PREVALENCE AND FACTORS ASSOCIATED WITH THE PERFORMANCE OF MAMMOGRAPHY AND PAP SMEAR TEST

Objective: To estimate the prevalence and factors associated with the performance of mammography and pap smear test in women from the city of Maringá, Paraná. Methods: Population-based cross-sectional study conducted with 345 women aged over 20 years in the period from March 2011 to April 2012. An interview was carried out using a questionnaire proposed by the Ministry of Health, which addressed sociodemographic characteristics, risk factors for chronic noncommunicable diseases and issues related to mammographic and pap screening. Data were analyzed using bivariate analysis, crude analysis with odds ratio (OR) and chi-squared test using Epi Info 3.5.1 program; multivariate analysis using logistic regression was performed using the software Statistica 7.1, with a significance level of 5% and a confidence interval of 95%. Results: The mean age of the women was 52.19 (±5.27) years. The majority (56.5%) had from 0 to 8 years of education. Additionally, 84.6% (n=266) of the women underwent pap smear and 74.3% (n=169) underwent mammography. The lower performance of pap smear test was associated with women with 9-11 years of education (p=0.01), and the lower performance of mammography was associated with women without private health insurance (p<0.01). Conclusion: The coverage of mammography and pap smear test was satisfactory among the women from Maringá, Paraná. Low education level and women who depended on the public health system presented lower performance of mammography.

Use of acoustic telemetry techniques to understand the individual variability in movement ecology of juvenile lemon sharks, Negaprion brevirostris, in natural conditions, around Bimini Islands, Bahamas: a comparison study with preliminary personality traits observed in mesocosms

Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Satisfação na educação à distância em uma disciplina semipresencial na área de saúde

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Ciências da Saúde, Programa de Pós-Graduação em Ciências da Saúde, 2016.

Trastornos gastrointestinales funcionales en menores de dos años: prevalencia y factores asociados en una IPS Bogotá 2015 - 2016

Antecedentes: Los trastornos gastrointestinales funcionales de la infancia (TGFI) son manifestaciones gastrointestinales crónicas en cualquier parte del tubo digestivo sin daño estructural o bioquímico los cuales se pueden clasificar según los criterios de ROMA III. Se desconoce su prevalencia en niños latinoamericanos menores de 4 años. Objetivos: Estimar la prevalencia de los TGFI y cada una de sus entidades en menores de 2 años y explorar sus factores asociados. Metodología: Estudio corte trasversal con muestra aleatoria (n=323) tomada de la población de una institución de salud en la ciudad de Bogotá, realizando mediante encuesta diligenciada por los padres. El análisis se realizó por medio del software SPSS© utilizando estadística descriptiva y análisis bivariado, como medida de asociación se calculó las Razones de Disparidad (RD) con IC95%. Resultados: Se encontró una prevalencia de TGFI de 22.1%, diarrea funcional 14.6%, disquecia 12%, regurgitación 9.2%, estreñimiento 3.3%, vómito cíclico 2%, cólico infantil 1.6% y rumiación 0%. La administración de tetero durante la estancia hospitalaria neonatal se asocia con vómito cíclico RD= 6 IC 95% (1.076 – 33.447) p=0.021. La administración de formula infantil durante los primeros 6 meses de vida se asocia con diarrea funcional RD= 0.348 IC 95% (0.149 – 0.813) p=0.012 Conclusiónes: Los TGFI son una causa frecuente de molestias en los menores de 2 años de edad. Sugerimos realizar la validación del cuestionario “questionnaire on infant/toddler gastrointestinal symptoms rome version III” con el fin de mejorar la validez y precisión de los hallazgos en estudios futuros.

