Marchand Carolin, Köppe Jeanette, Köster Helen Ann, Oelmeier Kathrin, Schmitz Ralf, Steinhard Johannes, Fruscalzo Arrigo, Kubiak Karol
Department of Gynecology and Obstetrics, St. Franziskus Hospital Muenster, 48145 Muenster, Germany.
Institute of Biostatistics and Clinical Research, University of Muenster, 48149 Muenster, Germany.
J Pers Med. 2022 Jul 11;12(7):1125. doi: 10.3390/jpm12071125.
The aim of this study was to identify growth-restricted fetuses using biometric parameters and to assess the validity and clinical value of individual ultrasound parameters and ratios, such as transcerebellar diameter/abdominal circumference (TCD/AC), head circumference/abdominal circumference (HC/AC), and femur length/abdominal circumference (FL/AC). In a retrospective single-center cross-sectional study, the biometric data of 9292 pregnancies between the 15th and 42nd weeks of gestation were acquired. Statistical analysis included descriptive data, quantile regression estimating the 10th and 90th percentiles, and multivariable analysis. We obtained clinically noticeable results in predicting small-for-gestational-age (SGA) and fetal growth restriction (FGR) fetuses at advanced weeks of gestation using the AC with a Youden index of 0.81 and 0.96, respectively. The other individual parameters and quotients were less suited to identifying cases of SGA and FGR. The multivariable analysis demonstrated the best results for identifying SGA and FGR fetuses with an area under the curve of 0.95 and 0.96, respectively. The individual ultrasound parameters were better suited to identifying SGA and FGR than the ratios. Amongst these, the AC was the most promising individual parameter, especially at advanced weeks of gestation. However, the highest accuracy was achieved with a multivariable model.
本研究的目的是利用生物测量参数识别生长受限胎儿,并评估个体超声参数及比值(如小脑横径/腹围(TCD/AC)、头围/腹围(HC/AC)以及股骨长度/腹围(FL/AC))的有效性和临床价值。在一项回顾性单中心横断面研究中,获取了9292例妊娠15至42周之间的生物测量数据。统计分析包括描述性数据、估计第10和第90百分位数的分位数回归以及多变量分析。我们在妊娠晚期预测小于胎龄(SGA)和胎儿生长受限(FGR)胎儿方面获得了具有临床意义的结果,使用腹围时约登指数分别为0.81和0.96。其他个体参数和比值不太适合识别SGA和FGR病例。多变量分析显示识别SGA和FGR胎儿的最佳结果,曲线下面积分别为0.95和0.96。个体超声参数比比值更适合识别SGA和FGR。其中,腹围是最有前景的个体参数,尤其是在妊娠晚期。然而,多变量模型实现了最高的准确性。