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Purpose: Fetal cardiotocography is the most common method to assess fetal well-being during labor. Nevertheless, its predictive ability for acidemia is limited, both in low-risk and high-risk pregnancies (Nelson et al. in N Engl J Med 334: 613–9, 1996; Rinciples P et al. in Health and Human Development Workshop Report on Electronic Fetal Monitoring : Update on Definitions. no. 2007, 510–515, 2008), especially in high-risk pregnancies, such as those complicated by growth restriction. In this study we aim examine the association between deceleration and acceleration areas and other measure of fetal heart rate in intrapartum fetal monitoring and neonatal arterial cord blood pH in pregnancies complicated by growth restriction. Materials and methods: A retrospective cohort study of 100 deliveries complicated by growth restriction, delivered during 2018, was conducted. Known major fetal anomalies, non-vertex presentation and elective cesarean deliveries were excluded. Total deceleration and acceleration areas were calculated as the sum of the areas within the deceleration and acceleration, respectively. Results: In deliveries complicated by growth restriction, cord blood pH is significantly associated with total deceleration area (p = 0.05) and correlates with cumulative duration of the decelerations (Spearman's rank −0.363, p < 0.05), and total acceleration area (−0.358, p < 0.05). By comparing the cord blood pH in deliveries with a total deceleration area that was above and below the median total deceleration area, we demonstrated a significant difference between the categories. Conclusions: Cord blood pH significantly correlates with total deceleration area and other fetal monitoring characteristics in neonates with growth restriction. Future studies using real-time, machine-learning based techniques of fetal heart rate monitoring, may provide population specific threshold values that will support bedside clinical decision making and perhaps achieve better outcomes. [ABSTRACT FROM AUTHOR]

Objective: In the Netherlands, antenatal cardiotocography (aCTG) to assess fetal well‐being is performed in obstetrician‐led care. An innovative initiative was started to evaluate whether aCTG for specific indications—reduced fetal movements, external cephalic version, or postdate pregnancy—is feasible in non‐obstetrician‐led care settings by independent primary care midwives. Quality assessment is essential when reorganizing and shifting tasks and responsibilities. Therefore, we aimed to assess the inter‐ and intraobserver agreement for aCTG assessments between and within four professional groups involved in Dutch maternity care regarding the overall classification and assessment of the various components of aCTG. Method: This was a prospective study among 47 Dutch primary care midwives, hospital‐based midwives, residents, and obstetricians. Ten aCTG traces were assessed twice at a 1 month interval. To ensure a representative sample, we used two different sets of 10 aCTG traces each. We calculated the degree of agreement using the proportions of agreement. Results: The proportions of agreement for interobserver agreement on the classification of aCTG between and within the four professional groups varied from 0.82 to 0.94. The proportions of agreement for each professional group were slightly higher for intraobserver (0.86–0.94) than for interobserver agreement. For the various aCTG components, the proportions of agreement for interobserver agreement varied from 0.64 (presence of contractions) to 0.98 (baseline heart frequency). Conclusion: The proportion of agreement levels between and within the maternity care professionals in the classification of aCTG traces among healthy women were comparable. This means that these professional groups are equally well able to classify aCTGs in healthy pregnant women. Synopsis: The proportion of agreement levels between and within professionals in midwife‐led and obstetrician‐led care in the classification of antenatal cardiotocography traces among healthy women are comparable. [ABSTRACT FROM AUTHOR]

Background: In an Australian randomized controlled trial (RCT), two techniques for intrapartum fetal surveillance were compared: ST analysis (STan) as an adjunct to cardiotocography (CTG), compared with CTG alone. The aim was to determine whether CTG + STan could reduce emergency cesarean birth rates while maintaining or improving neonatal outcomes. Secondary aims were to compare clinical, economic, and psychosocial outcomes. The purpose of this paper was to present psychosocial outcomes from one cohort enrolled in the trial. Methods: The study was conducted at one tertiary referral hospital. Participants who had taken part in the trial from the outset were invited to complete a questionnaire between March 2018 and January 2020, approximately 8 weeks after giving birth. Outcomes included depression, psychological distress, health‐related quality of life, and infant feeding practices. Analysis was by intention to treat. Results: N = 207/527 participants completed the questionnaire (n = 113, STan; n = 94, CTG alone). Overall, no statistically significant or clinically meaningful differences were found in the two groups for symptoms of depression, psychological distress, quality of life, or infant feeding. A statistically significant difference was observed for the subscale of pain‐discomfort, where scores were higher on average in the CTG alone arm relative to that in the CTG + STan arm. Conclusions: Although STan as an adjunct to CTG constitutes a different clinical technology from CTG alone, both monitoring types appeared to produce similar results in terms of postnatal psychosocial outcomes for women. Findings from this study provide service users and staff with a comprehensive assessment of STan that can be used to make evidence‐informed decisions about monitoring options should STan become more widely available. [ABSTRACT FROM AUTHOR]

Authors have expressed reservations regarding the use of base deficit measured in umbilical artery blood samples to assess fetal well-being during the course of labor and to predict neonatal neurologic morbidity. Despite its integration into clinical practice for more than 50 years, obstetricians and maternal-fetal medicine specialists may not realize that this marker has significant limitations in accurately identifying neonatal metabolic acidosis as a proxy for fetal well-being. In brief, there are 2 large families of base deficit, namely whole blood and extracellular fluid. Both rely on equations that use normal adult acid-base characteristics (pH 7.40 and partial CO 2 pressure of 40 mm Hg) that overlook the specificity of the normal in utero acid-base status of pH 7.27 and partial CO 2 pressure of 54 mm Hg. In addition, it ignores the unique characteristic of the in utero fetal response to acute hypoxia. The dependence on placental circulation for CO 2 elimination may lead to extremely high values (up to 130 to 150 mm Hg) during hypoxic events, a phenomenon that is absent in adults with acute metabolic acidosis who can hyperventilate. The dispute over if to include a correction for high partial CO 2 pressure in the bicarbonate estimation, as presented in the Great Trans-Atlantic Debates, remains unresolved. The key constants computed for adult acid-base physiology in the current base deficit algorithms, without accounting for the impact of high partial CO 2 pressure or other fetal characteristics of buffering capacity (eg, differences in body water content composition, plasma protein, and hemoglobin attributes), may lead to an overestimation of metabolic acidosis, especially in newborns who are experiencing hypercarbia during the early stages of the hypoxic response. These unrecognized limitations impact the base deficit results and may mislead clinicians on fetal well-being assessments when discussing the management of fetal heart rate monitoring and neonatal outcomes. Based on our arguments, we believe that it is prudent to consider an alternative to base deficit for drawing conclusions regarding fetal well-being during the course of birth management. We propose a marker specifically related to the newborn acid-base physiology––the neonatal eucapnic pH correction. This marker can be added to arterial cord blood gas analysis, and we have described how to interpret it as a marker of neonatal metabolic acidosis. [Display omitted] [ABSTRACT FROM AUTHOR]