Factores asociados a respuesta de abatacept subcutaneo en artritis reumatoide

INTRODUCCION Dado que la artritis reumatoide es la artropatía inflamatoria más frecuente en el mundo, siendo altamente discapacitante y causando gran impacto de alto costo, se busca ofrecer al paciente opciones terapéuticas y calidad de vida a través del establecimiento de un tratamiento oportuno y eficaz, teniendo presentes aquellos predictores de respuesta previo a instaurar determinada terapia. Existen pocos estudios que permitan establecer aquellos factores de adecuada respuesta para inicio de terapia biológica con abatacept, por lo cual en este estudio se busca determinar cuáles son esos posibles factores. METODOLOGIA Estudio analítico de tipo corte transversal de 94 pacientes con diagnóstico de AR, evaluados para determinar las posibles variables que influyen en la respuesta a terapia biológica con abatacept. Se incluyeron 67 de los 94 pacientes al modelo de regresión logística, que son aquellos pacientes en que fue posible medir la respuesta al tratamiento (respuesta EULAR) a través de la determinación del DAS 28 y así discriminar en dos grupos de comparación (respuesta y no respuesta). DISCUSION DE RESULTADOS La presencia de alta actividad de la enfermedad al inicio de la terapia biológica, aumenta la probabilidad de respuesta al tratamiento respecto al grupo con baja/moderada actividad de la enfermedad; OR 4,19 - IC 95%(1,18 – 14.9), (p 0,027). La ausencia de erosiones óseas aumenta la probabilidad de presentar adecuada respuesta a la terapia biológica respecto aquellos con erosiones, con un OR 3,1 (1,01-9,55), (p 0,048). Niveles de VSG y presencia de manifestaciones extra-articulares son otros datos de interés encontrados en el análisis bivariado. Respecto a las variables o características como predictores de respuesta al tratamiento con abatacept, se encuentran estudios que corroboran los hallazgos de este estudio, respecto al alto puntaje del DAS 28 al inicio de la terapia (9, 12). CONCLUSIONES Existen distintas variables que determinan la respuesta a los diferentes biológicos para manejo de AR. Es imprescindible evaluar dichos factores de manera individual con el fin de lograr de manera efectiva el control de la enfermedad y así mejorar la calidad de vida del individuo (medicina personalizada). Existen variables tales como la alta actividad de la enfermedad y la ausencia de erosiones como predictores de respuesta en la terapia con abatacept.

Factores de riesgo asociados al desarrollo de bacteriemia en pacientes adultos cirróticos hospitalizados

Introducción: La Bacteriemia en pacientes cirróticos es una causa importante de morbimortalidad, en gran parte favorecida por la especial vulnerabilidad de esta población ante procesos infecciosos. El objetivo fue determinar los factores asociados al desarrollo de bacteriemia primaria y secundaria en pacientes con Cirrosis, hospitalizados en la Fundación Cardioinfantil – Instituto de Cardiología entre 01 enero de 2010 y 31 enero de 2016. Materiales y Métodos: Estudio de casos y controles en pacientes mayores de 18 años con cirrosis hepática conocida o confirmada durante la hospitalización. Se realizó un análisis descriptivo, un análisis bivariado para determinar las diferencias entre los casos y los controles con respecto a las variables independientes un análisis de asociación mediante un modelo de regresión logística no condicional con variable dependiente bacteriemia. Los resultados se expresan en odds ratios con intervalos de confianza al 95%. Resultados: Las condiciones asociadas a bacteriemia como factores de riesgo fueron: Enfermedad renal crónica OR 9,1 (IC 95% 2,4-34), Escala Meld > 10 puntos OR 4,0 (IC 95% 2,-34), Infección previa OR 7,2 (IC 95% 2,1-24), presencia de catéter central OR 12,0 (IC 95% 1,8-80), presencia de sonda vesical OR 21,1 (IC 95% 1,6-276), estudio endoscópico OR 3,9 (IC 95% 1,1-14). Discusión: Factores relacionados con las condiciones clínicas del paciente evaluadas por las escalas Meld y Child-Pugh, el antecedente de infección previa y la presencia de dispositivos para monitorear el estado del paciente aumentan el riesgo de bacteriemia en pacientes hospitalizados con cirrosis.

