Validity of mathematical methods of quantitating fetal heart rate variability

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.

The change of fetal heart rate short-term variability during the course of histological chorioamnionitis in fetal sheep

OBJECTIVE

Histological chorioamnionitis (CAM) is related to neonatal mortality and morbidity. However, identifying intrauterine inflammation before delivery is challenging. The aim of this study was to investigate the changes in fetal heart rate (FHR) short-term variability (STV) during the course of histological CAM.

STUDY DESIGN

Changes in STV were measured in 7 chronically instrumented fetal sheep at 111-120 days of gestation. Lipopolysaccharide (LPS) was infused into the amniotic cavity for 2 days following the 4th postoperative day to develop histological CAM. STV was determined based on the R to R interval of the fetal electrocardiogram. We continued to observe the changes in STV until the time of intrauterine fetal death (IUFD). The umbilical cord and fetal membranes were evaluated histologically after IUFD. The experiment was divided into two phases: 1) the acute phase, defined as the 24-hour period between the first and second injections of LPS and 2) the perimortem phase, defined as the period between the second injection of LPS and IUFD. Changes in STV in both the acute and perimortem phases were evaluated using Friedman's test. A probability of <0.05 was accepted as statistically significant.

RESULTS

The fetuses died, on average, at 23.7 ± 4.9 h after the second injection of LPS. Both the umbilical cord and fetal membranes showed histological evidence of severe inflammation. During the perimortem phase, there were statistically significant differences in STV at each time point. STV increased significantly at 6, 4, and 3 h before intrauterine fetal death compared to the baseline.

CONCLUSION

Our study suggests that STV increased as the fetal condition deteriorated during the course of histological CAM.

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.

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Monitoring of foetal heart rate and its variability (FHRV) covers an important role in assessing health of foetus. Many analysis methods have been used to get quantitative measures of FHRV. FHRV has been studied in time and in frequency domain and interesting clinical results have been obtained. Nevertheless, a standardized definition of FHRV and a precise methodology to be used for its evaluation are lacking. We carried out a literature overview about both frequency domain analysis (FDA) and time domain analysis (TDA). Then, by using simulated FHR signals, we defined the methodology for FDA. Further, employing more than 400 real FHR signals, we analysed some of the most common indexes, Short Term Variability for TDA and power content of the spectrum bands and sympathovagal balance for FDA, and evaluated their ranges of values, which in many cases are a novelty. Finally, we verified the relationship between these indexes and two important parameters: week of gestation, indicator of foetal growth, and foetal state, classified as active or at rest. Our results indicate that, according to literature, it is necessary to standardize the procedure for FHRV evaluation and to consider week of gestation and foetal state before FHR analysis.

Comparison of a computer system evaluation of intrapartum cardiotocographic events and a consensus of clinicians

AIMS

To compare between computer analysis of intrapartum cardiotocography (CTG) features by the Omniview-SisPorto 3.5 and a consensus of clinicians.

METHODS

Agreement study using 50 consecutively acquired tracings (206 h of signals) with >60 min duration, <10% signal loss and recorded in labor at term by internal fetal heart rate (FHR) monitoring. Tracings were divided into 10-min segments and independently analyzed by three experienced clinicians, in order to estimate the FHR baseline and identify periodic events. A consensus was reached using a three round Delphi procedure. Results were compared with the analysis provided by the Omniview-SisPorto 3.5 system.

RESULTS

For baseline estimation, agreement between the computer and the consensus was high [intraclass correlation coefficient (ICC)=0.85; 95% confidence interval (CI) 0.46-0.93], with a mean difference of 3.7 bpm (limits of agreement -4.4-11.9 bpm), and 99% of differences under 15 bpm. A concordant identification was observed in 71% of accelerations (95% CI: 69%-73%), 68% of decelerations (95% CI: 66%-70%), and 87% of uterine contractions (95% CI: 85%-89%).

CONCLUSIONS

A high agreement was observed between the Omniview-SisPorto 3.5 and a consensus of clinicians in evaluation of intrapartum CTG baseline, accelerations, decelerations and uterine contractions.

