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).