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- Title
Prediction of stillbirth from biochemical and biophysical markers at 11–13 weeks.
- Authors
MASTRODIMA, S.; YERLIKAYA, G.; TZELEPIS, T.; NICOLAIDES, K. H.; AKOLEKAR, R.
- 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.
- Subjects
STILLBIRTH; BIOMARKERS; PREDICTION models; HISTORY of medicine; PLACENTA diseases; GESTATIONAL age; MEDICAL screening; MATHEMATICAL models; DIAGNOSIS
- Publication
Ultrasound in Obstetrics & Gynecology, 2016, Vol 48, p613
- ISSN
0960-7692
- Publication type
Article
- DOI
10.1002/uog.17289