Maternal Uterine Contractions Research Articles

A Fetal Well-Being Diagnostic Method Based on Cardiotocographic Morphological Pattern Utilizing Autoencoder and Recursive Feature Elimination.

Cardiotocography (CTG), which measures the fetal heart rate (FHR) and maternal uterine contractions (UC) simultaneously, is used for monitoring fetal well-being during delivery or antenatally at the third trimester. Baseline FHR and its response to uterine contractions can be used to diagnose fetal distress, which may necessitate therapeutic intervention. In this study, a machine learning model based on feature extraction (autoencoder), feature selection (recursive feature elimination), and Bayesian optimization, was proposed to diagnose and classify the different conditions of fetuses (Normal, Suspect, Pathologic) along with the CTG morphological patterns. The model was evaluated on a publicly available CTG dataset. This research also addressed the imbalance nature of the CTG dataset. The proposed model has a potential application as a decision support tool to manage pregnancies. The proposed model resulted in good performance analysis metrics. Using this model with Random Forest resulted in a model accuracy of 96.62% for fetal status classification and 94.96% for CTG morphological pattern classification. In rational terms, the model was able to accurately predict 98% Suspect cases and 98.6% Pathologic cases in the dataset. The combination of predicting and classifying fetal status as well as the CTG morphological patterns shows potential in monitoring high-risk pregnancies.

The Value of Non-invasive Electrocardiography in Assessing Fetal Status at Term Delivery.

The electrocardiograph (ECG) is efficient method for the accurate assessment of fetal heart rate. The barriers for accurate assessment are maternal heart rate, uterine contractions and abdominal muscles. Although previous monitoring methods have struggled to overcome these barriers, recent advances have led to a greater degree of success for listening and recording pulse-by-pulse fetal heart rate. A prospective cohort study evaluating the use, reliability and safety of non-invasive electrocardiography, in conjunction with Fetal Heart Rate parameters such as, Short Term Variability (STV) together with umbilical cord PH and Apgar score, during the active phase of childbirth. A total of 41 women with single, normal, full-term pregnancies had systematic obstetric monitoring with Monica AN24. 20 had only monitoring and 21 also had and arterial blood flow measurements. pH was measured and correlated with neonatal Apgar score at 1 and 5 min. The study also included a questionnaire about the safety and usability of obstetric monitoring. Statistical analysis was done using IBM SPSS v. 26.0. Mean age was 28.8 years, (SD ± 6.153). Electrocardiogram recordings (ECG) were classified as normal (71%) and suspicious (29%). Baseline between ECGs was different (p = 0.025) similarly for Short term variability (STV) (p <0.0001). BMI did not differentiate SVT rates. Only high acceleration (p <0.029) and small slowdowns had a statistically significant difference between normal and suspected cardiographs (p <0.029). APGAR score did not differ, whereas the umbilical cord pH was different in normal ECGs compared to the suspect (p = 0.012) and STV was also differentiated. A usability and safety survey was conducted after recording with MONIKA AN24, and the response to whether they would accept recording with the device again, was positive for 96% of the 30 responders. The present study shows that the use of electrocardiography in obstetrics allows to draw conclusions about the fetal hematopoiesis and oxygenation status. This method could be clinically applied and be an important tool for further screening in embryos that may be hypoxic and to decide whether to continue with a vaginal or cesarean delivery, thereby achieving the goal of reducing perinatal morbidity and mortality.

Non-invasive Fetal heartbeat detection using vibration sensing system

Monitoring the fetal heartbeat is essential for obtaining information about fetal condition during pregnancy. By measuring the maternal uterine contractions, the movement of the fetus, and the fetal heart rate, the state of the fetus is detected and taking appropriate measures prevent fetal health abnormality. The NST method is used to obtain the fetal heart rate. The ECG method is useful to observe heart rhythm. In this study, a system that can detect fetal heartbeat signals using vibration sensors is proposed. For vibration measurement, a band-type device with a sensor was proposed. The band was wrapped around the mother's stomach to sensing signals generated by the mother's body. In order to extract the fetal heartbeat signal, appropriate signal processing for denoising is performed. Processed signal was divided into several IMFs using the CEEMD method. The maternal heartbeat signal and fetal heartbeat signal were separated from the IMF. Through frequency analysis, the characteristics of each signal make clear

Forces Involved with Labor and Delivery-A Biomechanical Perspective.

