Aldo Reigosa

Factores Cardiometabólicos en una Comunidad de Valencia, Venezuela

Objetivo Evaluar la prevalencia de factores cardiometabolicos en residentes de una comunidad situada al norte de la ciudad de Valencia-Venezuela y establecer los patrones de asociacion de las alteraciones cardiometabolicas. Metodos Se estudiaron 100 individuos con edades entre 19-77 anos. Se determino el peso, talla, circunferencia abdominal, presion arterial, glicemia, perfil lipidico e insulina. Se estimo la resistencia a la insulina a traves de HOMA. Resultados Los cinco factores cardiometabolicos mas prevalentes fueron HDLc baja (90 %), sobrepeso/obesidad (78 %), obesidad abdominal (68 %), hipercolesterolemia (59 %) y resistencia a la insulina (54,8 %). La frecuencia de valores bajos de HDLc fue significativamente superior en las mujeres (p<0,01). El grupo etario que demostro mayor prevalencia de factores cardiometabolicos fue el comprendido entre 35 y 55 anos. La prevalencia de sindrome metabolico fue de 57 %, predominando en las mujeres. La mayoria de los sujetos presento tres a cuatro factores asociados. Los factores comunes en los diferentes patrones de asociacion identificados fueron el sobrepeso/obesidad, hipercolesterolemia y antecedentes familiares entre los factores tradicionales y en el caso de los no tradicionales la obesidad abdominal y la HDLc baja. El indice de masa corporal y la resistencia a la insulina predijeron el sindrome metabolico en el grupo evaluado. Conclusion Se observo una alta prevalencia de factores cardiometabolicos en la comunidad estudiada asi como una elevada tendencia a la asociacion simultanea de varios de ellos, indicando la necesidad de ejecutar programas enfocados a reducir el riesgo cardiometabolico.

Cardiovascular risk profile and insulin resistance according body mass index, waist circumference and hypertriglyceridemic waist in adult subjects

BACKGROUND Insulin plays a determinant role in the individual metabolic profile. Obesity, the most common cause of insulin resistance (IR), can be diagnosed by body mass index (BMI). Waist circumference (WC), specifically, measures accumulation of abdominal fat. The cardiovascular risk of an individual is strongly related to a combination of abdominal obesity with hypertriglyceridemia or hypertriglyceridemic waist (HTW). AIM To assess the metabolic profile of cardiovascular risk and RI according to BMI, WC and HTW in adult patients. MATERIAL AND METHODS Weight, height, BMI, blood pressure (BP), WC, HTW, blood glucose, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides and insulin were assessed and IR calculated by the homeostasis model assessment (HOMA) in 63 females aged 46+/-11 years and 12 males aged 4 7+/- 10 years. RESULTS Differences in weight, WC, BP, lipids, glucose, insulin and HOMA, were observed as BMI increased. When patients were grouped according to WC, there were significant differences only in systolic pressure, triglycerides, insulin and HOMA. Individuals with HTW had a more adverse metabolic profile than those without HTW or with only high WC. A multiple regression equation determined that body mass index, total cholesterol and diastolic blood pressure were independent predictors of insulin resistance. CONCLUSIONS Patients with HTW displayed an unfavorable cardiac risk profile.

Automatic Intraductal Breast Carcinoma Classification Using a Neural Network-Based Recognition System

Abstract: A contour‐based automatic recognition system was applied to classify intraductal breast carcinoma into high nuclear grade and low nuclear grade in a digitized histologic image. The image discriminating characteristics were selected by their invariability condition to rotation and translation. They were acquired from cellular contours information. The totally interconnected multilayer perceptron network architecture was selected, and it was trained with the error back propagation algorithm. Forty cases were analyzed by the system and the diagnoses were compared with that of pathologist consensus, obtaining agreement in 97.5% (p < .00001 of cases). The system may become a very useful tool for the pathologist in the definitive classification of intraductal carcinoma.

Interactive edge detection and tracing in cellular nuclei images using B-splines and neural network

During the analysis of histological images of cancer tissue, the specialist must carefully look for cellular shapes and sizes, as well as orientation, in order to make a diagnosis. This work develops an interactive auxiliary method to help the physician to quickly trace the edge for each cell, as selected by him (her) in a microscopic image. The method is based in a gradient and gray-level study of the image, along a series of radials centered in a selected cell. The analysis outputs a set of points from which the edge points are selected. The edge tracing is then performed using the B-spline method.