Internal versus external intrapartum foetal heart rate monitoring: the effect on linear and nonlinear parameters

Extracting fetal heart signals from Doppler using semi-supervised convolutional neural networks

Cardiotocography (CTG) measurements are critical for assessing fetal wellbeing during monitoring, and accurate assessment requires well-traceable CTG signals. The current FHR calculation algorithm, based on autocorrelation to Doppler ultrasound (DUS) signals, often results in periods of loss owing to its inability to differentiate signals. We hypothesized that classifying DUS signals by type could be a solution and proposed that an artificial intelligence (AI)-based approach could be used for classification. However, limited studies have incorporated the use of AI for DUS signals because of the limited data availability. Therefore, this study focused on evaluating the effectiveness of semi-supervised learning in enhancing classification accuracy, even in limited datasets, for DUS signals. Data comprising fetal heartbeat, artifacts, and two other categories were created from non-stress tests and labor DUS signals. With labeled and unlabeled data totaling 9,600 and 48,000 data points, respectively, the semi-supervised learning model consistently outperformed the supervised learning model, achieving an average classification accuracy of 80.9%. The preliminary findings indicate that applying semi-supervised learning to the development of AI models using DUS signals can achieve high generalization accuracy and reduce the effort. This approach may enhance the quality of fetal monitoring.

Fetal Heart Rate Preprocessing Techniques: A Scoping Review

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.

Computerized analysis of cardiotocograms in clinical practice and the SisPorto® system thirty-two years after: technological, physiopathological and clinical studies

OBJECTIVES

The objective of this study is to present the why, what and how about computerized analysis of cardiotocograms (cCTG) and the SisPorto system for cCTG.

CONTENT

A narrative review about cCTG and the SisPorto system for cCTG is presented. The meta-analysis of randomized controlled trials (RCT) performed so far have evidenced that cCGT compared to traditional CTG analysis may save time spent in hospital for women, in the antepartum period, and is objective with at least equivalent results in maternal and perinatal outcomes, both in the ante and intrapartum periods. The SisPorto system for cCTG closely follows the FIGO guidelines for fetal monitoring. It may be used both in the ante and intrapartum periods, alone or connected to a central monitoring station, with simultaneous monitoring of fetal and maternal signals, not only in singletons but also in twins. It has been assessed in technical, physiopathological and clinical studies, namely in one large multicentric international RCT during labor and two meta-analysis.

SUMMARY AND OUTLOOK

There is evidence that cCTG may be useful in clinical practice with advantages compared to traditional CTG analysis, although without clear impact on the decrease of preventable maternal and perinatal mortality and morbidity. More studies are warranted, namely on technical improvements and assessment in larger studies in a wider range of clinical settings.

Similarities between maternal and fetal RR interval tachograms and their association with fetal development

An association between maternal and fetal heart rate (HR) has been reported but, so far, little is known about its physiological implication and importance relative to fetal development. Associations between both HRs were investigated previously by performing beat-by-beat coupling analysis and correlation analysis between average maternal and fetal HRs. However, studies reporting on the presence of similarities between maternal and fetal HRs or RR intervals (RRIs) over the short term (e.g., 5-min) at different gestational ages (GAs) are scarce. Here, we demonstrate the presence of similarities in the variations exhibited by maternal and fetal RRl tachograms (RRITs). To quantify the same similarities, a cross-correlation (CC) analysis between resampled maternal and fetal RRITs was conducted; RRITs were obtained from non-invasive electrocardiogram (ECG). The degree of similarity between maternal and fetal RRITs (bmfRRITs) was quantified by calculating four CC coefficients. CC analysis was performed for a total of 330 segments (two 5-min segments from 158 subjects and one 5-min from 14 subjects). To investigate the association of the similarity bmfRRITs with fetal development, the linear correlation between the calculated CC coefficients and GA was calculated. The results from the latter analysis showed that similarities bmfRRITs are common occurrences, they can be negative or positive, and they increase with GA suggesting the presence of a regulation that is associated with proper fetal development. To get an insight into the physiological mechanisms involved in the similarity bmfRRITs, the association of the same similarity with maternal and fetal HR variability (HRV) was investigated by comparing the means of two groups in which one of them had higher CC values compared to the other. The two groups were created by using the data from the 158 subjects where fetal RRI (fRRI) calculation from two 5-min ECG segments was feasible. The results of the comparison showed that the maternal very low frequency (VLF) HRV parameter is potentially associated with the similarity bmfRRITs implying that maternal hormones could be linked to the regulations involved in the similarity bmfRRITs. Our findings in this study reinforce the role of the maternal intrauterine environment on fetal development.

Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review

The analysis of fetal heart rate variability has served as a scientific and diagnostic tool to quantify cardiac activity fluctuations, being good indicators of fetal well-being. Many mathematical analyses were proposed to evaluate fetal heart rate variability. We focused on non-linear analysis based on concepts of chaos, fractality, and complexity: entropies, compression, fractal analysis, and wavelets. These methods have been successfully applied in the signal processing phase and increase knowledge about cardiovascular dynamics in healthy and pathological fetuses. This review summarizes those methods and investigates how non-linear measures are related to each paper's research objectives. Of the 388 articles obtained in the PubMed/Medline database and of the 421 articles in the Web of Science database, 270 articles were included in the review after all exclusion criteria were applied. While approximate entropy is the most used method in classification papers, in signal processing, the most used non-linear method was Daubechies wavelets. The top five primary research objectives covered by the selected papers were detection of signal processing, hypoxia, maturation or gestational age, intrauterine growth restriction, and fetal distress. This review shows that non-linear indices can be used to assess numerous prenatal conditions. However, they are not yet applied in clinical practice due to some critical concerns. Some studies show that the combination of several linear and non-linear indices would be ideal for improving the analysis of the fetus's well-being. Future studies should narrow the research question so a meta-analysis could be performed, probing the indices' performance.

