Mateus Julio, Stevens Danielle R, Grantz Katherine L, Zhang Cuilin, Grewal Jagteshwar, Grobman William A, Owen John, Sciscione Anthony C, Wapner Ronald J, Skupski Daniel, Chien Edward, Wing Deborah A, Ranzini Angela C, Nageotte Michael P, Newman Roger B
Division of Maternal-Fetal Medicine, Atrium Health, Charlotte, North Carolina.
Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland.
Am J Perinatol. 2025 Jan;42(2):256-267. doi: 10.1055/s-0044-1788274. Epub 2024 Jul 29.
This study aimed to examine associations of fetal biometric and amniotic fluid measures with intrapartum primary cesarean delivery (PCD) and develop prediction models for PCD based on ultrasound parameters and maternal factors.
Secondary analysis of the National Institute of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-singleton cohort (2009-2013) including patients with uncomplicated pregnancies and intent to deliver vaginally at ≥37 weeks. The estimated fetal weight, individual biometric parameters, fetal asymmetry measurements, and amniotic fluid single deepest vertical pocket assessed at the final scan (mean 37.5 ± 1.9 weeks) were categorized as <10th, 10th to 90th (reference), and >90th percentiles. Logistic regression analyses examined the association between the ultrasound measures and PCD. Fetal and maternal SuperLearner prediction algorithms were constructed for the full and nulliparous cohorts.
Of the 1,668 patients analyzed, 249 (14.9%) had PCD. The fetal head circumference, occipital-frontal diameter, and transverse abdominal diameter >90th percentile (adjusted odds ratio [aOR] = 2.50, 95% confidence interval [95% CI]: 1.39, 4.51; aOR = 1.86, 95% CI: 1.02, 3.40; and aOR = 2.13, 95% CI: 1.16, 3.89, respectively) were associated with PCD. The fetal model demonstrated poor ability to predict PCD in the full cohort and in nulliparous patients (area under the receiver-operating characteristic curve [AUC] = 0.56, 95% CI: 0.52, 0.61; and AUC = 0.54, 95% CI: 0.49, 0.60, respectively). Conversely, the maternal model had better predictive capability overall (AUC = 0.79, 95% CI: 0.75, 0.82) and in the nulliparous subgroup (AUC = 0.72, 95% CI: 0.67, 0.77). Models combining maternal/fetal factors performed similarly to the maternal model (AUC = 0.78, 95% CI: 0.75, 0.82 in full cohort, and AUC = 0.71, 95% CI: 0.66, 0.76 in nulliparas).
Although a few fetal biometric parameters were associated with PCD, the fetal prediction model had low performance. In contrast, the maternal model had a fair-to-good ability to predict PCD.
· Fetal HC >90th percentile was associated with cesarean delivery.. · Fetal parameters did not effectively predict PCD.. · Maternal factors were more predictive of PCD.. · Maternal/fetal and maternal models performed similarly.. · Prediction models had lower performance in nulliparas..
本研究旨在探讨胎儿生物测量指标和羊水测量指标与产时初次剖宫产（PCD）之间的关联，并基于超声参数和母体因素建立PCD预测模型。
对尤妮斯·肯尼迪·施赖弗国家儿童健康与人类发展研究所（NICHD）胎儿生长研究单胎队列（2009 - 2013年）进行二次分析，纳入妊娠无并发症且计划在≥37周时经阴道分娩的患者。在最后一次扫描（平均孕周37.5±1.9周）时评估的估计胎儿体重、个体生物测量参数、胎儿不对称测量值以及羊水最大深度单垂直径被分为低于第10百分位数、第10至第90百分位数（参考值）和高于第90百分位数。逻辑回归分析检验超声测量指标与PCD之间的关联。为整个队列和初产妇队列构建胎儿和母体超学习预测算法。
在分析的1668例患者中，249例（14.9%）发生PCD。胎儿头围、枕额径和腹横径高于第90百分位数（校正比值比[aOR]分别为2.50，95%置信区间[95%CI]：1.39，4.51；aOR = 1.86，95%CI：1.02，3.40；aOR = 2.13，95%CI：1.16，3.89）与PCD相关。胎儿模型在整个队列和初产妇中预测PCD的能力较差（受试者操作特征曲线下面积[AUC]分别为0.56，95%CI：0.52，0.61；AUC = 0.54，95%CI：0.49，0.60）。相反，母体模型总体上具有更好的预测能力（AUC = 0.79，95%CI：0.75，0.82），在初产妇亚组中也是如此（AUC = 0.72，95%CI：0.67，0.77）。结合母体/胎儿因素的模型表现与母体模型相似（在整个队列中AUC = 0.78，95%CI：0.75，0.82，在初产妇中AUC = 0.71，95%CI：0.66，0.76）。
虽然一些胎儿生物测量参数与PCD相关，但胎儿预测模型性能较低。相比之下，母体模型具有较好至良好的PCD预测能力。
·胎儿头围高于第90百分位数与剖宫产相关。·胎儿参数不能有效预测PCD。·母体因素对PCD的预测性更强。·母体/胎儿模型和母体模型表现相似。·预测模型在初产妇中的性能较低。
