Statistical analysis
Statistical analysis was performed using GraphPad Prism 5.03 (GraphPad
Software, Inc., San Diego, CA), and R 3.4.4 (R Core Team, Vienna,
Austria). Propensity matching was performed to identify a two to one
control population for the patients who experienced a stroke. This was
performed using the ‘nearest-neighbour’ method whereby a control patient
whose propensity score is closest to that of a patient returning to
theatre is identified. Patients were matched on: age, sex, LV function,
BMI, operation priority, operation category and logistic EuroSCORE. If
multiple control patients have propensity scores that are equally close,
one of these control subjects is selected at random. Standardised
difference of means was calculated for both continuous and categorical
variables in order to ensure that the frequency of a variable was
equally balanced between the mini-bypass and matched populations.
The Kaplan-Meier method was used to plot the patient survival rates,
with the log-rank (Mantel-Cox) test used to compare groups. Univariate
analyses were performed. For comparison of groups, continuous variables
were analysed with the Mann-Whitney U test if not normally distributed
and with the Students t-test if normally distributed. Categorical
variables were analysed with Fisher’s exact test. p <
0.05 was considered statistically significant.