Fetal Heart Rate Fragmentation

Intrapartum fetal monitoring's primary goal is to avoid adverse perinatal outcomes related to hypoxia/acidosis without increasing unnecessary interventions. Recently, a set of indices were proposed as new biomarkers to analyze heart rate (HR), termed HR fragmentation (HRF). In this work, the HRF indices were applied to intrapartum fetal heart rate (FHR) traces to evaluate fetal acidemia. The fragmentation method produces four indices: PIP-Percentage of inflection points; IALS-Inverse of the average length of acceleration/deceleration segments; PSS-Percentage of short segments; PAS-Percentage of alternating segments. On the other hand, the symbolic approach studied the existence of different patterns of length four. We applied the measures to 246 selected FHR recordings sampled at 4 and 2 Hz, where 39 presented umbilical artery's pH ≤ 7.15. When applied to the 4 Hz FHR, the PIP, IASL, and PSS showed significantly higher values in the traces from acidemic fetuses. In comparison, the percentage of "words"W 1 h andW 2 s showed lower values for those traces. Furthermore, when using the 2 Hz, only IASL, W 0, andW 2 m achieved significant differences between traces from both acidemic and normal fetuses. Notwithstanding, the ideal sampling frequency is yet to be established. The fragmentation indices correlated with Sisporto variability measures, especially short-term variability. Accordingly, the fragmentation indices seem to be able to detect pathological patterns in FHR tracings. These indices have the advantage of being suitable and straightforward to apply in real-time analysis. Future studies should combine these indexes with others used successfully to detect fetal hypoxia, improving the power of discrimination in a larger dataset.

Can fetal heart rate variability obtained from cardiotocography provide the same diagnostic value like from electrophysiological interbeat intervals?

OBJECTIVE

Fetal heart rate variability (HRV) is widely used for monitoring fetal developmental disturbances. Only expensive fetal magnetocardiography (fMCG) allows the precise recording of the individual fetal heart beat intervals uncovering also highly frequent vagal modulation. In contrast, transabdominal fetal electrocardiography (fECG) suffers from noise overlaying the fetal cardiac signal. Cardiotocography (CTG) is the clinical method of choice, however, based on Doppler ultrasound, improper to resolve single beats concisely. The present work addresses the transferability of established electrophysiological HRV indices to CTG recordings during the fetal maturation period of 20-40 weeks of gestation (WGA).

APPROACH

We compared (a) HRV indices obtained from fMCG, CTG and fECG of short-term amplitude fluctuations (sAMPs) and long-term amplitude fluctuations (lAMPs) and complexity, and (b) their diagnostic value for identifying maturational age, fetal growth restriction (FGR) and small for gestational age (SGA). We used the functional brain age score (fABAS) and categories of long- and short-term regulation and complexity.

MAIN RESULTS

Integrating all substudies, we found: (a) indices related to long-term regulation, and with modified meaning and values of short-term regulation and sympathovagal balance (SVB) according to electrophysiological HRV standards can be obtained from CTG. (b) Models using HRV indices calculated from CTG allow the identification of maturational age and discriminate FGR from controls with almost similar precision as electrophysiological means. (c) A modified set of HRV parameters containing short- and long-term regulation and long-term/short-term ratio appeared to be most suitable to describe autonomic developmental state when CTG data is used.

SIGNIFICANCE

Whereas the predominantly vagally modulated beat-to-beat precise high frequencies of HRV are not assessable from CTG, we identified relevant related HRV indices and categories for CTG recordings with diagnostic potential. They require further evaluation and confirmation with respect to any issues of fetal developmental and perinatal problems in subsequent studies. This methodology significantly extends the measures of established CTG devices. Novelty and significance HRV indices provide predestinated diagnostic markers of autonomic control in fetuses. However, the established CTG does not provide the temporal precision of electrophysiological recordings. Beat-to-beat related, mainly vagally modulated behavior is not exactly represented in CTG. However, a set of CTG-specific HRV indices that are mainly comparable to established electrophysiological HRV parameters obtained by magnetocardiography or electrocardiography provided almost similar predictive value for fetal maturational age and were helpful in characterizing FGR. These results require validation in the monitoring of further fetal developmental disturbances. We recommend a corresponding extension of CTG methodology.

Systematic Review of Intrapartum Fetal Heart Rate Spectral Analysis and an Application in the Detection of Fetal Acidemia

It is fundamental to diagnose fetal acidemia as early as possible, allowing adequate obstetrical interventions to prevent brain damage or perinatal death. The visual analysis of cardiotocography traces has been complemented by computerized methods in order to overcome some of its limitations in the screening of fetal hypoxia/acidemia. Spectral analysis has been proposed by several studies exploring fetal heart rate recordings while referring to a great variety of frequency bands for integrating the power spectrum. In this paper, the main goal was to systematically review the spectral bands reported in intrapartum fetal heart rate studies and to evaluate their performance in detecting fetal acidemia/hypoxia. A total of 176 articles were reviewed, from MEDLINE, and 26 were included for the extraction of frequency bands and other relevant methodological information. An open-access fetal heart rate database was used, with recordings of the last half an hour of labor of 246 fetuses. Four different umbilical artery pH cutoffs were considered for fetuses' classification into acidemic or non-acidemic: 7.05, 7.10, 7.15, and 7.20. The area under the receiver operating characteristic curve (AUROC) was used to quantify the frequency bands' ability to distinguish acidemic fetuses. Bands referring to low frequencies, mainly associated with neural sympathetic activity, were the best at detecting acidemic fetuses, with the more severe definition (pH ≤ 7.05) attaining the highest values for the AUROC. This study shows that the power spectrum analysis of the fetal heart rate is a simple and powerful tool that may become an adjunctive method to CTG, helping healthcare professionals to accurately identify fetuses at risk of intrapartum hypoxia and to implement timely obstetrical interventions to reduce the incidence of related adverse perinatal outcomes.

