Statistics. Differences between continuous variables with normal distribution will be examined by Student's t test. The test of Wilcoxon rank sum will be used when continuous variables have failed in normality tests. To analyze categorical variables X2 will be used by Fisher's exact test or Yates correction. A two-tailed test with a p value < 0.05 will be considered as statistically significant. Logistic regression analysis will be used to select independent predictors in those variables that by univariate regression analysis had obtained a p value < 0.01. To avoid confusion, the relationship between historical variables for atherosclerosis and cardiovascular events will be examined through logistic regression and multivariate analysis. Cox proportional risk multivariate model will assess the relationship between each of these variables. Kaplan-Meier survival curves and Cox proportional risk model will be used for adjust survival analysis. A p value < 0.05 will be considered as statistically significant. Data will be expressed as percentages, mean, standard deviation, odds ratio and CI.