Comparison of short term variability indexes in cardiotocographic foetal monitoring

Concise indexes related to variability of foetal heart rate (FHR) are usually utilised for foetal monitoring; they enrich information provided by cardiotocography (CTG). Most attention is paid to the short term variability (STV), which relates to activity and reaction of autonomic nervous control of foetal heart. There is not a unique method to compute short term variability of the FHR but different formulas have been proposed and are employed in clinical and scientific environments: this leads to different evaluations and makes difficult comparative studies. Nine short term variability indexes: Arduini, Dalton, Organ, Sonicaid 8000, Van Geijn, Yeh, Zugaib a modified version of Arduini index and Standard Deviation were considered and compared to test their robustness in CTG applications. A large set of synthetic foetal heart rate series with known features were used to compare indexes performances. Different amounts of variability, mean foetal heart rate, storage rates, baseline variations were considered. The different indexes were in particular tested for their capability to recognise short term heart rate variability variation, their dependence on heart rate signal storage rate (as those provided by commercial cardiotocographic devices), on mean value of the foetal heart rate and on modifications of the floatingline, such in case of accelerations or decelerations. Concise statistical parameters relative to indexes scores were presented in comparative tables. Results indicate that although the indexes are able to recognise STV variation, they show substantial differences in magnitude and some in sensibility. Results depend on the frequency used to acquire and store FHR data (depending on devices); in general, the lower is data rate the more degraded are the results. Furthermore, results differently depend on FHR mean, some for their intrinsic definition; differences arise also in correspondences of accelerations and decelerations. Our results demonstrate that only indexes which refer directly to differences in FHR values, such as Organ and SD indexes, not show dependence on FHR mean. The use of the Standard Deviation index may provide efficient information while showing independence from the considered variables. Indexes performance in case of real cardiotocographic signals were also presented as examples.

A comparison of subjective and mathematical estimations of fetal heart rate variability

OBJECTIVES

To develop a computerized algorithm to quantify fetal heart rate (FHR) variability and compare it to perinatologists' interpretation of FHR variability.

METHODS

FHR variability was calculated using data from 30 women who had a fetal scalp electrode placed for a clinical indication, and compared to the assessment of FHR variability from four perinatologists who interpreted paper tracings of the same data. Inter-rater reliability was calculated and receiver-operator curve analysis was done.

RESULTS

Correlation between the computer algorithm's assessment of variability and the perinatologists' assessment (0.27-0.68) was similar to the inter-rater reliability between perinatologists (0.33-0.72).

CONCLUSIONS

A computer-based algorithm can assess FHR variability as well as expert clinicians.

Identification of fetal sufferance antepartum through a multiparametric analysis and a support vector machine

The present work is concerned with the automatic identification of fetal sufferance in intrauterine growth retarded (IUGR) fetuses, based on a multiparametric analysis of cardiotocographic recordings feeding a neural classifier. As classification tool, we propose a SVM (support vector machine), which receives the set of linear and nonlinear parameters extracted from the fetal heart rate signal (FHR) as input and gives the indication of fetal distress as output. SVM is a powerful supervised learning algorithm belonging to the statistical learning theory. It minimizes the structural risk performance in various classification problems. Three SVMs are built with different kernels. Their training set includes 70 cases: 35 normal and 35 IUGR suffering fetuses. Classification results obtained with a 2nd order polynomial kernel, on a test set of 30 unknown cases, show good values of accuracy, specificity and sensitivity. The SVM performance is very similar to that obtained with multilayer perceptron and neurofuzzy classifiers proposed in previous works. The introduction of a hybrid unsupervised/supervised learning scheme integrating independent component analysis (ICA) with SVM will be the natural development of this work with a further improvement of the diagnostic ability of the system.

