Cardiotocography Traces Research Articles

Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment

Cardiotocography (CTG) is applied routinely for fetal monitoring during the perinatal period to decrease the rates of neonatal mortality and morbidity as well as unnecessary interventions. The analysis of CTG traces has become an indispensable part of present clinical practices; however, it also has serious drawbacks, such as poor specificity and variability in its interpretation. The automated CTG analysis is seen as the most promising way to overcome these disadvantages. In this study, a novel prognostic model is proposed for predicting fetal hypoxia from CTG traces based on an innovative approach called image-based time-frequency (IBTF) analysis comprised of a combination of short time Fourier transform (STFT) and gray level co-occurrence matrix (GLCM). More specifically, from a graphical representation of the fetal heart rate (FHR) signal, the spectrogram is obtained by using STFT. The spectrogram images are converted into 8-bit grayscale images, and IBTF features such as contrast, correlation, energy, and homogeneity are utilized for identifying FHR signals. At the final stage of the analysis, different subsets of the feature space are applied as the input to the least square support vector machine (LS-SVM) classifier to determine the most informative subset. For this particular purpose, the genetic algorithm is employed. The prognostic model was performed on the open-access intrapartum CTU-UHB CTG database. The sensitivity and specificity obtained using only conventional features were 57.33% and 67.24%, respectively, whereas the most effective results were achieved using a combination of conventional and IBTF features, with a sensitivity of 63.45% and a specificity of 65.88%. Conclusively, this study provides a new promising approach for feature extraction of FHR signals. In addition, the experimental outcomes showed that IBTF features provided an increase in the classification accuracy.

Open-access software for analysis of fetal heart rate signals

Abstract Cardiotocography (CTG) comprises fetal heart rate (FHR) and uterine contraction (UC) signals that are simultaneously recorded. In clinical practice, a visual examination is subjectively performed by observers depending on the guidelines to evaluate CTG traces. Owing to this visual assessment, the variability in the interpretation of CTG between inter- and even intra-observers is considerably high. In addition, traditional clinical practice involves different human factors that distort the quantitative quality of the evaluation. Automated CTG analysis is the most promising way to tackle the main shortcomings of CTG by providing reproducibility of the evaluation as well as the quantitative results. In this study, open-access software (CTG-OAS) developed with MATLAB® is introduced for the analysis of FHR signals. The software contains important processes of the automated CTG analysis, from accessing the database to conducting model evaluations. In addition to traditionally used morphological, linear, nonlinear, and time–frequency features, the developed software introduces an innovative approach called image-based time–frequency features to characterize FHR signals. All functions of the software are well documented, and it is distributed freely for research purposes. In addition, an experimental study on the publicly accessible CTU-UHB database was performed using CTG-OAS to test the reliability of the software. The experimental study obtained results that included an accuracy of 77.81%, sensitivity of 76.83%, specificity of 78.27%, and geometric mean of 77.29%. These fairly promising results indicate that the software can be a valuable tool for the analysis of CTG signals. In addition, the results obtained using CTG-OAS can be easily compared to different algorithms. Moreover, different experimental setups can be designed using the tools provided by the software. Thus, the software can contribute to the development of new algorithms.

Pravastatin and-L-arginine combination improves umbilical artery blood flow and neonatal outcomes in dichorionic twin pregnancies through an nitric oxide-dependent vasorelaxant effect

