Multicentric intelligent cardiotocography signal interpretation using deep semi-supervised domain adaptation via minimax entropy and domain invariance.

BACKGROUND AND OBJECTIVE: Obstetricians use Cardiotocography (CTG), which is the continuous recording of fetal heart rate and uterine contraction, to assess fetal health status. Deep learning models for intelligent fetal monitoring trained on extensively labeled and identically distributed CTG records have achieved excellent performance. However, creation of these training sets requires excessive time and specialist labor for the collection and annotation of CTG signals. Previous research has demonstrated that multicenter studies can improve model performance. However, models trained on cross-domain data may not generalize well to target domains due to variance in distribution among datasets. Hence, this paper conducted a multicenter study with Deep Semi-Supervised Domain Adaptation (DSSDA) for intelligent interpretation of antenatal CTG signals. This approach helps to align cross-domain distribution and transfer knowledge from a label-rich source domain to a label-scarce target domain. METHODS: We proposed a DSSDA framework that integrated Minimax Entropy and Domain Invariance (DSSDA-MMEDI) to reduce inter-domain gaps and thus achieve domain invariance. The networks were developed using GoogLeNet to extract features from CTG signals, with fully connected, softmax layers for classification. We designed a Dynamic Gradient-driven strategy based on Mutual Information (DGMI) to unify the losses from Minimax Entropy (MME), Domain Invariance (DI), and supervised cross-entropy during iterative learning. RESULTS: We validated our DSSDA model on two datasets collected from collaborating healthcare institutions and mobile terminals as the source and target domains, which contained 16,355 and 3,351 CTG signals, respectively. Compared to the results achieved with deep learning networks without DSSDA, DSSDA-MMEDI significantly improved sensitivity and F1-score by over 6%. DSSDA-MMEDI also outperformed other state-of-the-art DSSDA approaches for CTG signal interpretation. Ablation studies were performed to determine the unique contribution of each component in our DSSDA mechanism. CONCLUSIONS: The proposed DSSDA-MMEDI is feasible and effective for alignment of cross-domain data and automated interpretation of multicentric antenatal CTG signals with minimal annotation cost.

Machine learning on cardiotocography data to classify fetal outcomes: A scoping review.

INTRODUCTION: Uterine contractions during labour constrict maternal blood flow and oxygen delivery to the developing baby, causing transient hypoxia. While most babies are physiologically adapted to withstand such intrapartum hypoxia, those exposed to severe hypoxia or with poor physiological reserves may experience neurological injury or death during labour. Cardiotocography (CTG) monitoring was developed to identify babies at risk of hypoxia by detecting changes in fetal heart rate (FHR) patterns. CTG monitoring is in widespread use in intrapartum care for the detection of fetal hypoxia, but the clinical utility is limited by a relatively poor positive predictive value (PPV) of an abnormal CTG and significant inter and intra observer variability in CTG interpretation. Clinical risk and human factors may impact the quality of CTG interpretation. Misclassification of CTG traces may lead to both under-treatment (with the risk of fetal injury or death) or over-treatment (which may include unnecessary operative interventions that put both mother and baby at risk of complications). Machine learning (ML) has been applied to this problem since early 2000 and has shown potential to predict fetal hypoxia more accurately than visual interpretation of CTG alone. To consider how these tools might be translated for clinical practice, we conducted a review of ML techniques already applied to CTG classification and identified research gaps requiring investigation in order to progress towards clinical implementation. MATERIALS AND METHOD: We used identified keywords to search databases for relevant publications on PubMed, EMBASE and IEEE Xplore. We used Preferred Reporting Items for Systematic Review and Meta-Analysis for Scoping Reviews (PRISMA-ScR). Title, abstract and full text were screened according to the inclusion criteria. RESULTS: We included 36 studies that used signal processing and ML techniques to classify CTG. Most studies used an open-access CTG database and predominantly used fetal metabolic acidosis as the benchmark for hypoxia with varying pH levels. Various methods were used to process and extract CTG signals and several ML algorithms were used to classify CTG. We identified significant concerns over the practicality of using varying pH levels as the CTG classification benchmark. Furthermore, studies needed to be more generalised as most used the same database with a low number of subjects for an ML study. CONCLUSION: ML studies demonstrate potential in predicting fetal hypoxia from CTG. However, more diverse datasets, standardisation of hypoxia benchmarks and enhancement of algorithms and features are needed for future clinical implementation.

