Establishment and Validation of a Risk Prediction Model for Cephalic Dystocia in Parturients Under Epidural Labor Analgesia

Yu Han,* Zengying Liu,* Yanqiong Gan, Xinlin Tan, Qiuyue Diao, Yuting Cao, Qi Shi Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qi Shi, Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, No. 63, Wenhua Road, Shunqing District, Nanchong, Sichuan, 637000, People’s Republic of China, Tel +86-15983789947, Email shiqistone@163.comBackground: While effectively relieving labor pain, epidural analgesia may decrease signs of cephalic dystocia, delaying timely diagnosis and intervention.Objective: Develop and validate a prediction model for cephalic dystocia risk under epidural analgesia.Methods: Between January 2021 and October 2024, 855 women who gave birth at the Obstetrics Department of the Affiliated Hospital of North Sichuan Medical College and received epidural analgesia were included in this study. To identify independent risk factors, univariate and multivariate logistic regression analyses were conducted and R software was used to construct a nomogram prediction model. ROC curve analysis, Hosmer-Lemeshow (H-L) tests, calibration plots, and decision curve analysis were used to evaluate the predictive ability of the model. Bootstrap resampling was used for internal validation.Results: The following factors were found to be independent predictors of cephalic dystocia under epidural analgesia: premature rupture of membranes (OR: 2.73, 95% CI: 1.46– 5.11), prolonged latent phase (OR: 13.82, 95% CI: 7.51– 25.42),fetal abdominal circumference (OR: 5.13, 95% CI: 2.22– 11.81), maternal age (OR:3.87, 95% CI:1.29– 11.59), parity (OR: 16.16, 95% CI: 2.95– 88.55), fetal presentation at the early stage of the active phase (OR: 2.82, 95% CI: 1.63– 4.88), and fetal position at the early stage of the active phase (OR:8.4, 95% CI:4.83– 14.59). The area under the curve (AUC) for this predictive model was 0.910 (95% CI: 0.878– 0.941). The Hosmer-Lemeshow goodness-of-fit test and calibration curve results showed that (P=0.992 > 0.05). Within the clinical decision curve, the net benefit of the nomogram model is higher across the threshold probability range of 0.05 to 0.83.Conclusion: This risk prediction model can identify high-risk cephalic dystocia post-epidural analgesia during the early active phase of labor, providing an instant assessment tool for timely intervention and better outcomes.Keywords: cephalic dystocia, epidural labor analgesia, predictive model, nomogram