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.