Objective: To construct algorithms with a sequential decision analysis pathway for monitoring of the fetal heart rate and managing fetal heart rate bradycardia, late decelerations and tachycardia during labour. Population: Low‐risk pregnant women in labour with singleton cephalic term pregnancies. Setting: Institutional births in low‐ and middle‐income countries. Search strategy: We sought relevant published clinical algorithms, guidelines and randomised trials/reviews by searching the Cochrane Library, PubMed and Google on the terms: "fetal AND heart AND rate AND algorithm AND (labour OR intrapartum)", up to March 2020. Case scenarios: The two scenarios included were fetal heart rate bradycardia or late decelerations (potentially related to uterine rupture, placental abruption, cord prolapse, maternal hypotension, uterine hyperstimulation or unexplained) and fetal heart rate tachycardia (potentially related to maternal hyperthermia, infection, dehydration or unexplained). The algorithms provide pathways for definition, assessment, diagnosis, interventions to correct the abnormalities and ongoing monitoring leading to mode of birth, and linking to other algorithms in the series. Conclusions: The algorithms provide a framework for monitoring and managing fetal heart rate bradycardia, late decelerations and tachycardia during labour. We emphasise the inherent diagnostic inaccuracy of fetal heart rate monitoring, the tendency to over‐diagnose fetal compromise, the need to consider fetal heart rate information in the context of other clinical features and the need to engage in informed, shared, family‐centred decision‐making. We note the need for further research on methods of fetal assessment during labour including clinical fetal arousal testing and the rapid biophysical profile test. Decision analysis algorithms for fetal bradycardia, late decelerations and tachycardia highlight diagnostic limitations. Decision analysis algorithms for fetal bradycardia, late decelerations and tachycardia highlight diagnostic limitations. [ABSTRACT FROM AUTHOR]

Background: The use of cardiotocography (CTG) to improve neonatal outcomes is controversial. The medical settings, subjects, utilizations, and interpretation guidelines of CTG are unclear for low‐ and middle‐income countries (LMICs). Objectives: To assess and review CTG use for studies identified in LMICs and provide insights on the potential for effective use of CTG to improve maternal and neonatal outcomes. Search Strategy: The databases Medline, CINAHL, EMBASE, and Cochrane Central Register of Controlled Trials (CENTRAL) were searched for published and unpublished literature through September 2023. Selection Criteria: Publications were identified which were conducted in LMICs, based on the World Bank list of economies for 2019; targeting pregnant women in childbirth; and focusing on the utilization of CTG and neonatal outcomes. Data Collection and Analysis: Publications were screened, and duplicates were removed. A scoping review was conducted using PRISMA‐ScR guidelines. Results: The searches generated 1157 hits, of which 67 studies were included in the review. In the studies there was considerable variation and ambiguity regarding the study settings, target populations, utilizations, timing, frequency, and duration of CTG. While cesarean section rates were extensively investigated as an outcome of studies of CTG itself and the effect of additional techniques on CTG, other clinically significant outcomes, including neonatal mortality, were not well reported. Conclusions: Variations and ambiguities were found in the use of CTG in LMICs. Due to the limited amount of evidence, studies are needed to examine CTG availability in the context of LMICs. Synopsis: Cardiotocography (CTG) use in low‐ and middle‐income countries (LMICs) lacks consistency and clarity, with limited evidence on outcomes. [ABSTRACT FROM AUTHOR]

Intrapartum care uses electronic fetal heart rate monitoring (EFHRM) for over 50 years to indirectly assess fetal oxygenation. However, this approach has been associated with an increase in cesarean delivery rates and limited improvements in neonatal hypoxic outcome. To address these shortcomings, a novel transabdominal fetal pulse oximeter (TFO) is being developed to provide an objective measurement of fetal oxygenation. Previous studies have evaluated the performance of TFO on pregnant ewe. Building on the animal model, this study aims to determine whether TFO can successfully capture human fetal heart rate (FHR) signals during non-stress testing (NST) as a proof-of-concept. Eight ongoing pregnancies meeting specific inclusion criteria (18–40 years old, singleton, and at least 36 weeks' gestation) were enrolled with consent. Each study session was 15 to 20 min long. Reference maternal heart rate (MHR) and FHR were obtained using finger pulse oximetry and cardiotocography for subsequent comparison. The overall root-mean-square error was 9.7BPM for FHR and 4.4 for MHR, while the overall mean-absolute error was 7.6BPM for FHR and 1.8 for MHR. Bland–Altman analysis displayed a mean bias ± standard deviation between TFO and reference of -3.9 ± 8.9BPM, with limits of agreement ranging from -21.4 to 13.6 BPM. Both maternal and fetal heart rate measurements obtained from TFO exhibited a p-value < 0.001, showing significant correlation with the reference. This proof-of-concept study successfully demonstrates that TFO can accurately differentiate maternal and fetal heart signals in human subjects. This achievement marks the initial step towards enabling fetal oxygen saturation measurement in humans using TFO. [ABSTRACT FROM AUTHOR]

The purpose of this study was to assess the significant factors that impact pregnant women’s willingness to use smart fetal heart-rate monitoring devices. We propose a research model that integrates technological factors (perceived compatibility and perceived credibility) and personal factors (health anxiety, personal physiological conditions, health consciousness, and health beliefs). The subjects of this study were Chinese women who were pregnant or had previously given birth. Data were collected and analyzed from 397 paper-andpencil and electronic questionnaires. Our structural equation model indicated that perceived usefulness (β = 0.490, t = 7.591, p < 0.001), perceived ease of use (β = 0.352, t = 5.631, p < 0.001), health anxiety (β = 0.095, t = 2.664, p = 0.008), personal physiological conditions (β = 0.075, t = 2.142, p = 0.032), and health consciousness (β = 0.078, t = 2.110, p = 0.035) were the determinants of the intention to use smart fetal heart-rate monitoring devices, with perceived usefulness having the highest degree of influence. Furthermore, we discovered that the levels of perceived compatibility and perceived credibility did not have direct correlations with the intention to use these devices, but they did significantly influence the model. Perceived compatibility (β = 0.345, t = 6.601, p < 0.001) and perceived credibility (β = 0.519, t = 9.958, p < 0.001) significantly influences perceived ease of use. Perceived credibility (β = 0.421, t = 7.802, p < 0.001) significantly influences perceived usefulness. Based on these results, suggestions for future research are put forward. [ABSTRACT FROM AUTHOR]

