2.5 Statistical analysis
The analysis was performed using the statistical software program SAS version 9.4(20). Descriptive statistics included means and standard deviations for parametric data, medians and interquartile ranges for non-parametric data and percentages for categorical data. Multivariable logistic regression was used to explore the relationship between volume of IV fluids in labour (high volume versus low volume) and estimated maternal blood loss ≥500 mL. A p value of <0.05 was considered statistically significant. Explanatory variables were determined prior to the analysis based on a review of the current literature. These were: maternal age, BMI, country of origin, parity, model of care, IV antibiotics for infection/suspected infection, type of birth, degree of perineal injury, duration of active labour, and birth weight. Continuous explanatory variables (e.g. maternal age, BMI, and birthweight) were tested for linear association by sorting into clinically relevant groups (e.g., maternal age <25, 25-29, 30-34, and ≥35 years) and plotting the beta-coefficients against the midpoints for each group. Variables without linearity were analysed by these groups. Multiple imputation was attended for missing data using 20 iterations. Logistic regression was performed on each of the 20 datasets and summary regression parameters were reported.