Development and Internal Validation of Prediction Model on Delivery within 7 Days for Spontaneous Late Preterm Labor: A Retrospective Cohort Study
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Abstract
Objective: To develop and internally validate a predictive model for estimating the likelihood of delivery within 7 days of the onset of spontaneous late preterm labor.
Methods: We conducted a retrospective cohort study involving singleton pregnancies with late preterm labor (gestational age 34-36+6 weeks) from October 1, 2018, to September 30, 2023. Predictors were selected based on expert consensus and stepwise backward elimination. The model was developed using multivariable logistic regression, with performance assessed through calibration (slope and plot), discrimination (AUROC), and overall prediction (Brier score). Internal validation was performed using 10-fold cross-validation.
Results: The study included 371 pregnancies: 254 delivered within 7 days and 117 later. The optimal model, based on the selected performance metrics, was the multivariable logistic regression model. It demonstrated robust discrimination and overall predictive accuracy, with an AUROC of 0.860 (95% CI, 0.756 to 0.942) and a Brier score of 0.144 (95% CI, 0.100 to 0.206). Calibration metrics included a calibration-in-the-large of -0.002 (95% CI, -0.076 to 0.063) and a calibration slope of 6.102 (95% CI, 2.596 to 12.208). Key predictors identified by the model were maternal age, gestational age at labor onset, coexisting infections, hypertension, cervical dilation, cervical effacement, uterine contractions, nulliparity, and coexisting diabetes
Conclusion: The model accurately predicts delivery within 7 days of spontaneous late preterm labor, demonstrating high predictive performance in the studied cohort. This supports clinical decision-making and potentially optimizes the timely use of dexamethasone interventions.
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