Childbirth is a primarily biomechanical process of physiology, and one that engineers have recently begun to address in a broader fashion. Computational models are being developed to address the biomechanical effects of parturition on both maternal and fetal tissues. Experimental research is being conducted to understand how maternal tissues adapt to intrauterine forces near the onset of labor. All of this research requires an understanding of the forces that are developed through maternal efforts-both uterine contractions and semi-voluntary pushing-and that can be applied by the clinician to assist with the delivery. This work reviews the current state of knowledge regarding forces of labor and delivery, with a focus on macro-level biomechanics.

Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state assessment. Reliable FHR signal can be obtained from an invasive direct fetal electrocardiogram (FECG), but this is limited to labour. Alternative abdominal (indirect) FECG signals can be recorded during pregnancy and labour. Quality, however, is much lower and the maternal heart and uterine contractions provide sources of interference. Here, we present ten twenty-minute pregnancy signals and 12 five-minute labour signals. Abdominal FECG and reference direct FECG were recorded simultaneously during labour. Reference pregnancy signal data came from an automated detector and were corrected by clinical experts. The resulting dataset exhibits a large variety of interferences and clinically significant FHR patterns. We thus provide the scientific community with access to bioelectrical fetal heart activity signals that may enable the development of new methods for FECG signals analysis, and may ultimately advance the use and accuracy of abdominal electrocardiography methods.

Placental MRI: Effect of maternal position and uterine contractions on placental BOLD MRI measurements

IntroductionBefore using blood-oxygen-level-dependent magnetic resonance imaging (BOLD MRI) during maternal hyperoxia as a method to detect individual placental dysfunction, it is necessary to understand spatiotemporal variations that represent normal placental function. We investigated the effect of maternal position and Braxton-Hicks contractions on estimates obtained from BOLD MRI of the placenta during maternal hyperoxia. MethodsFor 24 uncomplicated singleton pregnancies (gestational age 27–36 weeks), two separate BOLD MRI datasets were acquired, one in the supine and one in the left lateral maternal position. The maternal oxygenation was adjusted as 5 min of room air (21% O2), followed by 5 min of 100% FiO2. After datasets were corrected for signal non-uniformities and motion, global and regional BOLD signal changes in R2* and voxel-wise Time-To-Plateau (TTP) in the placenta were measured. The overall placental and uterine volume changes were determined across time to detect contractions. ResultsIn mothers without contractions, increases in global placental R2* in the supine position were larger compared to the left lateral position with maternal hyperoxia. Maternal position did not alter global TTP but did result in regional changes in TTP. 57% of the subjects had Braxton-Hicks contractions and 58% of these had global placental R2* decreases during the contraction. ConclusionBoth maternal position and Braxton-Hicks contractions significantly affect global and regional changes in placental R2* and regional TTP. This suggests that both factors must be taken into account in analyses when comparing placental BOLD signals over time within and between individuals.

Multivariate Variational Mode Decomposition

In this paper, a generic extension of variational mode decomposition (VMD) algorithm for multivariate or multichannel data sets is presented. We first define a model for multivariate modulated oscillations that is based on the presence of a joint or common frequency component among all channels of input data. Using that model for multivariate oscillations, we construct a variational optimization problem that aims to extract an ensemble of band-limited modes containing inherent multivariate modulated oscillations present in multivariate input signal. The cost function to be minimized is the sum of bandwidths of all signal modes across all input data channels, which is a generic extension of the cost function used in standard VMD to multivariate data. Minimization of the resulting variational model is achieved through the alternate direction method of multipliers (ADMM) approach. That yields an optimal set of multivariate modes in terms of narrow bandwidth and corresponding center frequencies that are assumed to be commonly present among all channels of a multivariate modulated oscillation. We demonstrate the effectiveness of the proposed method through results obtained from extensive simulations involving test (synthetic) and real world multivariate data sets. Specifically, we focus on the ability of the proposed method to yield joint oscillatory modes in multivariate data which is a prerequisite in many real world applications involving nonstationary multivariate data. We also highlight the utility of the proposed method in two real world applications which include the separation of alpha rhythms in multivariate electroencephalogram (EEG) data and the decomposition of bivariate cardiotocographic signals that consist of fetal heart rate and maternal uterine contraction (FHR-UC) as its two channels.

A Strategy for Classification of "Vaginal vs. Cesarean Section" Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings.

