Risk of Cesarean Delivery for Women with Obesity Using a Standardized Labor Induction Protocol

Prediction of intrapartum cesarean delivery among women with obesity: A retrospective cohort study

OBJECTIVE

To determine risk factors and design a clinically based predictive model for the risk of intrapartum cesarean delivery (CD) in women with obesity.

METHODS

A retrospective cohort study was conducted in a single tertiary medical center between 2012 and 2022 and included all consecutive women with a pre-gestational body mass index (BMI) ≥30 who planned a trial of labor. Uni- and multivariate analyses compared maternal and neonatal characteristics of women who delivered vaginally to those who underwent intrapartum CD. A specific risk prediction score was developed in accordance with the relative risk to predict the need for intrapartum CD.

RESULTS

Of the 5663 women with obesity included in the study cohort, 424 (7.5%) underwent intrapartum CD and 5239 (92.5%) delivered vaginally. The independent risk factors for CD were maternal age >35 years, pre-gestational BMI category (BMI 35-40 and BMI >40), nulliparity, epidural anesthesia, induction of labor, antibiotic administration during labor, multiple gestation, previous uterine scar, and pre-eclampsia. The intrapartum CD prediction score model demonstrated predictive performance with 85% sensitivity and 70% specificity.

CONCLUSION

Score model for intrapartum CD can be used by caregivers to offer a more informed consultation to women with obesity facing the decision of mode of delivery.

Buccal versus Vaginal Misoprostol Combined with a Foley Catheter among Individuals with Obesity Undergoing Induction

OBJECTIVE

 Combining pharmacologic agents with mechanical ripening achieves the shortest labor duration, yet there is no clear evidence on route of drug administration in obese individuals. The use of buccal misoprostol has shown greater patient acceptance but remains understudied. Our objective was to evaluate the difference in time to delivery of buccal compared with vaginal misoprostol in combination with a Foley catheter (FC) for induction of labor (IOL) in the obese population.

STUDY DESIGN

 This was a secondary analysis of a randomized controlled trial comparing identical dosages (25 μg) of buccal and vaginal misoprostol in combination with a FC. The parent trial was an institutional review board-approved, randomized clinical trial conducted from June 2019 through January 2020. Labor management was standardized among participants. Women undergoing IOL at ≥37 weeks with a singleton gestation and cervical dilation ≤2 cm were included. Body mass index (BMI, kg/m2) was stratified. The primary outcome was time to delivery.

RESULTS

 A total of 215 participants were included. Demographic characteristics were similar between the three groups. Vaginal drug administration achieved a faster median time to delivery than the buccal route among patients with a body mass index greater than or equal to 30 kg/m2 (vaginal misoprostol-FC: 21.3 hours vs. buccal misoprostol-FC: 25.2 hours, p = 0.006). There was no difference in the cesarean delivery rate between the two groups. Furthermore, patients with a BMI greater than or equal to 30 kg/m2 receiving vaginal misoprostol delivered 1.2 times faster than women who received buccal misoprostol after censoring for cesarean delivery and adjusting for parity (hazard ratio: 1.2, 95% confidence interval: 1.1-1.7). There were no significant differences in maternal and neonatal outcomes.

CONCLUSION

 We found that vaginal misoprostol was superior to buccal misoprostol when combined with a FC among individuals with a BMI greater than or equal to 30 kg/m2. Vaginal misoprostol should be the preferred route of drug administration for term IOL in this population.

KEY POINTS

· Vaginal misoprostol was superior to buccal route among patients with obesity.. · There was no difference in the cesarean delivery rate between the two groups.. · Vaginal misoprostol should be the preferred route of administration among patients with obesity..

Predicting cesarean delivery among gravidas with morbid obesity-a machine learning approach

BACKGROUND

Women with obesity have higher rates of complications following cesarean delivery, such as wound infection and endometritis, with risks being the highest if a cesarean delivery is performed after labor. Previous efforts at predicting whether a patient's labor course would ultimately result in cesarean delivery have been intermediate with area under the curve in the 0.75 to 78 range.

OBJECTIVE

This study aimed to assess whether machine learning algorithms would outperform traditional modeling in developing a cesarean delivery prediction model among gravidas with morbid obesity (body mass index of ≥40 kg/m2) to determine whether a primary cesarean delivery may be beneficial.

STUDY DESIGN

This was a secondary analysis of a retrospective cohort of 1298 patients with morbid obesity presenting for vaginal delivery at ≥37 weeks of gestation between 2011 and 2016 at a single institution. Data available at the time of admission and delivery were modeled using logistic regression, decision tree, random forest, and support vector modeling with evaluation of area under the curve, accuracy, sensitivity, and specificity.

RESULTS

Logistic regression demonstrated an area under the curve of 0.816 (95% confidence interval, 0.810-0.817), which was superior to machine learning models when evaluating data at the time of delivery (demographic data, initial cervical examinations, comorbidities, and obstetrical interventions) (P<.001). However, there was no significant difference between most machine learning models and logistic regression area under the curve of 0.799 (95% confidence interval, 0.795-0.804) when evaluating parameters available at the time of admission (demographic data, initial cervical examinations, and comorbidities). Race was noted to be a significant predictor in both models (P<.001).

CONCLUSION

Machine learning and traditional modeling techniques are likely equivalent concerning cesarean delivery prediction in this population. The models developed showed good discrimination and may be used to guide clinical decision-making concerning the optimal mode of delivery.