Complexity of Cardiotocographic Signals as A Predictor of Labor

Prediction of labor is of extreme importance in obstetric care to allow for preventive measures, assuring that both baby and mother have the best possible care. In this work, the authors studied how important nonlinear parameters (entropy and compression) can be as labor predictors. Linear features retrieved from the SisPorto system for cardiotocogram analysis and nonlinear measures were used to predict labor in a dataset of 1072 antepartum tracings, at between 30 and 35 weeks of gestation. Two groups were defined: Group A—fetuses whose traces date was less than one or two weeks before labor, and Group B—fetuses whose traces date was at least one or two weeks before labor. Results suggest that, compared with linear features such as decelerations and variability indices, compression improves labor prediction both within one (C-Statistics of 0.728) and two weeks (C-Statistics of 0.704). Moreover, the correlation between compression and long-term variability was significantly different in groups A and B, denoting that compression and heart rate variability look at different information associated with whether the fetus is closer to or further from labor onset. Nonlinear measures, compression in particular, may be useful in improving labor prediction as a complement to other fetal heart rate features.

Independent Analysis of Decelerations and Resting Periods through CEEMDAN and Spectral-Based Feature Extraction Improves Cardiotocographic Assessment

Fetal monitoring is commonly based on the joint recording of the fetal heart rate (FHR) and uterine contraction signals obtained with a cardiotocograph (CTG). Unfortunately, CTG analysis is difficult, and the interpretation problems are mainly associated with the analysis of FHR decelerations. From that perspective, several approaches have been proposed to improve its analysis; however, the results obtained are not satisfactory enough for their implementation in clinical practice. Current clinical research indicates that a correct CTG assessment requires a good understanding of the fetal compensatory mechanisms. In previous works, we have shown that the complete ensemble empirical mode decomposition with adaptive noise, in combination with time-varying autoregressive modeling, may be useful for the analysis of those characteristics. In this work, based on this methodology, we propose to analyze the FHR deceleration episodes separately. The main hypothesis is that the proposed feature extraction strategy applied separately to the complete signal, deceleration episodes, and resting periods (between contractions), improves the CTG classification performance compared with the analysis of only the complete signal. Results reveal that by considering the complete signal, the classification performance achieved 81.7% quality. Then, including information extracted from resting periods, it improved to 83.2%.

Relative accuracy of computerized intrapartum fetal heart rate pattern recognition by ultrasound and abdominal electrocardiogram detection

INTRODUCTION

Noninvasive fetal heart rate monitoring using transabdominal fetal electrocardiographic detection is now commercially available and has been demonstrated to be an effective alternative to traditional Doppler ultrasonographic techniques. Our objective in this study was to compare the results of computerized identification of fetal heart rate patterns generated by ultrasound-based and transabdominal fetal electrocardiogram-based techniques with simultaneously obtained fetal scalp electrode-derived heart rate information.

MATERIAL AND METHODS

We applied an objective computer-based analysis for recognition of fetal heart rate patterns (Monica Decision Support) to data obtained simultaneously from a direct fetal scalp electrode, Doppler ultrasound, and the abdominal-fetal electrocardiogram techniques. This allowed us to compare over 145 hours of fetal heart rate patterns generated by the external devices with those derived from the scalp electrode in 30 term singleton uncomplicated pregnancies during labor. The direct fetal scalp electrode is considered to be the most accurate and reliable technique used in current clinical practice, and was, therefore, used as the standard for comparison. The program quantified the baseline heart rate, long- and short-term variability. It indicated when an acceleration or deceleration was present and whether it was large or small.

RESULTS

Ultrasound was associated with significantly greater deviations from the fetal scalp electrode results than the abdominal fetal electrocardiogram technique in recognizing the correct baseline heart rate, its variability, and the presence of small and large accelerations and small decelerations. For large decelerations the two external methods were each not significantly different from the scalp electrode results.

CONCLUSIONS

Noninvasive fetal heart rate monitoring using maternal abdominal wall electrodes to detect fetal cardiac activity more reliably reproduced the computerized analysis of heart rate patterns derived from a direct fetal scalp electrode than did traditional ultrasound-based monitoring. Abdominal-fetal electrocardiogram should, therefore, be considered a primary option for externally monitored patients.

Use of automated fetal heart rate analysis to identify risk factors for umbilical cord acidosis at birth

OBJECTIVE

To identify clinical parameters and intrapartum fetal heart rate parameters associated with a risk of umbilical cord acidosis at birth, using an automated analysis method based on empirical mode decomposition.

METHODS

Our single-center study included 381 cases (arterial cord blood pH at birth pHa ≤7.15) and 1860 controls (pHa ≥7.25) extracted from a database comprising 8,383 full datasets for over-18 mothers after vaginal or caesarean non-twin, non-breech deliveries at term (>37 weeks of amenorrhea). The analysis of a 120-min period of the FHR recording (before maternal pushing or the decision to perform a caesarean section during labor) led to the extraction of morphological, frequency-related, and long- and short-term heart rate variability variables. After univariate analyses, sparse partial least square selection and logistic regression were applied.

RESULTS

Several clinical factors were predictive of fetal acidosis in a multivariate analysis: nulliparity (odds ratio (OR) 95% confidence interval (CI)]: 1.769 [1.362-2.300]), a male fetus (1.408 [1.097-1.811]), and the term of the pregnancy (1.333 [1.189-1.497]). The risk of acidosis increased with the time interval between the end of the FHR recording and the delivery (OR [95%CI] for a 1-min increment: 1.022 [1.012-1.031]). The risk factors related to the FHR signal were mainly the difference between the mean baseline and the mean FHR (OR [95%CI]: 1.292 [1.174-1.424]), the baseline range (1.027 [1.014-1.040]), fetal bradycardia (1.038 [1.003-1.075]) and the late deceleration area (1.002 [1.000-1.005]). The area under the curve for the multivariate model was 0.79 [0.76; 0.81].

CONCLUSION

In addition to clinical predictors, the automated FHR analysis highlighted other significant predictors, such as the baseline range, the instability of the FHR signal and the late deceleration area. This study further extends the routine application of automated FHR analysis during labor and, ultimately, contributes to the development of predictive scores for fetal acidosis.