Health Problems of Institutionalized Elderly

Introduction: human aging is marked by a decrease in the performance of some daily tasks, some even considered banal and imperceptibly when this limitation is followed by chronic diseases, the elderly becomes a source of concern for the family. Objective: identifying the health problems of the elderly living in long-stay institutions from self-reported diseases. This is a descriptive and quantitative study, conducted in northeastern Brazil capital, involving 138 elderly. For data collection we used a questionnaire containing demographic variables, institutional and related to self-reported health problems. Data were evaluated using bivariate analysis and association chi-square. Results: predominance of women was found (61.6%), aged 60-69 years old (39.1%), coming from the state capital (51.4%), and institutional permanence time between 1-5 years (77.5%). The most frequent diseases were related to the cardiovascular system (15.9%) and endocrine, nutritional and metabolic diseases (9.4%). It showed a significant association between self-reported diseases and the age of the elderly (p=0.047). Conclusion: it is expected to raise awareness among health professionals to provide a better assistance to the institutionalized elderly focusing on the real needs of these persons.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Modelling and Analysis of Bivariate Lifetime Data using Reversed Hazard Rates

Department of Statistics, Cochin University of Science and Technology

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table has n rows and m columns and all probabilities are non-null. This kind of table can be seen as an element in the simplex of n · m parts. In this context, the marginals are identified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclidean elements of the Aitchison geometry of the simplex can also be translated into the table of probabilities: subspaces, orthogonal projections, distances. Two important questions are addressed: a) given a table of probabilities, which is the nearest independent table to the initial one? b) which is the largest orthogonal projection of a row onto a column? or, equivalently, which is the information in a row explained by a column, thus explaining the interaction? To answer these questions three orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independent two-way tables and fully dependent tables representing row-column interaction. An important result is that the nearest independent table is the product of the two (row and column)-wise geometric marginal tables. A corollary is that, in an independent table, the geometric marginals conform with the traditional (arithmetic) marginals. These decompositions can be compared with standard log-linear models. Key words: balance, compositional data, simplex, Aitchison geometry, composition, orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure, contingency table

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

An analysis of quit and dismissal determinants between 1988 and 1999 using the bivariate probit model

Excessive labor turnover may be considered, to a great extent, an undesirable feature of a given economy. This follows from considerations such as underinvestment in human capital by firms. Understanding the determinants and the evolution of turnover in a particular labor market is therefore of paramount importance, including policy considerations. The present paper proposes an econometric analysis of turnover in the Brazilian labor market, based on a partial observability bivariate probit model. This model considers the interdependence of decisions taken by workers and firms, helping to elucidate the causes that lead each of them to end an employment relationship. The Employment and Unemployment Survey (PED) conducted by the State System of Data Analysis (SEADE) and by the Inter-Union Department of Statistics and Socioeconomic Studies (DIEESE) provides data at the individual worker level, allowing for the estimation of the joint probabilities of decisions to quit or stay on the job on the worker’s side, and to maintain or fire the employee on the firm’s side, during a given time period. The estimated parameters relate these estimated probabilities to the characteristics of workers, job contracts, and to the potential macroeconomic determinants in different time periods. The results confirm the theoretical prediction that the probability of termination of an employment relationship tends to be smaller as the worker acquires specific skills. The results also show that the establishment of a formal employment relationship reduces the probability of a quit decision by the worker, and also the firm’s firing decision in non-industrial sectors. With regard to the evolution of quit probability over time, the results show that an increase in the unemployment rate inhibits quitting, although this tends to wane as the unemployment rate rises.

On expectation of life in bivariate survival analysis

Includes bibliography

Bivariate meta-analysis of predictive values of diagnostic tests can be an alternative to bivariate meta-analysis of sensitivity and specificity

Meta-analysis of predictive values is usually discouraged because these values are directly affected by disease prevalence, but sensitivity and specificity sometimes show substantial heterogeneity as well. We propose a bivariate random-effects logitnormal model for the meta-analysis of the positive predictive value (PPV) and negative predictive value (NPV) of diagnostic tests.

