Prediction of stillbirth: an umbrella review of evaluation of prognostic variables.

BACKGROUND

Stillbirth accounts for over 2 million deaths a year worldwide and rates remains stubbornly high. Multivariable prediction models may be key to individualised monitoring, intervention or early birth in pregnancy to prevent stillbirth.

OBJECTIVES

To collate and evaluate systematic reviews of factors associated with stillbirth in order to identify variables relevant to prediction model development.

SEARCH STRATEGY

MEDLINE, Embase, DARE and Cochrane Library databases and reference lists were searched up to November 2019.

SELECTION CRITERIA

We included systematic reviews of association of individual variables with stillbirth without language restriction.

DATA COLLECTION AND ANALYSIS

Abstract screening and data extraction were conducted in duplicate. Methodological quality was assessed using AMSTAR and QUIPS criteria. The evidence supporting association with each variable was graded.

RESULTS

The search identified 1198 citations. Sixty-nine systematic reviews reporting 64 variables were included. The most frequently reported were maternal age (n = 5), body mass index (n = 6) and maternal diabetes (n = 5). Uterine artery Doppler appeared to have the best performance of any single test for stillbirth. The strongest evidence of association was for nulliparity and pre-existing hypertension.

CONCLUSION

We have identified variables relevant to the development of prediction models for stillbirth. Age, parity and prior adverse pregnancy outcomes had a more convincing association than the best performing tests, which were PAPP-A, PlGF and UtAD. The evidence was limited by high heterogeneity and lack of data on intervention bias.

TWEETABLE ABSTRACT

Review shows key predictors for use in developing models predicting stillbirth include age, prior pregnancy outcome and PAPP-A, PLGF and Uterine artery Doppler.