Figure 4
Primary analysis and sensitivity analysis of in-hospital mortality. The primary analysis was a propensity score matching that used the multiply-imputed dataset. The first sensitivity analysis was a cluster-exact propensity score matching that select 1:1 matched pairs of patients treated in the same institution and in the same injury period, to account for disparities between facilities. The second sensitivity analysis was a propensity score matching that used the naïve dataset without multiple imputation to test the robustness of the multiple imputations. The third sensitivity analysis tested the generalized linear mixed effects model used with the multiply-imputed datasets but without matching, to test the robustness of the propensity score matching. The other sensitivity analysis was a propensity score matching that used the Injury Severity Score for matching instead of the AIS score, and the analysis method itself was the same as the primary analysis. Outcomes were analyzed using the double-adjustment method. CI, confidence interval; ISS, Injury Severity Score; GLMM, generalized linear mixed effects model; MI, multiple imputation; OR, odds ratio; SAE, splenic artery embolization.
