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.

Manal Massalha, Misgav Rottenstreich, Bryon DeFrance, Kinga Malinowski, Jon F Barrett, Eran Ashwal

Abstract readValidation Study

In one paragraph

Article in Archives of gynecology and obstetrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Manal MassalhaRuth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel. MANALMA@TECHNION.AC.IL.

Misgav RottenstreichDepartment of Obstetrics & Gynecology, Shaare Zedek Medical Center, Hebrew University School of Medicine, 91031, Jerusalem, Israel.

Bryon DeFranceDepartment of Obstetrics and Gynecology, McMaster University, Hamilton, Canada.

Kinga MalinowskiDepartment of Obstetrics and Gynecology, McMaster University, Hamilton, Canada.

Jon F BarrettDepartment of Obstetrics and Gynecology, McMaster University, Hamilton, Canada.

Eran AshwalDepartment of Obstetrics and Gynecology, McMaster University, Hamilton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFoetal 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.

methodsThis 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.

resultsAmong 477 patients, 378 (79.2%) achieved vaginal delivery. Nulliparity (OR 0.22, 95% CI 0.12-0.38; p < 0.001), pre-pregnancy BMI (OR 0.93 per kg/m

conclusionThis four-variable model provides individualised prediction of vaginal delivery in late-onset FGR. External validation is required before clinical implementation.

Indexed as

Decision Support TechniquesDelivery, ObstetricFetal Growth RetardationAdultFemaleHumansLogistic ModelsMiddle Cerebral ArteryPregnancyRetrospective StudiesTrial of LaborUltrasonography, DopplerUltrasonography, PrenatalUmbilical ArteriesCerebroplacental ratioDecision curve analysisFoetal growth restrictionInduction of labourPrediction modelVaginal delivery

Identifiers

PMID42265440

DOI10.1007/s00404-026-08462-8

PMCPMC13473075

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.