlling for static and initial dynamic scores, varied between 0.91 for sexual recidivism (6 studies, 6 unique samples, n = 1,980) and 0.95 for any recidivism (3 studies, 3 unique samples, n = 1,172). These findings indicate that dynamic risk assessment instruments can, in terms of Andrews and Bonta's (2010) risk and need principles, be a useful tool for improving sex offender treatment. They have the potential to contribute to the selection of appropriate, more individually tailored treatment approaches (focusing on individually relevant criminogenic need factors) and can assist in the evaluation of treatment effects. Considering this, further development of dynamic risk assessment instruments is warranted. (PsycINFO Database Record

  14. Risk factors assessment and risk prediction models in lung cancer screening candidates

    PubMed Central

    Wachuła, Ewa; Szabłowska-Siwik, Sylwia; Boratyn-Nowicka, Agnieszka; Czyżewski, Damian

    2016-01-01

    From February 2015, low-dose computed tomography (LDCT) screening entered the armamentarium of diagnostic tools broadly available to individuals at high-risk of developing lung cancer. While a huge number of pulmonary nodules are identified, only a small fraction turns out to be early lung cancers. The majority of them constitute a variety of benign lesions. Although it entails a burden of the diagnostic work-up, the undisputable benefit emerges from: (I) lung cancer diagnosis at earlier stages (stage shift); (II) additional findings enabling the implementation of a preventive action beyond the realm of thoracic oncology. This review presents how to utilize the risk factors from distinct categories such as epidemiology, radiology and biomarkers to target the fraction of population, which may benefit most from the introduced screening modality. PMID:27195269

  15. Predictive Mapping of Human Risk for West Nile Virus (WNV) Based on Environmental and Socioeconomic Factors

    PubMed Central

    Rochlin, Ilia; Turbow, David; Gomez, Frank; Ninivaggi, Dominick V.; Campbell, Scott R.

    2011-01-01

    A West Nile virus (WNV) human risk map was developed for Suffolk County, New York utilizing a case-control approach to explore the association between the risk of vector-borne WNV and habitat, landscape, virus activity, and socioeconomic variables derived from publically available datasets. Results of logistic regression modeling for the time period between 2000 and 2004 revealed that higher proportion of population with college education, increased habitat fragmentation, and proximity to WNV positive mosquito pools were strongly associated with WNV human risk. Similar to previous investigations from north-central US, this study identified middle class suburban neighborhoods as the areas with the highest WNV human risk. These results contrast with similar studies from the southern and western US, where the highest WNV risk was associated with low income areas. This discrepancy may be due to regional differences in vector ecology, urban environment, or human behavior. Geographic Information Systems (GIS) analytical tools were used to integrate the risk factors in the 2000–2004 logistic regression model generating WNV human risk map. In 2005–2010, 41 out of 46 (89%) of WNV human cases occurred either inside of (30 cases) or in close proximity (11 cases) to the WNV high risk areas predicted by the 2000–2004 model. The novel approach employed by this study may be implemented by other municipal, local, or state public health agencies to improve geographic risk estimates for vector-borne diseases based on a small number of acute human cases. PMID:21853103

  16. Predictive mapping of human risk for West Nile virus (WNV) based on environmental and socioeconomic factors.

    PubMed

    Rochlin, Ilia; Turbow, David; Gomez, Frank; Ninivaggi, Dominick V; Campbell, Scott R

    2011-01-01

    A West Nile virus (WNV) human risk map was developed for Suffolk County, New York utilizing a case-control approach to explore the association between the risk of vector-borne WNV and habitat, landscape, virus activity, and socioeconomic variables derived from publically available datasets. Results of logistic regression modeling for the time period between 2000 and 2004 revealed that higher proportion of population with college education, increased habitat fragmentation, and proximity to WNV positive mosquito pools were strongly associated with WNV human risk. Similar to previous investigations from north-central US, this study identified middle class suburban neighborhoods as the areas with the highest WNV human risk. These results contrast with similar studies from the southern and western US, where the highest WNV risk was associated with low income areas. This discrepancy may be due to regional differences in vector ecology, urban environment, or human behavior. Geographic Information Systems (GIS) analytical tools were used to integrate the risk factors in the 2000-2004 logistic regression model generating WNV human risk map. In 2005-2010, 41 out of 46 (89%) of WNV human cases occurred either inside of (30 cases) or in close proximity (11 cases) to the WNV high risk areas predicted by the 2000-2004 model. The novel approach employed by this study may be implemented by other municipal, local, or state public health agencies to improve geographic risk estimates for vector-borne diseases based on a small number of acute human cases.

  17. Simple risk factors to predict urgent endoscopy in nonvariceal upper gastrointestinal bleeding pre-endoscopically

    PubMed Central

    Wang, Jianzong; Hu, Duanming; Tang, Wen; Hu, Chuanyin; Lu, Qin; Li, Juan; Zhu, Jianhong; Xu, Liming; Sui, Zhenyu; Qian, Mingjie; Wang, Shaofeng; Yin, Guojian

    2016-01-01

    Abstract The goal of this study is to evaluate how to predict high-risk nonvariceal upper gastrointestinal bleeding (NVUGIB) pre-endoscopically. A total of 569 NVUGIB patients between Match 2011 and January 2015 were retrospectively studied. The clinical characteristics and laboratory data were statistically analyzed. The severity of NVUGIB was based on high-risk NVUGIB (Forrest I–IIb), and low-risk NVUGIB (Forrest IIc and III). By logistic regression and receiver-operating characteristic curve, simple risk score systems were derived which predicted patients’ risks of potentially needing endoscopic intervention to control bleeding. Risk score systems combined of patients’ serum hemoglobin (Hb) ≤75 g/L, red hematemesis, red stool, shock, and blood urine nitrogen ≥8.5 mmol/L within 24 hours after admission were derived. As for each one of these clinical signs, the relatively high specificity was 97.9% for shock, 96.4% for red stool, 85.5% for red hematemesis, 76.7% for Hb ≤75 g/L, and the sensitivity was 50.8% for red hematemesis, 47.5% for Hb ≤75 g/L, 14.2% for red stool, and 10.9% for shock. When these 5 clinical signs were presented as a risk score system, the highest area of receiver-operating characteristic curve was 0.746, with sensitivity 0.675 and specificity 0.733, which discriminated well with high-risk NVUGIB. These simple risk factors identified patients with high-risk NVUGIB of needing treatment to manage their bleeding pre-endoscopically. Further validation in the clinic was required. PMID:27367977

  18. Depression Risk Predicts Blunted Neural Responses to Gains and Enhanced Responses to Losses in Healthy Children

    PubMed Central

    Luking, Katherine R.; Pagliaccio, David; Luby, Joan L.; Barch, Deanna M.

