Background: This study aimed to develop and validate a model to predict histologic chorioamnionitis (HCA) risk in late preterm and term premature rupture of membranes (PROM) patients using clinical and laboratory parameters.
Methods: We conducted a retrospective study on 116 late preterm and term PROM cases, divided into a training (n=81) and a validation set (n=35). A multivariable logistic regression model was developed using the training set. Performance was assessed via the area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI). Decision curve analysis (DCA) evaluated the model’s clinical utility. Additionally, nomograms and a web version of the model were developed.
Results: In the training set, the combined model constructed using maternal BMI, gravidity, amniotic fluid characteristics, and prenatal white blood cell (WBC) count showed significantly higher AUC than WBC alone (0.859 vs 0.710, P=0.010), with improved accuracy and sensitivity. In the validation set, the AUC of the combined model remained higher than that of WBC, but the difference was not statistically significant (0.728 vs 0.584, P=0.173). NRI analysis indicated that the combined model improved the correct classification of HCA by 25.0% (P=0.012) compared to that of WBC alone. DCA demonstrated that the combined model had a higher net benefit than WBC in most cases. The nomograms and web version of the model provided convenient tools for clinicians to predict the risk of HCA.
Conclusion: This study successfully developed and validated a clinically feasible multivariable model to predict the risk of HCA in women with late preterm and term PROM.

Keywords: histologic chorioamnionitis, laboratory indicators, late pregnancy, predictive model, premature rupture of membranes