Assessment of fetal neurodevelopment via fetal magnetocardiography

Fetal magnetocardiography (fMCG) offers unique capabilities for assessment of fetal heart rate (FHR) and fetal behavior, which are fundamental aspects of neurodevelopment. The most important attribute of fMCG for FHR monitoring is its high precision, which allows accurate assessment of beat-to-beat fetal heart rate variability (FHRV), including respiratory sinus arrhythmia. Using mathematical indices to assess FHRV, we find that short- and long-term FHRV both increase during gestation but not in the same manner. The largest increases in short-term FHRV occur during the last trimester, while the largest increases in long-term FHRV occur early on, with smaller changes occurring during the last trimester. The fMCG also allows assessment of fetal activity. This results from the high sensitivity of the signal to the position and orientation of the fetal heart. FMCG actograms are therefore specific for fetal trunk movement, which are thought to be more important than isolated extremity movements and other small fetal movements. The ability to assess FHR, FHRV, and fetal trunk movement simultaneously makes fMCG a valuable tool for neurodevelopment research.

Cardiovascular fluctuations and transfer function analysis in stable preterm infants

To examine the baroreceptor reflex function, a beat-to-beat analysis between systolic blood pressure (SBP) and R-R interval fluctuations was studied in 10 stable appropriate-for-gestational age preterm infants (range, 27.2-33.7 wk) in the first postnatal week during quiet sleep. Spectral power analysis, using fast Fourier transform, and transfer functions (gain and phase difference) between SBP and R-R fluctuations were estimated in a low-frequency band (LF, 0.03-0.2 Hz) and high-frequency band (HF defined as the frequency band between the 10th and 90th centiles of the individual respiratory frequency). The LF/HF ratio reflects the sympathovagal balance. The mean frequency (+/-SD) of LF peaks was centered at 0.07 +/- 0.02 Hz. The mean frequency (+/-SD) of the individual HF band was 0.82 +/- 0.21 Hz. The LF/HF ratio in the R-R interval series [median, 29; interquartile range (IQR), 16-40] was higher than in the SBP series (median, 8; IQR, 4-14). The gain between R-R interval and SBP fluctuations (median, 4.2 ms/mm Hg; IQR, 2.4-5.0) in the LF band was higher than in the HF band (median, 1.7 ms/mm Hg; IQR, 1.4-3.0). SBP fluctuations lead R-R interval fluctuations in the LF band with a median phase difference of +96 degrees (IQR, 67-132). At LF the fluctuations in SBP precede changes in R-R interval with a time delay of 3.8 s. These observations indicate a dominant role of the sympathetic system in stable preterm infants in comparison with published adult values. Cross-spectral analysis allows a test for tracking the development of the sympathetic system in neonates.

Irregularity and asynchrony in biologic network signals

The principal focus of this chapter has been the description of both ApEn, a quantification of serial irregularity, and of cross-ApEn, a thematically similar measure of two-variable asynchrony (conditional irregularity). Several properties of ApEn facilitate its utility for biological time series analysis: (1) ApEn is nearly unaffected by noise of magnitude below a de facto specified filter level; (2) ApEn is robust to outliers; (3) ApEn can be applied to time series of 50 or more points, with good reproducibility; (4) ApEn is finite for stochastic, noisy deterministic, and composite (mixed) processes, these last of which are likely models for complicated biological systems; (5) increasing ApEn corresponds to intuitively increasing process complexity in the settings of (4); and (6) changes in ApEn have been shown mathematically to correspond to mechanistic inferences concerning subsystem autonomy, feedback, and coupling, in diverse model settings. The applicability to medium-sized data sets and general stochastic processes is in marked contrast to capabilities of "chaos" algorithms such as the correlation dimension, which are properly applied to low-dimensional iterated deterministic dynamical systems. The potential uses of ApEn to provide new insights in biological settings are thus myriad, from a complementary perspective to that given by classical statistical methods. ApEn is typically calculated by a computer program, with a FORTRAN listing for a "basic" code referenced above. It is imperative to view ApEn as a family of statistics, each of which is a relative measure of process regularity. For proper implementation, the two input parameters m (window length) and r (tolerance width, de facto filter) must remain fixed in all calculations, as must N, the data length, to ensure meaningful comparisons. Guidelines for m and r selection are indicated above. We have found normalized regularity to be especially useful, as in the growth hormone studies discussed above; "r" is chosen as a fixed percentage (often 20%) of the subject's SD. This version of ApEn has the property that it is decorrelated from process SD--it remains unchanged under uniform process magnification, reduction, and translation (shift by a constant). Cross-ApEn is generally applied to compare sequences from two distinct yet interwined variables in a network. Thus we can directly assess network, and not just nodal, evolution, under different settings--e.g., to directly evaluate uncoupling and/or changes in feedback and control. Hence, cross-ApEn facilitates analyses of output from myriad complicated networks, avoiding the requirement to fully model the underlying system. This is especially important, since accurate modeling of (biological) networks is often nearly impossible. Algorithmically and insofar as implementation and reproducibility properties are concerned, cross-ApEn is thematically similar to ApEn. Furthermore, cross-ApEn is shown to be complementary to the two most prominent statistical means of assessing multivariate series, correlation and power spectral methodologies. In particular, we highlight, both theoretically and by case study examples, the many physiological feedback and/or control systems and models for which cross-ApEn can detect significant changes in bivariate asynchrony, yet for which cross-correlation and cross-spectral methods fail to clearly highlight markedly changing features of the data sets under consideration. Finally, we introduce spatial ApEn, which appears to have considerable potential, both theoretically and empirically, in evaluating multidimensional lattice structures, to discern and quantify the extent of changing patterns, and for the emergence and dissolution of traveling waves, throughout multiple contexts within biology and chemistry.