    2016-01-01

    Objective Maternal major depressive disorder (MDD) increases risk for MDD and predicts reduced reward responding in adolescent offspring. However, it is unclear whether alterations in neural response to reward can be detected in school-aged children at high risk prior to the typical increase in reward response observed in adolescence. Method To assess relationships between neural response to gain/loss feedback, MDD risk, and child depressive symptoms, forty-seven psychiatrically healthy 7–10-year-old children (16 at high-risk given maternal MDD) completed questionnaires and a functional magnetic resonance imaging (fMRI) card-guessing game where candy was gained and lost. Results High-risk children showed both blunted response to gain and greater deactivation/reduced activation to loss within the ventral striatum and anterior insula. Within the striatum, risk-group differences in response to loss feedback were significantly larger than for gain, with greater deactivation to loss predicting risk-group status above and beyond blunted gain activation. Anhedonia was related to reduced deactivation to loss (i.e. reduced sensitivity to loss), while negative mood was related to enhanced deactivation to loss (i.e. enhanced sensitivity to loss) in the ventral striatum. Conclusion High-risk children showed blunted ventral striatal activation to gain feedback, but ventral striatal deactivation to loss was a stronger predictor of MDD risk. Further, relationships between response to loss and elevated depressive symptoms within the ventral striatum and cingulate differed depending on the type of depressive symptom. Together these results highlight the potentially important role of response to loss of reward in childhood risk for depression. PMID:27015724

  19. Risk score predicts high‐grade prostate cancer in DNA‐methylation positive, histopathologically negative biopsies

    PubMed Central

    Van Neste, Leander; Partin, Alan W.; Stewart, Grant D.; Epstein, Jonathan I.; Harrison, David J.

    2016-01-01

    BACKGROUND Prostate cancer (PCa) diagnosis is challenging because efforts for effective, timely treatment of men with significant cancer typically result in over‐diagnosis and repeat biopsies. The presence or absence of epigenetic aberrations, more specifically DNA‐methylation of GSTP1, RASSF1, and APC in histopathologically negative prostate core biopsies has resulted in an increased negative predictive value (NPV) of ∼90% and thus could lead to a reduction of unnecessary repeat biopsies. Here, it is investigated whether, in methylation‐positive men, DNA‐methylation intensities could help to identify those men harboring high‐grade (Gleason score ≥7) PCa, resulting in an improved positive predictive value. METHODS Two cohorts, consisting of men with histopathologically negative index biopsies, followed by a positive or negative repeat biopsy, were combined. EpiScore, a methylation intensity algorithm was developed in methylation‐positive men, using area under the curve of the receiver operating characteristic as metric for performance. Next, a risk score was developed combining EpiScore with traditional clinical risk factors to further improve the identification of high‐grade (Gleason Score ≥7) cancer. RESULTS Compared to other risk factors, detection of DNA‐methylation in histopathologically negative biopsies was the most significant and important predictor of high‐grade cancer, resulting in a NPV of 96%. In methylation‐positive men, EpiScore was significantly higher for those with high‐grade cancer detected upon repeat biopsy, compared to those with either no or low‐grade cancer. The risk score resulted in further improvement of patient risk stratification and was a significantly better predictor compared to currently used metrics as PSA and the prostate cancer prevention trial (PCPT) risk calculator (RC). A decision curve analysis indicated strong clinical utility for the risk score as decision‐making tool for repeat biopsy

  20. Multi-institutional comparison of non-sentinel lymph node predictive tools in breast cancer patients with high predicted risk of further axillary metastasis.

    PubMed

    Cserni, Gábor; Bori, Rita; Maráz, Róbert; Leidenius, Marjut H K; Meretoja, Tuomo J; Heikkila, Paivi S; Regitnig, Peter; Luschin-Ebengreuth, Gero; Zgajnar, Janez; Perhavec, Andraz; Gazic, Barbara; Lázár, György; Takács, Tibor; Vörös, András; Audisio, Riccardo A

    2013-01-01

    Although axillary lymph node dissection (ALND) has been the standard intervention in breast cancer patients with sentinel lymph node (SLN) metastasis, only a small proportion of patients benefit from this operation, because most do not harbor additional metastases in the axilla. Several predictive tools have been constructed to identify patients with low risk of non-SLN metastasis who could be candidates for the omission of ALND. In the present work, predictive nomograms were used to predict a high (>50 %) risk of non-SLN metastasis in order to identify patients who would most probably benefit from further axillary treatment. Data of 1000 breast cancer patients with SLN metastasis and completion ALND from 5 institutions were tested in 4 nomograms. A subset of 313 patients with micrometastatic SLNs were also tested in 3 different nomograms devised for the micrometastatic population (the high risk cut-off being 20 %). Patients with a high predicted risk of non-SLN metastasis had higher rates of metastasis in the non-SLNs than patients with low predicted risk. The positive predictive values of the nomograms ranged from 44 % to 64 % with relevant inter-institutional variability. The nomograms for micrometastatic SLNs performed much better in identifying patients with low risk of non-SLN involvement than in high-risk-patients; for the latter, the positive predictive values ranged from 13 % to 20 %. The nomograms show inter-institutional differences in their predictive values and behave differently in different settings. They are worse in identifying high risk patients than low-risk ones, creating a need for new predictive models to identify high-risk patients.

  1. SY 04-2 LONG-TERM CVD RISK PREDICTION IN LOW-INCIDENCE EUROPEAN POPULATIONS.

    PubMed

    Veronesi, Giovanni

    2016-09-01

    In Italy, the European SCORE Project risk score is the recommended tool for cardiovascular disease risk stratification in the primary prevention setting. Among non-diabetic subjects aged 40 to 64, the model estimates the 10-year probability of death due to cardiovascular disease based on individual's age, total cholesterol, blood pressure and smoking status. A growing body of evidence suggests that in middle-aged adults this stratification may suffer from two major drawbacks. First, mortality risk severely underestimates the global burden of disease incidence. Second, younger individuals and women are likely to be classified in the "low 10-year risk" category despite the presence of risk factors.The latest European and American guidelines have eventually introduced the assessment of long-term risk of disease as additional tool to improve risk communication and increase risk awareness. Long-term risk scores were first developed in the US and in the UK, i.e. in high-risk populations. In low-incidence populations, these models may have poor calibration and discrimination ability, as shown for the Framingham equation. Therefore, our research team developed and validated a 20-year risk score for the Italian population. As part of a collaborative study with the Italian Health Institute, we pooled 7 population-based cohorts of middle-aged individuals recruited in Northern and in Central Italy in mid 1980 s and early 1990 s following a similar protocol with standardized MONICA procedures. Overall, more than 10500 men and women 35-69 years old and free of CVD at baseline, who developed 830 first major atherosclerotic events (coronary heart disease or ischemic strokes) during a median 17 years of follow-up. The score was based on traditional risk factors (age, blood lipids, systolic blood pressure and treatment, smoking and diabetes). In addition, social status and family history of coronary heart disease did improve risk prediction, at least in men. Finally we showed

  2. Predicting Dyslexia at Age 11 from a Risk Index Questionnaire at Age 5

    ERIC Educational Resources Information Center

    Helland, Turid; Plante, Elena; Hugdahl, Kenneth

    2011-01-01

    This study focused on predicting dyslexia in children ahead of formal literacy training. Because dyslexia is a constitutional impairment, risk factors should be seen in preschool. It was hypothesized that data gathered at age 5 using questions targeting the dyslexia endophenotype should be reliable and valid predictors of dyslexia at age 11. A…