Purpose: To compare perinatal outcomes between active and routine management in true knot of the umbilical cord (TKUC). Methods: A retrospective study of singletons born beyond 22 6/7 weeks with TKUC. Active management included weekly fetal heart rate monitoring(FHRM) ≥ 30 weeks and labor induction at 36–37 weeks. Outcomes in active and routine management were compared, including composite asphyxia-related adverse outcome, fetal death, labor induction, Cesarean section (CS) or Instrumental delivery due to non-reassuring fetal heart rate (NRFHR), Apgar5 score < 7, cord Ph < 7, neonatal intensive care unit (NICU) admission and more. Results: The Active (n = 59) and Routine (n = 1091) Management groups demonstrated similar rates of composite asphyxia-related adverse outcome (16.9% vs 16.8%, p = 0.97). Active Management resulted in higher rates of labor induction < 37 weeks (22% vs 1.7%, p < 0.001), CS (37.3% vs 19.2%, p = 0.003) and NICU admissions (13.6% vs 3%, p < 0.001). Fetal death occurred exclusively in the Routine Management group (1.8% vs 0%, p = 0.6). Conclusion: Compared with routine management, weekly FHRM and labor induction between 36 and 37 weeks in TKUC do not appear to reduce neonatal asphyxia. In its current form, active management is associated with higher rates of CS, induced prematurity and NICU admissions. Labor induction before 37 weeks should be avoided. [ABSTRACT FROM AUTHOR]

A 35‐year‐old woman (gravida 1, para 0) was admitted to our hospital at 28 weeks' gestation with vaginal bleeding from placenta previa. Severe fetal bradycardia was observed during fetal heart rate monitoring. Ultrasonography showed widely dilated veins on the fetal surface of the placenta and an extraordinarily low umbilical artery peak systolic velocity in the Doppler study. Umbilical cord torsion was suspected. On the subsequent day, we performed a cesarean section due to worsening fetal heart rate patterns. Umbilical artery blood gas analysis indicated severe acidemia (pH 7.063), and umbilical cord torsion was confirmed at the placental cord insertion site. Diagnosing UCT prenatally is challenging; however, it can be suspected by scanning for the widely dilated veins on the fetal placental surface, termed as the “Sunset Sign,” an abnormally low umbilical artery peak systolic velocity, and other fetal Doppler abnormalities. [ABSTRACT FROM AUTHOR]

To compare characteristics of labor, cardiotocography traces, and maternal and neonatal outcomes, in a cohort of pregnancies at term complicated by maternal intrapartum pyrexia, with or without a histologic diagnosis of chorioamnionitis. This is a retrospective case-control study including pregnancies at term with detection of maternal intrapartum pyrexia, delivered between January 2020 and June 2021. Cardiotocography traces were entirely evaluated, since admission till delivery, and classified according to the International Federation of Obstetrics and Gynecology (FIGO) guideline. Maternal and neonatal outcomes were also recorded as secondary outcomes. Placentas have been studied according to the Amniotic Fluid Infection Nosology Committee. Forty four patients met the inclusion criteria and were included in the study cohort. There was a significant association between the use of oxytocin augmentation in labor and the histologic diagnosis of chorioamnionitis. A significative recurrence of loss and/or absence of accelerations at the point of pyrexia was also documented in women with histological chorioamnionitis compared to the others. Chorioamnionitis appears to be associated with myometrial disfunction, as suggested by the increased use of oxytocin augmentation during active labor of women at term with intrapartum pyrexia and histologic diagnosis of chorioamnionitis. [ABSTRACT FROM AUTHOR]

Cardiotocography (CTG) is widely used to assess fetal well-being. CTG is typically obtained using ultrasound and autocorrelation methods, which extract periodicity from the signal to calculate the heart rate. However, during labor, maternal vessel pulsations can be measured, resulting in the output of the maternal heart rate (MHR). Since the autocorrelation output is displayed as fetal heart rate (FHR), there is a risk that obstetricians may mistakenly evaluate the fetal condition based on MHR, potentially overlooking the necessity for medical intervention. This study proposes a method that utilizes Doppler ultrasound (DUS) signals and artificial intelligence (AI) to determine whether the heart rate obtained by autocorrelation is of fetal origin. We developed a system to simultaneously record DUS signals and CTG and obtained data from 425 cases. The midwife annotated the DUS signals by auditory differentiation, providing data for AI, which included 30,160 data points from the fetal heart and 2160 data points from the maternal vessel. Comparing the classification accuracy of the AI model and a simple mathematical method, the AI model achieved the best performance, with an area under the curve (AUC) of 0.98. Integrating this system into fetal monitoring could provide a new indicator for evaluating CTG quality. [ABSTRACT FROM AUTHOR]

The study was conducted to investigate the effect of virtual reality on fetal movement, fetal heart rate, maternal satisfaction, fatigue and anxiety levels. The data of this randomized control experimental design study were collected using the State Anxiety Inventory, the Visual Analogue for Fatigue and the Newcastle-Satisfaction-Nursing-Care-Scale. A total of 88 pregnant women were included in the study. While the pregnant women in the experimental group watched a nature video with virtual reality during the Non-Stress Test procedure, those in the control group underwent the routine Non-Stress Test. The anxiety scores, the maternal satisfaction scores significantly higher in the experimental group. The virtual reality application is effective in reducing fatigue. There was a significant difference only in the experimental group in terms of systolic blood pressure, pulse values, the number of fetal movements and accelerations. It is recommended to have pregnant women use virtual reality during the Non-Stress Test procedure. [ABSTRACT FROM AUTHOR]

Cardiotocography (CTG) is used in pregnancy to monitor fetal heart rate and contractility, especially in the third trimester, to ensure fetal well-being and to detect early signs of distress CTG a inconsistency may indicate the need for further research and possible interventions. The objective is to increase the accuracy and reliability of cervical health classification by integrating machine learning algorithms with traditional CTG data. This approach seeks to improve the early detection of fetal distress to identify timely medical interventions. The system combines CTG data collection with machine learning algorithms to identify fetal health risks. It uses transducers to monitor fetal heart rate and contractions. Machine learning models are used to analyze CTG data, such as random forest, logistic regression, decision tree and KNN, the results showed that the random forest model outperformed the others, achieving an accuracy of 97.58 %. [ABSTRACT FROM AUTHOR]

Introduction: Fetal heart rate monitoring during labor can aid healthcare professionals in identifying alterations in the heart rate pattern. However, discrepancies in guidelines and obstetrician expertise present challenges in interpreting fetal heart rate, including failure to acknowledge findings or misinterpretation. Artificial intelligence has the potential to support obstetricians in diagnosing abnormal fetal heart rates. Methods: Employ preprocessing techniques to mitigate the effects of missing signals and artifacts on the model, utilize data augmentation methods to address data imbalance. Introduce a multi-scale long short-term memory neural network trained with a variety of time-scale data for automatically classifying fetal heart rate. Carried out experimental on both single and multi-scale models. Results: The results indicate that multi-scale LSTMmodels outperformregular LSTM models in various performance metrics. Specifically, in the single models tested, the model with a sampling rate of 10 exhibited the highest classification accuracy. The model achieves an accuracy of 85.73%, a specificity of 85.32%, and a precision of 85.53% on CTU-UHB dataset. Furthermore, the area under the receiver operating curve of 0.918 suggests that our model demonstrates a high level of credibility. Discussion: Compared to previous research, our methodology exhibits superior performance across various evaluation metrics. By incorporating alternative sampling rates into the model, we observed improvements in all performance indicators, including ACC (85.73% vs. 83.28%), SP (85.32% vs. 82.47%), PR (85.53% vs. 82.84%), recall (86.13% vs. 84.09%), F1-score (85.79% vs. 83.42%), and AUC(0.9180 vs. 0.8667). The limitations of this research include the limited consideration of pregnant women's clinical characteristics and disregard the potential impact of varying gestational weeks. [ABSTRACT FROM AUTHOR]

The article focuses on Electronic Fetal Monitoring (EFM) and its contentious role in obstetric care, questioning its effectiveness and ethical implications. Topics include critiques from both legal and medical perspectives, arguing that EFM lacks scientific validation, contributes to unnecessary interventions like C-sections, and fuels litigation rather than improving perinatal outcomes.

