ArticleIEEE access : practical innovations, open solutions2025
Time-Dependent Association Between Cardiotocographic Features and Hypoxic-Ischemic Encephalopathy.
Article in IEEE access : practical innovations, open solutions, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Time-surrogate variables enhance the association between cardiotocographic features and intrapartum hypoxic-ischemic encephalopathy.PLOS digital health · 2026Article
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9 authors.
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Abstract
Neonatal hypoxic-ischemic encephalopathy (HIE) is caused by sustained hypoxemia near birth. Clinical assessment using cardiotocography (CTG), which measures the fetal heart rate (FHR) and maternal uterine pressure (UP), aims to identify infants at increased risk of HIE. Although CTG is nonstationary, current automated methods for its analysis use time invariant discrimination rules. Our objective was to examine the association between features of CTG and the development of HIE to determine if accounting for the time to delivery (TTD) would strengthen these associations. We analyzed 88 features extracted from FHR and UP signals from 25,197 vaginally delivered infants for whom blood gas measurements were available. All infants were categorized according to their blood gas exams into three mutually exclusive groups: 167 HIE, 1,912 acidosis - a precursor to HIE, and 22,903 healthy cases. We evaluated CTG features during the last twelve hours of labor to explore the associations between 1) CTG features and TTD, 2) CTG features and the development of HIE, and 3) the conditional association between CTG features and the development of HIE given TTD. These associations were quantified using the normalized mutual information. We found that all CTG features varied with TTD. Furthermore, 48 out of 88 features were not significantly associated with the outcome of labor and might not be useful in classification studies. We also found that 40 out of 88 features had significant associations with the development of HIE; accounting for TTD increased the association for 26 of these features. Therefore, automated methods for prediction of infants at risk of HIE should focus on this set of CTG features and account for their time-varying properties.
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