Department of Obstetrics and Gynecology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
Department of Obstetrics and Gynaecology, St. George's University Hospitals NHS Foundation Trust, London, UK.
Int J Gynaecol Obstet. 2020 Sep;150(3):299-305. doi: 10.1002/ijgo.13229. Epub 2020 Jun 16.
Placental dysfunction has a deleterious influence on fetal size and is associated with higher rates of perinatal morbidity and mortality. This association underpins the strategy of fetal size evaluation as a mechanism to identify placental dysfunction and prevent stillbirth. The optimal method of routine detection of small for gestational age (SGA) remains to be clarified with choices between estimation of symphyseal-fundal height versus routine third-trimester ultrasound, various formulae for fetal weight estimation by ultrasound, and the variable use of national, customized, or international fetal growth references. In addition to these controversies, the strategy for detecting SGA is further undermined by data demonstrating that the relationship between fetal size and adverse outcome weakens significantly with advancing gestation such that near term, the majority of stillbirths and adverse perinatal outcomes occur in normally sized fetuses. The use of maternal serum biochemical and Doppler parameters near term appears to be superior to fetal size in the identification of fetuses compromised by placental dysfunction and at increased risk of damage or demise. Multiparameter models and predictive algorithms using maternal risk factors, and biochemical and Doppler parameters have been developed, but need to be prospectively validated to demonstrate their effectiveness.
胎盘功能障碍对胎儿大小有不良影响,并与围产期发病率和死亡率的升高有关。这种关联为胎儿大小评估策略提供了依据,该策略旨在识别胎盘功能障碍并预防死产。评估胎儿生长受限(SGA)的最佳常规检测方法仍不明确,需要在估计耻骨联合-宫底高度与常规孕晚期超声检查、超声胎儿体重估计的各种公式以及使用国家、定制或国际胎儿生长参考值之间进行选择。除了这些争议之外,SGA 的检测策略还因数据表明胎儿大小与不良结局之间的关系随着孕周的增加而显著减弱,以至于接近足月时,大多数死产和不良围产结局发生在正常大小的胎儿中而受到进一步破坏。在识别因胎盘功能障碍而受损并增加受损或死亡风险的胎儿时,使用接近足月的母体血清生化和多普勒参数似乎优于胎儿大小。已经开发了使用母体危险因素、生化和多普勒参数的多参数模型和预测算法,但需要前瞻性验证以证明其有效性。