Development and validation of a risk nomogram for failed conversion from labor epidural analgesia to cesarean epidural anesthesia.

PURPOSE: This study aimed to develop and validate a risk prediction nomogram for failed conversion from epidural labor analgesia to cesarean epidural anesthesia.

PATIENTS AND

METHODS

Parturients undergoing non-immediate cesarean section after epidural labor analgesia between January 2022 and December 2024 across two centers were retrospectively analyzed (model-development cohort: 389; external validation cohort: 129). Potential risk factors were screened by univariate analysis in the training cohort, and six independent predictors were identified using multivariable logistic regression. A predictive model was then developed based on these predictors and validated using external data. Model performance was evaluated by discrimination (AUROC), calibration, and internal/external validation.

RESULTS

The conversion failure rate was 18.5% in the model-development cohort and 18.6% in the external validation cohort. Six predictors were incorporated into the nomogram: obstetric anesthesiologist involvement, 10-min post-analgesia VAS score, breakthrough pain, frequent rescue epidural top-ups, asymmetric sensory blockade, and programmed intermittent epidural bolus (PIEB) pump mode. The model showed good discrimination in both the training (AUROC 0.89, 95% CI 0.85-0.94) and external validation (AUROC 0.89, 95% CI 0.83-0.96) cohorts, with acceptable calibration.

CONCLUSION

We developed and externally validated a clinically interpretable nomogram for predicting failed labor-to-cesarean epidural conversion. Incorporating six routinely available variables, this tool may help convert early clinical signs of inadequate epidural function into a quantitative decision aid for anesthetic planning.