Three-tiered fetal heart rate interpretation system and adverse neonatal and maternal outcomes: a systematic review and meta-analysis

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.

Development of a Practical Prediction Model for Adverse Neonatal Outcomes at the Start of the Second Stage of Labor

OBJECTIVE

To develop a prediction model for adverse neonatal outcomes using electronic fetal monitoring (EFM) interpretation data and other relevant clinical information known at the start of the second stage of labor.

METHODS

This was a retrospective cohort study of individuals who labored and delivered at two academic medical centers between July 2016 and June 2020. Individuals were included if they had a singleton gestation at term (more than 37 weeks of gestation), a vertex-presenting, nonanomalous fetus, and planned vaginal delivery and reached the start of the second stage of labor. The primary outcome was a composite of severe adverse neonatal outcomes. We developed and compared three modeling approaches to predict the primary outcome using factors related to EFM data (as interpreted and entered in structured data fields in the electronic health record by the bedside nurse), maternal comorbidities, and labor characteristics: traditional logistic regression, LASSO (least absolute shrinkage and selection operator), and extreme gradient boosting. Model discrimination and calibration were compared. Predicted probabilities were stratified into risk groups to facilitate clinical interpretation, and positive predictive values for adverse neonatal outcomes were calculated for each.

RESULTS

A total of 22,454 patients were included: 14,820 in the training set and 7,634 in the test set. The composite adverse neonatal outcome occurred in 3.2% of deliveries. Of the three modeling methods compared, the logistic regression model had the highest discrimination (0.690, 95% CI, 0.656-0.724) and was well calibrated. When stratified into risk groups (no increased risk, higher risk, and highest risk), the rates of the composite adverse neonatal outcome were 2.6% (95% CI, 2.3-3.1%), 6.7% (95% CI, 4.6-9.6%), and 10.3% (95% CI, 7.6-13.8%), respectively. Factors with the strongest associations with the composite adverse neonatal outcome included the presence of meconium (adjusted odds ratio [aOR] 2.10, 95% CI, 1.68-2.62), fetal tachycardia within the 2 hours preceding the start of the second stage (aOR 1.94, 95% CI, 1.03-3.65), and number of prior deliveries (aOR 0.77, 95% CI, 0.60-0.99).

Intrapartum electronic fetal heart rate monitoring to predict acidemia at birth with the use of deep learning

BACKGROUND

Electronic fetal monitoring is used in most US hospital births but has significant limitations in achieving its intended goal of preventing intrapartum hypoxic-ischemic injury. Novel deep learning techniques can improve complex data processing and pattern recognition in medicine.

OBJECTIVE

This study aimed to apply deep learning approaches to develop and validate a model to predict fetal acidemia from electronic fetal monitoring data.

STUDY DESIGN

The database was created using intrapartum electronic fetal monitoring data from 2006 to 2020 from a large, multisite academic health system. Data were divided into training and testing sets with equal distribution of acidemic cases. Several different deep learning architectures were explored. The primary outcome was umbilical artery acidemia, which was investigated at 4 clinically meaningful thresholds: 7.20, 7.15, 7.10, and 7.05, along with base excess. The receiver operating characteristic curves were generated with the area under the receiver operating characteristic assessed to determine the performance of the models. External validation was performed using a publicly available Czech database of electronic fetal monitoring data.

RESULTS

A total of 124,777 electronic fetal monitoring files were available, of which 77,132 had <30% missingness in the last 60 minutes of the electronic fetal monitoring tracing. Of these, 21,041 were matched to a corresponding umbilical cord gas result, of which 10,182 were time-stamped within 30 minutes of the last electronic fetal monitoring reading and composed the final dataset. The prevalence rates of the outcomes in the data were 20.9% with a pH of <7.2, 9.1% with a pH of <7.15, 3.3% with a pH of <7.10, and 1.3% with a pH of <7.05. The best performing model achieved an area under the receiver operating characteristic of 0.85 at a pH threshold of <7.05. When predicting the joint outcome of both pH of <7.05 and base excess of less than -10 meq/L, an area under the receiver operating characteristic of 0.89 was achieved. When predicting both pH of <7.20 and base excess of less than -10 meq/L, an area under the receiver operating characteristic of 0.87 was achieved. At a pH of <7.15 and a positive predictive value of 30%, the model achieved a sensitivity of 90% and a specificity of 48%.

CONCLUSION

The application of deep learning methods to intrapartum electronic fetal monitoring analysis achieves promising performance in predicting fetal acidemia. This technology could help improve the accuracy and consistency of electronic fetal monitoring interpretation.