  3. Adolescent inpatient girls׳ report of dependent life events predicts prospective suicide risk.

    PubMed

    Stone, Lindsey B; Liu, Richard T; Yen, Shirley

    2014-09-30

    Adolescents with a history of suicidal behavior are especially vulnerable for future suicide attempts, particularly following discharge from an inpatient psychiatric admission. This study is the first to test whether adolescents׳ tendency to generate stress, or report more dependent events to which they contributed, was predictive of prospective suicide events. Ninety adolescent psychiatric inpatients who were admitted for recent suicide risk, completed diagnostic interviews, assessments of history of suicidal behavior, and a self-report questionnaire of major life events at baseline. Participants were followed over the subsequent 6 months after discharge to assess stability vs. onset of suicide events. Cox proportional hazard regressions were used to predict adolescents׳ time to suicide events. Results supported hypothesis, such that only recent greater dependent events, not independent or overall events, predicted risk for prospective suicide events. This effect was specific to adolescent girls. Importantly, dependent events maintained statistical significance as a predictor of future suicide events after co-varying for the effects of several established risk factors and psychopathology. Results suggest that the tendency to generate dependent events may contribute unique additional prediction for adolescent girls׳ prospective suicide risk, and highlight the need for future work in this area.

  4. Predicting the Risk of Attrition for Undergraduate Students with Time Based Modelling

    ERIC Educational Resources Information Center

    Chai, Kevin E. K.; Gibson, David

    2015-01-01

    Improving student retention is an important and challenging problem for universities. This paper reports on the development of a student attrition model for predicting which first year students are most at-risk of leaving at various points in time during their first semester of study. The objective of developing such a model is to assist…

  5. Parental Literacy Predicts Children's Literacy: A Longitudinal Family-Risk Study

    ERIC Educational Resources Information Center

    Torppa, Minna; Eklund, Kenneth; van Bergen, Elsje; Lyytinen, Heikki

    2011-01-01

    This family-risk (FR) study examined whether the literacy skills of parents with dyslexia are predictive of the literacy skills of their offspring. We report data from 31 child-parent dyads where both had dyslexia (FR-D) and 68 dyads where the child did not have dyslexia (FR-ND). Findings supported the differences in liability of FR children with…

  6. Disorganized symptoms and executive functioning predict impaired social functioning in subjects at risk for psychosis.

    PubMed

    Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S

    2011-01-01

    Predictors of social functioning deficits were assessed in 22 individuals "at risk" for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

  7. Predicting High Risk Adolescents' Substance Use over Time: The Role of Parental Monitoring

    ERIC Educational Resources Information Center

    Clark, Heddy Kovach; Shamblen, Stephen R.; Ringwalt, Chris L.; Hanley, Sean

    2012-01-01

    We examined whether parental monitoring at baseline predicted subsequent substance use in a high-risk youth population. Students in 14 alternative high schools in Washington State completed self-report surveys at three time points over the course of 2 years. Primary analyses included 1,423 students aged 14-20 who lived with at least one parent or…

  8. DOSIMETRY MODELING OF INHALED FORMALDEHYDE: BINNING NASAL FLUX PREDICTIONS FOR QUANTITATIVE RISK ASSESSMENT

    EPA Science Inventory

    Dosimetry Modeling of Inhaled Formaldehyde: Binning Nasal Flux Predictions for Quantitative Risk Assessment. Kimbell, J.S., Overton, J.H., Subramaniam, R.P., Schlosser, P.M., Morgan, K.T., Conolly, R.B., and Miller, F.J. (2001). Toxicol. Sci. 000, 000:000.

    Interspecies e...

  9. Adolescent inpatient girls’ report of dependent life events predicts prospective suicide risk

    PubMed Central

    Stone, Lindsey Beth; Liu, Richard; Yen, Shirley

    2014-01-01

    Adolescents with a history of suicidal behavior are especially vulnerable for future suicide attempts, particularly following discharge from an inpatient psychiatric admission. This study is the first to test whether adolescents’ tendency to generate stress, or report more dependent events to which they contributed, was predictive of prospective suicide events. Ninety adolescent psychiatric inpatients who were admitted for recent suicide risk, completed diagnostic interviews, assessments of history of suicidal behavior, and a self-report questionnaire of major life events at baseline. Participants were followed over the subsequent 6 months after discharge to assess stability vs. onset of suicide events. Cox proportional hazard regressions were used to predict adolescents’ time to suicide events. Results supported hypothesis, such that only recent greater dependent events, not independent or overall events, predicted risk for prospective suicide events. This effect was specific to adolescent girls. Importantly, dependent events maintained statistical significance as a predictor of future suicide events after co-varying for the effects of several established risk factors and psychopathology. Results suggest that the tendency to generate dependent events may contribute unique additional prediction for adolescent girls’ prospective suicide risk, and highlight the need for future work in this area. PMID:24893759

  10. The Utility of Risk Assessment Instruments for the Prediction of Recidivism in Sexual Homicide Perpetrators

    ERIC Educational Resources Information Center

    Hill, Andreas; Rettenberger, Martin; Habermann, Niels; Berner, Wolfgang; Eher, Reinhard; Briken, Peer

    2012-01-01

    To examine the predictive accuracy of four well established risk assessment instruments (PCL-R, HCR-20, SVR-20, and Static-99) in an important subgroup of sexual offenders, these instruments were assessed retrospectively based on information from forensic psychiatric court reports in a sample of 90 released male sexual homicide offenders (out of…

  11. Predictive validity of adult risk assessment tools with juveniles who offended sexually.

    PubMed

    Ralston, Christopher A; Epperson, Douglas L

    2013-09-01

    An often-held assumption in the area of sexual recidivism risk assessment is that different tools should be used for adults and juveniles. This assumption is driven either by the observation that adolescents tend to be in a constant state of flux in the areas of development, education, and social structure or by the fact that the judicial system recognizes that juveniles and adults are different. Though the assumption is plausible, it is largely untested. The present study addressed this issue by scoring 2 adult sexual offender risk assessment tools, the Minnesota Sex Offender Screening Tool-Revised and the Static-99, on an exhaustive sample (N = 636) of juveniles who had sexually offended (JSOs) in Utah. For comparison, 2 tools designed for JSOs were also scored: the Juvenile-Sex Offender Assessment Protocol-II and the Juvenile Risk Assessment Scale. Recidivism data were collected for 2 time periods: before age 18 (sexual, violent, any recidivism) and from age 18 to the year 2004 (sexual). The adult actuarial risk assessment tools predicted all types of juvenile recidivism significantly and at approximately the same level of accuracy as juvenile-specific tools. However, the accuracy of longer term predictions of adult sexual recidivism across all 4 tools was substantially lower than the accuracy achieved in predicting juvenile sexual recidivism, with 2 of the tools producing nonsignificant results, documenting the greater difficulty in making longer term predictions on the basis of adolescent behavior.

  12. Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

    ERIC Educational Resources Information Center

    Jia, Pengfei; Maloney, Tim

    2015-01-01

    Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to…

  13. A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

    PubMed

    Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

    2015-09-20

    Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system.

