Stata for windows software

To process the collected variables, we built a database using an Excel spreadsheet and exported the data for analysis by using the Stata for Windows software package (version 11.0). We performed a descriptive analysis of the data, estimating the means, standard deviations, medians, and interquartile ranges, as well as absolute and relative frequencies, with their respective 95% confidence intervals (95% CIs). Differences in the frequency distributions of the qualitative (categorical) variables were analyzed by the Chi-square test.
We estimated the association of study variables with QOL by the prevalence ratio (PR) and the corresponding interval estimates (95% CIs) by Poisson regression analysis. For adjusted analyses, we used hierarchized modeling (Fig 1). In the adjusted model, variables with p < 0.10 were retained in each block, even when this value was changed by the inclusion of variables from subsequent blocks. An alpha level of 5% was adopted as the criterion for statistical significance. In all analyses, we considered the complex sample design effect (stratified and cluster sample) using the svy commands.

Statistical analyses were done using STATA for windows software (version SE/11; Stata corp, Texas USA). Where medians are used, interquartile range (IQR) is presented. Statistical testing was considered significant at the 5% significance level. Z-tests were used to compare differences in proportions between blood culture yield and mortality between the 2 cohorts. Univariate and multivariate logistic regression analysis were performed to identify potential factors associated with case-fatality and reported as odds ratios with 95% confidence intervals. Factors identified as significant by univariate analysis were included in the multivariate analysis. Incidence rates (IR) and incidence rate ratios (IRR) with their corresponding 95% confidence intervals were used to describe incidence of BSI in the 2009-10 cohort.