Human fetuses have nonlinear cardiac dynamics

Approximate entropy (ApEn) is a statistic that quantifies regularity in time series data, and this parameter has several features that make it attractive for analyzing physiological systems. In this study, ApEn was used to detect nonlinearities in the heart rate (HR) patterns of 12 low-risk human fetuses between 38 and 40 wk of gestation. The fetal cardiac electrical signal was sampled at a rate of 1,024 Hz by using Ag-AgCl electrodes positioned across the mother's abdomen, and fetal R waves were extracted by using adaptive signal processing techniques. To test for nonlinearity, ApEn for the original HR time series was compared with ApEn for three dynamic models: temporally uncorrelated noise, linearly correlated noise, and linearly correlated noise with nonlinear distortion. Each model had the same mean and SD in HR as the original time series, and one model also preserved the Fourier power spectrum. We estimated that noise accounted for 17.2-44.5% of the total between-fetus variance in ApEn. Nevertheless, ApEn for the original time series data still differed significantly from ApEn for the three dynamic models for both group comparisons and individual fetuses. We concluded that the HR time series, in low-risk human fetuses, could not be modeled as temporally uncorrelated noise, linearly correlated noise, or static filtering of linearly correlated noise.

Heart rate variability: origins, methods, and interpretive caveats

Components of heart rate variability have attracted considerable attention in psychology and medicine and have become important dependent measures in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability, however, remain complex issues and are fraught with pitfalls. The present report (a) examines the physiological origins and mechanisms of heart rate variability, (b) considers quantitative approaches to measurement, and (c) highlights important caveats in the interpretation of heart rate variability. Summary guidelines for research in this area are outlined, and suggestions and prospects for future developments are considered.

Relation of direct assessment of cardiac autonomic function with metaiodobenzylguanidine imaging to heart rate variability in diabetes mellitus

Myocardial metaiodobenzylguanidine uptake predicts autonomic function in patients with diabetes mellitus and is significantly related to indexes reflecting sympathetic neural modulation of heart rate variability.