  14. Integrated ecological risk assessment of pesticides in tropical ecosystems: a case study with carbofuran in Brazil.

    PubMed

    Chelinho, Sónia; Lopes, Isabel; Natal-da-Luz, Tiago; Domene, Xaxier; Nunes, Maria Edna Tenorio; Espíndola, Evaldo L G; Ribeiro, Rui; Sousa, Jose P

    2012-02-01

    The aim of the present study is to contribute an ecologically relevant assessment of the ecotoxicological effects of pesticide applications in agricultural areas in the tropics, using an integrated approach with information gathered from soil and aquatic compartments. Carbofuran, an insecticide/nematicide used widely on sugarcane crops, was selected as a model substance. To evaluate the toxic effects of pesticide spraying for soil biota, as well as the potential indirect effects on aquatic biota resulting from surface runoff and/or leaching, field and laboratory (using a cost-effective simulator of pesticide applications) trials were performed. Standard ecotoxicological tests were performed with soil (Eisenia andrei, Folsomia candida, and Enchytraeus crypticus) and aquatic (Ceriodaphnia silvestrii) organisms, using serial dilutions of soil, eluate, leachate, and runoff samples. Among soil organisms, sensitivity was found to be E. crypticus < E. andrei < F. candida. Among the aqueous extracts, mortality of C. silvestrii was extreme in runoff samples, whereas eluates were by far the least toxic samples. A generally higher toxicity was found in the bioassays performed with samples from the field trial, indicating the need for improvements in the laboratory simulator. However, the tool developed proved to be valuable in evaluating the toxic effects of pesticide spraying in soils and the potential risks for aquatic compartments.

  15. [Metabolic parameters and risk factors associated with abdominal obesity among female adolescents in public schools in the Distrito Federal (Brazil)].

    PubMed

    Pinto, Karina Alves de Castro; Priore, Silvia Eloiza; de Carvalho, Kênia Mara Baiocchi

    2011-03-01

    This study aimed to estimate the prevalence of abdominal obesity and investigate their association with parameters markers of metabolic syndrome (MS) and its risk factors in female adolescents. It is a cross-sectional study with 150 adolescents from 10 public schools in the Federal District, Brazil. The presence of abdominal obesity was considered by measuring waist circumference above the 80th percentile, according to Taylor et al. (2000). The associated factors included sociodemographic characteristics, health status of adolescents and their parents, physical activity, eating habits, blood pressure and biochemical profile. The abdominal obesity prevalence ratio (PR) was estimated by Poisson regression model, with 95% CI. Among the adolescents studied (age= 15.6 +/- 0.8 years; BMI = 21.0 +/- 3.0 kg/m2), prevalence of abdominal obesity was 20%, and this condition was not associated with sociodemographic variables, physical activity and diet. However, abdominal obesity was significantly associated with intake of less than 4 meals a day (PR = 2.27; IC95% 1.27-4.10), previous obesity (PR = 2.36; IC95% 1.31-4.01), history of parental chronic disease (PR = 3.55; IC 95% 1.63-7.75), fasting insulin = 15 uUi/mL (PR = 3.05; IC 95% 1.36-6.82) e HDL-c > 40 mg/dL (PR = 0.39; IC95% 0.23-0.67). In this population, modifiable factors, family history and determinants of MS, such as insulin and HDL-c were associated with abdominal obesity, which points to the need for effective health promotion among adolescents.

  16. Potential ecological risk assessment and prediction of soil heavy metal pollution around coal gangue dump

    NASA Astrophysics Data System (ADS)

    Jiang, X.; Lu, W. X.; Yang, Q. C.; Yang, Z. P.

    2014-03-01

    Aim of the present study is to evaluate the potential ecological risk and predict the trend of soil heavy metal pollution around a~coal gangue dump in Jilin Province (Northeast China). The concentrations of Cd, Pb, Cu, Cr and Zn were monitored by inductively coupled plasma mass spectrometry (ICP-MS). The potential ecological risk index method developed by Hakanson (1980) was employed to assess the potential risk of heavy metal pollution. The potential ecological risk in an order of E(Cd) > E(Pb) > E(Cu) > E(Cr) > E(Zn) have been obtained, which showed that Cd was the most important factor led to risk. Based on the Cd pollution history, the cumulative acceleration and cumulative rate of Cd were estimated, and the fixed number of years exceeding standard prediction model was established, which was used to predict the pollution trend of Cd under the accelerated accumulation mode and the uniform mode. Pearson correlation analysis and correspondence analysis are employed to identify the sources of heavy metal, and the relationship between sampling points and variables. These findings provide some useful insights for making appropriate management strategies to prevent and decrease heavy metal pollution around coal gangue dump in Yangcaogou coal mine and other similar areas elsewhere.

  17. Risk of severe asthma episodes predicted from fluctuation analysis of airway function.

    PubMed

    Frey, Urs; Brodbeck, Tanja; Majumdar, Arnab; Taylor, D Robin; Town, G Ian; Silverman, Michael; Suki, Béla

    2005-12-01

    Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

  18. The efficacy of violence prediction: a meta-analytic comparison of nine risk assessment tools.

    PubMed

    Yang, Min; Wong, Stephen C P; Coid, Jeremy

    2010-09-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their predictive efficacies for violence. The effect sizes were extracted from 28 original reports published between 1999 and 2008, which assessed the predictive accuracy of more than one tool. We used a within-subject design to improve statistical power and multilevel regression models to disentangle random effects of variation between studies and tools and to adjust for study features. All 9 tools and their subscales predicted violence at about the same moderate level of predictive efficacy with the exception of Psychopathy Checklist--Revised (PCL-R) Factor 1, which predicted violence only at chance level among men. Approximately 25% of the total variance was due to differences between tools, whereas approximately 85% of heterogeneity between studies was explained by methodological features (age, length of follow-up, different types of violent outcome, sex, and sex-related interactions). Sex-differentiated efficacy was found for a small number of the tools. If the intention is only to predict future violence, then the 9 tools are essentially interchangeable; the selection of which tool to use in practice should depend on what other functions the tool can perform rather than on its efficacy in predicting violence. The moderate level of predictive accuracy of these tools suggests that they should not be used solely for some criminal justice decision making that requires a very high level of accuracy such as preventive detention.

  19. Improving polygenic risk prediction from summary statistics by an empirical Bayes approach

    PubMed Central

    So, Hon-Cheong; Sham, Pak C.

    2017-01-01

    Polygenic risk scores (PRS) from genome-wide association studies (GWAS) are increasingly used to predict disease risks. However some included variants could be false positives and the raw estimates of effect sizes from them may be subject to selection bias. In addition, the standard PRS approach requires testing over a range of p-value thresholds, which are often chosen arbitrarily. The prediction error estimated from the optimized threshold may also be subject to an optimistic bias. To improve genomic risk prediction, we proposed new empirical Bayes approaches to recover the underlying effect sizes and used them as weights to construct PRS. We applied the new PRS to twelve cardio-metabolic traits in the Northern Finland Birth Cohort and demonstrated improvements in predictive power (in R2) when compared to standard PRS at the best p-value threshold. Importantly, for eleven out of the twelve traits studied, the predictive performance from the entire set of genome-wide markers outperformed the best R2 from standard PRS at optimal p-value thresholds. Our proposed methodology essentially enables an automatic PRS weighting scheme without the need of choosing tuning parameters. The new method also performed satisfactorily in simulations. It is computationally simple and does not require assumptions on the effect size distributions. PMID:28145530

  20. A biological approach to the interspecies prediction of radiation-induced mortality risk

    SciTech Connect

    Carnes, B.A.; Grahn, D.; Olshansky, S.J.