Artificial intelligence based cardiotocogram assessment during labor.

OBJECTIVE: To assess whether artificial intelligence, inspired by clinical decision-making procedures in delivery rooms, can correctly interpret cardiotocographic tracings and distinguish between normal and pathological events. STUDY DESIGN: A method based on artificial intelligence was developed to determine whether a cardiotocogram shows a normal response of the fetal heart rate to uterine activity (UA). For a given fetus and given the UA and previous FHR, the method predicts a fetal heart rate response, under the assumption that the fetus is still in good condition and based on how that specific fetus has responded so far. We hypothesize that this method, when having only learned from fetuses born in good condition, is incapable of predicting the response of a compromised fetus or an episode of transient fetal distress. The (in)capability of the method to predict the fetal heart rate response would then yield a method that can help to assess fetal condition when the obstetrician is in doubt. Cardiotocographic data of 678 deliveries during labor were selected based on a healthy outcome just after birth. The method was trained on the cardiotocographic data of 548 fetuses of this group to learn their heart rate response. Subsequently it was evaluated on 87 fetuses, by assessing whether the method was able to predict their heart rate responses. The remaining 43 cardiotocograms were segment-by-segment annotated by three experienced gynecologists, indicating normal, suspicious, and pathological segments, while having access to the full recording and neonatal outcome. This future knowledge makes the expert annotations of a quality that is unachievable during live interpretation. RESULTS: The comparison between abnormalities detected by the method (only using past and present input) and the annotated CTG segments by gynecologists (also looking at future input) yields an area under the curve of 0.96 for the distinction between normal and pathological events in majority-voted annotations. CONCLUSION: The developed method can distinguish between normal and pathological events in near real-time, with a performance close to the agreement between three gynecologists with access to the entire CTG tracing and fetal outcome. The method has a strong potential to support clinicians in assessing fetal condition in clinical practice.

Fetal Heart Rate Auscultation, 4th Edition.

Intermittent auscultation (IA) is an evidence-based method of fetal surveillance during labor for birthing people with low-risk pregnancies. It is a central component of efforts to reduce the primary cesarean rate and promote vaginal birth (American College of Obstetricians and Gynecologists, 2019; Association of Women's Health, Obstetric and Neonatal Nurses, 2022a). The use of intermittent IA decreased with the introduction of electronic fetal monitoring, while the increased use of electronic fetal monitoring has been associated with an increase of cesarean births. This practice monograph includes information on IA techniques; interpretation and documentation; clinical decision-making and interventions; communication; education, staffing, legal issues; and strategies to implement IA.

Large-scale analysis of interobserver agreement and reliability in cardiotocography interpretation during labor using an online tool.

