Temporal Evolution of Intrapartum Fetal Heart Rate Features

A systematic catalog of studies on fetal heart rate pattern and neonatal outcome variables

OBJECTIVES

To study the methodology and results of studies assessing the relationship between fetal heart rate and specified neonatal outcomes including, heart rate, infection, necrotizing enterocolitis, intraventricular hemorrhage, hypoxic-ischemic encephalopathy, and seizure.

METHODS

Embase, Medline ALL, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and CINAHL were searched from inception to October 5, 2023.

RESULTS

Forty-two studies were included, encompassing 57,232 cases that underwent fetal monitoring and were evaluated for neonatal outcome. Heterogeneity was observed in the timing and duration of fetal heart rate assessment, classification guidelines used, number of assessors, and definition and timing of neonatal outcome assessment. Nonreassuring fetal heart rate was linked to lower neonatal heart rate variability. A significant increase in abnormal fetal heart rate patterns were reported in neonates with hypoxic-ischemic encephalopathy, but the predictive ability was found to be limited. Conflicting results were reported regarding sepsis, seizure and intraventricular hemorrhage. No association was found between necrotizing enterocolitis rate and fetal heart rate.

CONCLUSIONS

There is great heterogeneity in the methodology used in studies evaluating the association between fetal heart rate and aforementioned neonatal outcomes. Hypoxic-ischemic encephalopathy was associated with increased abnormal fetal heart rate patterns, although the predictive ability was low. Further research on developing and evaluating an automated early warning system that integrates computerized cardiotocography with a perinatal health parameter database to provide objective alerts for patients at-risk is recommended.

Timely Detection of Infants at Risk of Intrapartum Acidosis and Hypoxic-Ischemic Encephalopathy Using Cardiotocography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-5. [PMID: 38083649 DOI: 10.1109/embc40787.2023.10340095]

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.

Multi-Chain Semi-Markov Analysis of Intrapartum Cardiotocography

Visual assessment of the evolution of fetal heart rate (FHR) and uterine pressure (UP) patterns is the standard of care in the intrapartum period. Unfortunately, this assessment has high levels of intra- and inter-observer variability. This study processed and analyzed FHR and UP patterns using computerized pattern recognition tools. The goal was to evaluate differences in FHR and UP patterns between fetuses with normal outcomes and those who developed hypoxic-ischemic encephalopathy (HIE). For this purpose, we modeled the sequence of FHR patterns and uterine contractions using Multi-Chain Semi-Markov models (MCSMMs). These models estimate the probability of transitioning between FHR or UP patterns and the dwell time of each pattern. Our results showed that in comparison to the control group, the HIE group had: (1) more frequent uterine contractions during the last 12 hours before birth; (2) more frequent FHR decelerations during the last 12 hours before birth; (3) longer decelerations during the last eight hours before birth; and (4) shorter baseline durations during the last five hours before birth. These results demonstrate that the fetuses in the HIE group were subject to a more stressful environment than those in the normal group. Clinical Relevance- Our results revealed statistically significant differences in FHR/UP patterns between the normal and HIE groups in the hours before birth. This indicates that features derived using MCSMMs may be useful in a machine learning framework to detect infants at increased risk of developing HIE allowing preventive interventions.