Department of Fetal Medicine and Prenatal Diagnosis Center, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China.
Department of Reproductive Medicine, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China.
Acta Obstet Gynecol Scand. 2020 Oct;99(10):1346-1353. doi: 10.1111/aogs.13890. Epub 2020 May 17.
Preeclampsia affects about 10% of twin pregnancies and significantly increases the risk of adverse pregnancy outcomes. However, screening models for preeclampsia in twin pregnancies remain elusive. The present study aimed to evaluate the performance of a multi-marker first trimester preeclampsia screening model in low-risk twin pregnancies.
Between 2014 and 2017, we prospectively assessed first trimester biomarkers for preeclampsia in a 'low-risk' twin pregnancy cohort at a single center. Multiple logistic regression was used to determine significant predictors for early preeclampsia (occurring prior to 34 weeks) and late preeclampsia (occurring after 34 weeks). The performance of the screening models fitted using the significant predictors was calculated using receiver operating characteristics curves, and internal validation was performed using bootstrapping.
A total of 769 twin pregnancies were included in the study. Early preeclampsia and late preeclampsia developed in 27 (3.5%) and 59 (7.7%) cases, respectively. Logistic regression analyses showed that maternal age, body mass index, mean artery pressure and placental growth factor were significant predictors for early preeclampsia. Maternal age, body mass index, mean artery pressure and pregnancy-associated plasma protein A were significant for late preeclampsia. Uterine artery pulsatility index was not predictive of either early or late preeclampsia. For the fitted screening model of early and late preeclampsia, the areas under receiver operating characteristics curves were 0.82 (95% confidence interval [CI] 0.76-0.88) and 0.66 (95% CI 0.59-0.73), which were expected to decrease to 0.77 and 0.60, respectively, based on bootstrapping; the positive predictive values were 10.2% and 12.5%; and the estimated detection rates were 40.7% and 22.0%, respectively, at a false-positive rate of 10%.
A multi-marker screening model for preeclampsia in low-risk twin pregnancies, using a modified version of Fetal Medicine Foundation predictors in singletons, does not perform well. Uterine artery pulsatility index is of little value in screening for preeclampsia in low-risk twin pregnancies.
子痫前期影响约 10%的双胎妊娠，并显著增加不良妊娠结局的风险。然而，双胎妊娠子痫前期的筛查模型仍难以捉摸。本研究旨在评估多标志物的子痫前期在低危双胎妊娠中的筛查模型的表现。
在 2014 年至 2017 年间，我们在一家单中心前瞻性评估了低危双胎妊娠队列中用于子痫前期的第一孕期生物标志物。多因素逻辑回归用于确定早期子痫前期（发生在 34 周之前）和晚期子痫前期（发生在 34 周之后）的显著预测因素。使用接收者操作特性曲线计算使用显著预测因素拟合的筛查模型的性能，并使用引导法进行内部验证。
共有 769 例双胎妊娠纳入研究。27 例（3.5%）和 59 例（7.7%）分别发生早期子痫前期和晚期子痫前期。逻辑回归分析显示，母亲年龄、体重指数、平均动脉压和胎盘生长因子是早期子痫前期的显著预测因素。母亲年龄、体重指数、平均动脉压和妊娠相关血浆蛋白 A 是晚期子痫前期的显著预测因素。子宫动脉搏动指数对早期或晚期子痫前期均无预测作用。对于早期和晚期子痫前期的拟合筛查模型，接收者操作特性曲线下面积分别为 0.82（95%置信区间 [CI] 0.76-0.88）和 0.66（95% CI 0.59-0.73），根据引导法预计会分别降至 0.77 和 0.60；阳性预测值分别为 10.2%和 12.5%；估计检出率分别为 40.7%和 22.0%，假阳性率为 10%。
使用单胎妊娠胎儿医学基金会预测因子的改良版本，为低危双胎妊娠的子痫前期建立的多标志物筛查模型表现不佳。子宫动脉搏动指数对子痫前期的筛查在低危双胎妊娠中价值不大。