We propose objective and robust measures for the purpose of classification of “vaginal vs. cesarean section” delivery by investigating temporal dynamics and complex interactions between fetal heart rate (FHR) and maternal uterine contraction (UC) recordings from cardiotocographic (CTG) traces. Multivariate extension of empirical mode decomposition (EMD) yields intrinsic scales embedded in UC-FHR recordings while also retaining inter-channel (UC-FHR) coupling at multiple scales. The mode alignment property of EMD results in the matched signal decomposition, in terms of frequency content, which paves the way for the selection of robust and objective time-frequency features for the problem at hand. Specifically, instantaneous amplitude and instantaneous frequency of multivariate intrinsic mode functions are utilized to construct a class of features which capture nonlinear and nonstationary interactions from UC-FHR recordings. The proposed features are fed to a variety of modern machine learning classifiers (decision tree, support vector machine, AdaBoost) to delineate vaginal and cesarean dynamics. We evaluate the performance of different classifiers on a real world dataset by investigating the following classifying measures: sensitivity, specificity, area under the ROC curve (AUC) and mean squared error (MSE). It is observed that under the application of all proposed 40 features AdaBoost classifier provides the best accuracy of 91.8% sensitivity, 95.5% specificity, 98% AUC, and 5% MSE. To conclude, the utilization of all proposed time-frequency features as input to machine learning classifiers can benefit clinical obstetric practitioners through a robust and automatic approach for the classification of fetus dynamics.

Digital cardiotocography: What is the optimal sampling frequency?

Cardiotocography (CTG) is the most popular prenatal diagnostic test for establishing fetal health and consists in simultaneous recording of fetal heart rate (FHR, bpm) and maternal uterine contraction (UC, mmHg) traces. Typically, FHR and UC traces are visually analyzed and interpreted by clinicians. Recently, software applications like CTG Analyzer have been developed to support visual CTG interpretation by making it more objective and independent from clinician’s experience. Automatic CTG analysis requires CTG-traces digitalization and thus assessment of a correct sampling frequency (SF). Thus, this paper aims to investigate dependency of automatic CTG analysis on SF in order to identify optimal SF (OSF) for FHR and UC traces that minimizes computational efforts without jeopardizing CTG interpretation. To this aim, the “CTU-CHB intra-partum CTG database” was considered and visually annotated by an expert gynecologist. FHR and UC traces, originally sampled at 4 Hz, were down sampled at 2 Hz, 1 Hz, 0.4 Hz and 0.2 Hz, and automatically analyzed using CTG Analyzer. Eventually, results obtained through automatic analysis were compared to visual annotations, which were taken as reference. A cumulative statistical index (CSI), ranging from 0.00% to 100.00%, was defined as a linear combination of positive-predictive value, sensitivity, false-positive rate and false-negative rate. OSF was defined as the one that maximizes CSI. If CSI was showing the same value for more than one SF, the lowest SF was selected as the optimal since minimizing computational efforts. Results indicate that OSF for FHR is 2 Hz (CSI ≥ 85.41%), whereas OSF for UC is 0.2 Hz (CSI = 75.21%).

Nonlinear characterization and complexity analysis of cardiotocographic examinations using entropy measures

The nonlinear analysis of biological time series provides new possibilities to improve computer aided diagnostic systems, traditionally based on linear techniques. The cardiotocography (CTG) examination records simultaneously the fetal heart rate (FHR) and the maternal uterine contractions. This paper shows, at first, that both signals present nonlinear components based on the surrogate data analysis technique and exploratory data analysis with the return (lag) plot. After that, a nonlinear complexity analysis is proposed considering two databases, intrapartum (CTG-I) and antepartum (CTG-A) with previously identified normal and suspicious/pathological groups. Approximate Entropy (ApEn) and Sample Entropy (SampEn), which are signal complexity measures, are calculated. The results show that low entropy values are found when the whole examination is considered, $$\hbox {ApEn}=0.3244\pm 0.1078$$ and $$\hbox {SampEn}=0.2351\pm 0.0758$$ ($$\hbox {average}\pm \hbox {standard}$$ deviation). Besides, no significant difference was found between the normal ($$\hbox {ApEn}=0.3366\pm 0.1250$$ and $$\hbox {SampEn}=0.2532\pm 0.0818$$) and suspicious/pathological ($$\hbox {ApEn}=0.3420\pm 0.1220$$ and $$\hbox {SampEn}=0.2457\pm 0.0850$$) groups for the CTG-A database. For a better analysis, this work proposes a windowed entropy calculation considering 5-min window. The windowed entropies presented higher average values ($$\hbox {ApEn}=0.6505\pm 0.2301$$ and $$\hbox {SampEn}=0.5290\pm 0.1188$$) for the CTG-A and ($$\hbox {ApEn}=0.5611\pm 0.1970$$ and $$\hbox {SampEn}=0.4909\pm 0.1782$$) for the CTG-I. The changes during specific long-term events show that entropy can be considered as a first-level indicator for strong FHR decelerations ($$\hbox {ApEn}=0.1487\pm 0.0341$$ and $$\hbox {SampEn}=0.1289\pm 0.0301$$), FHR accelerations ($$\hbox {ApEn}=0.1830\pm 0.1078$$ and $$\hbox {SampEn}=0.1501\pm 0.0703$$) and also for pathological behavior such as sinusoidal FHR ($$\hbox {ApEn}=0.1808\pm 0.0445$$ and $$\hbox {SampEn}=0.1621\pm 0.0381$$).