On the prediction of foetal acidaemia: A spectral analysis-based approach

A computational analysis of physiological systems has been used to support the understanding of how these systems work, and in the case of foetal heart rate, many different approaches have been developed in the last decades. Our objective was to apply a new method of classification, which is based on spectral analysis, in foetal heart rate (FHR) traces to predict foetal acidosis diagnosed with umbilical arterial blood pH ≤ 7.05. Fast Fourier transform was applied to a real database for the classification approach. To evaluate the models, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were used. Sensitivity equal to 1, specificity equal to 0.85 and an area under the ROC curve of 0.94 were found. In addition, when the definition of metabolic acidosis of umbilical arterial blood pH ≤ 7.05 and base excess ≤ -10 mmol/L was used, the proposed methodology obtained sensitivity = 1, specificity = 0.97 and area under the ROC curve = 0.98. The proposed methodology relies exclusively on the spectral frequency decomposition of the FHR signal. After further successful validation in more datasets, this approach can be incorporated easily in clinical practice due to its simple implementation. Likewise, the incorporation of this novel technique in an intrapartum monitoring station should be straightforward, thus enabling the assistance of labour professionals in the anticipated detection of acidaemia.

Recovery of signal loss adopting the residual bootstrap method in fetal heart rate dynamics

Fetal heart rate (FHR) data obtained from a non-stress test (NST) can be presented in a type of time series, which is accompanied by signal loss due to physical and biological causes. To recover or estimate FHR data, which is subjected to a high rate of signal loss, time series models [second-order autoregressive (AR(2)), first-order autoregressive conditional heteroscedasticity (ARCH(1)) and empirical mode decomposition and vector autoregressive (EMD-VAR)] and the residual bootstrap method were applied. The ARCH(1) model with the residual bootstrap technique was the most accurate [root mean square error (RMSE), 2.065] as it reflects the nonlinearity of the FHR data [mean absolute error (MAE) for approximate entropy (ApEn), 0.081]. As a result, the goal of predicting fetal health and identifying a high-risk pregnancy could be achieved. These trials may be effectively used to save the time and cost of repeating the NST when the fetal diagnosis is impossible owing to a large amount of signal loss.

Maternal exercise, season and sex modify the daily fetal heart rate rhythm

AIM

The knowledge on biological rhythms is rapidly expanding. We aimed to define the longitudinal development of the daily (24-hour) fetal heart rate rhythm in an unrestricted, out-of-hospital setting and to examine the effects of maternal physical activity, season and fetal sex.

METHODS

We recruited 48 women with low-risk singleton pregnancies. Using a portable monitor for continuous fetal electrocardiography, fetal heart rate recordings were obtained around gestational weeks 24, 28, 32 and 36. Daily rhythms in fetal heart rate and fetal heart rate variation were detected by cosinor analysis; developmental trends were calculated by population-mean cosinor and multilevel analysis.

RESULTS

For the fetal heart rate and fetal heart rate variation, a significant daily rhythm was present in 122/123 (99.2%) and 116/121 (95.9%) of the individual recordings respectively. The rhythms were best described by combining cosine waves with periods of 24 and 8 hours. With increasing gestational age, the magnitude of the fetal heart rate rhythm increased, and the peak of the fetal heart rate variation rhythm shifted from a mean of 14:25 (24 weeks) to 20:52 (36 weeks). With advancing gestation, the rhythm-adjusted mean value of the fetal heart rate decreased linearly in females (P < .001) and nonlinearly in males (quadratic function, P = .001). At 32 and 36 weeks, interindividual rhythm diversity was found in male fetuses during higher maternal physical activity and during the summer season.

CONCLUSION

The dynamic development of the daily fetal heart rate rhythm during the second half of pregnancy is modified by fetal sex, maternal physical activity and season.

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.

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.

A Comprehensive Evaluation of the Predictive Abilities of Fetal Electrocardiogram-Derived Parameters during Labor in Newborn Acidemia: Our Institutional Experience

This study aimed to identify cardiotocography patterns that discriminate fetal acidemia newborns by comprehensively evaluating the parameters obtained from Holter monitoring during delivery. Between June 1, 2015, and August 1, 2016, a prospective observational study of 85 patients was conducted using fetal Holter monitoring at the Beijing Obstetrics and Gynecology Hospital, Capital Medical University, China. Umbilical cord blood was sampled immediately after delivery and fetal acidemia was defined as umbilical cord arterial blood pH < 7.20. Fetal electrocardiogram- (FECG-) derived parameters, including basal fetal heart rate (BFHR), short-term variation (STV), large acceleration (LA), deceleration capacity (DC), acceleration capacity (AC), proportion of episodes of high variation (PEHV), and proportion of episodes of low variation (PELV), were compared between 16 fetuses with acidemia and 47 without. The areas under the curve (AUC) of receiver operating characteristics (ROC) were calculated. Although all the computerized parameters showed predictive values for acidemia (all AUC > 0.50), STV (AUC = 0.84, P < 0.001), DC (AUC = 0.84, P < 0.001), AC (AUC = 0.80, P < 0.001), and PELV (AUC = 0.71, P = 0.012) were more strongly associated with fetal acidemia. Our institutional experience suggests that FECG-derived parameters from Holter monitoring are beneficial in reducing the incidence of neonatal acidemia.

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

BACKGROUND AND OBJECTIVE

Cardiotocography (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.

METHODS

eCTG 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).

RESULTS

The 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.

CONCLUSIONS

eCTG procedure is a promising useful tool to accurately extract digital FHR and UC signals from digital CTG images.

Linear and nonlinear features of fetal heart rate on the assessment of fetal development in the course of pregnancy and the impact of fetal gender

OBJECTIVE

This work aims to investigate the impact of gestational age and fetal gender on fetal heart rate (FHR) tracings.

APPROACH

Different linear and nonlinear parameters indicating correlation or complexity were used to study the influence of fetal age and gender on FHR tracings. The signals were recorded from 99 normal pregnant women in a singleton pregnancy at gestational ages from 28 to 40 weeks, before the onset of labor. There were 56 female fetuses and 43 male.

MAIN RESULTS

Analysis of FHR shows that the means as well as measures of irregularity of FHR, such as approximate entropy and algorithmic complexity, decrease as gestation progresses. There were also indications that mutual information and multiscale entropy were lower in male fetuses in early pregnancy.

SIGNIFICANCE

Fetal age and gender seem to influence FHR tracings. Taking this into consideration would improve the interpretation of FHR monitoring.

