中国 33-39 孕周小胎龄儿的预测：二、三孕期超声数据和母体因素的逻辑回归模型贡献。
Prediction of small-for-gestational-age neonates at 33-39 weeks' gestation in China: logistic regression modeling of the contributions of second- and third-trimester ultrasound data and maternal factors.
机构信息
Reproductive Center, Taizhou Hospital of Zhejiang Province, Wezhou Medical University, Wenzhou, China.
Department of Obstetrics and Gynecology, Taizhou Hospital of Zhejiang Province, Wezhou Medical University, Wenzhou, China.
出版信息
BMC Pregnancy Childbirth. 2022 Aug 25;22(1):661. doi: 10.1186/s12884-022-04991-7.
OBJECTIVES
A screening model for prediction of small-for-gestational-age (SGA) neonates (SGAp) was established by logistic regression using ultrasound data and maternal factors (MF). We aimed to evaluate the ability of SGAp as well as abdominal circumference (AC) and estimated fetal weight (EFW) measurements to predict SGA neonates at 33-39 weeks' gestation.
METHODS
This retrospective study evaluated 5298 singleton pregnancies that had involved three ultrasound examinations at 21-27, 28-32, and 33-39 weeks. All ultrasound data were transformed to MoM values (multiple of the median). Multivariate logistic regression was used to analyze the correlation between SGA status and various variables (ultrasound data and MF) during pregnancy to build the SGAp model. EFW was calculated according to the Hadlock formula at 33-39 weeks of gestation. The predictive performance of SGAp, AC MoM value at 33-39 weeks (AC-M), EFW MoM value (EFW-M), EFW-M plus MF, AC value at 33-39 weeks (AC), AC growth velocity, EFW, and EFW plus MF was evaluated using ROC curves. The detection rate (DR) of SGA neonate with SGAp, AC-M, EFW-M, and EFW-M plus MF at false positive rate (FPR) of 5% and 10%, and the FPR at DR of 85%, 90%, and 95% were observed.
RESULTS
The AUCs of SGAp, AC-M, EFW-M, EFW-M plus MF, AC, AC growth velocity, EFW, and EFW plus MF for SGA neonates screening were 0.933 (95%CI: 0.916-0.950), 0.906 (95%CI: 0.887-0.925), 0.920 (95%CI: 0.903-0.936), 0.925 (95%CI: 0.909-0.941), 0.818 (95%CI: 0.791-0.845), 0.786 (95%CI: 0.752-0.821), 0.810 (95%CI: 0.782-0.838), and 0.834 (95%CI: 0.807-0.860), respectively. The screening efficiency of SGAp, AC-M, EFW-M, and EFW-M plus MF are significantly higher than AC, AC growth velocity, EFW, and EFW plus MF. The DR of SGAp, AC-M, EFW-M, and EFW-M plus MF for SGA neonates were 80.4%, 69.6%, 73.8% and 74.3% at 10% FPR. The AUCs of SGAp, AC-M, EFW-M, and EFW-M plus MF 0.950 (95%CI: 0.932-0.967), 0.929 (95%CI: 0.909-0.948), 0.938 (95%CI: 0.921-0.956) and 0.941 (95%CI: 0.924-0.957), respectively for screening SGA neonates delivered within 2 weeks after the assessment. The DR for these births increased to 85.8%, 75.8%, 80.0%, and 82.5%, respectively.
CONCLUSION
The rational use of ultrasound data can significantly improve the prediction of SGA statuses.
目的
利用逻辑回归建立基于超声数据和母体因素（MF）的预测小胎龄儿（SGA）的筛查模型。我们旨在评估 SGAp 以及腹围（AC）和估计胎儿体重（EFW）测量值预测 33-39 孕周 SGA 新生儿的能力。
方法
本回顾性研究评估了 5298 例单胎妊娠，这些妊娠在 21-27、28-32 和 33-39 周进行了三次超声检查。所有超声数据均转换为 MoM 值（中位数倍数）。多元逻辑回归用于分析 SGA 状态与妊娠期间各种变量（超声数据和 MF）之间的相关性，以建立 SGAp 模型。根据 Hadlock 公式在 33-39 孕周计算 EFW。使用 ROC 曲线评估 SGAp、33-39 孕周 AC MoM 值（AC-M）、EFW MoM 值（EFW-M）、EFW-M 加 MF、33-39 孕周 AC 值（AC）、AC 生长速度、EFW 和 EFW 加 MF 的预测性能。观察 SGAp、AC-M、EFW-M 和 EFW-M 加 MF 在假阳性率（FPR）为 5%和 10%时对 SGA 新生儿的检出率（DR），以及在 DR 为 85%、90%和 95%时的 FPR。
结果
SGAp、AC-M、EFW-M、EFW-M 加 MF、AC、AC 生长速度、EFW 和 EFW 加 MF 对 SGA 新生儿筛查的 AUC 分别为 0.933（95%CI：0.916-0.950）、0.906（95%CI：0.887-0.925）、0.920（95%CI：0.903-0.936）、0.925（95%CI：0.909-0.941）、0.818（95%CI：0.791-0.845）、0.786（95%CI：0.752-0.821）、0.810（95%CI：0.782-0.838）和 0.834（95%CI：0.807-0.860）。SGAp、AC-M、EFW-M 和 EFW-M 加 MF 的筛查效率明显高于 AC、AC 生长速度、EFW 和 EFW 加 MF。SGAp、AC-M、EFW-M 和 EFW-M 加 MF 对 SGA 新生儿的 DR 分别为 10% FPR 时的 80.4%、69.6%、73.8%和 74.3%。SGAp、AC-M、EFW-M 和 EFW-M 加 MF 的 AUC 分别为 0.950（95%CI：0.932-0.967）、0.929（95%CI：0.909-0.948）、0.938（95%CI：0.921-0.956）和 0.941（95%CI：0.924-0.957），用于筛查评估后 2 周内分娩的 SGA 新生儿。这些分娩的 DR 分别增加至 85.8%、75.8%、80.0%和 82.5%。
结论
合理利用超声数据可显著提高 SGA 状态的预测能力。
Zotero 插件