Statistical analysis
Descriptive statistics were calculated, and the data are presented as the means (standard deviations [SDs]) or medians (ranges) for numeric variables. Comparisons of normally and nonnormally distributed continuous variables between study groups were performed using the Kruskal-Wallis test. Categorical variables are reported as numbers (percentages) and were compared by Fisher’s exact test. Multivariable logistic regression analyses were performed to control potential cofounders and predict the successful fetal head rotation and vaginal delivery. The variables chosen in these logistic models were significant or marginally significant (P<0.1) in univariate analysis and were described in the previous studies 20, 39. Discrimination (the ability of the model to differentiate between the presence and absence of the event) was assessed by the area under the receiver operating characteristic curve (AUC). While calibration was assessed with calibration plots to measure how well the predicted outcome of the model agrees with the observed outcome. Statistical results with two-sided P values were reported, and a value of P < 0.05 was considered statistically significant. Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) version 26 (IBM, Armonk, NY, USA) and R statistical software, version 4.0.3.