Evolution of linear and nonlinear fetal heart rate indices throughout pregnancy in appropriate, small for gestational age and preterm fetuses: A cohort study

BACKGROUND AND OBJECTIVES

To assess the evolution of linear and nonlinear fetal heart rate (FHR) analysis throughout pregnancy in appropriate (AGA), small for gestational age (SGA) and preterm (PTB) fetuses.

METHODS

A prospective cohort study was carried out in 171 singleton pregnancies divided in three groups: AGA (n = 147), SGA (n = 13) fetuses and spontaneous PTB (n = 11). FHR was recorded with an external sensor from the 24th to the 40th week of gestation. Linear time- and frequency-domain and nonlinear FHR indices were computed on 10-min segments. Longitudinal analysis of indices throughout pregnancy was performed with generalized estimating equations, and receiver operating characteristic (ROC) curves were calculated for the prediction of SGA and PTB fetuses.

RESULTS

Increasing gestational age significantly affected most FHR indices, with a general increase in variability and entropy indices, and a decrease in mean FHR. The PTB group exhibited a significantly lower short-term variation, and no monotonic increase in the sympatho-vagal balance as observed in the AGA group. The SGA group exhibited higher long-term irregularity and lower short-term irregularity than the AGA group throughout gestation. In prediction of SGA and PTB, the largest areas under the ROC curves obtained were 0.76 and 0.78, respectively.

CONCLUSIONS

Linear and nonlinear FHR analysis provides useful information on the evolution of fetal autonomic nervous and complexity control systems throughout pregnancy, in relation with AGA, SGA and PTB fetuses, which may be helpful in clinical practice.

Gender-specific evolution of fetal heart rate variability throughout gestation: A study of 8823 cases

BACKGROUND

Fetal heart rate (FHR) variability throughout gestation reflects aspects of fetal development, and its analysis has been used for the assessment of fetal well-being.

AIM

The objective of this study was to provide a gender-specific analysis of the evolution of FHR variability indices throughout gestation, using linear time-domain, spectral and nonlinear FHR indices.

STUDY DESIGN

A large retrospective study was carried out using antepartum FHR recordings obtained from 4713 male and 4110 female fetuses, with normal pregnancy outcome, between 2004 and 2013, with gestational ages ranging between 25 and 40weeks.

OUTCOME MEASURES

FHR variability was analysed through linear time-domain methods, as well as using spectral analysis and entropy indices. Evolution of FHR indices throughout gestation was analysed through Spearman correlation coefficient. Comparison between male and female fetuses was performed using nonparametric bootstrap 95% confidence intervals for the median.

RESULTS

Mean FHR decreased significantly throughout gestation, whereas most variability indices increased. Sympatho-vagal balance measured by spectral analysis exhibited two local maxima at 29-30 and 34-35weeks and decreased afterwards. Entropy indices increased until around the 34th week, slightly decreasing after the 37th week. Female fetuses presented higher mean FHR and entropy from the 34th week afterwards, and lower short-term variability and sympatho-vagal balance in the same period.

CONCLUSIONS

Spectral and entropy analysis should be considered as a complement to conventional FHR variability analysis, aiming at a better characterization and follow-up of fetal development/maturation throughout gestation. Additionally, gestational age needs to be considered when defining reference ranges for FHR indices in systems of computerized analysis.

Simultaneous monitoring of maternal and fetal heart rate variability during labor in relation with fetal gender

Male gender is considered a risk factor for several adverse perinatal outcomes. Fetal gender effect on fetal heart rate (FHR) has been subject of several studies with contradictory results. The importance of maternal heart rate (MHR) monitoring during labor has also been investigated, but less is known about the effect of fetal gender on MHR. The aim of this study is to simultaneously assess maternal and FHR variability during labor in relation with fetal gender. Simultaneous MHR and FHR recordings were obtained from 44 singleton term pregnancies during the last 2 hr of labor (H_1, H₂ ). Heart rate tracings were analyzed using linear (time- and frequency-domain) and nonlinear indices. Both linear and nonlinear components were considered in assessing FHR and MHR interaction, including cross-sample entropy (cross-SampEn). Mothers carrying male fetuses (n = 22) had significantly higher values for linear indices related with MHR average and variability and sympatho-vagal balance, while the opposite occurred in the high-frequency component and most nonlinear indices. Significant differences in FHR were only observed in H₁ with higher entropy values in female fetuses. Assessing the differences between FHR and MHR, statistically significant differences were obtained in most nonlinear indices between genders. A significantly higher cross-SampEn was observed in mothers carrying female fetuses (n = 22), denoting lower synchrony or similarity between MHR and FHR. The variability of MHR and the synchrony/similarity between MHR and FHR vary with respect to fetal gender during labor. These findings suggest that fetal gender needs to be taken into account when simultaneously monitoring MHR and FHR.

The effect of cigarette smoking on fetal heart rate tracing during pregnancy

OBJECTIVE

The objective of this study is to investigate the alterations caused by smoking on the features of fetal heart rate (FHR) tracings as well as to make a comparison between pregnant smokers and pregnant women with intrauterine growth restriction (IUGR).

STUDY DESIGN

A number of established features derived from linear and nonlinear fields were employed to study the possible influence of maternal smoking on FHR tracings. Moreover, correlation and measures of complexity of the FHR were explored, in order to get closer to the core of information that the signal of FHR tracings conveys. Data included FHR tracings from 61 uncomplicated singleton pregnancies, 16 pregnant smoker cases, and 15 pregnancies of women with IUGR.

RESULTS

The analysis of FHR indicated that some parameters, such as mutual information (P=0.0025), multiscale entropy (P=0.01), and algorithmic complexity (P=0.024) appeared decreased in the group of pregnant smokers, while kurtosis (P=0.0011) increased. The comparison between pregnant smokers and pregnant women with IUGR indicated a reduction in Hjorth complexity (P=0.039) for the former.

CONCLUSION

Smoking during pregnancy seems to induce differences in several linear and nonlinear indices in recordings of FHR tracings. This may be the consequence of an altered neurodevelopmental maturation possibly resulting from chronic fetal hypoxemia in cigarette-exposed fetuses.

Monitoring fetal maturation-objectives, techniques and indices of autonomic function

Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of 'fetal programming', also known as 'developmental origins of adult disease hypothesis', e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is predestinated for its evaluation. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases.