Automatic Identification and Classification of Fetal Heart-Rate Decelerations from Cardiotocographic Recordings.

Cardiotocography (CTG) consists in the simultaneous recording of two distinct traces, the fetal heart rate (FHR; bpm) and the maternal uterine contractions (UCs; mmHg). CTG analysis consists in the evaluation of specific features of traces, among which fetal decelerations (DECs) are considered the "center-stage" since possibly related to fetal distress. DECs are classified based on their duration and occurrence in relation to UCs as prolonged, early, late and variable; each class associates to a specific status of the fetus health. Typically, CTG traces are visually interpreted; however, computerized CTG analysis may overcome subjectivity in CTG interpretation. Thus, this study proposes a new automatic algorithm for computerized identification and classification of DECs. The algorithm was tested on the 552 CTG recordings constituting the "CTU-CHB intra-partum CTG database" of Physionet. Of these, 470 (85.15%) were found suitable for automatic DECs identification and classification. Overall, 5888 DECs were identified, of which 3255 (55.28%) were classified while the other 2633 (44.72%) remained unclassified due to very strict preliminary classification criteria (now required for avoiding misclassifications). Among the classified DECs, 468 (14.38%) were classified as prolonged, 1498 (46.02%) as early, 32 (0.98%) as late, 1257 (38.62%) as variable. Thus, among the classified DECs, the most common are the early and the variable ones (overall 84.64%), the occurrence of which ranged from 0 to 14 DECs per recording. These findings are in agreement with what reported in literature. In conclusion, the proposed algorithm for automatic DECs identification and classification represents a useful tool for computerized CTG analysis.

ECTG: an automatic procedure to extract digital cardiotocographic signals from digital images

Background and objectiveCardiotocography (CTG), consisting in the simultaneous recording of fetal heart rate (FHR) and maternal uterine contractions (UC), is a popular clinical test to assess fetal health status. Typically, CTG machines provide paper reports that are visually interpreted by clinicians. Consequently, visual CTG interpretation depends on clinician's experience and has a poor reproducibility. The lack of databases containing digital CTG signals has limited number and importance of retrospective studies finalized to set up procedures for automatic CTG analysis that could contrast visual CTG interpretation subjectivity. In order to help overcoming this problem, this study proposes an electronic procedure, termed eCTG, to extract digital CTG signals from digital CTG images, possibly obtainable by scanning paper CTG reports. MethodseCTG was specifically designed to extract digital CTG signals from digital CTG images. It includes four main steps: pre-processing, Otsu's global thresholding, signal extraction and signal calibration. Its validation was performed by means of the “CTU-UHB Intrapartum Cardiotocography Database” by Physionet, that contains digital signals of 552 CTG recordings. Using MATLAB, each signal was plotted and saved as a digital image that was then submitted to eCTG. Digital CTG signals extracted by eCTG were eventually compared to corresponding signals directly available in the database. Comparison occurred in terms of signal similarity (evaluated by the correlation coefficient ρ, and the mean signal error MSE) and clinical features (including FHR baseline and variability; number, amplitude and duration of tachycardia, bradycardia, acceleration and deceleration episodes; number of early, variable, late and prolonged decelerations; and UC number, amplitude, duration and period). ResultsThe value of ρ between eCTG and reference signals was 0.85 (P < 10−560) for FHR and 0.97 (P < 10−560) for UC. On average, MSE value was 0.00 for both FHR and UC. No CTG feature was found significantly different when measured in eCTG vs. reference signals. ConclusionseCTG procedure is a promising useful tool to accurately extract digital FHR and UC signals from digital CTG images.

