Statistical analysis
anxiety
REGRESSION, SECONDARY
We first computed descriptive statistics to describe the sample and compare the participants assigned to the 3 treatment conditions [using a Fisher’s exact test or Chi-square test as appropriate for the categorical variables, and analysis of variance (ANOVA) F-test or Kruskal–Wallis test as appropriate for the continuous variables] to determine if they were equivalent at baseline. Then, to test the primary hypothesis, we used a mixed-effects random-intercept linear regression with treatment condition as the primary independent variable and the APAIS and VNRS scores as the dependent variable. [Mean values of preoperative anxiety by the APAIS and VNRS (95% confidence interval) before and after receiving study medication in pregabalin, diazepam and placebo groups, the changes in preoperative anxiety by the APAIS and VNRS (95% confidence interval) from baseline and after receiving study medication in each group, and the differences in changes between groups (95% confidence interval) were analyzed using mixed-effects random-intercept linear regression to account appropriately for the repeated measures.] To examine the effects of treatment condition on the secondary outcome variables, we used Kruskal–Wallis and Rank Sum test to analyze sleep quality and Chi-square test for sedation level among the 3 groups. 