The increase in fetal and neonatal morbidity and mortality associated with twin pregnancies correlates with an increased risk of preterm delivery, low birth weight, and intrauterine growth restriction (IUGR). Although the pathogenesis of IUGR is unclear and thus management remains a major challenge, feto-placental blood vessels are compromised, and altered umbilical blood flow is observed. In this pilot observational study we investigated the effects of pravastatin plus l-arginine on umbilical artery (umb art) blood flow. Between 2013 and 2016, five women received daily doses l-arginine and pravastatin when an umb art pulsatility index above limits for gestational age was observed and concerns about selective growth restrictions arose. All patients showed selective absent or reversed end-diastolic umbilical artery Doppler flow (AREDV) associated with increased perinatal mortality. Pravastatin (PRAV) plus l-arginine (l-Arg) treatment diminished umb art resistance significantly and allowed pregnancy to continue. No signs of acidosis or hypoxia, normal cardiotocography tracing, normal fetal movement and fetal weight gain were observed in the twins that showed abnormal umb art Dopplers. All neonates were born around 33 weeks (median 33 weeks, IQR [31.4–33.0]), thus diminishing substantially the chances for any prematurity-associated adverse neonatal outcomes. The infants now show normal growth and development. In in vitro studies, pravastatin induced relaxation of aortic rings. Murine studies identified were performed to investigate the mechanism behind PRAV+L-Arg beneficial effects. A nitric oxide (NO)-dependent synergistic vasorelaxant effect of PRAV+L-Arg was demonstrated using aortic rings. Increased levels of placental NO and increased synthesis of eNOS in placental endothelial cells were observed in mice treated with PRAV+L-Arg compared to untreated mice and mice treated with PRAV- or L-Arg alone.This study suggests that PRAV plus L-Arg might be a good therapeutic option to improve blood flow in umbilical arteries prolonging pregnancy and improving pregnancy outcomes in twins. A RCT should be organized to confirm these results.

Interobserver agreement in analysis of cardiotocograms recorded during trial of labor after cesarean

Introduction: To examine interobserver agreement in intrapartum cardiotocography (CTG) classification in women undergoing trial of labor after a cesarean section (TOLAC) at term with or without complete uterine rupture.Materials and methods: Nineteen blinded and independent Danish obstetricians assessed CTG tracings from 47 women (174 individual pages) with a complete uterine rupture during TOLAC and 37 women (133 individual pages) with no uterine rupture during TOLAC. Individual pages with CTG tracings lasting at least 20 min were evaluated by three different assessors and counted as an individual case. The tracings were analyzed according to the modified version of the Federation of Gynaecology and Obstetrics (FIGO) guidelines elaborated for the use of STAN (ST-analysis). Occurrence of defined abnormalities was recorded and the tracings were classified as normal, suspicious, pathological, or preterminal. The interobserver agreement was evaluated using Fleiss’ kappa.Results: Agreement on classification of a preterminal CTG was almost perfect. The interobserver agreement on normal, suspicious or pathological CTG was moderate to substantial. Regarding the presence of severe variable decelerations, the agreement was moderate. No statistical difference was found in the interobserver agreement between classification of tracings from women undergoing TOLAC with and without complete uterine rupture.Conclusions: The interobserver agreement on classification of CTG tracings from high-risk deliveries during TOLAC is best for assessment of a preterminal CTG and the poorest for the identification of severe variable decelerations.

Teaching childbirth with high-fidelity simulation. Is it better observing the scenario during the briefing session?

The design of optimal courses for obstetric undergraduate teaching is a relevant question. This study evaluates two different designs of simulator-based learning activity on childbirth with regard to respect to the patient, obstetric manoeuvres, interpretation of cardiotocography tracings (CTG) and infection prevention. This randomised experimental study which differs in the content of their briefing sessions consisted of two groups of undergraduate students, who performed two simulator-based learning activities on childbirth. The first briefing session included the observations of a properly performed scenario according to Spanish clinical practice guidelines on care in normal childbirth by the teachers whereas the second group did not include the observations of a properly performed scenario, and the students observed it only after the simulation process. The group that observed a properly performed scenario after the simulation obtained worse grades during the simulation, but better grades during the debriefing and evaluation. Simulator use in childbirth may be more fruitful when the medical students observe correct performance at the completion of the scenario compared to that at the start of the scenario.Impact statementWhat is already known on this subject? There is a scarcity of literature about the design of optimal high-fidelity simulation training in childbirth. It is known that preparing simulator-based learning activities is a complex process. Simulator-based learning includes the following steps: briefing, simulation, debriefing and evaluation. The most important part of high-fidelity simulations is the debriefing. A good briefing and simulation are of high relevance in order to have a fruitful debriefing session.What do the results of this study add? Our study describes a full simulator-based learning activity on childbirth that can be reproduced in similar facilities. The findings of this study add that high-fidelity simulation training in childbirth is favoured by a short briefing session and an abrupt start to the scenario, rather than a long briefing session that includes direct instruction in the scenario.What are the implications of these findings for clinical practice and/or further research? The findings of this study reveal what to include in the briefing of simulator-based learning activities on childbirth. These findings have implications in medical teaching and in medical practice.