Effectiveness of acupuncture versus spinal-epidural anesthesia on labor pain: a randomized controlled trial

ObjectiveTo evaluate the effectiveness of acupuncture analgesia (AA) compared with combined spinal-epidural anesthesia (CSEA) for labor pain relief and labor outcomes. MethodsWe evaluated 131 primiparous women who received respiratory guidance during maternal uterine contractions and received either AA (n = 43), CSEA (n = 45), or no additional treatment (control, n = 43). The groups were compared regarding visual analog scale (VAS) scores for abdominal and back pain, and labor outcomes. ResultsThe abdominal VAS scores of the AA and CSEA groups were significantly lower than that of the control group. In addition, the VAS scores of the CSEA group were significantly lower than that of the AA group at 10 and 60 min after intervention. The back pain VAS scores of the AA and CSEA groups were significantly lower than that of the control group at 5, 10, and 60 min after intervention. The duration of the active phase of labor in the CSEA group was significantly longer than that of the AA and control groups. The rates of oxytocin use (4.70%), urinary retention (4.70%), and postpartum hemorrhage (273.72 ± 53.63 mL) in the AA group were significantly lower than in the CSEA group (46.70%, 24.20%, and 320.00 ± 85.60 mL, respectively). ConclusionBoth AA and CSEA were effective for labor pain relief, CSEA provided more effective pain relief, while AA was associated with a shorter duration of labor and fewer adverse effects.and each has its advantages and disadvantages.

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.

Statistical baseline assessment in cardiotocography.

Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the "CTU-UHB intrapartum CTG database" from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<;10-19) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.

PARTIAL DIRECTED COHERENCE OF CARDIOTOCOGRAPHIC SIGNALS FOR ANALYSIS OF PRETERM BIRTH RISK

Traditional methods of fetal monitoring are used mainly during labor, leaving the only course of action . the caesarean intervention . in cases with high risk of fetal distress. We used another approach and set up a database that consists of cardiotocographic (CTG) recordings acquired ante partum during the 25th-28th week of pregnancy, by means of a Monica Healthcare AN24 fetal monitoring system. The analyzed signals are the maternal heart rate (MHR), the fetal heart rate (FHR) and the maternal uterine contractions (UC). The database is divided into two groups based on the risk of preterm labor: the control group that consists of 64 normal recordings and the study group that has 48 pathological or suspicious recordings. The analyzing method implemented is the Partial Directed Coherence (PDC) that determines the degree of correlation and the dynamic of couplings between corresponding signals. The purpose of the analysis is to identify the differences between the two groups and correlation degree for the specified signals in pathological or suspicious cases.

Expert systems for fetal assessment in labour

BACKGROUND: Cardiotocography (CTG) records the fetal heart rate in relation to maternal uterine contractions and is one of the most common forms of fetal assessment during labour. Despite guidelines for CTG interpretation, substantial inter- and intra-observer variation in interpretation has been reported among maternity care providers. Misinterpretation of CTG readings can lead to poor decisions, which can result in unnecessary intervention or delay or withholding of necessary intervention. Expert systems (ESs) represent a type of applied artificial intelligence, which can assist in complex clinical decision-making and potentially serve as a mechanism to improve interpretation of fetal heart rate tracings. OBJECTIVES: To evaluate the effectiveness of continuous or intermittent CTG monitoring during labour with an ES compared with (1) continuous or intermittent CTG monitoring during labour without an ES or (2) intermittent auscultation with a Pinard stethoscope or hand-held Doppler ultrasound device. Outcomes of interest included incidence of perinatal mortality, caesarean delivery, operative vaginal birth, fetal blood sampling, artificial rupture of amniotic membranes, oxytocin augmentation of labour, maternal satisfaction with labour, neonatal seizures, fetal acidaemia, hypoxic ischaemic encephalopathy, admission to neonatal special care and/or neonatal intensive care unit and an Apgar score less than seven at five minutes. SEARCH METHODS: We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (27 October 2014), Open Grey (6 October 2014) ProQuest Dissertation & Theses Database (6 October 2014) and reference lists of retrieved studies. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials comparing continuous or intermittent CTG monitoring during labour with an ES with continuous or intermittent CTG monitoring without an ES were eligible for this review. Trials comparing continuous or intermittent CTG monitoring during labour with an ES with intermittent auscultation with a Pinard or hand-held Doppler were also eligible. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed the eligibility and quality of the trials as well as extracted data to ensure accuracy. The authors of included trials were contacted to clarify aspects of the study design that were not clearly reported in the original trial publications. MAIN RESULTS: No studies comparing CTG monitoring during labour with an ES to intermittent auscultation were identified.Two randomised controlled trials comparing CTG monitoring during labour with an ES versus CTG without an ES were identified and included in the qualitative synthesis of results, but only one trial (n = 220) provided data for quantitative analysis. Both trials were classified as low risk of bias.There was no strong evidence that CTG with an ES has an effect on the incidence of caesarean delivery (risk ratio (RR) 0.61; 95% confidence interval (CI) 0.35 to 1.04) when compared with CTG with fetal blood sampling.There was no strong evidence supporting a reduction in the incidence of neonatal seizures (RR 0.33; 95% CI 0.01 to 8.09) or fetal acidaemia (RR 0.50; 95% CI 0.09 to 2.67) in women monitored using a CTG with an ES versus a CTG without an ES. Overall perinatal mortality could not be ascertained for this trial since data on early neonatal deaths were unavailable. Although fetal deaths were recorded, no fetal deaths occurred in either arm of the trial, and thus no risk estimates could be derived.There was no strong evidence supporting a reduction in the incidence of forceps-assisted vaginal birth (RR 0.50; 95% CI 0.05 to 5.43), hypoxic ischaemic encephalopathy (RR 0.33; 95% CI 0.01 to 8.09), admission to the neonatal intensive care unit (RR 0.40; 95% CI 0.08 to 2.02) or an Apgar less than seven at five minutes (RR 0.50; 95% CI 0.13 to 1.95).The trial did not report on artificial rupture of amniotic membranes,oxytocin augmentation of labour ormaternal satisfaction with labour. AUTHORS' CONCLUSIONS: Two trials met the inclusion criteria for this review but one trial did not provide data for any of this review's outcomes. The single trial that did contribute data was underpowered to evaluate the association between CTG monitoring with an ES and the primary outcomes of interest. No recommendations for clinical practice can be made at this time. Adequately powered trials are necessary before the impact of ESs for fetal assessment in labour can be determined.

