Pre-delivery prediction of vaginal delivery in late-onset foetal growth restriction: development and internal validation of a model with decision curve analysis and bedside calculator

PURPOSE: Foetal growth restriction (FGR) complicates 5-10% of pregnancies and is a major contributor to perinatal morbidity and mortality. In late-onset FGR, induction of labour is recommended; however, intrapartum caesarean rates remain high (20-40%). Accurate counselling regarding the likelihood of vaginal delivery is essential, yet no validated prediction model exists for this population. We aim to develop and internally validate a pre-delivery prediction model for vaginal delivery in patients with late-onset FGR undergoing a trial of labour, and to assess its clinical utility. METHODS: This retrospective cohort study included singleton pregnancies with late-onset FGR managed at a tertiary centre (2017-2024). Eligible patients had no prior caesarean delivery, underwent attempted labour, and had complete Doppler assessment within 7 days of delivery. Logistic regression models were constructed using clinical and Doppler variables. Internal validation was performed using bootstrap resampling, and clinical utility was assessed with decision curve analysis. RESULTS: , 95% CI 0.90-0.96; p < 0.001), abnormal cerebroplacental ratio (OR 0.47, 95% CI 0.28-0.78; p = 0.004), and pre-gestational diabetes (OR 0.28, 95% CI 0.10-0.78; p = 0.015) were independently associated with lower odds of vaginal delivery. The model demonstrated moderate discrimination (AUC 0.74, 95% CI 0.70-0.80) and good calibration, with net benefit above a 55% threshold. CONCLUSION: This four-variable model provides individualised prediction of vaginal delivery in late-onset FGR. External validation is required before clinical implementation.