BACKGROUND: While the effectiveness of cardiotocography in reducing neonatal morbidity is still debated, it remains the primary method for assessing fetal well-being during labor. Evaluating how accurately professionals interpret cardiotocography signals is essential for its effective use. The objective was to evaluate the accuracy of fetal hypoxia prediction by practitioners through the interpretation of cardiotocography signals and clinical variables during labor. MATERIAL AND METHODS: We conducted a cross-sectional online survey, involving 120 obstetric healthcare providers from several countries. One hundred cases, including fifty cases of fetal hypoxia, were randomly assigned to participants who were invited to predict the fetal outcome (binary criterion of pH with a threshold of 7.15) based on the cardiotocography signals and clinical variables. After describing the participants, we calculated (with a 95% confidence interval) the success rate, sensitivity and specificity to predict the fetal outcome for the whole population and according to pH ranges, professional groups and number of years of experience. Interobserver agreement and reliability were evaluated using the proportion of agreement and Cohen's kappa respectively. RESULTS: The overall ability to predict a pH level below 7.15 yielded a success rate of 0.58 (95% CI 0.56-0.60), a sensitivity of 0.58 (95% CI 0.56-0.60) and a specificity of 0.63 (95% CI 0.61-0.65). No significant difference in the success rates was observed with respect to profession and number of years of experience. The success rate was higher for the cases with a pH level below 7.05 (0.69) and above 7.20 (0.66) compared to those falling between 7.05 and 7.20 (0.48). The proportion of agreement between participants was good (0.82), with an overall kappa coefficient indicating substantial reliability (0.63). CONCLUSIONS: The use of an online tool enabled us to collect a large amount of data to analyze how practitioners interpret cardiotocography data during labor. Despite a good level of agreement and reliability among practitioners, the overall accuracy is poor, particularly for cases with a neonatal pH between 7.05 and 7.20. Factors such as profession and experience level do not present notable impact on the accuracy of the annotations. The implementation and use of a computerized cardiotocography analysis software has the potential to enhance the accuracy to detect fetal hypoxia, especially for ambiguous cardiotocography tracings.

Intrapartum cardiotocography with simultaneous maternal heart rate registration improves neonatal outcome.

BACKGROUND: Intrapartum cardiotocographic monitoring of fetal heart rate by abdominal external ultrasound transducer without simultaneous maternal heart rate recording has been associated with increased risk of early neonatal death and other asphyxia-related neonatal outcomes. It is unclear, however, whether this increase in risk is independently associated with fetal surveillance method or is attributable to other factors. OBJECTIVE: This study aimed to compare different fetal surveillance methods and their association with adverse short- and long-term fetal and neonatal outcomes in a large retrospective cohort of spontaneous term deliveries. STUDY DESIGN: Fetal heart rate and maternal heart rate patterns were recorded by cardiotocography during labor in spontaneous term singleton cephalic vaginal deliveries in the Hospital District of Helsinki and Uusimaa, Finland between October 1, 2005, and September 30, 2023. According to the method of cardiotocography monitoring at birth, the cohort was divided into the following 3 groups: women with ultrasound transducer, women with both ultrasound transducer and maternal heart rate transducer, and women with internal fetal scalp electrode. Umbilical artery pH and base excess values, low 1- and 5-minute Apgar scores, need for intubation and resuscitation, neonatal intensive care unit admission for asphyxia, neonatal encephalopathy, and early neonatal death were used as outcome variables. RESULTS: Among the 213,798 deliveries that met the inclusion criteria, the monitoring type was external ultrasound transducer in 81,559 (38.1%), both external ultrasound transducer and maternal heart rate recording in 62,268 (29.1%), and fetal scalp electrode in 69,971 (32.7%) cases, respectively. The rates of both neonatal encephalopathy (odds ratio, 1.48; 95% confidence interval, 1.08-2.02) and severe acidemia (umbilical artery pH <7.00 and/or umbilical artery base excess ≤-12.0 mmol/L) (odds ratio, 2.03; 95% confidence interval, 1.65-2.50) were higher in fetuses of women with ultrasound transducer alone compared with those of women with concurrent external fetal and maternal heart rate recording. Monitoring with ultrasound transducer alone was also associated with increased risk of neonatal intubation for resuscitation (odds ratio, 1.22; 95% confidence interval, 1.03-1.44). A greater risk of severe neonatal acidemia was observed both in the ultrasound transducer (odds ratio, 2.78; 95% confidence interval, 2.23-3.48) and concurrent ultrasound transducer and maternal heart rate recording (odds ratio, 1.37; 95% confidence interval, 1.05-1.78) groups compared with those monitored with fetal scalp electrodes. No difference in risk of neonatal encephalopathy was found between newborns monitored with concurrent ultrasound transducer and maternal heart rate recording and those monitored with fetal scalp electrodes. CONCLUSION: The use of external ultrasound transducer monitoring of fetal heart rate without simultaneous maternal heart rate recording is associated with higher rates of neonatal encephalopathy and severe neonatal acidemia. We suggest that either external fetal heart rate monitoring with concurrent maternal heart rate recording or internal fetal scalp electrode be used routinely as a fetal surveillance tool in term deliveries.

