AI Article Synopsis

  • This study focuses on improving the detection of fetuses at risk for fetal acidosis or hypoxic-ischemic encephalopathy (HIE) during labor by analyzing fetal heart rate (FHR) and uterine pressure (UP) signals.
  • A random forest classifier was developed to give intervention recommendations based on feature data from FHR and UP collected in 20-minute intervals, showing a significant increase in identifying at-risk babies well before delivery.
  • The system identified more cases of HIE and acidosis, suggesting early intervention opportunities that could lower HIE rates, despite a slight rise in cesarean section rates among healthy births.

Article Abstract

This work aims to improve the intrapartum detection of fetuses with an increased risk of developing fetal acidosis or hypoxic-ischemic encephalopathy (HIE) using fetal heart rate (FHR) and uterine pressure (UP) signals. Our study population comprised 40,831 term births divided into 3 classes based on umbilical cord or early neonatal blood gas assessments: 374 with verified HIE, 3,047 with acidosis but no encephalopathy and 37,410 healthy babies with normal gases. We developed an intervention recommendation system based on a random forest classifier. The classifier was trained using classical and novel features extracted electronically from 20-minute epochs of FHR and UP. Then, using the predictions of the classifier on each epoch, we designed a decision rule to determine when to recommended intervention. Compared to the Caesarean rates in each study group, our system identified an additional 5.68% of babies who developed HIE (54.55% vs 60.23%, p < 0.01) with a specific alert threshold. Importantly, about 75% of these recommendations were made more than 200 minutes before birth. In the acidosis group, the system identified an additional 17.44% (37.15% vs 54.59%, p < 0.01) and about 2/3 of these recommendations were made more than 200 minutes before birth. Compared to the Caesarean rate in the healthy group, the associated false positive rate was increased by 1.07% (38.80% vs 39.87%, p<0.01).Clinical Relevance- This method recommended intervention in more babies affected by acidosis or HIE, than the intervention rate observed in practice and most often did so 200 minutes before delivery. This was early enough to expect that interventions would have clinical benefit and reduce the rate of HIE. Given the high burden associated with HIE, this would justify the marginal increase in the normal Cesarean rate.

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http://dx.doi.org/10.1109/EMBC40787.2023.10340095DOI Listing

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Article Synopsis
  • * Researchers analyzed data from around 41,000 term births, comparing 374 cases of HIE, 3,056 with fetal acidosis, and 37,546 healthy infants, using a random forest classifier for prediction.
  • * The system showed improved detection rates for HIE (61.8%) and fetal acidosis (48.3%) without increasing false positives in healthy infants, allowing for potential early clinical interventions.
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