Prediction of adverse perinatal outcome by cerebroplacental ratio adjusted for estimated fetal weight

To evaluate the relationship between cerebroplacental ratio (CPR) and estimated fetal weight (EFW) in low- and high-risk singleton pregnancies. Furthermore, we evaluated the role of CPR in the prediction of adverse perinatal outcome and whether CPR measurements adjusted for EFW improve its predictive value. This was a retrospective cohort study including pregnancies in which Doppler investigations of umbilical artery (UA) and fetal middle cerebral artery (MCA) were performed at ≥ 30 weeks' gestation. Pregnancies were allocated to one of three groups according to EFW centile: small-for-gestational age (SGA) with EFW < 10th centile, appropriate-for-gestational age (AGA) and large-for-gestational age (LGA) with EFW > 90th centile. CPR was calculated as the ratio between the UA pulsatility index (PI) and MCA-PI and converted to CPR multiples of the median (MoMs) according to the three EFW groups. Linear regression analysis was performed to evaluate the relationship between CPR-MoMs and EFW centiles in low-risk pregnancies. Furthermore, MoMs of CPR adjusted according to EFW centile (aCPR-MoMs) were calculated. Adverse perinatal outcome was defined as presence of pathological cardiotocography (CTG) trace, arterial cord blood pH < 7.1, 5-min Apgar score < 7 and presence of meconium-stained amniotic fluid (MSAF). A total of 3515 (3016 low risk and 499 high risk) pregnancies, delivered between January 2010 and March 2016, were included. Linear regression analysis revealed a significant positive correlation between EFW centile and CPR-MoM. Receiver-operating characteristics (ROC) curve analysis showed a significant association between CPR-MoM and pathological CTG trace (AUC, 0.539; SD, 0.014; P = 0.005) and low Apgar score (AUC, 0.609; SD, 0.041; P = 0.008), but not with low arterial pH or MSAF. There was a significant association between aCPR-MoM and pathological CTG trace (AUC, 0.540; SD, 0.014; P = 0.003), low arterial cord blood pH (AUC, 0.546; SD, 0.022; P = 0.035) and low Apgar score (AUC, 0.609; SD, 0.044; P = 0.008), but not with MSAF. However, detection rates for adverse perinatal outcomes by CPR-MoM and aCPR-MoM were low, ranging from 6.7% to 28.6% for SGA, 12.1% to 22.2% for AGA and 0% to 33.3% for LGA, for a false-positive rate of 10%. In a subgroup analysis of cases in which ultrasound examination was performed at ≥ 34 weeks of gestation and within 4 weeks of delivery (n = 1439), the ROC curves for aCPR-MoM were significantly associated with all four outcomes evaluated. CPR-MoM values are dependent on EFW centiles; therefore, we suggest that CPR-MoM should be adjusted for EFW centile. However, both CPR- and aCPR-MoM showed a low prediction rate for adverse perinatal outcome. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

New FIGO and Swedish intrapartum cardiotocography classification systems incorporated in the fetal ECG ST analysis (STAN) interpretation algorithm: agreements and discrepancies in cardiotocography classification and evaluation of significant ST events.

