Johann Vargas-Calixto, Yvonne W Wu, Michael Kuzniewicz, Marie-Coralie Cornet, Heather Forquer, Lawrence Gerstley, Emily Hamilton, Philip Warrick, Robert Kearney
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引用次数: 0
Abstract
The objective of this work was to evaluate the utility of using intrapartum fetal heart rate (FHR) and uterine pressure (UP) events to detect infants at risk of hypoxic-ischemic encephalopathy (HIE). We analyzed data from 40,976 term births from three groups: 374 infants that developed HIE, 3,056 that developed fetal acidosis without HIE, and 37,546 healthy infants. We counted the transitions between FHR events and the length of FHR and UP events. Then, we used these features to train a random forest classifier to discriminate between the healthy and the pathological (acidosis or HIE) groups. Compared to the Caesarean delivery rates for each group, our system detected 6.9% more HIE cases (54.9% vs 61.8%, p<0.001) and 10.7% more acidosis cases (37.6% vs 48.3%, p<0.001), with no increase in the false positive rates in the healthy group (38.9% vs 38.8%, p=0.26). Importantly, over 3/4 of the HIE detections were made 3 hours or more before delivery. It is reasonable to expect that this would be enough lead time to permit clinical intervention to improve the outcome of birth.
这项研究的目的是评估利用产时胎儿心率(FHR)和子宫压力(UP)事件来检测婴儿缺氧缺血性脑病(HIE)风险的实用性。我们分析了 40976 名足月产婴儿的数据,这些婴儿分为三组:374 名发生 HIE 的婴儿、3056 名发生胎儿酸中毒但未发生 HIE 的婴儿和 37546 名健康婴儿。我们计算了 FHR 事件之间的转换以及 FHR 和 UP 事件的长度。然后,我们利用这些特征来训练随机森林分类器,以区分健康组和病理组(酸中毒或 HIE)。与各组的剖腹产率相比,我们的系统多检测出 6.9% 的 HIE 病例(54.9% vs 61.8%,P