Cardiac abnormalities in the acquired immunodeficiency syndrome. A prospective study with a clinical-pathological correlation in twenty-one adult patients

OBJECTIVE - To evaluate the cardiac abnormalities and their evolution during the course of the acquired immunodeficiency syndrome, as well as to correlate clinical and pathological data. METHODS - Twenty-one patients, admitted to the hospital with the diagnosis of acquired immunodeficiency syndrome, were prospectively studied and followed until their death. Age ranged from 19 to 42 years (17 males). ECG and echocardiogram were also obtained every six months. After death, macro- and microscopic examinations were also performed. RESULTS - The most frequent causes of referral to the hospital were: diarrhea or repeated pneumonias, tuberculosis, toxoplasmosis or Kaposi sarcoma. The most frequent findings were acute or chronic pericarditis (42%) and dilated cardiomyopathy (19%). Four patients died of cardiac problems: infective endocarditis, pericarditis with pericardial effusion, bacterial myocarditis and infection by Toxoplasma gondii. CONCLUSION - Severe cardiac abnormalities were the cause of death in some patients. In the majority of the patients, a good correlation existed between clinical and anatomical-pathological data. Cardiac evaluation was important to detect early manifestations and treat them accordingly, even in asymptomatic patients.

Congestive heart failure. Correlation between functional class and systolic and diastolic functions assessed by Doppler echocardiography

OBJECTIVE: To evaluate the influence of systolic or diastolic dysfunction, or both on congestive heart failure functional class. METHODS: Thirty-six consecutive patients with a clinical diagnosis of congestive heart failure with sinus rhythm, who were seen between September and November of 1998 answered an adapted questionnaire about tolerance to physical activity for the determination of NYHA functional class. The patients were studied with transthoracic Doppler echocardiography. Two groups were compared: group 1 (19 patients in functional classes I and II) and group 2 (17 patients in functional classes III and IV). RESULTS: The average ejection fraction was significantly higher in group 1 (44.84%±8.04% vs. 32.59%±11.48% with p=0.0007). The mean ratio of the initial/final maximum diastolic filling velocity (E/A) of the left ventricle was significantly smaller in group 1 (1.07±0.72 vs. 1.98±1.49 with p=0.03). The average maximum systolic pulmonary venous velocity (S) was significantly higher in group 1 (53.53cm/s ± 12.02cm/s vs. 43.41cm/s ± 13.55cm/s with p=0.02). The mean ratio of maximum systolic/diastolic pulmonary venous velocity was significantly higher in group 1 (1.52±0.48 vs. 1.08±0.48 with p=0.01). A predominance of pseudo-normal and restrictive diastolic patterns existed in group 2 (58.83% in group 2 vs. 21.06% in group 1 with p=0.03). CONCLUSION: Both the systolic dysfunction index and the patterns of diastolic dysfunction evaluated by Doppler echocardiography worsened with the evolution of congestive heart failure.

Estimation of statistical cure from cancer using population-based data

Dissertação de mestrado em Estatística

Epworth's sleepiness scale in outpatients with different values of arterial blood pressure

OBJECTIVE: To compare sleepiness scores of the Epworth scale in patients with different levels of arterial pressure when undergoing outpatient monitoring within the context of clinical evaluation. METHODS: A total of 157 patients selected for outpatient monitoring of arterial pressure during hypertension evaluation were divided into 3 groups: group 1 - normotensive; group 2 - hypertensive; group 3 - resistant hypertensive. For analysis, values > or = 11 were considered as associated with respiratory disturbances during sleep. RESULTS: Seventeen (10.8%) patients in group 1, 112 (71.3%) in group 2, and 28 (17.8%) in group 3, which was composed of aged, more severely hypertensive individuals, were analyzed. Groups were similar relative to sex and body mass index, but different in relation to systolic and diastolic pressure levels and age. Despite an absolute difference, no statistically significant difference occurred between Epworth scores and in the proportion of patients with values > or = 11 (5.9% vs. 18.8% vs. 212.4%; P=0.37). Despite the positive association between degree of sleepiness measured with the scale and the severity of the hypertension, no statistical significance occurred following control by age (p=0.18). CONCLUSION: A positive correlation exists between degree of sleepiness and hypertension severity. The absence of a statistical significance shown in the present study could be due to a beta type of error. Instruments that render this complaint into an objective finding could help in the pursuit of an investigation of respiratory disturbances during sleep in more severely hypertensive patients, and should therefore be studied better.