Analyzing the Study of Using Acupuncture in Delivery in the Past Ten Years in China

The use of acupuncture in inducing delivery has a long history in China. With progress over time, it has been applied in many aspects. For further study of acupuncture in delivery, this paper analyzed the papers using acupuncture in delivery in the past ten years in mainland China. 87 literatures were picked out by searching relevant electronic databases and bibliographies of relevant journals. The analysis showed randomized controlled trials that were the major type of research, while preclinical researches and literature reviews only account for around ten percent, respectively. Clinical researches indicated that acupuncture can relieve labor pain, promote maternal uterine contraction, shorten birth process, and treat postpartum disorders. Preclinical researches found that acupuncture can adjust certain hormones and improve uterus contraction of late-stage pregnant rats. However, due to lack of large multicenter randomized controlled clinical trials, standardized evaluations of clinical effects in clinical researches and detailed mechanism study in preclinical researches and unequivocal conclusions about the effectiveness, efficacy, and mechanisms of acupuncture in this field cannot be obtained from those researches yet. Further clinical and preclinical studies about the use of acupuncture in delivery with improved methodology is still needed.

Effects and Mechanisms of Complementary and Alternative Medicine during the Reproductive Process.

Effects and Mechanisms of Complementary and Alternative Medicine during the Reproductive Process.

Study of correlation between maternal fatigue and uterine contraction pattern in the active phase of labour

To evaluate the correlation between maternal fatigue and uterine contraction pattern at the beginning of the active phase of labour. Fatigue is one of the most common complaints in pregnant women that often continues until delivery. Maternal fatigue prolongs the labour process and increases the rate of cesarian section. Studies on the pattern of uterine contractions have shown that the length of the fall time is longer in prolonged labours than in normal deliveries. A cross-sectional study. This study was conducted on 100 primiparous women who were referred to Ommolbanin Hospital (Mashhad, Iran) in 2011. Maternal fatigue was assessed at the beginning of the active phase of labour. Then, the pattern of uterine contractions was monitored for 30 minutes by an external tocodynamometer. The F/R ratio was determined by measuring the time for a contraction to return to its baseline from its peak and the time for a contraction to rise to its peak. The data were analysed by chi-square and anova tests. The results showed that there was a significant relationship between maternal fatigue and uterine contraction pattern. The F/R ratio was increased with increase in fatigue severity. Fatigue causes changes in the pattern of uterine contractions. The return time of a contraction from its peak to its baseline (fall) is increased with increase in fatigue severity. Offering strategies to prevent tiredness and reduce the related fatigue complications.