Standard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intra-observer disagreement. Therefore, recent studies have proposed deep-learning-based methods to interpret FHR signals and detect fetal compromise. These methods have typically focused on evaluating fixed-length FHR segments at the conclusion of labour, leaving little time for clinicians to intervene. In this study, we propose a novel FHR evaluation method using an input length invariant deep learning model (FHR-LINet) to progressively evaluate FHR as labour progresses and achieve rapid detection of fetal compromise. Using our FHR-LINet model, we obtained approximately 25% reduction in the time taken to detect fetal compromise compared to the state-of-the-art multimodal convolutional neural network while achieving 27.5%, 45.0%, 56.5% and 65.0% mean true positive rate at 5%, 10%, 15% and 20% false positive rate respectively. A diagnostic system based on our approach could potentially enable earlier intervention for fetal compromise and improve clinical outcomes. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study is to measure staff compliance with the local umbilical cord lactate (UCL) sampling guideline and investigate the quality of paired UCG samples at a tertiary maternity unit. Methods: We performed a retrospective consecutive sampling of 100 babies delivered via emergency caesarean section and 50 babies with each of all other guideline‐based indications for UCL sampling born on and before 31 December 2021. Data were extracted from physical and electronic records. Compliance with guideline‐based indications for UCL at birth was measured. The proportion of valid UCG samples was calculated. Samples were considered invalid under the following cases: (i) inadvertently collecting from the same vessel, (ii) switching arterial and venous samples, (iii) collecting from only one vessel or (iv) committing errors during sample collection and handling. Results: Of the samples collected at birth from 321 babies, 280 (87%) had UCL. Small for gestational age and concerns about fetal well‐being in labour were indications associated with poorer compliance, 66% and 78%, respectively. About 99 (44%) babies of 226 babies with UCG performed had valid UCG samples. The most common reasons for invalid samples were collection and handling errors (22%) and inadvertent collection from the same vessel (15%). Conclusions: Generally, compliance with the guidelines is good. However, invalid UCG samples were more frequent than expected. [ABSTRACT FROM AUTHOR]

Background and Purpose: It is challenging to predict preterm births accurately. We sought to compare the diagnostic performance of cervical length in predicting preterm birth to those of contraction recording in cardiotocography (CTG), cervical funneling, and Bishop score. Methods: A total of 371 women with singleton pregnancies and threatened preterm labor admitted to tertiary hospitals of northwestern Iran were included in this prospective cohort study and followed up until childbirth. Transvaginal ultrasound was utilized to assess the cervical length and funneling. Also, a CTG test and digital vaginal examination were performed. The data of 218 women were analyzed in the STATA software. The sensitivity and other diagnostic performances, and 95% confidence intervals, were reported. Results: The CTG uterine contraction recording had the highest sensitivity for predicting birth within the next 2 days, whereas a Bishop score ≥6 revealed the highest specificity, positive predictive value, and positive likelihood ratio. Inadequate cervical length for gestational age exhibited a high negative predictive value and the lowest negative likelihood ratio. Conclusion: The cervical length test has good diagnostic and prognostic performance among the four tests for preterm birth. Cervical funneling and CTG tests have poor predictive value, whereas the Bishop score has a superior diagnostic performance to the other tests. [ABSTRACT FROM AUTHOR]

Background: The objective of this research was to conduct a qualitative study among a diverse group of providers to identify their clinical needs, barriers, and adverse safety events in the peripartum care of people with a body mass index (BMI) ≥ 50 kg/m2. Methods: Obstetricians, anesthesiologists, certified nurse midwives, nurse practitioners, and nurses were invited to participate in focus group discussions if they were employed at the hospital for >6 months. Key concepts in the focus group guide included: (1) Discussion of challenging situations, (2) Current peripartum management approaches, (3) Patient and family knowledge and counseling, (4) Design and implementation of a guideline (e.g., checklist or toolkit) for peripartum care. The audiotaped focus groups were transcribed verbatim, uploaded to a qualitative analysis software program, and analyzed using inductive and constant comparative approaches. Emerging themes were summarized along with representative quotes. Results: Five focus groups of 27 providers were completed in 2023. The themes included staffing (level of experience, nursing-patient ratios, safety concerns), equipment (limitations of transfer mats, need for larger sizes, location for blood pressure cuff, patient embarrassment), titrating oxytocin (lack of guidelines, range of uses), monitoring fetal heart rate and contractions, patient positioning, and communication (lack of patient feedback, need for bias training, need for interdisciplinary relationships). Providers gave examples of items to include in a "BMI cart" and suggestions for a guideline including designated rooms for patients with a BMI ≥ 50 kg/m2, defining nursing ratios and oxytocin titration plans, postpartum incentive spirometer, and touch points with providers (nursing, physicians) at every shift change. Conclusions: Providers discussed a range of challenges and described how current approaches to care may negatively affect the peripartum experience and pose threats to safety for patients with a BMI ≥ 50 kg/m2 and their providers. We gathered information on improving equipment and communication among providers. [ABSTRACT FROM AUTHOR]