    1997-08-01

    Evolutionary explanations for why sexually reproducing organisms grow old suggest that the forces of natural selection affect the ages when diseases occur that are subject to a genetic influence (referred to here as intrinsic diseases). When extended to the population level for a species, this logic leads to the general prediction that age-specific death rates from intrinsic causes should begin to rise as the force of selection wanes once the characteristic age of sexual maturity is attained. Results consistent with these predictions have been found for laboratory mice, beagles, and humans where, after adjusting for differences in life span, it was demonstrated that these species share a common age pattern of mortality for intrinsic causes of death. In quantitative models used to predict radiation-induced mortality, risks are often expressed as multiples of those observed in a control population. A control population, however, is an aging population. As such, mortality risks related to exposure must be interpreted relative to the age-specific risk of death associated with aging. Given the previous success in making interspecies predictions of age-related mortality, the purpose of this study was to determine whether radiation-induced mortality observed in one species could also be predicted quantitatively from a model used to describe the mortality consequences of exposure to radiation in a different species. Mortality data for B6CF{sub 1} mice and beagles exposed to {sup 60}Co {gamma}-rays for the duration of life were used for analysis.

  1. Improving prediction of outcomes in African Americans with normal stress echocardiograms using a risk scoring system.

    PubMed

    Sutter, David A; Thomaides, Athanasios; Hornsby, Kyle; Mahenthiran, Jothiharan; Feigenbaum, Harvey; Sawada, Stephen G

    2013-06-01

    Cardiovascular mortality is high in African Americans, and those with normal results on stress echocardiography remain at increased risk. The aim of this study was to develop a risk scoring system to improve the prediction of cardiovascular events in African Americans with normal results on stress echocardiography. Clinical data and rest echocardiographic measurements were obtained in 548 consecutive African Americans with normal results on rest and stress echocardiography and ejection fractions ≥50%. Patients were followed for myocardial infarction and death for 3 years. Predictors of cardiovascular events were determined with Cox regression, and hazard ratios were used to determine the number of points in the risk score attributed to each independent predictor. During follow-up of 3 years, 47 patients (8.6%) had events. Five variables-age (≥45 years in men, ≥55 years in women), history of coronary disease, history of smoking, left ventricular hypertrophy, and exercise intolerance (<7 METs in men, <5 METs in women, or need for dobutamine stress)-were independent predictors of events. A risk score was derived for each patient (ranging from 0 to 8 risk points). The area under the curve for the risk score was 0.82 with the optimum cut-off risk score of 6. Among patients with risk scores ≥6, 30% had events, compared with 3% with risk score <6 (p <0.001). In conclusion, African Americans with normal results on stress echocardiography remain at significant risk for cardiovascular events. A risk score can be derived from clinical and echocardiographic variables, which can accurately distinguish high- and low-risk patients.

  2. At risk or not at risk? A meta-analysis of the prognostic accuracy of psychometric interviews for psychosis prediction

    PubMed Central

    Fusar-Poli, Paolo; Cappucciati, Marco; Rutigliano, Grazia; Schultze-Lutter, Frauke; Bonoldi, Ilaria; Borgwardt, Stefan; Riecher-Rössler, Anita; Addington, Jean; Perkins, Diana; Woods, Scott W; McGlashan, Thomas H; Lee, Jimmy; Klosterkötter, Joachim; Yung, Alison R; McGuire, Philip

    2015-01-01

    An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR−). The reference index was psychosis onset over time in both CHR+ and CHR− subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan’s nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR−: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan’s nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide. PMID:26407788

  3. Prediction of high-risk types of human papillomaviruses using statistical model of protein "sequence space".

    PubMed

    Wang, Cong; Hai, Yabing; Liu, Xiaoqing; Liu, Nanfang; Yao, Yuhua; He, Pingan; Dai, Qi

    2015-01-01

    Discrimination of high-risk types of human papillomaviruses plays an important role in the diagnosis and remedy of cervical cancer. Recently, several computational methods have been proposed based on protein sequence-based and structure-based information, but the information of their related proteins has not been used until now. In this paper, we proposed using protein "sequence space" to explore this information and used it to predict high-risk types of HPVs. The proposed method was tested on 68 samples with known HPV types and 4 samples without HPV types and further compared with the available approaches. The results show that the proposed method achieved the best performance among all the evaluated methods with accuracy 95.59% and F1-score 90.91%, which indicates that protein "sequence space" could potentially be used to improve prediction of high-risk types of HPVs.

  4. A Model-Free Machine Learning Method for Risk Classification and Survival Probability Prediction.

    PubMed

    Geng, Yuan; Lu, Wenbin; Zhang, Hao Helen

    2014-01-01

    Risk classification and survival probability prediction are two major goals in survival data analysis since they play an important role in patients' risk stratification, long-term diagnosis, and treatment selection. In this article, we propose a new model-free machine learning framework for risk classification and survival probability prediction based on weighted support vector machines. The new procedure does not require any specific parametric or semiparametric model assumption on data, and is therefore capable of capturing nonlinear covariate effects. We use numerous simulation examples to demonstrate finite sample performance of the proposed method under various settings. Applications to a glioma tumor data and a breast cancer gene expression survival data are shown to illustrate the new methodology in real data analysis.

  5. Predicting conduct problems: can high-risk children be identified in kindergarten and grade 1?

    PubMed

    Bennett, K J; Lipman, E L; Brown, S; Racine, Y; Boyle, M H; Offord, D R

    1999-08-01

    Externalizing behavior symptoms (EBS) in childhood are a strong predictor of future conduct problems. This study evaluated their predictive accuracy using logistic regression and receiver operating characteristic curve techniques. EBS, alone and in combination with other child and familial risk factors, were used to predict conduct problems 30 months later in a nonclinic population of kindergartners and Grade 1 children. The sensitivity (Sn) and positive predictive value (PPV) of EBS alone were below preset criteria of > or = 50% for each (prevalence < or = 15%). Sn and PPV increased when other child and familial factors were combined with symptoms but did not exceed the preset criteria. From a developmental perspective, substantial stability of EBS exists over time. However, from the perspective of prevention science, significant levels of misclassification will occur when EBS are used to designate high-risk status under the low-prevalence conditions of normal populations.

