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.