IntroductionThe updated intrapartum cardiotocography (CTG) classification system by FIGO in 2015 (FIGO2015) and the FIGO2015‐approached classification by the Swedish Society of Obstetricians and Gynecologist in 2017 (SSOG2017) are not harmonized with the fetal ECG ST analysis (STAN) algorithm from 2007 (STAN2007). The study aimed to reveal homogeneity and agreement between the systems in classifying CTG and ST events, and relate them to maternal and perinatal outcomes.Material and methodsAmong CTG traces with ST events, 100 traces originally classified as normal, 100 as suspicious and 100 as pathological were randomly selected from a STAN database and classified by two experts in consensus. Homogeneity and agreement statistics between the CTG classifications were performed. Maternal and perinatal outcomes were evaluated in cases with clinically hidden ST data (n = 151). A two‐tailed p < 0.05 was regarded as significant.ResultsFor CTG classes, the heterogeneity was significant between the old and new systems, and agreements were moderate to strong (proportion of agreement, kappa index 0.70–0.86). Between the new classifications, heterogeneity was significant and agreements strong (0.90, 0.92). For significant ST events, heterogeneities were significant and agreements moderate to almost perfect (STAN2007 vs. FIGO2015 0.86, 0.72; STAN2007 vs. SSOG2017 0.92, 0.84; FIGO2015 vs. SSOG2017 0.94, 0.87). Significant ST events occurred more often combined with STAN2007 than with FIGO2015 classification, but not with SSOG2017; correct identification of adverse outcomes was not significantly different between the systems.ConclusionThere are discrepancies in the classification of CTG patterns and significant ST events between the old and new systems. The clinical relevance of the findings remains to be shown.

Early Effect of Epidural Analgesia on Fetal Acid-base Balance in the First Stage of Labour

Introduction: Epidural analgesia is a consolidated therapeutic technique generally used for the relief of labor pain. Since its introduction in obstetrics, there have been many studies that evaluate the effect that this type of analgesia has over the course of labor, and its possible repercussions on the mother and the fetus/newborn by analyzing data at birth. However, there exist very few studies that analyze the early effect that epidural analgesia has on the fetus. Objectives: The main objective of this study is to analyze the early effects of epidural analgesia on the fetal status by evaluating the possible changes in the acid-base fetal state, the most precise way to evaluate fetal wellbeing during labor, and cardiotocographic (CTG) tracing of the fetal heart rate after the administration of an epidural. Methods: This is a prospective study of 193 patients, in which a determination of the fetal acid-base equilibrium was done before the administration of epidural analgesia and repeated 60 min afterwards, evaluating possible changes in the results motivated by analgesia. Results: There was a statistically significant descent on fetal blood pH after the administration of epidural analgesia, as well as a significant increase in the number of fetal heart traces with alterations. The descent of fetal pH was greater in patients that had some gestational associated conditions. Conclusion: The administration of epidural analgesia during the first stage of labor caused, as an early effect, a significant descent in fetal blood pH, without that descent being clinically relevant over the fetal status in healthy fetuses. There must be a strict control in fetuses with some initial alteration in the CTG tracings.

Study of fetal heart rate abnormalities observed on cardiotocography in Lubumbashi: about a cases followed at the Lubumbashi University Clinic and the General Hospital of the Cinquantenaire