  6. Predicting Negative Events: Using Post-discharge Data to Detect High-Risk Patients

    PubMed Central

    Sulieman, Lina; Fabbri, Daniel; Wang, Fei; Hu, Jianying; Malin, Bradley A

    2016-01-01

    Predicting negative outcomes, such as readmission or death, and detecting high-risk patients are important yet challenging problems in medical informatics. Various models have been proposed to detect high-risk patients; however, the state of the art relies on patient information collected before or at the time of discharge to predict future outcomes. In this paper, we investigate the effect of including data generated post discharge to predict negative outcomes. Specifically, we focus on two types of patients admitted to the Vanderbilt University Medical Center between 2010-2013: i) those with an acute event - 704 hip fractures and ii) those with chronic problems — 5250 congestive heart failure (CHF) patients. We show that the post-discharge model improved the AUC of the LACE index, a standard readmission scoring function, by 20 - 30%. Moreover, the new model resulted in higher AUCs by 15 - 27% for hip fracture and 10 - 12% for CHF compared to standard models. PMID:28269914

  7. An examination of the predictive validity of the risk matrix 2000 in England and wales.

    PubMed

    Barnett, Georgia D; Wakeling, Helen C; Howard, Philip D

    2010-12-01

    This study examined the predictive validity of an actuarial risk-assessment tool with convicted sexual offenders in England and Wales. A modified version of the RM2000/s scale and the RM2000 v and c scales (Thornton et al., 2003) were examined for accuracy in predicting proven sexual violent, nonsexual violent, and combined sexual and/or nonsexual violent reoffending in a sample of sexual offenders who had either started a community sentence or been released from prison into the community by March 2007. Rates of proven reoffending were examined at 2 years for the majority of the sample (n = 4,946), and 4 years ( n = 578) for those for whom these data were available. The predictive validity of the RM2000 scales was also explored for different subgroups of sexual offenders to assess the robustness of the tool. Both the modified RM2000/s and the complete v and c scales effectively classified offenders into distinct risk categories that differed significantly in rates of proven sexual and/or nonsexual violent reoffending. Survival analyses on the RM2000/s and v scales (N = 9,284) indicated that the higher risk groups offended more quickly and at a higher rate than lower risk groups. The relative predictive validity of the RM2000/s, v, and c, as calculated using Receiver Operating Characteristics (ROC) analyses, were moderate (.68) for RM2000/s and large for both the RM2000/c (.73) and RM2000/v (.80), at the 2-year follow-up. RM2000/s was moderately accurate in predicting relative risk of proven sexual reoffending for a variety of subgroups of sexual offenders.

  8. Recent developments in the ability to predict and modify breast cancer risk.

    PubMed

    Prado, Arturo; Andrades, Patricio; Parada, Francisco

    2010-10-01

    The identification of women at higher risk for breast cancer is a matter of public health and anyone who participates in any treatment modality of this condition (this includes the plastic surgeon) should be aware of the tools and predictive models of breast cancer. Screening for breast cancer in the community, and probably during the daily plastic surgery consultation, until recently, was limited to decisions about when to initiate a mammography study. New developments that predict and modify breast cancer risk must be clearly understood by our specialty through identification of women at higher risk for breast cancer and be familiar with the current issues related to screening and risk-reduction measures. In this review, we discuss current knowledge regarding the recent data of breast cancer risk, screening strategies for high-risk women and medical and surgical approaches to reduce breast cancer risk. Patients with breast cancer belong to one of three groups: a. Sporadic breast cancer (75%)--patients without family history or those who have a breast biopsy with proliferative changes. b. Genetic mutation breast cancer (5%)--women who have a genetic predisposition, and most of these are attributable to mutations in the breast cancer susceptibility gene 1 (BRCA1) and breast cancer susceptibility gene 2 (BRCA2). c. Cluster family breast cancer (20%)--seen in women with a relevant history of breast cancer in the family and breast biopsy with proliferative breast changes with no association with mutations.Those at high risk for breast cancer should investigate the family history with genetic testing consideration, clinical history, including prior breast biopsies and evaluation of mammographic density. Tools for breast cancer risk assessment include the Gail and Claus model, genetic screening,BRCAPRO and others that are evaluated in this review.

  9. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

    PubMed

    Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

    2012-01-11

    Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

  10. Ensembled support vector machines for human papillomavirus risk type prediction from protein secondary structures.

    PubMed

    Kim, Sun; Kim, Jeongmi; Zhang, Byoung-Tak

    2009-02-01

    Infection by the human papillomavirus (HPV) is regarded as the major risk factor in the development of cervical cancer. Detection of high-risk HPV is important for understanding its oncogenic mechanisms and for developing novel clinical tools for its diagnosis, treatment, and prevention. Several methods are available to predict the risk types for HPV protein sequences. Nevertheless, no tools can achieve a universally good performance for all domains, including HPV and nor do they provide confidence levels for their decisions. Here, we describe ensembled support vector machines (SVMs) to classify HPV risk types, which assign given proteins into high-, possibly high-, or low-risk type based on their confidence level. Our approach uses protein secondary structures to obtain the differential contribution of subsequences for the risk type, and SVM classifiers are combined with a simple but efficient string kernel to handle HPV protein sequences. In the experiments, we compare our approach with previous methods in accuracy and F1-score, and present the predictions for unknown HPV types, which provides promising results.

  11. Using Dynamic Risk and Protective Factors to Predict Inpatient Aggression: Reliability and Validity of START Assessments

    PubMed Central

    Desmarais, Sarah L.; Nicholls, Tonia L.; Wilson, Catherine M.; Brink, Johann

    2012-01-01

    The Short-Term Assessment of Risk and Treatability (START) is a relatively new structured professional judgment guide for the assessment and management of short-term risks associated with mental, substance use, and personality disorders. The scheme may be distinguished from other violence risk instruments because of its inclusion of 20 dynamic factors that are rated in terms of both vulnerability and strength. This study examined the reliability and validity of START assessments in predicting inpatient aggression. Research assistants completed START assessments for 120 male forensic psychiatric patients through review of hospital files. They additionally completed Historical-Clinical-Risk Management – 20 (HCR-20) and the Hare Psychopathy Checklist: Screening Version (PCL:SV) assessments. Outcome data was coded from hospital files for a 12-month follow-up period using the Overt Aggression Scale (OAS). START assessments evidenced excellent interrater reliability and demonstrated both predictive and incremental validity over the HCR-20 Historical subscale scores and PCL:SV total scores. Overall, results support the reliability and validity of START assessments, and use of the structured professional judgment approach more broadly, as well as the value of using dynamic risk and protective factors to assess violence risk. PMID:22250595

  12. Prediction of cardiovascular disease risk among low-income urban dwellers in metropolitan Kuala Lumpur, Malaysia.

    PubMed

    Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Bulgiba, Awang; Majid, Hazreen Abdul

    2015-01-01

    We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers.

  13. Cognitive Failure and Alexithymia and Predicting High–Risk Behaviors of Students With Learning Disabilities

    PubMed Central

    Abbasi, Moslem; Bagyan, Mohammad Javad; Dehghan, Hamidreza

    2014-01-01

    Background: One of the threatening health issues is prevalence of high-risk behaviors in various groups. Because of rapid social changes, it has been considered as of the most important problems of society by health organizations, administrative laws, and social policymakers. Objectives: The aim of this study was to determine the role of cognitive failure and alexithymia in predicting high-risk behaviors of students with learning disabilities. Patients and Methods: This was a correlational research including all 14-16 years old students during 2012-2013 school year in Arak, IR Iran. Eighty students with learning disabilities were sampled by simply random sampling. The data were collected by cognitive failures questionnaire, Toronto alexithymia scale, and high-risk behavior questionnaire. Results: The results showed that high-risk behaviors had significant positive correlations with difficulty identifying feelings (r = 0.321), difficulty describing feelings (r = 0.336), externally oriented thinking (r = 0.248), distractibility (0.292), memory distortion (r = 0.374), blunders (r = 0.335), and names amnesia (r = 0.275). Multiple regression analysis showed that cognitive failure and alexithymia predicted 32% of the total variance of high-risk behaviors. Conclusions: These findings demonstrated that cognitive failure and alexithymia had important roles in strengthening and appearance of high-risk behaviors in students with learning disabilities. Therefore, considering those problems, precautionary actions might be necessary. PMID:25032160

