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 to evaluate the performance of screening with this model for all stillbirths and those due to impaired placentation and to unexplained causes.

METHODS

This was a prospective screening study of 113 415 singleton pregnancies at 11 + 0 to 13 + 6 weeks' gestation and at 19 + 0 to 24 + 6 weeks. The study 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. Multivariable 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 (odds ratio (OR), 1.01 per kg above 69 kg), was higher in women of Afro-Caribbean racial origin (OR, 2.01), those with assisted conception (OR, 1.79), cigarette smokers (OR, 1.71), and in those with a history of chronic hypertension (OR, 2.62), systemic lupus erythematosus/antiphospholipid syndrome (OR, 3.61) or diabetes mellitus (OR, 2.55) and was increased in women with a history of previous stillbirth (OR, 4.81). Screening with the model predicted 26% of unexplained stillbirths and 31% 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 (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. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.