Delivery timing in dichorionic diamniotic twin pregnancies complicated by preeclampsia: a decision analysis

Abstract

Objective

To determine the optimal timing of delivery in Dichorionic-diamniotic (DCDA) pregnancies complicated by preeclampsia without severe features.

Methods

A decision-analytic model was created to compare outcomes of expectant management vs. delivery from 34 to 37w0d. Outcomes included quality-adjusted life years (QALYs), development of severe preeclampsia, maternal mortality, maternal stroke, small for gestational age (SGA) due to fetal growth restriction (FGR) detected antenatally, stillbirth, cerebral palsy (CP), and neonatal mortality. Probabilities, utilities, and life expectancies were derived from the literature. Univariate analysis was used to evaluate the impact of delivery at various gestational ages. Maternal and neonatal outcomes were calculated for a theoretical cohort of 10,000 DCDA pregnancies with preeclampsia.

Results

The optimal gestational age for delivery was 36w0d when the total QALYs (868,112) were highest. Delivery at 34w0d resulted in the fewest cases of severe preeclampsia, maternal mortality, and maternal stroke (0, 4, and 15 cases per 10,000, respectively). The incidence of each of these adverse outcomes increased with gestational age, with the greatest number of adverse outcomes at 37w0d (2452 cases of severe preeclampsia, eight maternal deaths, and 31 cases of maternal stroke per 10,000). Delivery at 34w0d resulted in the fewest cases of severe preeclampsia (0), maternal stroke (15), maternal mortality (4), stillbirth (0), and SGA (1183). However, this strategy was also associated with most cases of neonatal CP (91) and neonatal mortality (87).

Conclusion

DCDA twin pregnancies complicated by preeclampsia without severe features appear to have the best outcomes when delivered at 36w0d. Specifically, when compared to delivery at 37w0d, this strategy reduced maternal and neonatal morbidity and mortality.

Keywords:

• Dichorionic diamniotic twins
• preeclampsia
• decision analysis

Acknowledgments

The authors would like to thank Rachel Psoinos, MD, Ph.D. for her contribution in the preparation of this manuscript.

Disclosure statement

The authors have no relevant conflicts of interest to disclose and did not receive any financial support to complete this research.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.