title: [Newborn shoulder width: physiological variations and predictive value for shoulder dystocia].
abstract: OBJECTIVE
  The purpose of this study was to determine maternal and infant characteristics affecting newborn shoulder width (NSW) and to evaluate the predictive value of NSW measurement in cases of shoulder dystocia.
  
  
  METHODS
  NSW was systematically measured at birth during a period of 18 months.
  
  
  METHODS
  Department of Obstetrics and Gynaecology of Saint-Antoine University Hospital (Paris-France).
  
  
  METHODS
  A total of 2.222 NSW measurements were performed and 22 cases of true shoulder dystocia occurred during the study period.
  
  
  METHODS
  NSW measurements were reviewed and correlated with maternal age, parity, nonpregnant weight, weight gain during pregnancy, height, race, fasting glucose and one hour glucose levels, gestational age, birthweight and sex of the neonate. A Receiver Operating Characteristics (ROC) curve was constructed to evaluate NSW as a test for predicting shoulder dystocia.
  
  
  RESULTS
  The mean NSW was 122.06 mm +/-0.50 SD. Stepwise multiple regression showed that NSW was significantly associated with birthweight (p<0.001), parity (p = 0.04), and nonpregnant weight (p = 0.04). We estimated that the best cut-off for shoulder dystocia prediction was a NSW measurement with a low false positive rate (<10%) in association with a high sensitivity rate. Therefore, NSW measurement above or equal to 140 mm was selected. This measurement should have a low sensitivity of 27.27%, a specificity of 91.82%, a positive predictive value of 4.02%, and a predictive negative value of 99.01% for shoulder dystocia prediction. Nevertheless, birthweight above or equal to 4000 g should retrospectively have a better predictive value for shoulder dystocia.
  
  
  CONCLUSIONS
  NSW measurement, which is strongly correlated with birth weight, still remains a poor predictor for shoulder dystocia, even when this evaluation is correct antenatally.
authors.affiliation: Service de Gynécologie-Obstétrique, CHU Rouen. eric.verspyck@chu-rouen.fr
authors.forename: E
authors.initials: E
authors.lastname: Verspyck
authors.forename: F
authors.initials: F
authors.lastname: Goffinet
authors.forename: M F
authors.initials: MF
authors.lastname: Hellot
authors.forename: J
authors.initials: J
authors.lastname: Milliez
authors.forename: L
authors.initials: L
authors.lastname: Marpeau
mesh_terms: D000886:Anthropometry; D001724:Birth Weight; D001786:Blood Glucose / Q000032:analysis; D001835:Body Weight; D004420:Dystocia; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D008423:Maternal Age; D010298:Parity; D011247:Pregnancy; D012372:ROC Curve; D012016:Reference Values; D012044:Regression Analysis; D012782:Shoulder / Q000033:anatomy & histology*; D015430:Weight Gain
chemical_list: D001786:Blood Glucose