Flood frequency analysis by a bivariate model based on copulas

La adecuada estimación de avenidas de diseño asociadas a altos periodos de retorno es necesaria para el diseño y gestión de estructuras hidráulicas como presas. En la práctica, la estimación de estos cuantiles se realiza normalmente a través de análisis de frecuencia univariados, basados en su mayoría en el estudio de caudales punta. Sin embargo, la naturaleza de las avenidas es multivariada, siendo esencial tener en cuenta características representativas de las avenidas, tales como caudal punta, volumen y duración del hidrograma, con el fin de llevar a cabo un análisis apropiado; especialmente cuando el caudal de entrada se transforma en un caudal de salida diferente durante el proceso de laminación en un embalse o llanura de inundación. Los análisis de frecuencia de avenidas multivariados han sido tradicionalmente llevados a cabo mediante el uso de distribuciones bivariadas estándar con el fin de modelar variables correlacionadas. Sin embargo, su uso conlleva limitaciones como la necesidad de usar el mismo tipo de distribuciones marginales para todas las variables y la existencia de una relación de dependencia lineal entre ellas. Recientemente, el uso de cópulas se ha extendido en hidrología debido a sus beneficios en relación al contexto multivariado, permitiendo superar los inconvenientes de las técnicas tradicionales. Una copula es una función que representa la estructura de dependencia de las variables de estudio, y permite obtener la distribución de frecuencia multivariada de dichas variables mediante sus distribuciones marginales, sin importar el tipo de distribución marginal utilizada. La estimación de periodos de retorno multivariados, y por lo tanto, de cuantiles multivariados, también se facilita debido a la manera en la que las cópulas están formuladas. La presente tesis doctoral busca proporcionar metodologías que mejoren las técnicas tradicionales usadas por profesionales para estimar cuantiles de avenida más adecuados para el diseño y la gestión de presas, así como para la evaluación del riesgo de avenida, mediante análisis de frecuencia de avenidas bivariados basados en cópulas. Las variables consideradas para ello son el caudal punta y el volumen del hidrograma. Con el objetivo de llevar a cabo un estudio completo, la presente investigación abarca: (i) el análisis de frecuencia de avenidas local bivariado centrado en examinar y comparar los periodos de retorno teóricos basados en la probabilidad natural de ocurrencia de una avenida, con el periodo de retorno asociado al riesgo de sobrevertido de la presa bajo análisis, con el fin de proporcionar cuantiles en una estación de aforo determinada; (ii) la extensión del enfoque local al regional, proporcionando un procedimiento completo para llevar a cabo un análisis de frecuencia de avenidas regional bivariado para proporcionar cuantiles en estaciones sin aforar o para mejorar la estimación de dichos cuantiles en estaciones aforadas; (iii) el uso de cópulas para investigar tendencias bivariadas en avenidas debido al aumento de los niveles de urbanización en una cuenca; y (iv) la extensión de series de avenida observadas mediante la combinación de los beneficios de un modelo basado en cópulas y de un modelo hidrometeorológico. Accurate design flood estimates associated with high return periods are necessary to design and manage hydraulic structures such as dams. In practice, the estimate of such quantiles is usually done via univariate flood frequency analyses, mostly based on the study of peak flows. Nevertheless, the nature of floods is multivariate, being essential to consider representative flood characteristics, such as flood peak, hydrograph volume and hydrograph duration to carry out an appropriate analysis; especially when the inflow peak is transformed into a different outflow peak during the routing process in a reservoir or floodplain. Multivariate flood frequency analyses have been traditionally performed by using standard bivariate distributions to model correlated variables, yet they entail some shortcomings such as the need of using the same kind of marginal distribution for all variables and the assumption of a linear dependence relation between them. Recently, the use of copulas has been extended in hydrology because of their benefits regarding dealing with the multivariate context, as they overcome the drawbacks of the traditional approach. A copula is a function that represents the dependence structure of the studied variables, and allows obtaining the multivariate frequency distribution of them by using their marginal distributions, regardless of the kind of marginal distributions considered. The estimate of multivariate return periods, and therefore multivariate quantiles, is also facilitated by the way in which copulas are formulated. The present doctoral thesis seeks to provide methodologies that improve traditional techniques used by practitioners, in order to estimate more appropriate flood quantiles for dam design, dam management and flood risk assessment, through bivariate flood frequency analyses based on the copula approach. The flood variables considered for that goal are peak flow and hydrograph volume. In order to accomplish a complete study, the present research addresses: (i) a bivariate local flood frequency analysis focused on examining and comparing theoretical return periods based on the natural probability of occurrence of a flood, with the return period associated with the risk of dam overtopping, to estimate quantiles at a given gauged site; (ii) the extension of the local to the regional approach, supplying a complete procedure for performing a bivariate regional flood frequency analysis to either estimate quantiles at ungauged sites or improve at-site estimates at gauged sites; (iii) the use of copulas to investigate bivariate flood trends due to increasing urbanisation levels in a catchment; and (iv) the extension of observed flood series by combining the benefits of a copula-based model and a hydro-meteorological model.