Fetal Medicine Research Institute, King's College Hospital, London, UK.
Fetal Medicine Unit, Medway Maritime Hospital, Gillingham, UK.
Ultrasound Obstet Gynecol. 2022 Nov;60(5):612-619. doi: 10.1002/uog.26057. Epub 2022 Oct 12.
To develop further a competing-risks model for the prediction of a small-for-gestational-age (SGA) neonate by including sonographically estimated fetal weight (EFW) and biomarkers of impaired placentation at 36 weeks' gestation, and to compare the performance of the new model with that of the traditional EFW < 10 percentile cut-off.
This was a prospective observational study in 29 035 women with a singleton pregnancy undergoing routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation. A competing-risks model for the prediction of a SGA neonate was used. The parameters included in the prior-history model were provided in previous studies. An interaction continuous model was used for the EFW likelihood. A folded plane regression model was fitted to describe likelihoods of biomarkers of impaired placentation. Stratification plans were also developed. The new model was evaluated and compared with EFW percentile cut-offs.
The performance of the model was better for predicting SGA neonates delivered closer to the point of assessment. The prediction provided by maternal factors alone was improved significantly by the addition of EFW, uterine artery pulsatility index (UtA-PI) and placental growth factor (PlGF) but not by mean arterial pressure or soluble fms-like tyrosine kinase-1. At a 10% false-positive rate, maternal factors and EFW predicted 77.6% and 65.8% of SGA neonates < 10 percentile delivered before 38 and 42 weeks, respectively. The respective figures for SGA < 3 percentile were 85.5% and 74.2%. Addition of UtA-PI and PlGF resulted in marginal improvement in prediction of SGA < 3 percentile requiring imminent delivery. A competing-risks approach that combines maternal factors and EFW performed better when compared with fixed EFW percentile cut-offs at predicting a SGA neonate, especially with increasing time interval between assessment and delivery. The new model was well-calibrated.
A competing-risks model provides effective risk stratification for a SGA neonate at 35 + 0 to 36 + 6 weeks' gestation and is superior to EFW percentile cut-offs. The use of biomarkers of impaired placentation in addition to maternal factors and fetal biometry results in small improvement of the predictive performance for a neonate with severe SGA. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.
通过纳入 36 孕周时超声估计胎儿体重（EFW）和胎盘功能障碍的生物标志物，进一步开发预测小于胎龄儿（SGA）的竞争风险模型，并比较新模型与传统 EFW <10 百分位截断值的性能。
这是一项在 29035 名单胎妊娠妇女中进行的前瞻性观察性研究，这些妇女在 35+0 至 36+6 孕周进行常规超声检查。使用竞争风险模型预测 SGA 新生儿。既往史模型中包含的参数在前瞻性研究中提供。EFW 似然性采用交互连续模型。拟合折叠平面回归模型描述胎盘功能障碍生物标志物的似然性。还制定了分层计划。评估新模型并与 EFW 百分位截断值进行比较。
对于预测更接近评估点的 SGA 新生儿，该模型的表现更好。仅通过母体因素的预测通过添加 EFW、子宫动脉搏动指数（UtA-PI）和胎盘生长因子（PlGF）得到显著改善，但通过平均动脉压或可溶性 fms 样酪氨酸激酶-1 则不然。在假阳性率为 10%时，母体因素和 EFW 分别预测了 38 周和 42 周前出生的 <10%百分位的 SGA 新生儿 77.6%和 65.8%，而对于 <3%百分位的 SGA 新生儿，这一比例分别为 85.5%和 74.2%。添加 UtA-PI 和 PlGF 可略微改善对需要立即分娩的 SGA <3%百分位的预测。与固定的 EFW 百分位截断值相比，结合母体因素和 EFW 的竞争风险方法在预测 35+0 至 36+6 孕周的 SGA 新生儿时表现更好，尤其是在评估与分娩之间的时间间隔增加时。新模型具有良好的校准度。
竞争风险模型为 35+0 至 36+6 孕周的 SGA 新生儿提供了有效的风险分层，优于 EFW 百分位截断值。除了母体因素和胎儿生物测量外，使用胎盘功能障碍的生物标志物可略微提高严重 SGA 新生儿的预测性能。 © 2022 年国际妇产科超声学会。
