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.