医学
小于胎龄
子宫动脉
产科
胎龄
妊娠期
人口
接收机工作特性
出生体重
回顾性队列研究
胎儿
怀孕
内科学
遗传学
环境卫生
生物
作者
Yi‐Yun Tai,Chien‐Nan Lee,H.‐C. Juan,M.‐W. Lin,J.‐C. Liao,Hung‐Yuan Li,Shin‐Yu Lin,Liona C. Poon
摘要
ABSTRACT Objective Small‐for‐gestational‐age (SGA) neonates are at increased risk of perinatal mortality and morbidity. We aimed to investigate the performance of uterine artery pulsatility index (UtA‐PI) at 19–24 weeks' gestation to predict the delivery of a SGA neonate in a Chinese population. Methods This was a retrospective cohort study using data obtained between January 2010 and June 2018. Doppler ultrasonography was performed at 19–24 weeks' gestation. SGA was defined as birth weight below the 10 th centile according to the INTERGROWTH‐21 st fetal growth standards. The performance of UtA‐PI to predict the delivery of a SGA neonate was assessed using receiver‐operating‐characteristics (ROC)‐curve analysis. Results We included 6964 singleton pregnancies, of which 748 (11%) delivered a SGA neonate, including 115 (15%) women with preterm delivery. Increased UtA‐PI was associated with an elevated risk of SGA, both in neonates delivered at or after 37 weeks' gestation (term SGA) and those delivered before 37 weeks (preterm SGA). The areas under the ROC curve (AUCs) for UtA‐PI were 64.4% (95% CI, 61.5–67.3%) and 75.8% (95% CI, 69.3–82.3%) for term and preterm SGA, respectively. The performance of combined screening by maternal demographic/clinical characteristics and estimated fetal weight in the detection of term and preterm SGA was improved significantly by the addition of UtA‐PI, although the increase in AUC was modest (2.4% for term SGA and 4.9% for preterm SGA). Conclusions This is the first Chinese study to evaluate the role of UtA‐PI at 19–24 weeks' gestation in the prediction of the delivery of a neonate with SGA. The addition of UtA‐PI to traditional risk factors improved the screening performance for SGA, and this improvement was greater in predicting preterm SGA compared with term SGA. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.
科研通智能强力驱动
Strongly Powered by AbleSci AI