  14. Robust Risk Prediction with Biomarkers under Two-Phase Stratified Cohort Design

    PubMed Central

    Payne, Rebecca; Yang, Ming; Zheng, Yingye; Jensen, Majken K.; Cai, Tianxi

    2016-01-01

    Summary Identification of novel biomarkers for risk prediction is important for disease prevention and optimal treatment selection. However, studies aiming to discover which biomarkers are useful for risk prediction often require the use of stored biological samples from large assembled cohorts, and thus the depletion of a finite and precious resource. To make efficient use of such these stored samples, two-phase sampling designs are often adopted as resource-efficient sampling strategies, especially when the outcome of interest is rare. Existing methods for analyzing data from two-phase studies focus primarily on single marker analysis or fitting the Cox regression model to combine information from multiple markers. However, the Cox model may not fit the data well. Under model misspecification, the composite score derived from the Cox model may not perform well in predicting the outcome. Under a general two-phase stratified cohort sampling design, we present a novel approach to combining multiple markers to optimize prediction by fitting a flexible non-parametric transformation model. Using inverse probability weighting to account for the outcome dependent sampling, we propose to estimate the model parameters by maximizing an objective function which can be interpreted as a weighted C-statistic for survival outcomes. Regardless of model adequacy, the proposed procedure yields a sensible composite risk score for prediction. A major obstacle for making inference under two phase studies is due to the correlation induced by the finite population sampling, which prevents standard inference procedures such as the bootstrap from being used for variance estimation. We propose a resampling procedure to derive valid confidence intervals for the model parameters and the C-statistic accuracy measure. We illustrate the new methods with simulation studies and an analysis of a two-phase study of high-density lipoprotein cholesterol (HDL-C) subtypes for predicting the risk of

  15. Robust risk prediction with biomarkers under two-phase stratified cohort design.

    PubMed

    Payne, Rebecca; Yang, Ming; Zheng, Yingye; Jensen, Majken K; Cai, Tianxi

    2016-12-01

    Identification of novel biomarkers for risk prediction is important for disease prevention and optimal treatment selection. However, studies aiming to discover which biomarkers are useful for risk prediction often require the use of stored biological samples from large assembled cohorts, and thus the depletion of a finite and precious resource. To make efficient use of such stored samples, two-phase sampling designs are often adopted as resource-efficient sampling strategies, especially when the outcome of interest is rare. Existing methods for analyzing data from two-phase studies focus primarily on single marker analysis or fitting the Cox regression model to combine information from multiple markers. However, the Cox model may not fit the data well. Under model misspecification, the composite score derived from the Cox model may not perform well in predicting the outcome. Under a general two-phase stratified cohort sampling design, we present a novel approach to combining multiple markers to optimize prediction by fitting a flexible nonparametric transformation model. Using inverse probability weighting to account for the outcome-dependent sampling, we propose to estimate the model parameters by maximizing an objective function which can be interpreted as a weighted C-statistic for survival outcomes. Regardless of model adequacy, the proposed procedure yields a sensible composite risk score for prediction. A major obstacle for making inference under two phase studies is due to the correlation induced by the finite population sampling, which prevents standard inference procedures such as the bootstrap from being used for variance estimation. We propose a resampling procedure to derive valid confidence intervals for the model parameters and the C-statistic accuracy measure. We illustrate the new methods with simulation studies and an analysis of a two-phase study of high-density lipoprotein cholesterol (HDL-C) subtypes for predicting the risk of coronary heart

  16. Concepts and challenges in cancer risk prediction for the space radiation environment

    NASA Astrophysics Data System (ADS)

    Barcellos-Hoff, Mary Helen; Blakely, Eleanor A.; Burma, Sandeep; Fornace, Albert J.; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G.; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M.

    2015-07-01

    Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

  17. Concepts and challenges in cancer risk prediction for the space radiation environment.

    PubMed

    Barcellos-Hoff, Mary Helen; Blakely, Eleanor A; Burma, Sandeep; Fornace, Albert J; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M

    2015-07-01

    Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

  18. Urban and architectural risk factors for malaria in indigenous Amazonian settlements in Brazil: a typological analysis.

    PubMed

    Leandro-Reguillo, Patricia; Thomson-Luque, Richard; Monteiro, Wuelton M; de Lacerda, Marcus V G

    2015-07-22

    In the Amazon, m alaria is highly endemic in indigenous populations, which are often considered one of the last barriers to malaria elimination due to geographic isolation. Although the improvement of housing conditions is a good strategy towards the control and prevention of vector-borne diseases, such as malaria, this preventive practice has been barely undertaken in Latin America. An analysis of the architectural and urban features of indigenous Amazonian populations is essential to define and adapt these vector control measures. A total of 32 villages of 29 different ethnicities were studied and mapped by reviewing literature and visual information, and using a geographic information system. The most important architectural and urban characteristics influencing malaria were analysed according to the following categories: number of households and dimensions, supporting area, openings, materials, lifespan and location. Housing typologies found were classified within each of these variables. The results of this typological analysis included an easy-to-handle working template and revealing of features that benefit or hamper the presence of malaria vectors in Amerindians communities. Among risk factors, presence of open eaves, permeable walls, open-side constructions, large number of sleepers indoors, temporary-ephemeral houses, linear villages along stream banks, houseboats villages, poor urban drainage and villages surrounded by anthropogenic environments were highlighted. Indigenous settlements very permissive for anophelines were identified in ethnic groups, such as the Yanomami, Palikur, Paumari, Waimiri-Atroari and Wajãpi. Positive features were also recognized, including opaque and closed houses, large radial villages on bare soil, highly elevated stilted houses and the fire indoors, found among the Yawalapiti, Ashaninka, and Gavião-Parkatejê tribes. However, as Amazonian indigenous settlement typologies vary greatly even among villages of the same ethnic

  19. Youth substance use and body composition: does risk in one area predict risk in the other?

    PubMed

    Pasch, Keryn E; Velazquez, Cayley E; Cance, Jessica Duncan; Moe, Stacey G; Lytle, Leslie A

    2012-01-01

    Both substance use and obesity are prevalent among youth. As youth age, substance use rates increase and over the past three decades, obesity rates among youth have tripled. While these two factors have both short- and long-term health impacts, little research has explored how substance use and obesity among youth may be related. This study explores the bi-directional longitudinal relationships between substance use and body composition. Participants (N = 704; 50.7% female) were mostly white (86.4%) with a baseline mean age of 14.7 years. Objectively measured body composition was used to calculate body mass index z-scores (BMI z-score) and percent body fat. Cross-lagged structural equation models, accounting for clustering at the school level, were run to determine the longitudinal association between body composition and self-reported substance use (alcohol, cigarette, and marijuana), adjusting for socio-demographic characteristics, pubertal status, and weight satisfaction. Baseline alcohol use predicted decreased BMI z-score at follow-up and a similar association with percent body fat approached significance. Baseline cigarette use predicted increased percent body fat. No longitudinal associations were seen between baseline body composition and future substance use. Our results suggest that substance use contributes to subsequent body composition; however, body composition does not contribute to subsequent substance use. Continued research that explores these relationships longitudinally is greatly needed.