Evaluation and patient experience of wireless noninvasive fetal heart rate monitoring devices.

INTRODUCTION: In clinical practice, fetal heart rate monitoring is performed intermittently using Doppler ultrasound, typically for 30 minutes. In case of a non-reassuring heart rate pattern, monitoring is usually prolonged. Noninvasive fetal electrocardiography may be more suitable for prolonged monitoring due to improved patient comfort and signal quality. This study evaluates the performance and patient experience of four noninvasive electrocardiography devices to assess candidate devices for prolonged noninvasive fetal heart rate monitoring. MATERIAL AND METHODS: Non-critically sick women with a singleton pregnancy from 24 weeks of gestation were eligible for inclusion. Fetal heart rate monitoring was performed during standard care with a Doppler ultrasound device (Philips Avalon-FM30) alone or with this Doppler ultrasound device simultaneously with one of four noninvasive electrocardiography devices (Nemo Fetal Monitoring System, Philips Avalon-Beltless, Demcon Dipha-16 and Dräger Infinity-M300). Performance was evaluated by: success rate, positive percent agreement, bias, 95% limits of agreement, regression line, root mean square error and visual agreement using FIGO guidelines. Patient experience was captured using a self-made questionnaire. RESULTS: A total of 10 women were included per device. For fetal heart rate, Nemo performed best (success rate: 99.4%, positive percent agreement: 94.2%, root mean square error 5.1 BPM, bias: 0.5 BPM, 95% limits of agreement: -9.7 - 10.7 BPM, regression line: y = -0.1x + 11.1) and the cardiotocography tracings obtained simultaneously by Nemo and Avalon-FM30 received the same FIGO classification. Comparable results were found with the Avalon-Beltless from 36 weeks of gestation, whereas the Dipha-16 and Infinity-M300 performed significantly worse. The Avalon-Beltless, Nemo and Infinity-M300 closely matched the performance of the Avalon-FM30 for maternal heart rate, whereas the performance of the Dipha-16 deviated more. Patient experience scores were higher for the noninvasive electrocardiography devices. CONCLUSIONS: Both Nemo and Avalon-Beltless are suitable devices for (prolonged) noninvasive fetal heart rate monitoring, taking their intended use into account. But outside its intended use limit of 36 weeks' gestation, the Avalon-Beltless performs less well, comparable to the Dipha-16 and Infinity-M300, making them currently unsuitable for (prolonged) noninvasive fetal heart rate monitoring. Noninvasive electrocardiography devices appear to be preferred due to greater comfort and mobility.

Hybrid-FHR: a multi-modal AI approach for automated fetal acidosis diagnosis.

BACKGROUND: In clinical medicine, fetal heart rate (FHR) monitoring using cardiotocography (CTG) is one of the most commonly used methods for assessing fetal acidosis. However, as the visual interpretation of CTG depends on the subjective judgment of the clinician, this has led to high inter-observer and intra-observer variability, making it necessary to introduce automated diagnostic techniques. METHODS: In this study, we propose a computer-aided diagnostic algorithm (Hybrid-FHR) for fetal acidosis to assist physicians in making objective decisions and taking timely interventions. Hybrid-FHR uses multi-modal features, including one-dimensional FHR signals and three types of expert features designed based on prior knowledge (morphological time domain, frequency domain, and nonlinear). To extract the spatiotemporal feature representation of one-dimensional FHR signals, we designed a multi-scale squeeze and excitation temporal convolutional network (SE-TCN) backbone model based on dilated causal convolution, which can effectively capture the long-term dependence of FHR signals by expanding the receptive field of each layer's convolution kernel while maintaining a relatively small parameter size. In addition, we proposed a cross-modal feature fusion (CMFF) method that uses multi-head attention mechanisms to explore the relationships between different modalities, obtaining more informative feature representations and improving diagnostic accuracy. RESULTS: Our ablation experiments show that the Hybrid-FHR outperforms traditional previous methods, with average accuracy, specificity, sensitivity, precision, and F1 score of 96.8, 97.5, 96, 97.5, and 96.7%, respectively. CONCLUSIONS: Our algorithm enables automated CTG analysis, assisting healthcare professionals in the early identification of fetal acidosis and the prompt implementation of interventions.

