Statistical Analysis
Continuous variables were expressed as means and standard deviations if normally distributed or median and range for skewed distributions. Categorical variables were expressed as frequencies and proportions. Differences between groups were evaluated using the χ2 test or Fisher’s exact test for categorical variables as appropriate and independent samples Student t test or the Mann-Whitney U test for continuous variables depending on the distribution. Survival curves of the primary end point of all-cause mortality were constructed with Kaplan-Meier methodology. Due to limited number of events, the propensity score adjusted proportional hazards model was fit with only resident/junior attending vs senior attending status and propensity scores incorporated as covariates to evaluate the adjusted risk. Propensity scores were calculated using logistic regression for resident/junior attending cases adjusting for preoperative comorbidities including age, gender, ejection fraction, diabetes, dialysis dependent, cerebral vascular accident, chronic obstructive lung disease, preoperative intubation, peripheral vascular disease, NYHA classification III or IV, prosthetic aortic valve endocarditis, causative organism, as well as operative details such as aorto-mitral curtain reconstruction, fistula repair, pulmonary homograft use, ascending aorta replacement, mitral valve repair, mitral valve replacement, tricuspid valve repair, coronary artery bypass grafting (the C-statistic 0.81). Proportional hazards assumption was evaluated and valid. We also conducted the sensitivity analysis categorizing the groups between trainee vs attending cases by adding junior attending cases to senior attending cases and the finds remained the same. All tests were two-tailed and an alpha level of 0.05 was considered statistically significant. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, North Carolina).