Key result
An 11-variable nomogram predicts abnormal FHR patterns with an AUC of 0.80.
Why the study?
Predictors and a multivariable prediction model were needed for Category II and III foetal heart rate patterns in parturients undergoing labour epidural analgesia.
Can an 11-variable nomogram predict Category II and III foetal heart rate patterns in parturients undergoing labour epidural analgesia?
Cohort (n=237)
Can an 11-variable nomogram predict Category II and III foetal heart rate patterns in parturients undergoing labour epidural analgesia?
Effect estimate: AUC 0.800
An 11-variable nomogram incorporating routinely available clinical variables can predict abnormal foetal heart rate patterns during labour epidural analgesia with good discrimination.
May aid risk stratification in epidural labor; leaves open prospective validation before clinical use.
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)
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Li et al. (2026) conducted a cohort in Parturients undergoing labour epidural analgesia (n=237). 11-variable predictive nomogram was evaluated on Abnormal FHR patterns (Category II and III) (AUC 0.800). An 11-variable nomogram incorporating maternal intrapartum temperature, initial LEA bolus count, BMI, and oxytocin dosage predicted abnormal foetal heart rate patterns with an AUC of 0.800.
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