Developments in CTG analysis

FHR monitoring has been the subject of many debates. The technique, in itself, can be considered to be accurate and reliable both in the antenatal period, when using the Doppler signal in combination with autocorrelation techniques, and during the intrapartum period, in particular when the FHR signal can be obtained from a fetal ECG electrode placed on the presenting part. The major problems with FHR monitoring relate to the reading and interpretation of the CTG tracings. Since the FHR pattern is primarily an expression of the activity of the control by the central and peripheral nervous system over cardiovascular haemodynamics, it is possibly too indirect a signal. In other specialities such as neonatology, anaesthesiology and cardiology, monitoring and graphic display of heart rate patterns have not gained wide acceptance among clinicians. Digitized archiving, numerical analysis and even more advanced techniques, as described in this chapter, have primarily found a place in obstetrics. This can be easily explained, since the obstetrician is fully dependent on indirectly collected information regarding the fetal condition, such as (a) movements experienced by the mother, observed with ultrasound or recorded with kinetocardiotocography (Schmidt, 1994), (b) perfusion of various vessels, as assessed by Doppler velocimetry, (c) the amount of amniotic fluid or (d) changes reflected in the condition of the mother, such as the development of gestation-induced hypertension and (e) the easily, continuously obtainable FHR signal. It is of particular comfort to the obstetrician that a normal FHR tracing reliably predicts the birth of the infant in a good condition, which makes cardiotocography so attractive for widespread application. However, in the intrapartum period, many traces cannot fulfil the criteria of normality, especially in the second stage. In this respect, cardiotocography remains primarily a screening and not so much a diagnostic method. As long as continuous monitoring of fetal acid-base balance has not been extensively tested in clinical practice, microblood sampling of the fetal presenting part (Saling, 1994) is a useful adjunct. The problem with non-normal tracings is that their significance is very often unclear. They may indicate serious fetal distress, finally resulting in preventable destruction of critical areas in the fetal brain and damage to various organs; or, on the contrary, they may indicate temporary changes in cardiovascular control as a reaction to the intermittent effects on fetal haemodynamics of, for example, uterine contractions, whether or not in combination with partial or complete compression of umbilical cord vessels or the vessels on the chorionic plate (van Geijn, 1994). Many factors influence the FHR and its variability, which further complicates the interpretation of FHR patterns; some have been discussed here in some detail. Undoubtedly, there is a need for quantitative and objective FHR analysis, as long as it does not lead to erroneous results. Close collaboration between engineers and clinicians is a prerequisite for further advances in this field. Decision support systems certainly have a future but only if they are able to take into account a large set of clinical data and can combine it with data obtained from FHR signals and other parameters referring to the fetal condition, such as fetal growth, Doppler velocimetry, amniotic fluid volume and biochemical and biophysical data obtained from the mother. Basic technical concepts inherent in computerized CTG analysis, such as sampling rate (Chang et al, 1995), signal loss, artefact detection (van Geijn et al, 1980), further processing of intervals, archiving in digitized format and monitor display, should receive considerable attention. There is still a long way to go until decision support systems find their way into obstetric practice. Further developments can only be achieved thanks to efforts of many basic and clinical researchers, wo

The effect of change in sympatho-vagal balance on heart rate and blood pressure variability in the foetal lamb

Cardiac and vascular function is mainly under autonomic nervous control within seconds to minutes, although the control is not mature at birth. We studied sympathovagal control of heart rate and blood pressure in chronically catheterized foetal lambs in the last trimester of gestation. Power spectral analysis was used to quantitate the frequency-specific heart rate variability (HRV) and blood pressure variability. We performed 15 experiments in seven foetal lambs. These preliminary studies showed that parasympathetic blockade by atropine (eight experiments) had no significant effect on the distribution of HRV to different frequencies. Beta-sympathetic blockade by propranolol (seven experiments) decreased the ratio of low and mid to high frequency (0.025-0.13 to 0.13-1.00 Hz) HRV (P = 0.02). The increased high frequency HRV in the absence of a similar increase in blood pressure variability and tracheal pressure variability suggests enhanced baroreflex responsiveness after propranolol administration. The frequency-specific sympathetic control of HRV in foetal lambs, the change in ratio of low and mid to high frequency HRV, might have clinical implications in estimating the level of foetal sympathetic activation in the follow-up of high-risk pregnancies.

Power spectral analysis of fetal heart rate

This chapter examines the role of power spectral analysis (PSA) in elucidation of the physiological control mechanisms of fetal heart rate and as a potential indicator of fetal well-being. The importance of fetal heart rate variability (FHRV) as an indicator of fetal oxygenation is discussed, and the limitations in the current methods of measurement of FHRV are highlighted. Evidence is presented for the paramount influence of the autonomic nervous system in the control of heart rate variability. The basic proposition underlying spectral analysis is that the two autonomic branches influence heart rate in a frequency-dependent way, and their differential effects can be determined by PSA which breaks down the heart rate trace into its component frequencies. The application of PSA to heart rate variability data is an established tool in cardiology, and the published literature related to its use in the adult, neonate and fetus is reviewed. The power spectrum is sensitive to the activity state of the fetus, particularly fetal breathing movements, which have a variable effect on short- and long-term FHRV. There are a variety of mathematical approaches to the construction of power spectra, and a particular method of data acquisition and analysis is presented together with some theoretical background. Recent experimental evidence indicates a role for PSA as an indicator of fetal activity state, and the effect of hypoxia on the spectrum of the fetus in labour is discussed. There are some problems with the technique of PSA, particularly in regard to accepted definitions and methods of analysis. It is a powerful non-invasive tool in the elucidation of fetal cardiac control, but its value in the detection of the compromised fetus has yet to be tested in a clinical trial.