Objective: To propose a computerized system utilizing multiscene analysis based on a support vector machine (SVM) and convolutional neural network (CNN) to assess cardiotocography (CTG) intelligently. Methods: We retrospectively collected 2542 CTG records of singleton pregnancies delivered at the maternity ward of the First Affiliated Hospital of Xi'an Jiaotong University from October 10, 2020, to August 7, 2021. CTG records were divided into five categories (baseline, variability, acceleration, deceleration, and normality). Apart from the category of normality, the other four different categories of abnormal data correspond to four scenes. Each scene was divided into training and testing sets at 9:1 or 7:3. We used three computer algorithms (dynamic threshold, SVM, and CNN) to learn and optimize the system. Accuracy, sensitivity, and specificity were performed to evaluate performance. Results: The global accuracy, sensitivity, and specificity of the system were 93.88%, 93.06%, and 94.33%, respectively. In acceleration and deceleration scenes, when the convolution kernel was 3, the test data set reached the highest performance. Conclusion: The multiscene research model using SVM and CNN is a potential effective tool to assist obstetricians in classifying CTG intelligently. Synopsis: The computer‐aided diagnosis system based on support vector machine and convolutional neural network is valuable for classification of cardiotocography. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BACKGROUND: Following the latest trends in the development of artificial intelligence (AI), the possibility of processing an immense amount of data has created a breakthrough in the medical field. Practitioners can now utilize AI tools to advance diagnostic protocols and improve patient care. OBJECTIVE: The aim of this article is to present the importance and modalities of AI in maternal-fetal medicine and obstetrics and its usefulness in daily clinical work and decision-making process. METHODS: A comprehensive literature review was performed by searching PubMed for articles published from inception up until August 2023, including the search terms "artificial intelligence in obstetrics", "maternal-fetal medicine", and "machine learning" combined through Boolean operators. In addition, references lists of identified articles were further reviewed for inclusion. RESULTS: According to recent research, AI has demonstrated remarkable potential in improving the accuracy and timeliness of diagnoses in maternal-fetal medicine and obstetrics, e.g., advancing perinatal ultrasound technique, monitoring fetal heart rate during labor, or predicting mode of delivery. The combination of AI and obstetric ultrasound can help optimize fetal ultrasound assessment by reducing examination time and improving diagnostic accuracy while reducing physician workload. CONCLUSION: The integration of AI in maternal-fetal medicine and obstetrics has the potential to significantly improve patient outcomes, enhance healthcare efficiency, and individualized care plans. As technology evolves, AI algorithms are likely to become even more sophisticated. However, the successful implementation of AI in maternal-fetal medicine and obstetrics needs to address challenges related to interpretability and reliability. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Electronic fetal monitoring (EFM) is used to identify early signs of fetal deterioration. However, caution is advised when interpreting cardiotocographic parameters. A promising alternative is umbilical cord blood sampling. The analysis of blood gases and lactate levels in the cord within the initial minutes of life is a recommended approach. STUDY DESIGN: This prospective cohort study, conducted over eighteen months from June 2021 to December 2022, enrolled 70 patients with non-reactive and 70 with reactive cardiotocograph (CTG) patterns. APGAR scores were recorded at 1 and 5-minute intervals. 1 ml of umbilical artery blood was assessed in an arterial blood gas machine and fetal acidosis was defined as pH <7.0 and a lactate concentration exceeding 4 mmol/L. RESULTS: In the non-reactive CTG group, 35.7% had early decelerations, 37.1% had variable decelerations, and 17.1% had late decelerations (p<0.001). The mean cord blood lactate was 5.220±1.970 mmol/L in the non-reactive CTG group and 3.400±0.228 mmol/L in the reactive CTG group. Similarly, the mean cord blood pH was 7.030±0.007 in the non-reactive CTG group and 7.170±0.076 in the reactive CTG group (p<0.001). 14.3% of cases in the non-reactive CTG group had a 5-minute APGAR <7, with a higher APGAR score in the reactive group. CONCLUSION: The study suggests that abnormal or indeterminate CTG readings are linked to a higher risk of intrapartum fetal acidosis. Non-reactive CTG results were associated with higher mean cord blood lactate and pH levels and more number of Neonatal Intensive Care Unit (NICU) admissions. There is a definite correlation between abnormal CTG patterns and poorer neonatal outcomes. [ABSTRACT FROM AUTHOR]

OBJECTIVES: This study was conducted to evaluate the impact of listening to fetal heartbeats (FHBs) on the feelings of normal and high-risk pregnancies (HRPs), and to learn the colors and geometrical figures representing their feelings. STUDY DESIGN: This retrospective cohort study consisted of 291 pregnant women who applied for a non-stress test (NST). Participants were divided into two groups; 1: Normal pregnancies (Group1) and 2: HRPs (Group2). Demographic variables, feelings in response to listening to FHBs (negative, neutral, positive), grade mark (0-10) of feelings, color (warm, neutral, cold), and figure (simple, complex) preferences were retrospectively evaluated. RESULTS: Of the 291 women, 172 (59.1%) Group 1 participants were compared to 119 (40.9%) Group 2 participants. Group 1 and Group 2 had similar feelings (p>0.05), however, the rate of negative feelings was higher in Group 2 (11.6% vs. 20.2%). Higher marks were observed in Group 2 with happiness and peace/relaxation after listening to FHBs. Fear was the lowest mark in women with positive/neutral feelings in both groups. Women in Group 1 preferred warm colors regardless of their feelings. Women in Group 2 who have positive feelings chose warm colors, whereas women who felt neutral or negative more commonly chose cold (55.5%) and neutral (41.7%) colors (p=0.017). Independent of feelings, simple figures were predominately preferred (p=0.04). CONCLUSION: NST is more than a perinatal surveillance method and listening to FHBs has a positive impact on the feelings of pregnancies. Warm colors were commonly related to positive feelings. Simple figures were preferred regardless of feelings. [ABSTRACT FROM AUTHOR]

Purpose: To explore the contribution of maternal and fetal parameters in predicting the time interval between diagnosis and development of adverse events leading to delivery in singleton pregnancies complicated with fetal microsomia. Methods: Prospective study on singleton pregnancies referred to a tertiary center because of suspicion of fetal smallness in the third trimester. The study cohort included cases with fetal abdominal circumference (AC) ≤ 10th centile or estimated fetal weight ≤ 10th centile or umbilical artery pulsatitlity index ≥ 90th centile. Development of pre-eclampsia, fetal demise, and fetal deterioration diagnosed by fetal Doppler studies or fetal heart rate monitoring and leading to delivery were considered as adverse events. Maternal demographics, obstetric history, blood pressure, serum PLGF, and fetal Doppler studies were explored as predictors of the time interval between the first visit to the clinic and the diagnosis of complications. Results: In 59 women, the median incubation period from presentation to the clinic to an adverse event was 6, 2 weeks, whereas half of the pregnancies (52.5%) did not develop any adverse event. PLGF was the strongest predictor of adverse events. Both PLGF in raw values and PLGF MOM had equally good predictive ability (AUC 0.82 and 0.78 respectively). Optimal cut-off points were 177.7 pg/ml for PLGF raw values (sensitivity 83% and specificity 66.7%) and 0.277 MoM (sensitivity 76% and specificity 86.7%). On multiple Cox regression analysis, maternal systolic blood pressure, PLGF, fetal increased umbilical artery PI, and reduced CP ratio were independently associated with adverse events. Half of the pregnancies with low PLGF and only one in ten with high PLGF were delivered within two weeks after the initial visit. Conclusion: Half of the pregnancies carrying a small fetus in the third trimester will not develop maternal or fetal complications. PLGF is a strong predictor of adverse events that can be used to customize antenatal care. [ABSTRACT FROM AUTHOR]

Monitoring fetal heart rate (FHR) through cardiotocography is crucial for the early diagnosis of fetal distress situations, necessitating prompt obstetrical intervention. However, FHR signals are often marred by various contaminants, making preprocessing techniques essential for accurate analysis. This scoping review, following PRISMA-ScR guidelines, describes the preprocessing methods in original research articles on human FHR (or beat-to-beat intervals) signal preprocessing from PubMed and Web of Science, published from their inception up to May 2021. From the 322 unique articles identified, 54 were included, from which prevalent preprocessing approaches were identified, primarily focusing on the detection and correction of poor signal quality events. Detection usually entailed analyzing deviations from neighboring samples, whereas correction often relied on interpolation techniques. It was also noted that there is a lack of consensus regarding the definition of missing samples, outliers, and artifacts. Trends indicate a surge in research interest in the decade 2011–2021. This review underscores the need for standardizing FHR signal preprocessing techniques to enhance diagnostic accuracy. Future work should focus on applying and evaluating these methods across FHR databases aiming to assess their effectiveness and propose improvements. [ABSTRACT FROM AUTHOR]

