Establishment and validation of a prediction model for successful trial of labor after cesarean in scarred uteruses

OBJECTIVE: To develop and validate a prediction model for successful trial of labor after cesarean (TOLAC) in women with a scarred uterus using clinical data from a single center with an external temporal validation set. METHODS: This retrospective study developed a prediction model using data from a single center (Huai'an Maternal and Child Health Hospital) with scarred uterus planning TOLAC, collected from January 2016 to December 2023. Assessed variables included maternal characteristics, obstetric history, and prenatal examination findings. Univariate and multivariate logistic regression were used to identify predictors and develop the model. The model was temporally validated using an independent external dataset from two other tertiary hospitals. Its performance was evaluated by the area under the ROC curve (AUC), sensitivity, and specificity, and was compared with the Grobman model. RESULTS: Among 2,386 eligible women, 1,721 (72.1%) had a successful TOLAC. Univariate analysis identified 10 significant variables (P