Correlation between intrapartum CTG findings and interleukin-6 levels in the umbilical cord arterial blood: A prospective cohort study.

OBJECTIVE: to investigate the correlation between the intrapartum CardioTocoGraphic (CTG) findings "suggestive of fetal inflammation" ("SOFI") and the interleukin (IL)-6 level in the umbilical arterial blood. STUDY DESIGN: prospective cohort study conducted at a tertiary maternity unit and including 447 neonates born at term. METHODS: IL-6 levels were systematically measured at birth from a sample of blood taken from the umbilical artery. The intrapartum CTG traces were retrospectively reviewed by two experts who were blinded to the postnatal umbilical arterial IL-6 values as well as to the neonatal outcomes. The CTG traces were classified into "suggestive of fetal inflammation (SOFI)" and "no evidence of fetal inflammation (NEFI) according to the principles of physiologic interpretation the CTG traces. The CTG was classified as "SOFI" if there was a persistent fetal heart rate (FHR) increase > 10 % compared with the observed baseline FHR observed at the admission or at the onset of labor without any preceding repetitive decelerations. The occurrence of Composite Adverse Outcome (CAO) was defined as Neonatal Intensive Care Unit (NICU) or Special Care Baby Unit (SCBU) admission due to one or more of the following: metabolic acidaemia, Apgar score at 5 min ≤ 7, need of neonatal resuscitation, respiratory distress, tachypnoea/polypnea, jaundice requiring phototherapy, hypotension, body temperature instability, poor perinatal adaptation, suspected or confirmed early neonatal sepsis. MAIN OUTCOME MEASURES: To compare the umbilical IL-6 values between the cases with intrapartum CTG traces classified as "SOFI" and those classified as "NEFI"; to assess the correlation of umbilical IL-6 values with the neonatal outcome. RESULTS: 43 (9.6 %) CTG traces were categorized as "SOFI"; IL-6 levels were significantly higher in this group compared with the "NEFI" group (82.0[43.4-325.0] pg/ml vs. 14.5[6.8-32.6] pg/mL; p <.001). The mean FHR baseline assessed 1 h before delivery and the total labor length showed an independent and direct association with the IL-6 levels in the umbilical arterial blood (p <.001 and p = 0.005, respectively). CAO occurred in 33(7.4 %) cases; IL-6 yielded a good prediction of the occurrence of the CAO with an AUC of 0.72 (95 % CI 0.61-0.81). CONCLUSION: Intrapartum CTG findings classified as "SOFI" are associated with higher levels of IL-6 in the umbilical arterial blood.

Fetal heart rate spectral analysis in raw signals and PRSA-derived curve: normal and pathological fetuses discrimination.

Cardiotocography (CTG) is the most common technique for electronic fetal monitoring and consists of the simultaneous recording of fetal heart rate (FHR) and uterine contractions. In analogy with the adult case, spectral analysis of the FHR signal can be used to assess the functionality of the autonomic nervous system. To do so, several methods can be employed, each of which has its strengths and limitations. This paper aims at performing a methodological investigation on FHR spectral analysis adopting 4 different spectrum estimators and a novel PRSA-based spectral method. The performances have been evaluated in terms of the ability of the various methods to detect changes in the FHR in two common pregnancy complications: intrauterine growth restriction (IUGR) and gestational diabetes. A balanced dataset containing 2178 recordings distributed between the 32nd and 38th week of gestation was used. The results show that the spectral method derived from the PRSA better differentiates high-risk pregnancies vs. controls compared to the others. Specifically, it more robustly detects an increase in power percentage within the movement frequency band and a decrease in high frequency between pregnancies at high risk in comparison to those at low risk.

