title: Evaluation of fetal anthropometric measures to predict the risk for shoulder dystocia.
abstract: OBJECTIVE
  To evaluate the quality of anthropometric measures to improve the prediction of shoulder dystocia by combining different sonographic biometric parameters.
  
  
  METHODS
  This was a retrospective cohort study of 12,794 vaginal deliveries with complete sonographic biometry data obtained within 7 days before delivery. Receiver-operating characteristics (ROC) curves of various combinations of the biometric parameters, namely, biparietal diameter (BPD), occipitofrontal diameter (OFD), head circumference, abdominal diameter (AD), abdominal circumference (AC) and femur length were analyzed. The influences of independent risk factors were calculated and their combination used in a predictive model.
  
  
  RESULTS
  The incidence of shoulder dystocia was 1.14%. Different combinations of sonographic parameters showed comparable ROC curves without advantage for a particular combination. The difference between AD and BPD (AD - BPD) (area under the curve (AUC) = 0.704) revealed a significant increase in risk (odds ratio (OR) 7.6 (95% CI 4.2-13.9), sensitivity 8.2%, specificity 98.8%) at a suggested cut-off ≥ 2.6 cm. However, the positive predictive value (PPV) was low (7.5%). The AC as a single parameter (AUC = 0.732) with a cut-off ≥ 35 cm performed worse (OR 4.6 (95% CI 3.3-6.5), PPV 2.6%). BPD/OFD (a surrogate for fetal cranial shape) was not significantly different between those with and those without shoulder dystocia. The combination of estimated fetal weight, maternal diabetes, gender and AD - BPD provided a reasonable estimate of the individual risk.
  
  
  CONCLUSIONS
  Sonographic fetal anthropometric measures appear not to be a useful tool to screen for the risk of shoulder dystocia due to a low PPV. However, AD - BPD appears to be a relevant risk factor. While risk stratification including different known risk factors may aid in counseling, shoulder dystocia cannot effectively be predicted.
authors.affiliation: Department of Obstetrics and Gynecology, University Hospital of Zürich, Zürich, Switzerland.
authors.forename: T
authors.initials: T
authors.lastname: Burkhardt
authors.forename: M
authors.initials: M
authors.lastname: Schmidt
authors.forename: J
authors.initials: J
authors.lastname: Kurmanavicius
authors.forename: R
authors.initials: R
authors.lastname: Zimmermann
authors.forename: L
authors.initials: L
authors.lastname: Schäffer
mesh_terms: D000005:Abdomen / Q000000981:diagnostic imaging* / Q000196:embryology; D000328:Adult; D019540:Area Under Curve; D001699:Biometry; D002508:Cephalometry; D004420:Dystocia / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000209:etiology; D005260:Female; D020567:Fetal Weight; D005333:Fetus; D006801:Humans; D015994:Incidence; D007231:Infant, Newborn; D009035:Mothers; D011237:Predictive Value of Tests; D011247:Pregnancy; D011254:Pregnancy in Diabetics; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012782:Shoulder / Q000000981:diagnostic imaging* / Q000196:embryology; D016216:Ultrasonography, Prenatal
keywords: anthropometry; biometry; prediction; shoulder dystocia