Comparison of the two matched groups was performed using descriptive statistics to report central tendency statistics (mean and standard deviation) as well as bivariate analysis to identify the variables that had significant associations between the two matched groups. McNemar test was used to compare categorical variables (mortality, marital status, employment, crime history, addiction history, psychiatric medication history, suicide history, full-thickness burn, inhalation burn, domestic gas, flame, cardiopulmonary resuscitation (CPR) attempts, substance dependency). Paired t-test was applied to compare continuous variables (age, TBSA, length of stay, intensive care unit (ICU) stays, transfusion units and ventilator support). The conditional logistic regression (CLR) model to control possible confounders affecting mortality was used. The CLR permits the use of both continuous variables and categorical variables. Survival analysis using the Kaplan-Meier curve of survival was applied for the addicted and non-addicted groups (
14). Data analysis was performed using the SPSS software, version 15.0 (SPSS Inc., Chicago, Illinois). Aside from analysis of matched data, all admitted male burn patients during the observational period (October 2012-July 2013) were analyzed as the unmatched group in the BU. In fact, the current study reported two sets of measured data. The first dataset, included 152 patients organized in matched groups, and the second data set included 237 burn patients (unmatched group), that composed of 152 matched patients and another 85 patients that couldn`t be paired into matched groups. Statistical power analysis was conducted by G*power 3.1. A post-hoc power analysis was completed to determine the study power according to mortality proportions (π11 = 0.03, π12 = 0.46, π21 = 0.06 and π22 = 0.44) using inequality, two dependent groups (McNemar) method, so a power coefficient of 0.99 was achieved.