Is the fetus fit for labor? Introducing fast-and-frugal trees (FFTrees) to simplify triage of women for STAN monitoring: An interobserver agreement comparison with traditional classification.

INTRODUCTION: It is a shortcoming of traditional cardiotocography (CTG) classification table formats that CTG traces are frequently classified differently by different users, resulting in poor interobserver agreements. A fast-and-frugal tree (FFTree) flow chart may help provide better concordance because it is straightforward and has clearly structured binary questions with understandable "yes" or "no" responses. The initial triage to determine whether a fetus is suitable for labor when utilizing fetal ECG ST analysis (STAN) is very important, since a fetus with restricted capacity to respond to hypoxic stress may not generate STAN events and therefore may become falsely negative. This study aimed to compare physiology-focused FFTree CTG interpretation with FIGO classification for assessing the suitability for STAN monitoring. MATERIAL AND METHODS: A retrospective study of 36 CTG traces with a high proportion of adverse outcomes (17/36) selected from a European multicenter study database. Eight experienced European obstetricians evaluated the initial 40 minutes of the CTG recordings and judged whether STAN was a suitable fetal surveillance method and whether intervention was indicated. The experts rated the CTGs using the FFTree and FIGO classifications at least 6 weeks apart. Interobserver agreements were calculated using proportions of agreement and Fleiss' kappa (κ). RESULTS: The proportions of agreement for "not suitable for STAN" were for FIGO 47% (95% confidence interval [CI] 42%-52%) and for FFTree 60% (95% CI 56-64), ie a significant difference; the corresponding figures for "yes, suitable" were 74% (95% CI 71-77) and 70% (95% CI 67-74). For "intervention needed" the figures were 52% (95% CI 47-56) vs 58% (95% CI 54-62) and for "expectant management" 74% (95% CI 71-77) vs 72% (95% CI 69-75). Fleiss' κ agreement on "suitability for STAN" was 0.50 (95% CI 0.44-0.56) for the FIGO classification and 0.57 (95% CI 0.51-0.63) for the FFTree classification; the corresponding figures for "intervention or expectancy" were 0.53 (95% CI 0.47-0.59) and 0.57 (95% CI 0.51-0.63). CONCLUSIONS: The proportion of agreement among expert obstetricians using the FFTree physiological approach was significantly higher compared with the traditional FIGO classification system in rejecting cases not suitable for STAN monitoring. That might be of importance to avoid false negative STAN recordings. Other agreement figures were similar. It remains to be shown whether the FFTree simplicity will benefit less experienced users and how it will work in real-world clinical scenarios.

Antenatal cardiotocography in dutch primary midwife-led care: Maternal and perinatal outcomes and serious adverse events. A prospective observational cohort study.

PROBLEM: It is yet unknown whether shifting antenatal cardiotocography (aCTG) from obstetrician-led to midwife-led care leads to a safe reduction in referrals. BACKGROUND: ACTG is used to assess fetal well-being. In the Netherlands, the procedure has until now been performed as part of obstetrician-led care. Developments in E-health facilitates the performance of aCTG outside the hospital in midwife-led care, hereby increasing continuity of care. AIM: To evaluate 1) process outcomes of implementing aCTG for specific indications in primary midwife-led care; 2) maternal and perinatal outcomes of pregnant women receiving aCTG in midwife-led care; 3) serious adverse events (with outcomes, causes, avoidability, and potential prevention strategies) that have occurred during the innovation project 'aCTG in midwife-led care'. METHODS: Prospective observational cohort study and a case series study of serious adverse events. FINDINGS: A total of 1584 pregnant women with a specific aCTG indication were included in this cohort study for whom 1795 aCTGs were performed in midwife-led care. 1591 aCTGs(89.7%) were classified as reassuring. Referral to obstetrician-led care occurred for 234 women(13.0%) after an aCTG in midwife-led care of whom 202(86%) were referred back. Severe neonatal morbidity occurred in 27 neonates (1.7%). In the 5736 aCTGs included in the case series study, one case with a serious neonatal outcome was assessed as a serious adverse event attributable to human factors. DISCUSSION: ACTGs performed in midwife-led care increased continuity of care. In this innovation project, maternal and perinatal outcomes were in the expected range for women in midwife-led care.