Objective: Although prior attempts have failed to identify the beneficial effects of intensive fetal monitoring on cerebral palsy, the association between nonreassuring fetal status (NRFS) during labor and the incidence of long‐term neurodevelopmental delays in offspring remains unclear. This study aimed to evaluate this association using a nationwide birth cohort. Methods: Data from 72 869 women with singleton deliveries at and after 37 weeks of gestation from the Japan Environment and Children's Study (2011–2014) were analyzed. Multivariable logistic regression models were used to analyze the odds ratios (ORs) for neurodevelopmental delays using the Ages & Stages Questionnaire (Third Edition) in offspring aged 3 years. Results: The adjusted ORs for personal–social problems were 1.52 (95% confidence interval [CI], 1.06–2.16) for offspring delivered vaginally by nulliparous mothers and 1.51 (95% CI, 1.05–2.18) (for males, 1.70 [95% CI, 1.15–2.50]) for those delivered via cesarean section. No significant changes in adjusted ORs for neurodevelopmental delays were observed among participants without neonatal Apgar scores (ASs) <7 and without umbilical arterial pH (UmA‐pH) <7.20. Conclusion: NRFS during labor was associated with an increased incidence of personal–social problems in offspring aged 3 years. However, this association was not confirmed after excluding participants with neonatal ASs <7 and UmA‐pH <7.20. The association between NRFS and offspring's neurodevelopmental delays might vary based on delivery settings, offspring sex, and short‐term neonatal outcomes. Synopsis: Nonreassuring fetal status during labor in certain delivery settings is associated with an increased incidence of personal–social problems in offspring aged 3 years. [ABSTRACT FROM AUTHOR]

Background Problems in intrapartum electronic fetal monitoring with cardiotocography (CTG) remain a major area of preventable harm. Poor understanding of the range of influences on safety may have hindered improvement. Taking an interdisciplinary perspective, we sought to characterise the everyday practice of CTG monitoring and the work systems within which it takes place, with the goal of identifying potential sources of risk. Methods Human factors/ergonomics (HF/E) experts and social scientists conducted 325 hours of observations and 23 interviews in three maternity units in the UK, focusing on how CTG tasks were undertaken, the influences on this work and the cultural and organisational features of work settings. HF/E analysis was based on the Systems Engineering Initiative for Patient Safety 2.0 model. Social science analysis was based on the constant comparative method. Results CTG monitoring can be understood as a complex sociotechnical activity, with tasks, people, tools and technology, and organisational and external factors all combining to affect safety. Fetal heart rate patterns need to be recorded and interpreted correctly. Systems are also required for seeking the opinions of others, determining whether the situation warrants concern, escalating concerns and mobilising response. These processes may be inadequately designed or function suboptimally, and may be further complicated by staffing issues, equipment and ergonomics issues, and competing and frequently changing clinical guidelines. Practice may also be affected by variable standards and workflows, variations in clinical competence, teamwork and situation awareness, and the ability to communicate concerns freely. Conclusions CTG monitoring is an inherently collective and sociotechnical practice. Improving it will require accounting for complex system interdependencies, rather than focusing solely on discrete factors such as individual technical proficiency in interpreting traces. [ABSTRACT FROM AUTHOR]

Non-invasive fetal electrocardiography (NI-ECG) is based on the acquisition of signals from electrodes on the mother's abdominal surface. This abdominal ECG (aECG) signal consists of the maternal ECG (mECG) along with the fetal ECG (fECG) and other noises and artifacts. These records allow the acquisition of valuable and reliable information that helps ensure fetal well-being during pregnancy. This paper proposes a procedure based on principal component analysis (PCA) to obtain a single-channel master abdominal ECG record that can be used as input to fetal heart rate extraction techniques. The new procedure requires three main processing stages: PCA-based analysis for fECG-component extraction, polarity test, and curve fitting. To show the advantages of the proposal, this PCA-based method has been used as the feeding stage to a previously developed clustering-based method for single-channel aECG fetal heart rate monitoring. The results obtained for a set of real abdominal ECG recordings from annotated public aECG databases, the Abdominal and Direct Fetal ECG Database and the Challenge 2013 Training Set A, show improved efficiency in fetal heart rate extraction and illustrate the benefits derived from the use of such a master abdominal ECG channel. This allows us to achieve proper fetal heart rate monitoring without the need for manual inspection and selection of channels to be processed, while also allowing us to analyze records that would have been discarded otherwise. [ABSTRACT FROM AUTHOR]

Non-invasive electrocardiography (NI-ECG) has become an indispensable tool for monitoring fetal and neonatal cardiac activity throughout the stages of pregnancy and postpartum care. This review emphasizes the distinct advantages of NI-ECG, including extended monitoring capabilities and valuable insights into fetal and neonatal health. The exploration of textile electrodes is highlighted as a promising alternative, offering improved comfort and reduced skin irritation compared to traditional adhesive electrodes. However, challenges in NI-ECG persist, with electrode placement, quantity, and noise removal being key considerations. The review underscores the significance of addressing interference sources, such as maternal and fetal body signals, motion artifacts, and electrode-skin contact. Additionally, the discussion extends to computer-aided diagnostics, presenting novel approaches for classifying fetal and neonatal health during pregnancy and delivery. Ongoing research aims to optimize electrode placement, develop advanced noise reduction algorithms, and explore sophisticated classification methodologies. These advancements hold the potential to enhance electronic monitoring, enabling early detection of abnormalities and promoting improved outcomes in prenatal and neonatal care.

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. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to investigate perinatal outcome in singleton pregnancies at term with isolated oligohydramnios, diagnosed by using the single deepest pocket method. Patients and Methods: In this historic cohort study, the perinatal outcomes of 196 women with isolated oligohydramnios at term, diagnosed by using the single deepest pocket method, were compared to 8,676 women with normal amniotic fluid volume. The primary outcome measure was the Cesarean section rate. Further outcome parameters included the rate of induction of labor, abnormal cardiotocography, umbilical cord pH and base excess, Apgar, meconium-stained liquor and admission to neonatal intensive care unit. Results: In the group with isolated oligohydramnios, there were significantly more Cesarean sections (p=0.0081) and more abnormal cardiotocographies (p=0.0005). Univariate and multivariate analyses showed that this difference was seen particularly in nulliparous women (p=0.0025 for Cesarean section and 0.0368 for abnormal cardiotocography). Peripartal and perinatal outcome parameters were not different between the two groups. Conclusion: In women with isolated oligohydramnios at term, there is no impact on fetal outcome. The influence of isolated oligohydramnios on the rate of cesarean section and abnormal cardiotocography is considered to be less than that of parity. [ABSTRACT FROM AUTHOR]

