Antenatal Prediction of Shoulder Dystocia and Birth Trauma Using Routine Maternal and Ultrasound Variables: Retrospective Cohort Study

OBJECTIVE: To develop antenatal prediction models for shoulder dystocia and birth trauma using routinely collected maternal and sonographic variables. DESIGN: Retrospective cohort study. SETTING: Single tertiary referral centre in the UK. POPULATION OR SAMPLE: All singleton term liveborn pregnancies delivered between January 2016 and November 2024 with a third-trimester ultrasound performed at or beyond 36 weeks' gestation. METHODS: Multivariable logistic regression was used to develop antenatal prediction models for shoulder dystocia and birth trauma, incorporating maternal characteristics and fetal biometry including abdominal circumference (AC; centile or mm) and estimated fetal weight (EFW; grams or centile). Model performance was assessed using tests for multicollinearity, discrimination (area under the ROC curve, AUC) and calibration. MAIN OUTCOME MEASURES: Shoulder dystocia and birth trauma, the latter defined as a composite of shoulder dystocia, postpartum haemorrhage requiring blood transfusion, caesarean delivery at full dilatation, or hypoxic-ischaemic encephalopathy (HIE ≥ 1). RESULTS: A total of 24 334 singleton term pregnancies were included; 432 (1.8%) were complicated by shoulder dystocia and 1210 (5.0%) by birth trauma. The model including maternal characteristics and AC centile demonstrated the best discrimination. For shoulder dystocia, the apparent AUC was 0.706 (95% CI 0.682-0.730); the optimism-corrected AUC after bootstrap validation was 0.699. For birth trauma, the apparent AUC was 0.669 (95% CI 0.654-0.685); the optimism-corrected AUC was 0.665. At a 10% false-positive rate, sensitivity was 31.5% for shoulder dystocia and 22.8% for birth trauma, compared with 20.4% and 14.0%, respectively, using EFW ≥ 90th centile. CONCLUSIONS: Antenatal models combining fetal AC centile with maternal risk factors outperform EFW-based thresholds currently used in clinical practice. Although discrimination was modest, the model may be useful for antenatal risk stratification and counselling, rather than as a stand-alone clinical test. Such models may help identify pregnancies at increased risk of delivery-related complications associated with fetal overgrowth and inform future studies evaluating targeted interventions.

Authors

Institutions

Publication Details

Journal
BJOG An International Journal of Obstetrics & Gynaecology
Published
2026-04-22
DOI
https://doi.org/10.1111/1471-0528.70250
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Antenatal Prediction of Shoulder Dystocia and Birth Trauma Using Routine Maternal and Ultrasound Variables: Retrospective Cohort Study

M. Minopoli, Basky Thilaganathan, C. Di Ilio, Daniele Di Mascio et al.
BJOG An International Journal of Obstetrics & Gynaecology
Gestational Diabetes Research and Management
article

Antenatal Prediction of Shoulder Dystocia and Birth Trauma Using Routine Maternal and Ultrasound Variables: Retrospective Cohort Study

M. Minopoli, Basky Thilaganathan, C. Di Ilio, Daniele Di Mascio, A. Schwartz, AG Bhide
article en

Abstract

OBJECTIVE: To develop antenatal prediction models for shoulder dystocia and birth trauma using routinely collected maternal and sonographic variables. DESIGN: Retrospective cohort study. SETTING: Single tertiary referral centre in the UK. POPULATION OR SAMPLE: All singleton term liveborn pregnancies delivered between January 2016 and November 2024 with a third-trimester ultrasound performed at or beyond 36 weeks' gestation. METHODS: Multivariable logistic regression was used to develop antenatal prediction models for shoulder dystocia and birth trauma, incorporating maternal characteristics and fetal biometry including abdominal circumference (AC; centile or mm) and estimated fetal weight (EFW; grams or centile). Model performance was assessed using tests for multicollinearity, discrimination (area under the ROC curve, AUC) and calibration. MAIN OUTCOME MEASURES: Shoulder dystocia and birth trauma, the latter defined as a composite of shoulder dystocia, postpartum haemorrhage requiring blood transfusion, caesarean delivery at full dilatation, or hypoxic-ischaemic encephalopathy (HIE ≥ 1). RESULTS: A total of 24 334 singleton term pregnancies were included; 432 (1.8%) were complicated by shoulder dystocia and 1210 (5.0%) by birth trauma. The model including maternal characteristics and AC centile demonstrated the best discrimination. For shoulder dystocia, the apparent AUC was 0.706 (95% CI 0.682-0.730); the optimism-corrected AUC after bootstrap validation was 0.699. For birth trauma, the apparent AUC was 0.669 (95% CI 0.654-0.685); the optimism-corrected AUC was 0.665. At a 10% false-positive rate, sensitivity was 31.5% for shoulder dystocia and 22.8% for birth trauma, compared with 20.4% and 14.0%, respectively, using EFW ≥ 90th centile. CONCLUSIONS: Antenatal models combining fetal AC centile with maternal risk factors outperform EFW-based thresholds currently used in clinical practice. Although discrimination was modest, the model may be useful for antenatal risk stratification and counselling, rather than as a stand-alone clinical test. Such models may help identify pregnancies at increased risk of delivery-related complications associated with fetal overgrowth and inform future studies evaluating targeted interventions.

BJOG An International Journal of Obstetrics & Gynaecology
St George's, University of London (GB), St George’s University Hospitals NHS Foundation Trust (GB), Health Foundation (GB), Sapienza University of Rome (IT)
Openalex Percentile: Top 18%
Gestational Diabetes Research and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.