Abstract
Background
This study aimed to identify predictors and develop a multivariable prediction model for Category II and III foetal heart rate (FHR) patterns in parturients undergoing labour epidural analgesia (LEA).Methods
A retrospective cohort study of 237 parturients receiving LEA was conducted. To address the multicollinearity of 18 intrapartum variables, least absolute shrinkage and selection operator (LASSO) regression and cross-validation were used for feature selection. A predictive nomogram was constructed and internally validated. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC), calibration plots, and Decision Curve Analysis (DCA).Results
Abnormal FHR patterns (Category II and III) occurred in 168 (70.9%) parturients. The LASSO algorithm identified 11 predictors. Multivariable logistic regression demonstrated that maternal intrapartum temperature (OR = 3.518), initial LEA bolus count (OR = 3.625), body mass index (BMI), and oxytocin dosage were independent predictors associated with abnormal FHR patterns. The constructed nomogram demonstrated good discrimination (AUC = 0.800) and good calibration. DCA demonstrated potential clinical net benefit across a wide range of threshold probabilities (0.02-0.99).Conclusions
We developed and internally validated an 11-variable nomogram (AUC = 0.800) to predict abnormal FHR patterns during LEA. By integrating routinely available clinical variables, the nomogram facilitate early risk stratification and support individualised intrapartum management.Trial registration
Clinical trial registration: (https://www.chictr.org.cn ChiCTR2300073493; registered 12th July 2023).