Statistical analysis
For the descriptive analysis, Shapiro-Wilk test was used to determine
normality of the variables for n < 50, while
Kolmogorov-Smirnov test was used to determine normality of the variables
for n ≥ 50. Normally distributed continuous variables were reported as
mean and standard deviation (SD). Ordinal variables and non-normally
distributed continuous variables were reported as median and
inter-quartile range (IQR) values. Categorical variables were reported
as frequencies and percentages.
For the analysis for plasma concentrations and bleeding events, patients
were categorized into four classes (Class I, II, III and IV) based on
equal quartiles of the populations’ range of plasma concentrations
adapted from Testa et al [12, 13], with Class I corresponding to the
group of patients whom plasma concentrations fall within the lowest
quartile and Class IV corresponding to the group of patients whom plasma
concentrations fall within the highest quartile.
Statistical tests were performed using the Independent-sample’s t-test
for normally distributed continuous variables, Mann-Whitney U test for
ordinal variables and non-normally distributed continuous variables, and
Chi-square test or Fisher’s exact test for categorical variables, to
identify predictors for bleeding and SSE events.
Univariable logistic regression was performed to estimate relative risk
for bleeding and SSE. Results were reported as odds ratio (OR) and 95%
confidence interval (CI). Multivariable logistic regression was
performed for covariates with a p-value <0.1 from the
univariable analysis to adjust for confounders.
Statistical analyses were performed with the IBM SPSS Statistics 27 for
Windows. A p-value of <0.05 was considered to be statistically
significant.