Prediction of stillbirth from maternal demographic and pregnancy characteristics

Objectives: To develop a model for prediction of stillbirth based on maternal characteristics and components of medical history and evaluate the performance of screening of this model for all stillbirths and those due to impaired placentation and unexplained causes.

Methods: This was a prospective screening study of 113,415 singleton pregnancies at 11+0-13+6 and 19+0-24+6 weeks’ gestation. The population included 113,019 live births and 396 (0.35%) antepartum stillbirths; 230 (58%) were secondary to impaired placentation and 166 (42%) were due to other or unexplained causes. Multivariate logistic regression analysis was used to determine the factors from maternal characteristics and medical history which provided a significant contribution to the prediction of stillbirth.

Results: The risk for stillbirth increased with maternal weight (OR 1.01 per kg after 69 kg), was higher in women of Afro-Caribbean race (OR 2.01), assisted conception (OR 1.79), cigarette smokers (OR 1.71), those with a history of chronic hypertension (OR 2.62), SLE/APS (OR 3.61) or diabetes mellitus (OR 2.55) and was increased in parous women with a history of previous stillbirth (OR 4.81). The model predicted 26% of unexplained stillbirths and 31% of those due to impaired placentation at FPR of 10%; within the impaired placentation group the DR of stillbirth at <32 weeks’ gestation was higher than that of stillbirth at >37 weeks (38% vs 28%).

Conclusions: A model based on maternal characteristics and medical history recorded in early pregnancy can potentially predict one third of subsequent stillbirths. The extent to which such stillbirths could be prevented remains to be determined.

Fetal Medicine Foundation Grant Number: 1037116