Development and validation of a nomogram for predicting intrapartum fever in parturients with epidural analgesia

Intrapartum fever is a common complication during labor that may adversely affect both maternal and neonatal outcomes. However, its underlying multifactorial etiology remains incompletely understood.

This study aimed to investigate the clinical and inflammatory factors associated with intrapartum fever and to construct a predictive model for individualized risk assessment.

In this retrospective cohort study, we analyzed clinical data from 1,692 parturients who received epidural analgesia during term singleton vaginal delivery between September 2019 and October 2021. Participants were randomly divided into training and validation sets (7:3). Independent predictors of intrapartum fever were identified using multivariate logistic regression. A nomogram was constructed and evaluated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).

Intrapartum fever occurred in 5.0% of cases. Seven independent predictors were identified, including admission body temperature, premature rupture of membranes (PROM), duration of the first stage of labor, number of vaginal examinations, interleukin-6 (IL-6), systemic immune-inflammation index (SII), and neutrophil-to-lymphocyte ratio (NLR). Among these, IL-6 and SII demonstrated the strongest predictive performance, with SII showing a higher AUC than NLR (0.846 vs. 0.716). The final nomogram incorporating six variables achieved excellent discrimination (AUC = 0.910 in the training set and 0.906 in the validation set) and demonstrated good calibration and clinical utility.

Intrapartum fever is associated with both obstetric stress and systemic inflammation. The proposed nomogram, integrating readily available clinical and inflammatory markers, enables individualized risk assessment and may assist in early identification of high-risk parturients, supporting timely clinical intervention during labor.