Electrocardiography versus photoplethysmography in assessment of maternal heart rate variability during labor

Purpose

Evaluation of maternal heart rate (MHR) variability provides useful information on the maternal-fetal clinical state. Electrocardiography (ECG) is the most accurate method to monitor MHR but it may not always be available, and pulse oximetry using photoplethysmography (PPG) can be an alternative. In this study we compared ECG and PPG signals, obtained with conventional fetal monitors, to evaluate signal loss, MHR variability indices, and the ability of the latter to predict fetal acidemia and operative delivery.

Methods

Both signals were simultaneously acquired in 51 term pregnancies during the last 2 h of labor (H₁ and H₂). Linear time- and frequency-domain, and nonlinear MHR variability indices were estimated, and the dataset was divided into normal and acidemic cases, as well as into normal and operative deliveries. Differences between ECG and PPG signals were assessed using non-parametric confidence intervals, hypothesis testing, correlation coefficient and a measure of disagreement. Prediction of fetal acidemia and operative delivery was assessed using areas under the receiver operating characteristic curve (auROC).

Results

Signal loss was higher with ECG during the first segments of H₁, and higher with PPG in the last segment of H₂, and it increased in both signals with labour progression. MHR variability indices were significantly different when acquired with ECG and PPG signals, with low correlation coefficients and high disagreement for entropy and fast oscillation-based indices, and low disagreement for the mean MHR and slow oscillation-based indices. However, both acquisition modes evidenced significant differences between H₁ and H₂ and comparable auROC values were obtained in the detection of fetal acidemia and operative vaginal delivery.

Conclusion

Although PPG captures the faster oscillations of the MHR signal less well than ECG and is prone to have higher signal loss in the last 10-min preceding delivery, it can be considered an alternative for MHR monitoring during labor, with adaptation of cut-off values for MHR variability indices.

Software for computerised analysis of cardiotocographic traces

Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.

Improvements in fetal heart rate analysis by the removal of maternal-fetal heart rate ambiguities

Background

Misinterpretation of the maternal heart rate (MHR) as fetal may lead to significant errors in fetal heart rate (FHR) interpretation. In this study we hypothesized that the removal of these MHR-FHR ambiguities would improve FHR analysis during the final hour of labor.

Methods

Sixty-one MHR and FHR recordings were simultaneously acquired in the final hour of labor. Removal of MHR-FHR ambiguities was performed by subtracting MHR signals from their FHR counterparts when the absolute difference between the two was less or equal to 5 beats per minute. Major MHR-FHR ambiguities were defined when they exceeded 1 % of the tracing. Maternal, fetal and neonatal characteristics were evaluated in cases where major MHR-FHR ambiguities occurred and computer analysis of FHR recordings was compared, before and after removal of the ambiguities.

Results

Seventy-two percent of tracings (44/61) exhibited episodes of major MHR-FHR ambiguities, which were not significantly associated with any maternal, fetal or neonatal characteristics, but were associated with MHR accelerations, FHR signal loss and decelerations. Removal of MHR-FHR ambiguities resulted in a significant decrease in FHR decelerations, and improvement in FHR tracing classification.

Conclusions

FHR interpretation during the final hour of labor can be significantly improved by the removal of MHR-FHR ambiguities.

Toward the improvement in fetal monitoring during labor with the inclusion of maternal heart rate analysis

Fetal heart rate (FHR) monitoring is used routinely in labor, but conventional methods have a limited capacity to detect fetal hypoxia/acidosis. An exploratory study was performed on the simultaneous assessment of maternal heart rate (MHR) and FHR variability, to evaluate their evolution during labor and their capacity to detect newborn acidemia. MHR and FHR were simultaneously recorded in 51 singleton term pregnancies during the last two hours of labor and compared with newborn umbilical artery blood (UAB) pH. Linear/nonlinear indices were computed separately for MHR and FHR. Interaction between MHR and FHR was quantified through the same indices on FHR-MHR and through their correlation and cross-entropy. Univariate and bivariate statistical analysis included nonparametric confidence intervals and statistical tests, receiver operating characteristic curves and linear discriminant analysis. Progression of labor was associated with a significant increase in most MHR and FHR linear indices, whereas entropy indices decreased. FHR alone and in combination with MHR as FHR-MHR evidenced the highest auROC values for prediction of fetal acidemia, with 0.76 and 0.88 for the UAB pH thresholds 7.20 and 7.15, respectively. The inclusion of MHR on bivariate analysis achieved sensitivity and specificity values of nearly 100 and 89.1%, respectively. These results suggest that simultaneous analysis of MHR and FHR may improve the identification of fetal acidemia compared with FHR alone, namely during the last hour of labor.

Sampling frequency of fetal heart rate impacts the ability to predict pH and BE at birth: a retrospective multi-cohort study

Fetal heart rate (FHR) sampling rate used on the bedside is equal or less than 4 Hz. Current FHR analysis methods fail to detect incipient fetal acidemia. In a fetal sheep model of human labour we showed that FHR sampling rates near 1000 Hz are needed to detect fetal acidemia. Trans-abdominal fetal ECG (t-a fECG) sampling FHR at 900 Hz combined with a complex signals bioinformatics approach showed promise in a human cohort. Here we validate this finding in a retrospective human cohort study by comparing the performance of the same bioinformatics approach to predict pH and BE at birth in the cohorts with FHR sampled either at 4 Hz or at 900 Hz.The 4 Hz FHR recording data sets consisted of the open access intrapartum CTG data base with n = 552 subjects used to develop the predictive model and another cohort of prospectively recruited n = 11 labouring women to then validate it. 900 Hz FHR data set comprised two prospectively recruited t-a fECG cohorts of n = 60 and n = 23 subjects. Recruitment criteria were similar across the cohorts. We have determined the goodness of fit (R(2)) and root mean square error (RMSE) as the performance indicators of the model on each cohort.The clinical characteristics of all cohorts were similar (gestational age 280   ±   8 d; gender 50% male; birth body weight 3.5   ±   0.5 kg; pH and BE at birth 7.25   ±   0.1 and  -5.7   ±   3.4 mmol L(  -  1), respectively; 1' and 5' Apgar scores at birth 8.5   ±   1.4 and 9.4   ±   0.6, respectively). The 4 Hz FHR cohort rendered-for pH and BE-R(2) = 0.26 and 0.2 and RMSE = 0.087 and 3.44, respectively. This could not be confirmed in the validation cohort for neither pH nor BE prediction. The 900 Hz FHR cohort rendered-for pH and BE-R(2) = 0.9 and 0.77 and RMSE = 0.03 and 1.70, respectively, and the pH prediction was validated.In our model, lower FHR sampling rate increased the predicted error range ~3-4 fold. We show that increasing FHR sampling rate to 900 Hz improves prediction of fetal pH and BE at birth. This should improve early identification of babies at risk of brain injury.