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic. Various cardiotocography measures infer wrongly and give wrong predictions because of human error. The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well. Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being. In the current period Machine learning (ML) is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional results. ML techniques play a pivotal role in detecting fetal disease in its early stages. This research article uses Federated machine learning (FML) and ML techniques to classify the condition of the fetus. This study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the data. So, the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06% and 0.94% of prediction accuracy and misprediction rate, respectively, and parallel the proposed model applying K-nearest neighbor (KNN) and achieves 82.93% and 17.07% of prediction accuracy and misprediction accuracy, respectively. So, by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Provision of effective care to all women and newborns during the perinatal period is a viable strategy for achieving the Sustainable Development Goal 3 targets on reducing maternal and neonatal mortality. This study examined perinatal care (antenatal, intrapartum, postpartum) and its association with perinatal deaths at three district hospitals in Bunyoro region, Uganda. Methods: A cross-sectional study was conducted in which a questionnaire was administered consecutively to 872 postpartum women before discharge who had attended antenatal care and given birth in the study hospitals. Data on care received during antenatal, labour, delivery, and postpartum period, and perinatal outcome were extracted from medical records of the enrolled postnatal women using a pre-tested structured tool. The care received from antenatal to 24 h postpartum period was assessed against the standard protocol of care established by World Health Organization (WHO). Poisson regression was used to assess the association between care received and perinatal death. Results: The mean age of the women was 25 years (standard deviation [SD] 5.95). Few women had their blood tested for hemoglobin levels, HIV, and Syphilis (n = 53, 6.1%); had their urine tested for glucose and proteins (n = 27, 3.1%); undertook an ultrasound scan (n = 262, 30%); and had their maternal status assessed (n = 122, 14%) during antenatal care as well as had their uterus assessed for contraction and bleeding during postpartum care (n = 63, 7.2%). There were 19 perinatal deaths, giving a perinatal mortality rate of 22/1,000 births (95% Confidence interval [CI] 8.1–35.5). Of these 9 (47.4%) were stillbirths while the remaining 10 (52.6%) were early neonatal deaths. In the antenatal phase, only fetal examination was significantly associated with perinatal death (adjusted prevalence ratio [aPR] = 0.22, 95% CI 0.1–0.6). No significant association was found between perinatal deaths and care during labour, delivery, and the early postpartum period. Conclusion: Women did not receive all the required perinatal care during the perinatal period. Perinatal mortality rate in Bunyoro region remains high, although it's lower than the national average. The study shows a reduction in the proportion of perinatal deaths for pregnancies where the mother received fetal monitoring. Strategies focused on strengthened fetal status monitoring such as fetal movement counting methods and fetal heart rate monitoring devices during pregnancy need to be devised to reduce the incidence of perinatal deaths. Findings from the study provide valuable information that would support the strengthening of perinatal care services for improved perinatal outcomes. [ABSTRACT FROM AUTHOR]

Objective The objective of this study was to compare performance of a maternal surface electrode patch with ultrasound- and tocodynamometer-based monitoring to detect fetal heart rate and uterine contractility in late preterm labors. Study Design Thirty women between 34 0/7 and 36 6/7 weeks' gestation were monitored simultaneously with a Doppler/tocodynamometer system and a wireless fetal–maternal abdominal surface electrode system. Fetal and maternal heart rate and uterine contraction data from both systems were compared. Reliability was measured by the success rate and percent agreement. Deming regression and Bland–Altman analysis estimated the concordance between the systems. Uterine contractions were assessed by visual interpretation of monitor tracings. Results The success rate for the surface electrode system was 89.5% (95% confidence interval [CI], 85.7–93.3), and for ultrasound it was 88.4% (95% CI, 84.9–91.9; p = 0.73), with a percent agreement of 88.1% (95% CI, 84.2–92.8). Results were uninfluenced by the patients' body mass. The mean Deming slope was 1 and the y-intercept was −3.0 beats per minute (bpm). Bland–Altman plots also showed a close relationship between the methods, with limits of agreement less than 10 bpm. The percent agreement for maternal heart rate was 98.2% (95% CI, 97.4–98.8), and for uterine contraction detection it was 89.5% (95% CI, 85.5–93.4). Conclusion Fetal heart rate and uterine contraction monitoring at 34 0/7 to 36 6/7 weeks using abdominal surface electrodes was not inferior to Doppler ultrasound/tocodynamometry for fetal–maternal assessment. Registration clinicaltrials.gov/February 20, 2017/identifier NCT03057275. Key Points Monitoring the preterm fetal heart rate with surface electrodes is feasible. Preterm contractions can be monitored with surface electrodes. The technique was noninferior to standard external monitors. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is gaining increasing interest in the field of medicine because of its capacity to process big data and pattern recognition. Cardiotocography (CTG) is widely used for the assessment of foetal well-being and uterine contractions during pregnancy and labour. It is characterised by inter- and intraobserver variability in interpretation, which depends on the observers' experience. Artificial intelligence (AI)-assisted interpretation could improve its quality and, thus, intrapartal care. Cardiotocography (CTG) raw signals from labouring women were extracted from the database at the University Hospital of Bern between 2006 and 2019. Later, they were matched with the corresponding foetal outcomes, namely arterial umbilical cord pH and 5-min APGAR score. Excluded were deliveries where data were incomplete, as well as multiple births. Clinical data were grouped regarding foetal pH and APGAR score at 5 min after delivery. Physiological foetal pH was defined as 7.15 and above, and a 5-min APGAR score was considered physiologic when reaching ≥7. With these groups, the algorithm was trained to predict foetal hypoxia. Raw data from 19,399 CTG recordings could be exported. This was accomplished by manually searching the patient's identification numbers (PIDs) and extracting the corresponding raw data from each episode. For some patients, only one episode per pregnancy could be found, whereas for others, up to ten episodes were available. Initially, 3400 corresponding clinical outcomes were found for the 19,399 CTGs (17.52%). Due to the small size, this dataset was rejected, and a new search strategy was elaborated. After further matching and curation, 6141 (31.65%) paired data samples could be extracted (cardiotocography raw data and corresponding maternal and foetal outcomes). Of these, half will be used to train artificial intelligence (AI) algorithms, whereas the other half will be used for analysis of efficacy. Complete data could only be found for one-third of the available population. Yet, to our knowledge, this is the most exhaustive and second-largest cardiotocography database worldwide, which can be used for computer analysis and programming. A further enrichment of the database is planned. [ABSTRACT FROM AUTHOR]

