Bivariate comparisons were made using Pearson's x 2 test for categorical variables and Student's t-test for continuous variables. As a measure of association, the relative risk (OR) and 95% CI were calculated. Logistic regression was applied in the multivariate analysis for dichotomous adverse outcomes. To determine the variables to be included in the multivariate analysis, the procedure described by Sun et al. 8 was followed. Intermediate variables were discarded. We ran two stepwise models, one backward and another forward, including variables with P, 0.2. 9, 10 We constructed a list of predictors of mortality identified in other studies. Using information from stepwise models and the list of predictors, a saturated model was built, and by using a heuristic approach, variables that did not change the coefficient of the bundles by more than 10% were discarded, in order to construct a parsimonious model retaining all important confounders.