Continuous monitoring of heart rate variability in preterm infants

A method for continuous monitoring and recording of neonatal heart rate variability (HRV) and further physiological parameters in the intensive care unit is presented: 16 neonatal monitors were connected via two input/output processor boards to a personal computer. Patient data were processed by special software. Every day a 24-h record was printed for each infant, including a continuous registration of long-term (LTV) and short-term variability (STV) of heart rate along with baseline heart rate, respiratory rate, body temperature, temperature of the incubator and transcutaneous partial pressures of oxygen and carbon dioxide (tcPO2 and tcPCO2). For each parameter automatic artefact removal was implemented. Median and percentiles were computed once daily from all valid values. The influence of gestational and postnatal age and of respiratory distress syndrome (RDS) on HRV was studied in 105 preterm infants below 33 weeks of gestation during the first 7 days of life. An increase of both LTV and STV was seen with increasing gestational and postnatal age. In infants with RDS a decreased LTV was found in relation to the severity of the disease. HRV was also decreased in impaired brain function due to intraventricular hemorrhage, asphyxia or sedative treatment.

Quantification of evolution from order to randomness in practical time series analysis

The principal focus of this chapter is the description of a recently developed, readily usable regularity statistic, ApEn, that quantifies the continuum from perfectly orderly to completely random in time series data. Several properties of ApEn facilitate its utility for practical time series analysis: (1) ApEn is nearly unaffected by noise of magnitude below a de facto specified filter level; (2) ApEn is robust to outliers; (3) ApEn can be applied to time series of 100 or more points, with good confidence (established by standard deviation calculations); (4) ApEn is finite for stochastic, noisy deterministic, and composite (mixed) processes, the last of which are likely models for complicated biological systems; (5) increasing ApEn corresponds to intuitively increasing process complexity in the settings of (4). This applicability to medium-sized data sets and general stochastic processes is in marked contrast to capabilities of "chaos" algorithms such as the correlation dimension, which are properly applied to low-dimensional iterated deterministic dynamical systems. The potential uses of ApEn to provide new insights in biological settings are thus myriad, from a perspective complementary to that given by classic statistical methods. The ApEn statistic is typically calculated by a computer program, with a FORTRAN listing for a "basic" code referenced above. It is imperative to view ApEn as a family of statistics, each of which is a relative measure of process regularity. For proper implementation, the two input parameters m (window length) and r (tolerance width, de facto filter) must remain fixed in all calculations, as must N, the data length, to ensure meaningful comparisons. Guidelines for m and r selection are indicated above. We have found normalized regularity to be especially useful; "r" is chosen as a fixed percentage (often 15 or 20%) of the SD of the subject rather than of a group SD. This version of ApEn has the property that it is decorrelated from process SD, in that it remains unchanged under uniform process magnification or reduction; thus we can entirely separate the questions of SD change and regularity change in data analysis. Because regularity questions are thematically orthogonal to the type of information that, for example, moment statistics ascertain, we highly recommend that ApEn be used in conjunction with other such statistics, rather than as a sole indicator of process typicality. Last and yet foremost, we recommend the following order of detail in Practical analysis. First, either visually or algorithmically, eliminate outliers.(ABSTRACT TRUNCATED AT 400 WORDS)

A comparison between visual and computer analysis of antepartum fetal heart rate tracings

OBJECTIVE

This study was designed to determine the intraobserver and interobserver variability in the visual assessment of fetal heart rate tracings and to evaluate the accuracy of the visual detection of accelerations and decelerations when compared with computerized fetal heart rate analysis.

