Fetal Growth Biometry as Predictors of Shoulder Dystocia in a Low-Risk Obstetrical Population. Article uri icon

Overview

abstract

  • OBJECTIVE: To evaluate fetal biometrics as predictors of shoulder dystocia in a low-risk obstetrical population. STUDY DESIGN: Participants were enrolled as part of a U.S.-based prospective cohort study of fetal growth in low-risk singleton gestations (n=2,802). Eligible women had liveborn singletons ≥2500g delivered vaginally. Sociodemographic, anthropometric, and pregnancy outcome data were abstracted by research staff. The diagnosis of shoulder dystocia was based on the recorded clinical impression of the delivering physician. Simple logistic regression models were used to examine associations between fetal biometrics and shoulder dystocia. Fetal biometric cut points, selected by Youden's J and clinical determination, were identified to optimize predictive capability. A final model for shoulder dystocia prediction was constructed using backward selection. Our dataset was randomly divided into training (60%) and test (40%) datasets for model building and internal validation. RESULTS: 1691 women (98.7%) had an uncomplicated vaginal delivery while 23 (1.3%) experienced shoulder dystocia. There were no differences in sociodemographic or maternal anthropometrics between groups. Epidural anesthesia use was significantly more common (100% vs 82.4%; p=0.03) among women who experienced shoulder dystocia compared to those who did not. Several fetal biometric measures were significantly associated with shoulder dystocia when dichotomized based on clinically selected cut-points. A final prediction model was internally valid with an area under the curve of 0.90 (95% Confidence Interval 0.81- 0.99). At a model probability of 1%, sensitivity (71.4%), specificity (77.5%), positive (3.5%), and negative predictive values (99.6%) did not indicate the ability of the model to predict shoulder dystocia in a clinically meaningful way. CONCLUSION: Other than epidural anesthesia use, neither sociodemographic nor maternal anthropometrics were significantly associated with shoulder dystocia in this low-risk population. Both individually and in combination, fetal biometrics had limited ability to predict shoulder dystocia and lack clinical usefulness.

publication date

  • March 3, 2022

Research

keywords

  • Biometry
  • Fetal Development
  • Shoulder Dystocia

Identity

Digital Object Identifier (DOI)

  • 10.1055/a-1787-6991

PubMed ID

  • 35240706