Accelerations of the Fetal Heart Rate in the Screening for Fetal Growth Restriction at 34-38 Week's Gestation.

Global journal of pediatrics & neonatal care Pub Date : 2021-01-01 Epub Date: 2021-10-30
H J Odendaal, I C Crockart, C Du Plessis, L Brink, C A Groenewald
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Abstract

Objectives: To use machine learning to determine what information on Doppler velocimetry and maternal and fetal heart rates, collected at 20-24 weeks gestation, correlates best with fetal growth restriction according to the estimated fetal weight at 34-38 weeks.

Study design: Data of 4496 pregnant women, collected prospectively for the Safe Passage Study, from August 2007 to August 2016, were used for the present analysis. Doppler flow velocity of the uterine, umbilical, and middle cerebral arteries and transabdominally recorded maternal and fetal ECGs were collected at 20-24 weeks gestation and fetal biometry collected at 34-38 weeks from which the estimated fetal weight was calculated. Fetal growth restriction was defined as an estimated fetal weight below the 10th centile. Accelerations and decelerations of the fetal and maternal heart rates were quantified as gained or lost beats per hour of recording respectively. Machine learning with receiver operative characteristic curves were then used to determine which model gives the best performance.

Results: The final model performed exceptionally well across all evaluation metrics, particularly so for the Stochastic Gradient Descent method: achieving a 93% average for Classification Accuracy, Recall, Precision and F1-Score to identify the fetus with an estimated weight below the 10th percentile at 34-38 weeks. Ranking determined that the most important standard feature was the umbilical artery pulsatility index. However, the excellent overall accuracy is likely due to the value added by the pre-processed features regarding fetal gained beats and accelerations.

Conclusion: Fetal movements, as characterized by gained beats as early as 20-24 weeks gestation, contribute to the value of the flow velocimetry of the umbilical artery at 34-38 weeks in identifying the growth restricted fetus.

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妊娠34-38周胎儿生长受限筛查中胎儿心率加速的研究。
目的:利用机器学习来确定在妊娠20-24周收集的多普勒测速仪和母胎心率的哪些信息,根据34-38周的胎儿体重估计,与胎儿生长受限最相关。研究设计:本研究使用2007年8月至2016年8月期间为安全通道研究前瞻性收集的4496名孕妇的数据。在妊娠20-24周收集子宫、脐带和大脑中动脉的多普勒血流速度以及经腹记录的母体和胎儿心电图,在妊娠34-38周收集胎儿生物测量数据,以此计算胎儿体重。胎儿生长受限定义为胎儿体重低于第10百分位。胎儿和母亲心率的加速和减速分别被量化为每小时记录的增加或减少心跳。然后使用带有接收者操作特征曲线的机器学习来确定哪个模型具有最佳性能。结果:最终模型在所有评估指标上都表现得非常好,特别是随机梯度下降法:在识别34-38周估计体重低于第10百分位的胎儿时,分类准确率、召回率、精确度和f1评分平均达到93%。排名决定了最重要的标准特征是脐动脉搏动指数。然而,出色的整体准确性可能是由于有关胎儿获得的心跳和加速度的预处理特征所增加的价值。结论:胎儿运动在妊娠20-24周就以心跳加快为特征,有助于34-38周脐带动脉流速测定在鉴别生长受限胎儿方面的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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