  20. Fracture risk prediction: importance of age, BMD and spine fracture status.

    PubMed

    Krege, John H; Wan, Xiaohai; Lentle, Brian C; Berger, Claudie; Langsetmo, Lisa; Adachi, Jonathan D; Prior, Jerilynn C; Tenenhouse, Alan; Brown, Jacques P; Kreiger, Nancy; Olszynski, Wojciech P; Josse, Robert G; Goltzman, David

    2013-01-01

    Our purpose was to identify factors for a parsimonious fracture risk assessment model considering morphometric spine fracture status, femoral neck bone mineral density (BMD) and the World Health Organization (WHO) clinical risk factors. Using data from 2761 subjects from the Canadian Multicentre Osteoporosis Study (CaMos), a prospective, longitudinal cohort study of randomly selected community-dwelling men and women aged ⩾50 years, we previously reported that a logistic regression model considering age, BMD and spine fracture status provided as much predictive information as a model considering these factors plus the remaining WHO clinical risk factors. The current analysis assesses morphometric vertebral fracture and/or nonvertebral fragility fracture at 5 years using data from an additional 1964 CaMos subjects who have now completed 5 years of follow-up (total N=4725). Vertebral fractures were identified from lateral spine radiographs assessed using quantititative morphometry at baseline and end point. Nonvertebral fragility fractures were determined by questionnaire and confirmed using radiographs or medical records; fragility fracture was defined as occurring with minimal or no trauma. In this analysis, a model including age, BMD and spine fracture status provided a gradient of risk per s.d. (GR/s.d.) of 1.88 and captured most of the predictive information of a model including morphometric spine fracture status, BMD and all WHO clinical risk factors (GR/s.d. 1.92). For comparison, this model provided more information than a model considering BMD and the WHO clinical risk factors (GR/s.d. 1.74). These findings confirm the value of age, BMD and spine fracture status for predicting fracture risk.

  1. Fracture risk prediction: importance of age, BMD and spine fracture status

    PubMed Central

    Krege, John H; Wan, Xiaohai; Lentle, Brian C; Berger, Claudie; Langsetmo, Lisa; Adachi, Jonathan D; Prior, Jerilynn C; Tenenhouse, Alan; Brown, Jacques P; Kreiger, Nancy; Olszynski, Wojciech P; Josse, Robert G; Goltzman, David; Goltzman, David; Kreiger, Nancy; Tenenhouse, Alan; Godmaire, Suzanne; Dumont, Silvia; Berger, Claudie; Zhou, Wei; Joyce, Carol; Kovacs, Christopher; Sheppard, Emma; Kirkland, Susan; Kaiser, Stephanie; Stanfield, Barbara; Brown, Jacques P; Bessette, Louis; Gendreau, Marc; Anastassiades, Tassos; Towheed, Tanveer; Matthews, Barbara; Josse, Bob; Jamal, Sophie; Murray, Tim; Gardner-Bray, Barbara; Adachi, Jonathan D.; Papaioannou, Alexandra; Pickard, Laura; Olszynski, Wojciech P.; Davison, K. Shawn; Thingvold, Jola; Hanley, David A.; Allan, Jane; Prior, Jerilynn C.; Patel, Millan; Vigna, Yvette; Andjelic, Nerkeza; Lentle, Brian

    2013-01-01

    Our purpose was to identify factors for a parsimonious fracture risk assessment model considering morphometric spine fracture status, femoral neck bone mineral density (BMD) and the World Health Organization (WHO) clinical risk factors. Using data from 2761 subjects from the Canadian Multicentre Osteoporosis Study (CaMos), a prospective, longitudinal cohort study of randomly selected community-dwelling men and women aged ⩾50 years, we previously reported that a logistic regression model considering age, BMD and spine fracture status provided as much predictive information as a model considering these factors plus the remaining WHO clinical risk factors. The current analysis assesses morphometric vertebral fracture and/or nonvertebral fragility fracture at 5 years using data from an additional 1964 CaMos subjects who have now completed 5 years of follow-up (total N=4725). Vertebral fractures were identified from lateral spine radiographs assessed using quantititative morphometry at baseline and end point. Nonvertebral fragility fractures were determined by questionnaire and confirmed using radiographs or medical records; fragility fracture was defined as occurring with minimal or no trauma. In this analysis, a model including age, BMD and spine fracture status provided a gradient of risk per s.d. (GR/s.d.) of 1.88 and captured most of the predictive information of a model including morphometric spine fracture status, BMD and all WHO clinical risk factors (GR/s.d. 1.92). For comparison, this model provided more information than a model considering BMD and the WHO clinical risk factors (GR/s.d. 1.74). These findings confirm the value of age, BMD and spine fracture status for predicting fracture risk. PMID:24228164

  2. Predictive accuracy of risk scales following self-harm: multicentre, prospective cohort study.

    PubMed

    Quinlivan, Leah; Cooper, Jayne; Meehan, Declan; Longson, Damien; Potokar, John; Hulme, Tom; Marsden, Jennifer; Brand, Fiona; Lange, Kezia; Riseborough, Elena; Page, Lisa; Metcalfe, Chris; Davies, Linda; O'Connor, Rory; Hawton, Keith; Gunnell, David; Kapur, Nav

    2017-03-16

    BackgroundScales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking.AimsTo evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months.MethodA multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy.ResultsIn total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% (n = 145). Sensitivity ranged from 1% (95% CI 0-5) for the SAD PERSONS scale, to 97% (95% CI 93-99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2-47) for the Modified SAD PERSONS Scale to 47% (95% CI 41-53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50-0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69-0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk (P<0.001).ConclusionsRisk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm.

  3. Retinopathy Signs Improved Prediction and Reclassification of Cardiovascular Disease Risk in Diabetes: A prospective cohort study

    PubMed Central

    Ho, Henrietta; Cheung, Carol Y.; Sabanayagam, Charumathi; Yip, Wanfen; Ikram, Mohammad Kamran; Ong, Peng Guan; Mitchell, Paul; Chow, Khuan Yew; Cheng, Ching Yu; Tai, E. Shyong; Wong, Tien Yin

    2017-01-01

    CVD risk prediction in diabetics is imperfect, as risk models are derived mainly from the general population. We investigate whether the addition of retinopathy and retinal vascular caliber improve CVD prediction beyond established risk factors in persons with diabetes. We recruited participants from the Singapore Malay Eye Study (SiMES, 2004–2006) and Singapore Prospective Study Program (SP2, 2004–2007), diagnosed with diabetes but no known history of CVD at baseline. Retinopathy and retinal vascular (arteriolar and venular) caliber measurements were added to risk prediction models derived from Cox regression model that included established CVD risk factors and serum biomarkers in SiMES, and validated this internally and externally in SP2. We found that the addition of retinal parameters improved discrimination compared to the addition of biochemical markers of estimated glomerular filtration rate (eGFR) and high-se