Statistical analysis
Data were analyzed using SPSS 20.0 software. Normally distributed
continuous data were presented as mean ± standard deviation, and
non-normally distributed continuous data were expressed as median and
quartile interval (M [P25-P75]). Categorical data were reported as
the number of cases and frequency (%). Independent sample T-test was
used for intergroup comparisons of normally distributed continuous data.
Non-parameter test (rank-sum) was
used for non-normal distribution. The Chi-square tests (or Fisher’s
exact tests, if appropriate) were used to determine the statistical
significance between percentages for categorical data. A multivariate
logistic regression model was used to determine odds ratios (ORs) and
associated 95% confidence intervals (CIs) when comparing LBR and CLBR
between two BMI groups. Models were adjusted for a series of possible
confounders: maternal age, fertilization method, basal
follicle-stimulating hormone (FSH), antral follicle count, and retrieved
oocytes. Statistical significance was set at P < 0.05.