Background: While prior data have suggested worse outcomes in women after acute type A aortic dissection (ATAAD) repair when compared to men, results have been inconsistent across studies over time. This study sought to evaluate the impact of sex on short- and long-term outcomes after ATAAD repair. Methods: This was a retrospective study utilizing an institutional database of ATAAD repairs from 2007 to 2021. Patients were stratified according to sex. Kaplan-Meier survival estimation and multivariable Cox regression were performed. Supplementary analysis using propensity score matching was also performed. Results: Of the 601 patients who underwent ATAAD repair, 361 were males (60.1%) and 240 (39.9%) were females. Females were significantly older, more likely to have hypertension, and more likely to have chronic lung disease. Females were also significantly more likely than males to undergo hemiarch replacement, while males were significantly more likely than females to undergo total arch replacement and frozen elephant trunk. Operative mortality was 9.4% among males and 13.8% among females, though this was not a statistically significant difference (p=0.098). Postoperative complications were comparable between groups. Kaplan-Meier survival estimates were similar for men and women, and, on multivariable Cox regression, sex was not significantly associated with long-term survival (HR 1.00, 95% CI: 0.73, 1.37, p=0.986). Outcomes remained comparable after supplementary propensity score matched analysis. Conclusion: ATAAD repair can be performed with comparable short-term and long-term outcomes in both men and women.

Objective The Model for End- Stage Liver Disease (MELD) score is a composite number of physiologic parameters and likely has non-linear effects on operative outcomes. . We use machine learning to evaluate the relationship between MELD score and outcomes of cardiac surgery. Methods All STS indexed elective cardiac surgical procedures at our institution between 2011 and 2018 were included. MELD score was retrospectively calculated. Logistic regression models and an imbalanced random forest classifier was created on operative mortality using 30 preoperative characteristics. Cox regression models and random forest survival models were created for long-term survival. Variable importance analysis (VIMP) was conducted to rank variables by predictive power. Linear and machine learned models were compared with their receiver operating characteristic (ROC) and Brier score respectively. Results The patient population included 3,872 individuals. Operative mortality was 1.7% and 5-year survival was 82.1%. MELD score was the 4th largest positive predictor on VIMP analysis for both operative long-term survival and the strongest negative predictor for operative mortality. The logistic model ROC area was 0.762, compared to the random forest classifier ROC of 0.674. The Brier score of the random forest survival model was larger (worse) than the cox regression starting at 2 years and continuing throughout the study period. Conclusions MELD score and other continuous variables had high degrees of non-linearity to mortality. This is demonstrated by the fact that MELD score was not significant in the cox multivariable regression but was strongly important in the random forest survival model.