Correlations Between the Collagen Content of the Human Left Ventricular Myocardium, Measured by Biochemical and Morphometric Methods

OBJECTIVE: To assess, in myocardium specimens obtained from necropsies, the correlation between the concentration of hydroxyproline, measured with the photocolorimetric method, and the intensity of fibrosis, determined with the morphometric method. METHODS: Left ventricle myocardium samples were obtained from 45 patients who had undergone necropsy, some of them with a variety of cardiopathies and others without any heart disease. The concentrations of hydroxyproline were determined with the photocolorimetric method. In the histologic sections from each heart, the myocardial fibrosis was quantified by using a light microscope with an integrating ocular lens. RESULTS: A median of, respectively, 4.5 and 4.3 mug of hydroxyproline/mg of dry weight was found in fixed and nonfixed left ventricle myocardium fragments. A positive correlation occurred between the hydroxyproline concentrations and the intensity of fibrosis, both in the fixed (Sr=+0.25; p=0.099) and in the nonfixed (Sr=+0.32; p=0.03) specimens. CONCLUSION: The biochemical methodology was proven to be adequate, and manual morphometry was shown to have limitations that may interfere with the statistical significance of correlations for the estimate of fibrosis intensity in the human myocardium.

Correlation between turbidimetric and nephelometric methods of measuring C-reactive protein in patients with unstable angina or non-ST elevation acute myocardial infarction

OBJECTIVE: To evaluate the performance of the turbidimetric method of C-reactive protein (CRP) as a measure of low-grade inflammation in patients admitted with non-ST elevation acute coronary syndromes (ACS). METHODS: Serum samples obtained at hospital arrival from 68 patients (66±11 years, 40 men), admitted with unstable angina or non-ST elevation acute myocardial infarction were used to measure CRP by the methods of nephelometry and turbidimetry. RESULTS: The medians of C-reactive protein by the turbidimetric and nephelometric methods were 0.5 mg/dL and 0.47 mg/dL, respectively. A strong linear association existed between the 2 methods, according to the regression coefficient (b=0.75; 95% C.I.=0.70-0.80) and correlation coefficient (r=0.96; P<0.001). The mean difference between the nephelometric and turbidimetric CRP was 0.02 ± 0.91 mg/dL, and 100% agreement between the methods in the detection of high CRP was observed. CONCLUSION: In patients with non-ST elevation ACS, CRP values obtained by turbidimetry show a strong linear association with the method of nephelometry and perfect agreement in the detection of high CRP.

Behavior of inflammatory markers of myocardial injury in cardiac surgery: laboratory correlation with the clinical picture of postpericardiotomy syndrome

OBJECTIVE: To verify the association of serum markers of myocardial injury, such as troponin I, creatinine kinase, and creatinine kinase isoenzyme MB, and inflammatory markers, such as tumor necrosis factor alpha (TNF-alpha), C-reactive protein, and the erythrocyte sedimentation rate in the perioperative period of cardiac surgery, with the occurrence of possible postpericardiotomy syndrome. METHODS: This was a cohort study with 96 patients undergoing cardiac surgery assessed at the following 4 different time periods: the day before surgery (D0); the 3rd postoperative day (D3); between the 7th and 10th postoperative days (D7-10); and the 30th postoperative day (D30). During each period, we evaluated demographic variables (sex and age), surgical variables (type and duration , extracorporeal circulation), and serum dosages of the markers of myocardial injury and inflammatory response. RESULTS: Of all patients, 12 (12.5%) met the clinical criteria for a diagnosis of postpericardiotomy syndrome, and their mean age was 10.3 years lower than the age of the others (P=0.02). The results of the serum markers for tissue injury and inflammatory response were not significantly different between the 2 assessed groups. No significant difference existed regarding either surgery duration or extracorporeal circulation. CONCLUSION: The patients who met the clinical criteria for postpericardiotomy syndrome were significantly younger than the others were. Serum markers for tissue injury and inflammatory response were not different in the clinically affected group, and did not correlate with the different types and duration of surgery or with extracorporeal circulation.

O crescimento do sector bancário e a concessão de crédito às empresas : o caso de Angola

Mestrado em Ciências Empresariais

Desarrollos estadísticos para el procesamiento de información genómica masiva en agro-biotecnología. Statistical developments for processing massive genomic information in agro-biotechnology.

