Interpretation (in light of other evidence)
Antenatal estimation of the relationship between the maternal pelvis and
fetal size is essential to evaluate obstetrical prognosis. Various
pelvic diameters have been proposed to assess the risk of unplanned
cesarean
delivery. Several studies reported a
significant positive correlation between obstetric conjugate and vaginal
delivery15, 19. Besides, Joyce et al.20 asserted the minimum obstetric conjugate of 10 cm
that required a fetus of 3400g to pass through the birth canal.
Similarly, our final model incorporated the obstetric conjugate as a
significant predictive factor for dystocia. Another significant variable
is the interspinous diameter, which is considered as the parameter
representing mid-pelvis. Our study showed that the
interspinous diameter was
significantly associated with the cesarean delivery group
by
univariable analysis, which agrees
with the previous report15, 21. However, the final
multivariate model eliminated the
interspinous diameter as an independent factor to predict the overall
cesarean risk for dystocia. Moreover, we identified the bilateral
femoral head diameter as a predictive factor in both univariable and
multivariate analysis, which can be a novel parameter measuring the
transverse distance of the mid-pelvis. The mid-pelvis was considered as
an elemental plane of the birth canal, through which the fetus’ head
usually passes in sagittal orientation. Therefore, the bilateral femoral
head distance, which is located in the central of the maternal pelvis in
anatomical structure, can be a reliable parameter to assess the capacity
of the mid-pelvis.
Because unplanned cesarean delivery is associated with a greater risk of
maternal morbidity and surgical complications than scheduled cesarean
delivery and vaginal delivery22, it would be
clinically beneficial to predict the labor outcome in women with
suspected CPD. There have been previous efforts to provide predictive
models for quantifying CPD. Morgan et al. originally proposed the fetal
pelvic index 6, which combined fetal head and
abdominal circumferences with maternal pelvic inlet and mid pelvis
circumferences to identify CPD. However, it has been criticized for the
clinically useful as a poor overall prediction value23, 24. Burke et al. developed a nomogram based on
five parameters (maternal age, height, BMI, fetal abdominal
circumference and fetal head circumference) to assess the risk of
primary cesarean delivery with limited predictive accuracy (AUC =
0.69)25. Nevertheless, previous models were either
limited diagnostic accuracy25, 26 or too complex for
routine clinical practice27, 28. Additionally, some
prediction tools required intrapartum factors that counseling about
likely outcomes cannot be made until labor occurs29.
Our nomogram model based on antepartum factors may be a clinically
beneficial and accurate tool for predicting cesarean delivery risk in
nulliparous women.
Previous studies have demonstrated that MRI is a reliable and accurate
method to evaluate labor outcomes
irrespective of the experience. A
randomized trial conducted by Van Loon et. al.30asserted that MRI pelvic measurements allowed the better choice of
delivery modes with a significantly lower emergency cesarean section
rate of breech presentation at term. Some researchers attempted to
identify if MRI pelvimetry could predict the success of vaginal delivery
in women with previous cesarean sections31. As the
study comprised only 16 patients, we considered the results should be
supported by larger ones.
Sporri
et. al.21 confirmed the significant association
between MRI pelvimetry and CPD in 42 women, especially the parameters of
the interspinous dimension and obstetric conjugate.
However, the inclusion criteria were
unrepresentative and MRI pelvimetry was performed postpartum. Previous
attempts have shown that several MRI pelvimetric parameters are
associated with CPD, such as anterior-posterior mid-pelvis diameter,
interspinous diameter, and mid-pelvis capacity15, 32,
33. Another application of MRI is to estimate fetal weight; compared
with ultrasound biometry, it is more accurate 34. To
date, there has not been an established method for accessing the effects
of multiple risk factors incorporated MRI measurements for determining
the probability of primary cesarean delivery in an individual woman. Our
study expands the findings of previous investigations to develop a
nomogram model based on pelvic dimensions and fetal biometry measured by
MRI to predict successful vaginal delivery.