Obstetricians utilize cardiotocography (CTG) to assess the fetal heart and lungs during pregnancy. It can help determine if the foetus is healthy, in doubt, or suffering from disease by providing data on the fetal heart rate and uterine breathing. The analysis of CTG data has typically made use of machine learning (ML) techniques such as support vector machines and decision trees to forecast fetal health and enhance the detection procedure. Fetal heart rate and uterine contraction timing were recorded by CTG. Monitoring fetal health and ensuring normal fetal growth and development throughout pregnancy rely heavily on CTG intelligent categorization. Pregnancies with a higher risk of problems are the most common cases in which CTG is used to evaluate the health of the fetus. ML algorithms are utilized to evaluate state of the foetal health based on CTG-obtained factors. Compared to ML techniques, ensemble models have been shown to increase detection speed and effectiveness. Ensemble modeling refers to the practice of combining the scores or distributions from multiple related but distinct analytical models. In order to predict foetal health, ensemble models such as Boosting, AdaBoost, Extreme Gradient Boosting, Light gradient boost method (LightGBM), and stack models were used in the paper. When the outcomes are compared, the proposed stack model using logistic regression, decision tree, random forest and LightGBM proved to obtain the best performance with 96.71% success rate. The proposed methodology, which can be used to classify foetal health based on Fetal Heart Rate (FHR) data, is more efficient and superior to existing machine learning models, which have already been taken into consideration. [ABSTRACT FROM AUTHOR]

The article focuses on congenital syphilis, its epidemiology, and its impact on maternal and neonatal health outcomes. It discusses the historical context, recent trends, and the rising rates of congenital syphilis, emphasizing its consequences globally. It also touches upon the pathogenesis, maternal screening, clinical presentation during pregnancy, and the diagnosis of syphilis.

Objective The fetal consequences of intrapartum fetal tachycardia with maternal fever or clinical chorioamnionitis are not well studied. We evaluated the association between perinatal morbidity and fetal tachycardia in the setting of intrapartum fever. Study Design Secondary analysis of a multicenter randomized control trial that enrolled 5,341 healthy laboring nulliparous women ≥36 weeks' gestation. Women with intrapartum fever ≥ 38.0°C (including those meeting criteria for clinical chorioamnionitis) after randomization were included in this analysis. Isolated fetal tachycardia was defined as fetal heart rate (FHR) ≥160 beats per minute for at least 10 minutes in the absence of other FHR abnormalities. FHR abnormalities other than tachycardia were excluded from the analysis. The primary outcome was a perinatal composite (5-minute Apgar's score ≤3, intubation, chest compressions, or mortality). Secondary outcomes included low arterial cord pH (pH < 7.20), base deficit ≥12, and cesarean delivery. Results A total of 986 (18.5%) of women in the trial developed intrapartum fever, and 728 (13.7%) met criteria to be analyzed; of these, 728 women 336 (46.2%) had maternal-fetal medicine (MFM) reviewer-defined fetal tachycardia, and 349 of the 550 (63.5%) women during the final hour of labor had validated software (PeriCALM) defined fetal tachycardia. After adjusting for confounders, isolated fetal tachycardia was not associated with a significant difference in the composite perinatal outcome (adjusted odds ratio [aOR] = 3.15 [0.82–12.03]) compared with absence of tachycardia. Fetal tachycardia was associated with higher odds of arterial cord pH <7.2, aOR = 1.48 (1.01–2.17) and of infants with a base deficit ≥ 12, aOR = 2.42 (1.02–5.77), but no significant difference in the odds of cesarean delivery, aOR = 1.33 (0.97–1.82). Conclusion Fetal tachycardia in the setting of intrapartum fever or chorioamnionitis is associated with significantly increased fetal acidemia defined as a pH <7.2 and base excess ≥12 but not with a composite perinatal morbidity. Key Points The perinatal outcomes associated with fetal tachycardia in the setting of maternal fever are undefined. Fetal tachycardia was not significantly associated with perinatal morbidity although the sample size was limited. Fetal tachycardia was associated with an arterial cord pH <7.2 and base deficit of 12 or greater. [ABSTRACT FROM AUTHOR]

Background: Perinatal deaths due to hypoxia are preventable with continuous monitoring. Cardiotocography (CTG) is standard for intrapartum foetal assessment, aiming to detect signs of distress and intervene promptly to mitigate risk. Objective: To determine the accuracy of advanced intrapartum monitoring system in comparison with electronic CTG in tracking of non-reassuring foetal symptoms by pattern analysis of the FHR. Materials and methods: A single-centre, observation study was conducted at a tertiary care hospital from January 2020 to December 2021. CTG and an advanced portable intrapartum monitoring system (KEYAR) were applied simultaneously to all participants. Twenty-minute-long recording traces were obtained from both devices. Mode of delivery was noted for all patients along with Apgar score at 1 minute and 5 minutes. Results: The final study cohort was constituted by 94 participants. Most participants (57.4%) were primigravida. The mean (95% CI) sensitivity, specificity, positive predictive value and negative predictive value of KEYAR tracing were 33% (9.6, 70), 97.7% (92.09, 99.37), 50% (15, 85) and 95.5% (89.12, 98.26), respectively. The overall, diagnostic accuracy of KEYAR was 93.6% (86.77, 97.04). Conclusions: Advanced portable intrapartum monitoring device (KEYAR) is a new application with the benefits of easy user operability and portability. [ABSTRACT FROM AUTHOR]

BACKGROUND: The monitoring of fetal heart rate (FHR) before intrapartum has been crucial in modern obstetrics. FHR has been used for about 300 years to determine fetal status, leading to the development of monitoring devices to prevent fetal death during gestation. While medical devices like fetal electrocardiograms exist for disease detection, their size and cost limit individual use. OBJECTIVE: To address cardiovascular issues during pregnancy, a mobile system is developed to display heart rates and blood pressure on mobile devices. The system is generated from a medical device with Bluetooth communication, supplementing traditional monitoring. METHOD: The study focuses on creating a mobile system that connects to mobile operating systems, enhancing treatment, diagnosis, and patient monitoring. The mobile system displays cardiovascular data obtained from the medical device. RESULTS: The results are expected to have an immediate impact on cases where abnormal measurement parameters of the monitoring system occur during pregnancy. The use of mobile systems or applications on smartphones is seen as beneficial in distributing processing and census of embedded health systems. CONCLUSION: The study highlights the potential benefits of mobile systems in distributing processing for health systems, particularly in addressing cardiovascular problems during pregnancy. The creation of a mobile system for displaying cardiovascular data could significantly improve monitoring and early detection. [ABSTRACT FROM AUTHOR]

Objective: To determine whether COVID-19 infection in pregnancy is associated with adverse obstetric and perinatal outcomes. Methods: We conducted a retrospective cohort study in pregnant women who delivered in the Queen Elizabeth Hospital between 1 February 2022 and 30 April 2022. Outcome measures included adverse maternal outcomes (maternal intensive care unit [ICU] admission), obstetric outcomes (abnormal cardiotocography, mode of delivery, postpartum haemorrhage), and adverse perinatal outcomes (preterm delivery, low Apgar score, low birth weight, neonatal ICU admission, neonatal death). The association between maternal COVID-19 infection status and preterm delivery was evaluated. Results: Among 481 pregnant women, 136 were infected with or recovered from COVID-19 during pregnancy and 345 were not. COVID-19 infection during pregnancy resulted in higher rates of preterm delivery (adjusted odds ratio=2.30), maternal ICU admission, and neonatal ICU admission. Conclusion: COVID-19 infection during pregnancy is associated with an increased risk of adverse maternal and perinatal outcomes. [ABSTRACT FROM AUTHOR]

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