Statistical Analysis
A Shapiro-Wilks test was used to assess normality of distribution of
continuous data. Data of normal distribution was averaged as a mean with
standard deviation (SD) and analysed using student t-test. Non-normally
distributed data was averaged as a median with interquartile range (IQR)
and analysed using a rank sum test. Categorical data is presented as
frequencies and compared using a Chi-squared test. For binary outcomes,
a logistical regression model was used. For continuous outcomes, a
linear regression model was used. Multivariable analysis was used to
assess relationships between sex and our outcomes, adjusting for
baseline characteristics including age, body mass index (BMI), smoking
status, diabetes, chronic obstructive pulmonary disease (COPD), renal
failure, cerebrovascular disease, peripheral vascular disease, atrial
fibrillation (AF) and hypertension. P-value <0.05 was
considered significant in all the analysis. Statistical analysis was
performed using R version 4.0.0 using the packages sjplot, lme4,
lmertest, gtsummary, ggplot2.