L'usage du cardiotocographe (CTG) est très récent à Lubumbashi mais aucune étude approfondie n'est encore menée pour dégager son impact sur la morbi-mortalité périnatale. L'objectif de cette étude est de déterminer la fréquence des anomalies du rythme cardiaque fœtal (RCF), d'en rechercher les facteurs associés afin de proposer une prise en charge appropriée. Il s'agit d'une étude descriptive transversale réalisée durant 19 mois (de mars 2015 à décembre 2016) chez 411 parturientes. En présence des anomalies pathologiques du RCF, la sensibilité et la valeur prédictive positive de l'examen cardiotocographique, dans le dépistage de la souffrance fœtale aigue étaient respectivement de 82,95 et 45,35%. Les anomalies du RCF étaient retrouvées chez deux parturientes sur cinq. Les décélérations étaient les plus fréquentes de toutes les anomalies du RCF observées (50,8%) avec une prédominance remarquable des décélérations tardives (22,1% de toutes les anomalies). Les facteurs associés aux anomalies pathologiques du RCF étaient le travail prolongé (OR = 14,64, IC = 3,91-54,81), la chorioamniotite (OR = 14,56, IC = 3,83-55,34), l'anémie chronique maternelle (OR = 4,99, IC = 1,48-16,85), La primiparité (OR = 2,69, IC = 1,49-4,85), la prématurité (OR = 2,90, IC = 1,51-5,54) et la grossesse prolongée (OR = 3,22, IC = 1,38-7,52). Le Retard de Croissance Intrautérin et l'hypertension artérielle étaient associés particulièrement aux tracés plats et aux décélérations tardives (OR = 7,79, IC = 2,50-24,30 et OR = 2,74, IC = 1,31-5,72). Le CTG est un outil de dépistage de la souffrance fœtale aigue mais avec un taux élevé de faux positifs (55%); il convient de lui associer les autres moyens de dépistage de la souffrance fœtale aigue de seconde ligne en vue de réduire ce taux. Les facteurs associés aux anomalies pathologiques du RCF sont souvent à l'origine des causes de la souffrance fœtale aigue et exigent ainsi une analyse rigoureuse des tracés du CTG.

A Study of Artificial Neural Network Training Algorithms for Classification of Cardiotocography Signals

Cardiotocography (CTG) that contains fetal heart rate (FHR) and uterine contraction (UC) signals is a monitoring technique. During the last decades, FHR signals have been classified as normal, suspicious, and pathological using machine learning techniques. As a classifier, artificial neural network (ANN) is notable due to its powerful capabilities. For this reason, behaviors and performances of neural network training algorithms were investigated and compared on classification task of the CTG traces in this study. Training algorithms of neural network were categorized in five group as Gradient Descent, Resilient Backpropagation, Conjugate Gradient, Quasi-Newton, and Levenberg-Marquardt. Two different experimental setups were performed during the training and test stages to achieve more generalized results. Furthermore, several evaluation parameters, such as accuracy (ACC), sensitivity (Se), specificity (Sp), and geometric mean (GM), were taken into account during performance comparison of the algorithms. An open access CTG dataset containing 2126 instances with 21 features and located under UCI Machine Learning Repository was used in this study. According to results of this study, all training algorithms produced rather satisfactory results. In addition, the best classification performances were obtained with Levenberg-Marquardt backpropagation (LM) and Resilient Backpropagation (RP) algorithms. The GM values of RP and LM were obtained as 89.69% and 86.14%, respectively. Consequently, this study confirms that ANN is a useful machine learning tool to classify FHR recordings.

Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces

Human visual inspection of Cardiotocography traces is used to monitor the foetus during labour and avoid neonatal mortality and morbidity. The problem, however, is that visual interpretation of Cardiotocography traces is subject to high inter and intra observer variability. Incorrect decisions, caused by miss-interpretation, can lead to adverse perinatal outcomes and in severe cases death. This study presents a review of human Cardiotocography trace interpretation and argues that machine learning, used as a decision support system by obstetricians and midwives, may provide an objective measure alongside normal practices. This will help to increase predictive capacity and reduce negative outcomes. A robust methodology is presented for feature set engineering using an open database comprising 552 intrapartum recordings. State-of-the-art in signal processing techniques is applied to raw Cardiotocography foetal heart rate traces to extract 13 features. Those with low discriminative capacity are removed using Recursive Feature Elimination. The dataset is imbalanced with significant differences between the prior probabilities of both normal deliveries and those delivered by caesarean section. This issue is addressed by oversampling the training instances using a synthetic minority oversampling technique to provide a balanced class distribution. Several simple, yet powerful, machine-learning algorithms are trained, using the feature set, and their performance is evaluated with real test data. The results are encouraging using an ensemble classifier comprising Fishers Linear Discriminant Analysis, Random Forest and Support Vector Machine classifiers, with 87% (95% Confidence Interval: 86%, 88%) for Sensitivity, 90% (95% CI: 89%, 91%) for Specificity, and 96% (95% CI: 96%, 97%) for the Area Under the Curve, with a 9% (95% CI: 9%, 10%) Mean Square Error.