Prediction of labour outcomes using prelabour computerised cardiotocogram and maternal and fetal Doppler indices: A prospective cohort study.

OBJECTIVES: To investigate the association and the potential value of prelabour fetal heart rate short-term variability (STV) determined by computerised cardiotocography (cCTG) and maternal and fetal Doppler in predicting labour outcomes. DESIGN: Prospective cohort study. SETTING: The Prince of Wales Hospital, a tertiary maternity unit, in Hong Kong SAR. POPULATION: Women with a term singleton pregnancy in latent phase of labour or before labour induction were recruited during May 2019-November 2021. METHODS: Prelabour ultrasonographic assessment of fetal growth, Doppler velocimetry and prelabour cCTG monitoring including Dawes-Redman CTG analysis were registered shortly before induction of labour or during the latent phase of spontaneous labour. MAIN OUTCOME MEASURES: Umbilical cord arterial pH, emergency delivery due to pathological CTG during labour and neonatal intensive care unit (NICU)/special care baby unit (SCBU) admission. RESULTS: Of the 470 pregnant women invited to participate in the study, 440 women provided informed consent and a total of 400 participants were included for further analysis. Thirty-four (8.5%) participants underwent emergency delivery for pathological CTG during labour. A total of 6 (1.50%) and 148 (37.00%) newborns required NICU and SCBU admission, respectively. Middle cerebral artery pulsatility index (MCA-PI) and MCA-PI z-score were significantly lower in pregnancies that required emergency delivery for pathological CTG during labour compared with those that did not (1.23 [1.07-1.40] versus 1.40 [1.22-1.64], p = 0.002; and 0.55 ± 1.07 vs. 0.12 ± 1.06), p = 0.049]. This study demonstrated a weakly positive correlation between umbilical cord arterial pH and prelabour log10 STV (r = 0.107, p = 0.035) and the regression analyses revealed that the contributing factors for umbilical cord arterial pH were smoking (p = 0.006) and prelabour log10 STV (p = 0.025). CONCLUSIONS: In pregnant women admitted in latent phase of labour or for induction of labour at term, prelabour cCTG STV had a weakly positive association with umbilical cord arterial pH but was not predictive of emergency delivery due to pathological CTG during labour.

Intrapartum fetal heart rate monitoring: Rationalise, refine or replace?

Monitoring the fetal heartbeat underpins assessment of fetal wellbeing in labour. Although commonly employed in clinical practice, shortcomings remain. A recent review of clinical practice guidelines highlights the variation in definitions of the fetal heart rate that will lead to differences in interpretation. Will intrapartum care be improved by greater consensus around clinical practice guidelines through rationalisation or refinement of guidelines, or will the future see this technique replaced by more accurate forms of fetal monitoring?

ST waveform analysis vs cardiotocography alone for intrapartum fetal monitoring: An updated systematic review and meta-analysis of randomized trials.

INTRODUCTION: ST waveform analysis (STAN) was introduced as an adjunct to cardiotocography (CTG) to improve neonatal and maternal outcomes. The aim of the present study was to quantify the efficacy of STAN vs CTG and assess the quality of the evidence using GRADE. MATERIAL AND METHODS: We performed systematic literature searches to identify randomized controlled trials and assessed included studies for risk of bias. We performed meta-analyses, calculating pooled risk ratio (RR) or Peto odds ratio (OR). We also performed post hoc trial sequential analyses for selected outcomes to assess the risk of false-positive results and the need for additional studies. RESULTS: Nine randomized controlled trials including 28 729 women were included in the meta-analysis. There were no differences between the groups in operative deliveries for fetal distress (10.9 vs 11.1%; RR 0.96; 95% confidence interval [CI] 0.82-1.11). STAN was associated with a significantly lower rate of metabolic acidosis (0.45% vs 0.68%; Peto OR 0.66; 95% CI 0.48-0.90). Accordingly, 441 women need to be monitored with STAN instead of CTG alone to prevent one case of metabolic acidosis. Women allocated to STAN had a reduced risk of fetal blood sampling compared with women allocated to conventional CTG monitoring (12.5% vs 19.6%; RR 0.62; 95% CI 0.49-0.80). The quality of the evidence was high to moderate. CONCLUSIONS: Absolute effects of STAN were minor and the clinical significance of the observed reduction in metabolic acidosis is questioned. There is insufficient evidence to state that STAN as an adjunct to CTG leads to important clinical benefits compared with CTG alone.