Nuevas biotecnologías, como los marcadores de la molécula de ADN, permiten caracterizar el genoma vegetal. El uso de la información genómica producida para cientos o miles de posiciones cromosómicas permite identificar genotipos superiores en menos tiempo que el requerido por la selección fenotípica tradicional. La mayoría de los caracteres de las especies vegetales cultivadas de importancia agronómica y económica, son controlados por poli-genes causantes de un fenotipo con variación continua, altamente afectados por el ambiente. Su herencia es compleja ya que resulta de la interacción entre genes, del mismo o distinto cromosoma, y de la interacción del genotipo con el ambiente, dificultando la selección. Estas biotecnologías producen bases de datos con gran cantidad de información y estructuras complejas de correlación que requieren de métodos y modelos biométricos específicos para su procesamiento. Los modelos estadísticos focalizados en explicar el fenotipo a partir de información genómica masiva requieren la estimación de un gran número de parámetros. No existen métodos, dentro de la estadística paramétrica capaces de abordar este problema eficientemente. Además los modelos deben contemplar no-aditividades (interacciones) entre efectos génicos y de éstos con el ambiente que son también dificiles de manejar desde la concepción paramétrica. Se hipotetiza que el análisis de la asociación entre caracteres fenotípicos y genotipos moleculares, caracterizados por abundante información genómica, podría realizarse eficientemente en el contexto de los modelos mixtos semiparamétricos y/o de métodos no-paramétricos basados en técnicas de aprendizaje automático. El objetivo de este proyecto es desarrollar nuevos métodos para análisis de datos que permitan el uso eficiente de información genómica masiva en evaluaciones genéticas de interés agro-biotecnológico. Los objetivos específicos incluyen la comparación, respecto a propiedades estadísticas y computacionales, de estrategias analíticas paramétricas con estrategias semiparamétricas y no-paramétricas. Se trabajará con aproximaciones por regresión del análisis de loci de caracteres cuantitativos bajo distintas estrategias y escenarios (reales y simulados) con distinto volúmenes de datos de marcadores moleculares. En el área paramétrica se pondrá especial énfasis en modelos mixtos, mientras que en el área no paramétrica se evaluarán algoritmos de redes neuronales, máquinas de soporte vectorial, filtros multivariados, suavizados del tipo LOESS y métodos basados en núcleos de reciente aparición. La propuesta semiparamétrica se basará en una estrategia de análisis en dos etapas orientadas a: 1) reducir la dimensionalidad de los datos genómicos y 2) modelar el fenotipo introduciendo sólo las señales moleculares más significativas. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, nuevas herramientas y procedimientos de análisis que permitan maximizar la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos y su aplicación en desarrollos agro-biotecnológicos.

Estrategias estadístico-computacionales avanzadas para análisis de expresión de proteínas/genes en cáncer. Advanced statistical and computational strategies for protein/gene expression analysis in cancer.

El objetivo de este proyecto, enmarcado en el área de metodología de análisis en bioingeniería-biotecnología aplicadas al estudio del cancer, es el análisis y caracterización a través modelos estadísticos con efectos mixtos y técnicas de aprendizaje automático, de perfiles de expresión de proteínas y genes de las vías metabolicas asociadas a progresión tumoral. Dicho estudio se llevará a cabo mediante la utilización de tecnologías de alto rendimiento. Las mismas permiten evaluar miles de genes/proteínas en forma simultánea, generando así una gran cantidad de datos de expresión. Se hipotetiza que para un análisis e interpretación de la información subyacente, caracterizada por su abundancia y complejidad, podría realizarse mediante técnicas estadístico-computacionales eficientes en el contexto de modelos mixtos y técnias de aprendizaje automático. Para que el análisis sea efectivo es necesario contemplar los efectos ocasionados por los diferentes factores experimentales ajenos al fenómeno biológico bajo estudio. Estos efectos pueden enmascarar la información subycente y así perder informacion relavante en el contexto de progresión tumoral. La identificación de estos efectos permitirá obtener, eficientemente, los perfiles de expresión molecular que podrían permitir el desarrollo de métodos de diagnóstico basados en ellos. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, herramientas y procedimientos de análisis que maximicen la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos/proteómicos que permitan extraer información biológica relevante pertinente al análisis, clasificación o predicción de cáncer, el diseño de tratamientos y terapias específicos y el mejoramiento de los métodos de detección como así tambien aportar al entendimieto de la progresión tumoral mediante análisis computacional intensivo.

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Application of multivariate statistical process control to fuel cell manufacturing

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

Statistical Characteristics of Flash Flood in Georgia

Results are presented from the analysis of observations data on flash flood in Georgia over a period of 45 years, from 1961 to 2005, provided of the of Hydro-meteorology Service of Georgia.