Obstetric outcomes of pre-induction of labor with a 200 μg misoprostol vaginal insert.

Labor induction is indicated in 20% to 40% of pregnancies. Over half of pregnancies qualified for the induction of labor require stimulation of the cervix to ripen. The drug used increasingly more often in pre-induction is the PGE-1 pros-taglandin analog - misoprostol 200 μg. The study includes a total of 100 patients qualified for labor pre-induction with Misodel® (miso-prostol 200 μg vaginal insert). The study group comprises two subgroups: primigravidas and multiparas. Assessments included: indications for labor pre-induction, time from Misodel application to delivery, caesarean section rate and indica-tions, duration of first and second stage of labor, rate of vaginal deliveries, need for oxytocin or fenoterol administration side effects and newborn condition. The most common indication for labor induction was gestational diabetes and pregnancy past term. The average time to vaginal delivery was 14 h 45 min, time to the onset of active phase of labor - 11 h 45 min, time to membranes' rupture - 15 h, time to vaginal delivery - 14 h 18 min. The times of multiparas were significantly shorter. The rate of vaginal deliveries within 12 hours amounted to 42.42%, while within 24 hours it reached 83.33%. The overall caesarean section rate was 33%. The most common indication for caesarean section was the risk of intrauterine hypoxia. Tachysystole and hyperstimulation was observed in 4% of cases, while abnormalities in the cardiotocographic tracing in 43%. Misodel is an effective method for labor pre-induction, without affecting the caesarean section rate and has no adverse effect on the newborn condition.

Classification of caesarean section and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms

BackgroundVisual inspection of cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% positive predictive value for the classification of pathological outcomes. This has a significant negative impact on the perinatal foetus and often results in cardio-pulmonary arrest, brain and vital organ damage, cerebral palsy, hearing, visual and cognitive defects and in severe cases, death. This paper shows that using machine learning and foetal heart rate signals provides direct information about the foetal state and helps to filter the subjective opinions of medical practitioners when used as a decision support tool. The primary aim is to provide a proof-of-concept that demonstrates how machine learning can be used to objectively determine when medical intervention, such as caesarean section, is required and help avoid preventable perinatal deaths.MethodsThis is evidenced using an open dataset that comprises 506 controls (normal virginal deliveries) and 46 cases (caesarean due to pH ≤ 7.20—acidosis, n = 18; pH > 7.20 and pH < 7.25—foetal deterioration, n = 4; or clinical decision without evidence of pathological outcome measures, n = 24). Several machine-learning algorithms are trained, and validated, using binary classifier performance measures.ResultsThe findings show that deep learning classification achieves sensitivity = 94%, specificity = 91%, Area under the curve = 99%, F-score = 100%, and mean square error = 1%.ConclusionsThe results demonstrate that machine learning significantly improves the efficiency for the detection of caesarean section and normal vaginal deliveries using foetal heart rate signals compared with obstetrician and midwife predictions and systems reported in previous studies.

Evidence of lower oxygen reserves during labour in the growth restricted human foetus: a retrospective study