The significance of meeting Dawes-Redman criteria in computerised antenatal fetal heart rate assessment.

OBJECTIVE: To investigate the significance of not meeting Dawes-Redman criteria on computerised cardiotocography in high-risk pregnancies. DESIGN: Retrospective observational study. SETTING: UK university hospital. POPULATION: High-risk pregnancies undergoing antenatal assessment. METHODS: We interrogated the database for records of computerised fetal heart rate assessment and pregnancy outcomes. MAIN OUTCOME MEASURES: Neonatal outcome and stillbirths. RESULTS: Excluding duplicate assessment in the same pregnancy, 14 025 records with complete information on the criteria of normality having been met and the outcome of the pregnancy were available. Criteria were not met for 907 records (6.46%). The gestational age of assessment was lower in the group not meeting criteria of normality. Overall, 32 stillbirths occurred in normally formed fetuses (2.28/1000). Stillbirths were more frequent in the group not meeting criteria (odds ratio [OR] 8.78, 95% CI 4.28-18.02). This finding persisted even after records with abnormally low short-term variation (STV) were excluded. The confidence intervals around the rate of stillbirth in the two groups overlapped beyond an STV of 8 ms. CONCLUSIONS: Approximately 1:16 pregnancies do not meet the criteria of normality. The criteria are not met more often at preterm gestation than at term. The risk of stillbirth was higher in the group not meeting criteria of normality, even if cases with low STV are excluded. Cases not meeting criteria should be followed up closely, unless the STV is ≥8 ms. Stillbirths still occurred in the group meeting criteria, but the rate was lower than in the general population.

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.

Machine Learning to Classify Cardiotocography for Fetal Hypoxia Detection.

Fetal hypoxia can cause damaging consequences on babies' such as stillbirth and cerebral palsy. Cardiotocography (CTG) has been used to detect intrapartum fetal hypoxia during labor. It is a non-invasive machine that measures the fetal heart rate and uterine contractions. Visual CTG suffers inconsistencies in interpretations among clinicians that can delay interventions. Machine learning (ML) showed potential in classifying abnormal CTG, allowing automatic interpretation. In the absence of a gold standard, researchers used various surrogate biomarkers to classify CTG, where some were clinically irrelevant. We proposed using Apgar scores as the surrogate benchmark of babies' ability to recover from birth. Apgar scores measure newborns' ability to recover from active uterine contraction, which measures appearance, pulse, grimace, activity and respiration. The higher the Apgar score, the healthier the baby is.We employ signal processing methods to pre-process and extract validated features of 552 raw CTG. We also included CTG-specific characteristics as outlined in the NICE guidelines. We employed ML techniques using 22 features and measured performances between ML classifiers. While we found that ML can distinguish CTG with low Apgar scores, results for the lowest Apgar scores, which are rare in the dataset we used, would benefit from more CTG data for better performance. We need an external dataset to validate our model for generalizability to ensure that it does not overfit a specific population.Clinical Relevance- This study demonstrated the potential of using a clinically relevant benchmark for classifying CTG to allow automatic early detection of hypoxia to reduce decision-making time in maternity units.

Timely Detection of Infants at Risk of Intrapartum Acidosis and Hypoxic-Ischemic Encephalopathy Using Cardiotocography.

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.