Statistical methods and analysis
The cohort was stratified by their racial/ethnicity background in whites or Caucasians, black or African American, Hispanic, and others to assess baseline characteristics and outcomes comparatively. Sampling weights provided by the NIS were used for national estimations. TEVAR incidence rates were calculated for White, Black, and Hispanic patients using race-specific US Census population data for each year (Supplementary Table 2 ). Univariate comparison between groups was performed with Pearson Chi2 test for categorical variables. Continuous data, including patient age, hospital length of stay, and total charges, were compared using the Kruskal-Wallis or ANOVA after testing for normality using the Shapiro–Wilk test. Bonferroni correction and Tukey’s multiple comparison adjustment prevented Type I error. We have four groups which mean six pairwise; the significance value of p used was less than 0.05/6=0.008 to reject the null hypothesis. The primary outcome was in-hospital mortality. Secondary outcomes included complications identified through ICD codes (Supplementary Table 3 ) and resources utilization, such as length of stay and hospital charges. A mixed-effects multivariable logistic regression assessed the relationship between race and the primary outcome, using hospitals as the random effect to account for interhospital variability. Adjusting covariates were selected through a correlation matrix. R (4.0.0 ’Arbor Day’) was utilized for the analysis.