A nomogram for Antenatal Estimation of Cephalopelvic Disproportion in Primiparous Women based on MRI Measurements

Abstract

Objective: To develop and validate a predictive model assessing the risk of cesarean delivery in primiparous women based on the findings of magnetic resonance imaging (MRI) studies. Design: Observational study Setting: University teaching hospital. Population: 168 primiparous women with clinical findings suggestive of cephalopelvic disproportion. Methods: All women underwent MRI measurements prior to the onset of labor. A nomogram model to predict the risk of cesarean delivery was proposed based on the MRI data. The discrimination of the model was calculated by the area under the receiver operating characteristic curve (AUC) and calibration was assessed by calibration plots. The decision curve analysis was applied to evaluate the net clinical benefit. Main Outcome Measures: Cesarean delivery. Results: A total of 88 (58.7%) women achieved vaginal delivery, and 62 (41.3%) required cesarean section caused by obstructed labor. In multivariable modeling, the maternal body mass index before delivery, induction of labor, bilateral femoral head distance, obstetric conjugate, fetal head circumference and fetal abdominal circumference were significantly associated with the likelihood of cesarean delivery. The discrimination calculated as the AUC was 0.845 (95% CI: 0.783-0.908; P < 0.001). The sensitivity and specificity of the nomogram model were 0.918 and 0.629, respectively. The model demonstrated satisfactory calibration. Moreover, the decision curve analysis proved the superior net benefit of the model compared with each factor included. Conclusion: Our study provides a nomogram model that can accurately identify primiparous women at risk of cesarean delivery caused by cephalopelvic disproportion based on the MRI measurements.

Editorial for “Magnetic Resonance Imaging‐Based Nomogram to Antenatal Predict Cesarean Delivery for Cephalopelvic Disproportion in Primiparous Women”

“…In predicting the proportion of Cesarean section delivery, the area under the Receiver Operatorating Characteristic curve for their nomogram was 0.85. This seems to be a satisfactory result 9 . Although three‐dimensional data acquisition, which may provide more accurate pelvic pelvimetry, 5 was not used in this study, their results encourage using MR to predict obstetrical outcomes.…”

“…This seems to be a satisfactory result. 9 Although threedimensional data acquisition, which may provide more accurate pelvic pelvimetry, 5 was not used in this study, their results encourage using MR to predict obstetrical outcomes. In addition, this nomogram, based on statistical results from an investigation, seems a clinically friendly tool.…”

“…These authors have established a new nomogram predicting the risk of dystocia requiring Cesarean section after examining multiple parameters obtained by MR pelvimetry in this issue of JMRI. 9 As mentioned above, dystocia can be caused by various risk factors, including CPD. The authors studied risk factors for Cesarean delivery with MR pelvimetry data and previously noted risk factors such as short maternal stature or high body mass index (BMI).…”

“…These authors have established a new nomogram predicting the risk of dystocia requiring Cesarean section after examining multiple parameters obtained by MR pelvimetry in this issue of JMRI 9 . As mentioned above, dystocia can be caused by various risk factors, including CPD.…”