BackgroundThe aim of the present study is to test the hypothesis that Growth Restricted foetuses (FGR) have the tendency to develop more pathological cardiotocograpic tracings during labour than do appropriate for gestational age foetuses and that there is a shorter time lapse from the beginning of labour and the advent of a pathological cardiotocograpic tracing.MethodsThe study was carried out at the Maternal-Foetal Medicine Unit of the Sant’Anna University Hospital, Turin, Italy. A total of 930 foetuses born at term between January and December 2012 were analysed: 355 small for gestational age (SGA) comprising both constitutional small for gestational age and growth restricted foetuses (cases group) and 575 Appropriate for Gestational Age (AGA) foetuses (control group). Tracings were evaluated independently by two obstetric consultants, according to the International Federation of Gynaecology and Obstetrics (FIGO) classification. The main outcomes considered were the incidence of pathological cardiotocograpic tracings and the time interval between the beginning of labour and the advent of pathological cardiotocograpic tracing.The Student’s t-test, chi-square test and ANOVA were used for comparisons between cases and controls and amongst groups. Significance was set at <0.05. Univariate and multivariate odds-ratios were calculated.ResultsFoetuses with birthweight <3rd centile (growth restricted foetuses) more frequently presented pathological cardiotocograpic tracings in labour than did controls (43.8% vs. 21.6%; p < 0.001). Pathological cardiotocograpic tracing developed faster in the foetuses with birthweight <3rd centile group (53′, 0′-277′) than it did in the control group (170.5′, 0′-550′; p < 0.05).A higher induction rate was observed in the cases (29.6%) than in the control group (17%), with statistical significance p < 0.001. To correct for this possible confounding factor a multivariate logistic regression analysis was performed. It confirmed a statistically significant increased risk of pathological cardiotocographic tracings in the FGR group (OR 1.63; CI 1.30–2.05).ConclusionThe results confirm the hypothesis that Growth Restricted foetuses (FGR) have fewer oxygen reserves to deal with labour. Our results underscore the importance of the prenatal detection of these foetuses and of their continuous cardiotocographic monitoring during labour.

CTG Analyzer: A graphical user interface for cardiotocography.

Cardiotocography (CTG) is the most commonly used test for establishing the good health of the fetus during pregnancy and labor. CTG consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions (UC; mmHg). FHR is characterized by baseline, baseline variability, tachycardia, bradycardia, acceleration and decelerations. Instead, UC signal is characterized by presence of contractions and contractions period. Such parameters are usually evaluated by visual inspection. However, visual analysis of CTG recordings has a well-demonstrated poor reproducibility, due to the complexity of physiological phenomena affecting fetal heart rhythm and being related to clinician's experience. Computerized tools in support of clinicians represents a possible solution for improving correctness in CTG interpretation. This paper proposes CTG Analyzer as a graphical tool for automatic and objective analysis of CTG tracings. CTG Analyzer was developed under MATLAB®; it is a very intuitive and user friendly graphical user interface. FHR time series and UC signal are represented one under the other, on a grid with reference lines, as usually done for CTG reports printed on paper. Colors help identification of FHR and UC features. Automatic analysis is based on some unchangeable features definitions provided by the FIGO guidelines, and other arbitrary settings whose default values can be changed by the user. Eventually, CTG Analyzer provides a report file listing all the quantitative results of the analysis. Thus, CTG Analyzer represents a potentially useful graphical tool for automatic and objective analysis of CTG tracings.

Prenatal, perinatal and neonatal risk factors for perinatal arterial ischaemic stroke: a systematic review and meta-analysis.

The aim of the present study was to perform a meta-analysis of published data to determine the significance of clinical factors and exposures to the risk of perinatal arterial ischaemic stroke (PAIS) and provide guidance for clinical diagnosis and treatment. A comprehensive literature search of the PubMed, Embase, MEDLINE and Cochrane Library databases for relevant observational studies (cohort/case-control) from March 1984 to March 2016 was undertaken. Two review authors independently examined the full text records to determine which studies met the inclusion criteria and evaluated risk factors for PAIS. Risk ratios, odds ratios and 95% confidence intervals were estimated. A total of 11 studies were included in the analyses. Intrapartum fever >38°C, pre-eclampsia, oligohydramnios, primiparity, forceps delivery, vacuum delivery, fetal heart rate abnormalities, abnormal cardiotocography tracing, cord abnormalities, birth asphyxia, emergency caesarean section, tight nuchal cord, meconium-stained amniotic fluid, umbilical arterial pH <7.10, Apgar score at 5 min <7, resuscitation at birth, hypoglycaemia, male gender and small for gestational age were identified as risk factors for PAIS. This systemic review and meta-analysis provides a preliminary evidence-based assessment of the risk factors for PAIS. Patients with any of the risk factors identified in this analysis should be given careful consideration to ensure the prevention of PAIS. Future studies focusing on the combined effects of multiple prenatal, perinatal and neonatal risk factors for PAIS are warranted.