Differences between external and internal fetal heart rate monitoring during the second stage of labor: a prospective observational study

OBJECTIVE

To compare fetal heart rate (FHR) signals acquired simultaneously by an external ultrasound probe and a scalp electrode during the second stage of labor.

METHODS

This was a prospective observational study in a labor ward of a tertiary care university hospital. The population was women in labor with uneventful singleton pregnancies at term. Simultaneous external and internal FHR monitoring was performed in 67 consecutively recruited women during the second stage of labor. Cases were subsequently excluded if the trace length was under 40 min, cesarean birth occurred, or the interval between trace-end and birth exceeded 5 min, leaving a total of 33 traces for analysis. The last 40-60 min of these traces were analyzed by a computer system (Omniview-SisPorto 3.5; Speculum, Lisbon, Portugal) to quantify cardiotocographic parameters. Paired sample t-test and Bland-Altman limits of agreement (LoA) were used for statistical analysis, setting significance at 0.05. The main outcome measures were signal loss, FHR baseline, periodic events, and percentage of periodic events coinciding with contractions.

RESULTS

A higher signal loss was observed with external monitoring [10% vs. 4%; P<0.001, LoA=(-6, 18)]. No differences were found in mean FHR baseline [129 bpm vs. 130 bpm, P=0.245, LoA=(-15, 12)], but more accelerations [12 vs. 8, P<0.001, LoA=(-5, 13)] and less decelerations [8 vs. 10, P<0.001, LoA=(-8, 4)] were detected with external monitoring. With this method there were also more accelerations (66% vs. 55%, P=0.036) and less decelerations (68% vs. 81%, P=0.017) coinciding with contractions.

CONCLUSIONS

External FHR monitoring during the second stage of labor results in higher signal loss, increased number of accelerations, and decreased number of decelerations when compared with internal monitoring.

Application of an automatic adaptive filter for Heart Rate Variability analysis

The presence of artifacts and noise effects in temporal series can seriously hinder the analysis of Heart Rate Variability (HRV). The tachograms should be carefully edited to avoid erroneous interpretations. The physician should carefully analyze the tachogram in order to detect points that might be associated with unlikely biophysical behavior and manually eliminate them from the data series. However, this is a time-consuming procedure. To facilitate the pre-analysis of the tachogram, this study uses a method of data filtering based on an adaptive filter which is quickly able to analyze a large amount of data. The method was applied to 229 time series from a database of patients with different clinical conditions: premature newborns, full-term newborns, healthy young adults, adults submitted to a very-low-calorie diet, and adults under preoperative evaluation for coronary artery bypass grafting. This proposed method is compared to the demanding conventional method, wherein the corrections of occasional ectopic beats and artifacts are usually manually executed by a specialist. To confirm the reliability of the results obtained, correlation coefficients were calculated, using both automatic and manual methods of ltering for each HRV index selected. A high correlation between the results was found, with highly significant p values, for all cases, except for some parameters analyzed in the premature newborns group, an issue that is thoroughly discussed. The authors concluded that the proposed adaptive filtering method helps to efficiently handle the task of editing temporal series for HRV analysis.

Gender-specific heart rate dynamics in severe intrauterine growth-restricted fetuses

BACKGROUND

Management of intrauterine growth restriction (IUGR) remains a major issue in perinatology.

AIMS

The objective of this paper was the assessment of gender-specific fetal heart rate (FHR) dynamics as a diagnostic tool in severe IUGR.

SUBJECTS

FHR was analyzed in the antepartum period in 15 severe IUGR fetuses and 18 controls, matched for gestational age, in relation to fetal gender.

OUTCOME MEASURES

Linear and entropy methods, such as mean FHR (mFHR), low (LF), high (HF) and movement frequency (MF), approximate, sample and multiscale entropy. Sensitivities and specificities were estimated using Fisher linear discriminant analysis and the leave-one-out method.

RESULTS

Overall, IUGR fetuses presented significantly lower mFHR and entropy compared with controls. However, gender-specific analysis showed that significantly lower mFHR was only evident in IUGR males and lower entropy in IUGR females. In addition, lower LF/(MF+HF) was patent in IUGR females compared with controls, but not in males. Rather high sensitivities and specificities were achieved in the detection of the FHR recordings related with IUGR male fetuses, when gender-specific analysis was performed at gestational ages less than 34 weeks.

CONCLUSIONS

Severe IUGR fetuses present gender-specific linear and entropy FHR changes, compared with controls, characterized by a significantly lower entropy and sympathetic-vagal balance in females than in males. These findings need to be considered in order to achieve better diagnostic results.

Comparison of fetal heart rate patterns using nonlinear dynamics in breech versus cephalic presentation at term

BACKGROUND

It has been reported that breech fetuses have inferior neurological outcomes regardless of mode of delivery, raising the possibility that in utero neurological impairment is more frequent in breech fetuses, possibly contributing to malpresentation.

AIMS

To assess differences between the cardiovascular autonomic nervous systems (ANSs) of breech and cephalic fetuses using nonlinear dynamic indices of fetal heart rate (FHR) variability.

STUDY DESIGN AND SUBJECTS

This study included 86 fetuses with breech presentation and 173 fetuses with cephalic presentation, with no other maternal or fetal problems. We analyzed FHR variability and spectral indices as markers of ANS behavior. We used nonlinear dynamic indices to represent the complexity of heart rate regulation, as well as correlation dimension as a chaotic index of the cardiovascular control system.