Relative uteroplacental insufficiency of labor

Relative uteroplacental insufficiency of labor (RUPI-L) is a clinical condition that refers to alterations in the fetal oxygen "demand-supply" equation caused by the onset of regular uterine activity. The term RUPI-L indicates a condition of "relative" uteroplacental insufficiency which is relative to a specific stressful circumstance, such as the onset of regular uterine activity. RUPI-L may be more prevalent in fetuses in which the ratio between the fetal oxygen supply and demand is already slightly reduced, such as in cases of subclinical placental insufficiency, post-term pregnancies, gestational diabetes, and other similar conditions. Prior to the onset of regular uterine activity, fetuses with a RUPI-L may present with normal features on the cardiotocography. However, with the onset of uterine contractions, these fetuses start to manifest abnormal fetal heart rate patterns which reflect the attempt to maintain adequate perfusion to essential central organs during episodes of transient reduction in oxygenation. If labor is allowed to continue without an appropriate intervention, progressively more frequent, and stronger uterine contractions may result in a rapid deterioration of the fetal oxygenation leading to hypoxia and acidosis. In this Commentary, we introduce the term relative uteroplacental insufficiency of labor and highlight the pathophysiology, as well as the common features observed in the fetal heart rate tracing and clinical implications.

Fetal monitoring technologies for the detection of intrapartum hypoxia - challenges and opportunities

Intrapartum fetal hypoxia is related to long-term morbidity and mortality of the fetus and the mother. Fetal surveillance is extremely important to minimize the adverse outcomes arising from fetal hypoxia during labour. Several methods have been used in current clinical practice to monitor fetal well-being. For instance, biophysical technologies including cardiotocography, ST-analysis adjunct to cardiotocography, and Doppler ultrasound are used for intrapartum fetal monitoring. However, these technologies result in a high false-positive rate and increased obstetric interventions during labour. Alternatively, biochemical-based technologies including fetal scalp blood sampling and fetal pulse oximetry are used to identify metabolic acidosis and oxygen deprivation resulting from fetal hypoxia. These technologies neither improve clinical outcomes nor reduce unnecessary interventions during labour. Also, there is a need to link the physiological changes during fetal hypoxia to fetal monitoring technologies. The objective of this article is to assess the clinical background of fetal hypoxia and to review existing monitoring technologies for the detection and monitoring of fetal hypoxia. A comprehensive review has been made to predict fetal hypoxia using computational and machine-learning algorithms. The detection of more specific biomarkers or new sensing technologies is also reviewed which may help in the enhancement of the reliability of continuous fetal monitoring and may result in the accurate detection of intrapartum fetal hypoxia.

Heterogeneity in management of category II fetal tracings: data from a multihospital healthcare system

BACKGROUND

Electronic fetal monitoring is widely used to identify and intervene in suspected fetal hypoxia and/or acidemia. Category II fetal heart rate tracings are the most common class of fetal monitoring in labor, and intrauterine resuscitation is recommended given the association of category II fetal heart rate tracings with fetal acidemia. However, limited published data are available to guide intrauterine resuscitation technique selection, leading to heterogeneity in the response to category II fetal heart rate tracings.

OBJECTIVE

This study aimed to characterize approaches to intrauterine resuscitation in response to category II fetal heart rate tracings.

STUDY DESIGN

This was a survey study administered to labor unit nurses and delivering clinicians (physicians and midwives) across 7 hospitals in a Midwestern healthcare system spanning 2 states. The survey posed 3 category II fetal heart rate tracing scenarios (recurrent late decelerations, minimal variability, and recurrent variable decelerations) and asked participants to select first- and second-line intrauterine resuscitation management strategies. The participants were asked to quantify the level of influence certain factors have on their choice using a scale from 1 to 5. Intrauterine resuscitation strategy selection was compared by clinical role and hospital type (nurses vs delivering clinicians and university-affiliated hospital vs non-university-affiliated hospital).

RESULTS

Of 610 providers invited to take the survey, 163 participated (response rate of 27%): 37% of participants from university-affiliated hospitals, 62% of nurses, and 37% of physicians. Maternal repositioning was the most selected first-line strategy, regardless of the type of category II fetal heart rate tracing. First-line management varied by clinical role and hospital affiliation for each fetal heart rate tracing scenario, particularly for minimal variability, which was associated with the most heterogeneity in the first-line approach. Previous experience and recommendations from professional societies were the most influential factors in intrauterine resuscitation selection overall. Of note, 16.5% of participants reported that published evidence did not influence their choice at all. Participants from a university-affiliated hospital were more likely than participants from a non-university-affiliated hospital to consider patient preference when selecting an intrauterine resuscitation technique. Nurses and delivering clinicians differed significantly in the rationale for management choices: nurses were more often influenced by advice from other healthcare providers on the team (P<.001), whereas delivering clinicians were more influenced by literature (P=.02) and ease of technique (P=.02).

CONCLUSION

There was significant heterogeneity in the management of category II fetal heart rate tracing. In addition, motivations for choice in intrauterine resuscitation technique varied by hospital type and clinical role. These factors should be considered when creating fetal monitoring and intrauterine resuscitation protocols.