Reliability in cardiotocography interpretation - impact of extended on-site education in addition to web-based learning: an observational study.

Previous studies have shown poor reproducibility in cardiotocography (CTG) interpretation. Studies evaluating the Swedish web-based CTG-education program have not proven to increase accurate CTG assessments. The aim of this study was to evaluate whether an extended education can improve inter- and intra-observer reliability in CTG interpretation. Six obstetricians from two different departments interpreted 106 CTG tracings on two occasions. Both departments used a Swedish national web-based CTG education and test for training. One department had, in addition, an extended education program consisting of on-site lectures and oral examinations. Inter- and intra-observer agreements were calculated by simple or weighted kappa (κ) values for the five parameters assessed on CTG. In both departments inter-observer and intra-observer κ showed moderate to excellent agreement (ranges for κ 0.41-0.76 and 0.65-0.93, respectively). Obstetricians at the department with extended CTG education had better inter-observer reliability for variability and accelerations. This was also the case for intra-observer reliability with the addition of baseline frequency. Both inter- and intra-observer agreement increased from moderate to substantial in both departments when decelerations were dichotomized into harmless (including early and simple variable decelerations) or hypoxic (including late, severe variable, prolonged and combined decelerations) (κ 0.63-0.78) compared with the current sub-classification of decelerations (κ 0.42-0.65). Agreement in CTG interpretation was better than expected in both departments, especially when divided into harmless/hypoxic changes. Combination of different learning methods (web-based, on-site lectures and case discussion) might result in a better CTG interpretation agreement compared with web-based learning solely.

Recognition of chronic hypoxia and pre-existing foetal injury on the cardiotocograph (CTG): Urgent need to think beyond the guidelines

Chronic utero-placental insufficiency may result in progressive hypoxia culminating in fetal decompensation and acidosis and this is termed ‘chronic’ or ‘long-standing’ hypoxia. It is essential to recognise the features of chronic hypoxia on the CTG trace so as to institute timely and appropriate action. The current guidelines may not capture a fetus who starts labour already compromised or limited in its ability to compensate for hypoxic or mechanical stresses during labour. The aim of this short review is to explore the CTG features that allow the clinician to recognise a fetus who may present with an antenatal insult such as chronic hypoxia, anaemia, infection, fetal arrhythmias and preexisting non-hypoxic brain injury.

Midwife’s decisive action saved my baby’s life

When I was 38 weeks pregnant, I went to the labour ward of Harrogate District Hospital to get a cardiotocography (CTG) trace, after becoming concerned by reduced fetal movements.

Mother-newborn health indicators in possible victims of gender-based violence during pregnancy

BackgroundPregnancy increases the risk of gender-based violence, considered an underdiagnosed public health problem. ObjectiveTo determine the association between the situation of possible gender-based violence in the pregnant woman and variables related to pregnancy, labor, puerperium, and newborn health. DesignAn observational multicenter study. SettingsThree Spanish hospitals during 2015. Participants141 pregnant women in which information is collected sociodemographic variables and data related to pregnancy, labor, and puerperium were gathered by interview and from clinical records. Comparisons of means and logistic regression analyses were performed, calculating crude and adjusted odds ratios. ResultsThe study included 141 women; 44 in a situation of possible abuse required more medication during labor (p=0.018), had less early skin contact with their newborn (p=0.021) and more non-reassuring cardiotocography traces (p=0.012), and reported greater pain during labor (p=0.013). The children of the mothers in this situation had a lower mean Apgar score (p˂0.059), less frequently began breastfeeding early (p=0.008), and had higher risk of low birth weight (p˂0.001). ConclusionThe situation of possible abuse in pregnant women may negatively affect their pregnancy, their pain and need for medication during labor, and other newborn health indicators, among other health parameters.