RESULTS

One of FHR parameters (Mean minute range) was significantly lower in breech than cephalic fetuses (p=0.0294). However, there were no other significant differences in any linear or nonlinear indices, nor in clinical outcomes, between breech and cephalic fetuses.

CONCLUSION

Our data suggest that breech fetuses have neither more active ANS nor less active complexity control systems than do cephalic fetuses. This indicates that the neurologic maturation of breech fetuses is not inferior to cephalic ones. The practical implication of these findings is that the nervous system integrity of breech fetuses may not result directly in neonatal complications.

Comparison of different methods of heart rate entropy analysis during acute anoxia superimposed on a chronic rat model of pulmonary hypertension

Acute life-threatening situations are particularly critical when superimposed on chronic diseases. The objective of this study was the assessment of heart rate (HR) dynamics during episodes of acute anoxia superimposed on a rat model of chronic pulmonary hypertension. In 10 adult Wistar rats, five weeks after pulmonary hypertension induction with Monocrotaline, we analysed eight 1-min HR segments, during episodes of baseline, mechanical ventilation and acute anoxia, using linear indices, approximate entropy (ApEn), sample entropy (SampEn) and multiscale entropy (MSE). The transition from baseline or mechanical ventilation to early anoxia was identified through almost all indices, but SampEn(2,0.6) was the index that better identified all the transitions. MSE presented limited performance, possibly due to the non-stationary nature and short duration of the acute anoxia episodes. A systematic evaluation of all computed HR indices may help to identify which indices or combination of indices more adequately discriminates and monitors critical acute events superimposed on chronic clinical conditions.

Specific change in spectral power of fetal heart rate variability related to fetal acidemia during labor: comparison between preterm and term fetuses

BACKGROUND

Spectral analysis of fetal heart rate (FHR) variability is a useful method to assess fetal condition. There have been several studies involving the change in spectral power related to fetal acidemia, but the results have been inconsistent.

AIMS

To determine the change in spectral power related to fetal umbilical arterial pH at birth, dividing cases into preterm (31-36 weeks) and term (≥37 weeks) gestations.

STUDY DESIGN

Case-control study. The 514 cases of deliveries were divided into a low-pH group (an umbilical arterial pH <7.2) and a control group (pH≥7.2).

SUBJECTS

FHR recorded on cardiotocography during the last 2h of labor.

OUTCOME MEASURES

The spectral powers in various bands of FHR variability.

RESULTS

In preterm fetuses, the total, low (LF), and movement (MF) frequency spectral powers and LF/HF ratio were significantly lower in the low-pH group than the control group (all P<0.05). In contrast, in term fetuses, the total frequency, LF, and MF powers were significantly higher in the low-pH group than the control group (all P<0.05). The area under the receiver operating characteristic of LF power to detect a low pH at birth was 0.794 in preterm fetuses and 0.595 in term fetuses. The specificity was 86.8% and 93.3% in preterm and term fetuses, respectively.

CONCLUSIONS

The changes in spectral power responding to a low pH are different between term and preterm fetuses. Spectral analysis of FHR variability may be useful fetal monitoring for early detection of fetal acidemia.

Fractal and nonlinear changes in the long-term baseline fluctuations of fetal heart rate

The interpretation of heart rate patterns obtained by fetal monitoring relies on the definition of a baseline, which is considered as the running average heart rate in the absence of external stimuli during periods of fetal rest. We present a study along gestation of the baseline's fluctuations, in relation to fractal and nonlinear properties, to assess these fluctuations according with time-varying attracting levels introduced by maturing regulatory mechanisms. A low-risk pregnancy was studied weekly from the 17th to 38th week of gestation during long-term recording sessions at night (>6 h). Fetal averaged pulse rate samples and corresponding baseline series were obtained from raw abdominal ECG ambulatory data. The fractal properties of these series were evaluated by applying detrended fluctuation analysis. The baseline series were also explored to evaluate nonlinear properties and time ordering by applying the scaling magnitude and sign analyses. Our main findings are that the baseline shows fractal and even nonlinear anticorrelated fluctuations. This condition was specially the case before mid-gestation, as revealed by α values near to unit, yet becoming significantly more complex after 30 weeks of gestation as indicated by α(mag) values >0.5. The structured (i.e. not random) fluctuations and particular nonlinear changes that we found thus suggest that the baseline provides on itself information concerning the functional integration of cardiac regulatory mechanisms.

Automatic evaluation of intrapartum fetal heart rate recordings: a comprehensive analysis of useful features

Cardiotocography is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO), used routinely since the 1960s by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. We assess the features on a large data set (552 records) and unlike in other published papers we use three-class expert evaluation of the records instead of the pH values. We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. The number of accelerations and decelerations, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.

Analysis of heart rate variability in a rat model of induced pulmonary hypertension

Monocrotaline (MCT) is commonly used to experimentally induce pulmonary hypertension (PH), which might lead to chronic heart failure. In this study, linear and non-linear heart rate (HR) dynamics were weekly assessed in MCT-treated and non-treated Wistar rats. The HR of 10 adult Wistar rats injected with MCT (MCT group) and of 10 similar rats injected with vehicle (non-MCT group), anesthetized with Ketamine, was weekly recorded during 4 weeks. The first four segments of 1-min length of each HR recording were analysed using linear, time and frequency domains, and approximate (ApEn) and sample (SampEn) entropy indices, considering recently proposed values for the threshold parameter of ApEn and SampEn. Statistical analysis was performed using 95% confidence intervals and statistical tests. Along the study period, an overall weekly maintenance of HR indices, or a decrease, namely in weeks 1-2, was manifest, in the MCT group, except for LF and LF/HF, in week 1, denoting a short-term increase in sympathetic activity without any other changes. On the other hand, a maintenance of HR indices, or an increase, namely on week 4, was observed in the non-MCT group, except for LF/HF, denoting a long-term increase of the overall activity of HR control systems, with a parasympathetic like dominance. Studies on long-term HR dynamics should be performed in very carefully controlled experimental settings, as significant weekly changes may occur, both among anesthetized MCT-treated and non-treated rats.