S Mastrodima1, R Akolekar1,2, G Yerlikaya1, T Tzelepis1, K H Nicolaides1. 1. Harris Birthright Research Centre for Fetal Medicine, King's College Hospital, London, UK. 2. Department of Fetal Medicine, Medway Maritime Hospital, Gillingham, UK.
Abstract
OBJECTIVES: To develop a model for the prediction of stillbirth that is based on a combination of maternal characteristics and medical history with first-trimester biochemical and biophysical markers and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and unexplained causes. METHODS: This was a prospective screening study of 76 897 singleton pregnancies, including 76 629 live births and 268 (0.35%) antepartum stillbirths; 157 (59%) were secondary to impaired placentation and 111 (41%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to determine if there was a significant contribution to prediction of stillbirth from the maternal factor-derived a-priori risk, fetal nuchal translucency thickness, ductus venosus pulsatility index for veins (DV-PIV), uterine artery pulsatility index (UtA-PI) and maternal serum free β-human chorionic gonadotropin and pregnancy-associated plasma protein-A (PAPP-A). The significant contributors were used to derive a model for first-trimester prediction of stillbirth. RESULTS: Significant contribution to prediction of stillbirth was provided by maternal factors, PAPP-A, UtA-PI and DV-PIV. A model combining these variables predicted 40% of all stillbirths and 55% of those due to impaired placentation, at a false-positive rate of 10%. Within the impaired-placentation group, the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (64% vs 42%). CONCLUSIONS: A model based on maternal factors and first-trimester biomarkers can potentially predict more than half of subsequent stillbirths that occur due to impaired placentation. The extent to which such stillbirths could be prevented remains to be determined.
OBJECTIVES: To develop a model for the prediction of stillbirth that is based on a combination of maternal characteristics and medical history with first-trimester biochemical and biophysical markers and to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and unexplained causes. METHODS: This was a prospective screening study of 76 897 singleton pregnancies, including 76 629 live births and 268 (0.35%) antepartum stillbirths; 157 (59%) were secondary to impaired placentation and 111 (41%) were due to other or unexplained causes. Multivariable logistic regression analysis was used to determine if there was a significant contribution to prediction of stillbirth from the maternal factor-derived a-priori risk, fetal nuchal translucency thickness, ductus venosus pulsatility index for veins (DV-PIV), uterine artery pulsatility index (UtA-PI) and maternal serum free β-human chorionic gonadotropin and pregnancy-associated plasma protein-A (PAPP-A). The significant contributors were used to derive a model for first-trimester prediction of stillbirth. RESULTS: Significant contribution to prediction of stillbirth was provided by maternal factors, PAPP-A, UtA-PI and DV-PIV. A model combining these variables predicted 40% of all stillbirths and 55% of those due to impaired placentation, at a false-positive rate of 10%. Within the impaired-placentation group, the detection rate of stillbirth < 32 weeks' gestation was higher than that of stillbirth ≥ 37 weeks (64% vs 42%). CONCLUSIONS: A model based on maternal factors and first-trimester biomarkers can potentially predict more than half of subsequent stillbirths that occur due to impaired placentation. The extent to which such stillbirths could be prevented remains to be determined.
Authors: M Griffin; P T Seed; S Duckworth; R North; J Myers; L Mackillop; N Simpson; J Waugh; D Anumba; L C Kenny; C W G Redman; A H Shennan; L C Chappell Journal: Ultrasound Obstet Gynecol Date: 2018-02-07 Impact factor: 7.299
Authors: J W Nijkamp; N J Sebire; K Bouman; F J Korteweg; J J H M Erwich; S J Gordijn Journal: Semin Fetal Neonatal Med Date: 2017-03-18 Impact factor: 3.926