STUDY DESIGN

One hundred antepartum fetal heart rate tracings, of good quality and of 30 minutes' duration, were visually assessed by five expert observers on three occasions during a 12-month period. There were a total of seven questions related to either judgment or accuracy of each recording. Visual detection of fetal heart rate acceleration, deceleration, and estimated baseline was compared with computerized analysis. Statistical significance was determined by kappa coefficient and contingency table chi 2 analysis.

RESULTS

Analysis with kappa coefficient reflecting intraobserver and interobserver agreement of judgment-related questions indicated poor agreement between observers when assessing short-term fetal heart rate variability (kappa 0.18), when making a decision to stop or continue recording (kappa 0.39), and when judging whether there is concern regarding fetal heart rate tracing (kappa 0.26). When compared with computerized analysis, clinicians had a tendency to recognize tracings as normal. In particular, they failed to identify 35% of tracings with 0 or 1 acceleration and failed to detect 92% of fetal heart rate decelerations. Variable decelerations associated with fetal movements were the major source of disagreement between observers and the computer. Only the estimation of baseline fetal heart rate had a high level of accuracy.

CONCLUSION

We concluded that the poor level of accuracy in several components of the nonstress test was responsible for the low interobserver agreement seen in simple judgment-related questions such as decision to continue or stop fetal heart rate recordings.

Fetal heart rate variability and behavioral state: analysis by power spectrum

OBJECTIVE

We attempted to determine the relationship between the fetal heart rate power spectrum and fetal state.

STUDY DESIGN

Interbeat intervals, electrocortical activity, and fetal breathing movements were recorded from five near-term fetal lambs. Interbeat intervals were taken from epochs of low-voltage electrocortical activity with breathing, low-voltage electrocortical activity without breathing, and high-voltage electrocortical activity without breathing. Power spectral techniques were applied to determine the underlying frequencies contributing to fetal heart rate variability. Spectral analysis was also performed on fetal breathing data from three animals.

RESULTS

Significant differences were found between low-voltage electrocortical activity with breathing and high-voltage electrocortical activity without breathing at 0.62 Hz and from 1.09 to 1.56 Hz. There was no clear relationship between the breathing and heart rate spectra.

CONCLUSIONS

Fetal heart rate is mediated by both state and respiratory variables. The respiratory component is not strictly related to respiratory rate.

Fetal heart rate patterns and chronic exposure to antiepileptic drugs

Fetal heart rate (FHR) characteristics of fetuses exposed and not exposed to antiepileptic drugs (AEDs) were studied. FHR is considered to reflect central nervous system (CNS) integrity. Three intervals during pregnancy were investigated: 20, 32, and 38 weeks. At 32 and 38 weeks, FHR was studied in relation to quiet (C1F) and active (C2F) sleep periods. For each tracing, a baseline was determined and accelerations and decelerations were identified. To assess FHR variability, the long-term irregularity, interval difference and absolute beat-to-beat indexes, and the bandwidth were calculated for 30-s intervals between accelerations and decelerations. No marked differences were noted between study and control groups concerning basal FHR and the occurrence of accelerations. For FHR derived from the fetal ECG, all indexes of FHR variability and the bandwidth were lower for the study group as compared with the control group, although the differences did not reach statistical significance. Our study shows that chronic prenatal exposure to AEDs does not seriously interfere with modulation of fetal heart rhythm by the CNS.

Quantitated fetal heart rhythm at 20, 32 and 38 weeks of gestation and dependence on rest-activity patterns

Quantitative parameters of fetal heart rate (FHR) were automatically analysed at 20, 32 and 38 weeks of pregnancy. FHR was obtained both by the fetal ECG method and by wide range Doppler ultrasound with autocorrelation. At 32 and 38 weeks, FHR was studied in relation to fetal rest-activity according to the fetal behavioural state concept (coincidence 1F and 2F). Basal fetal heart rate was significantly higher at 20 weeks of gestation than at 32 and 38 weeks. The number of accelerations increased significantly from 20 weeks to 32 and 38 weeks for C2F periods. Parameters of FHR variability, i.e. ID, ABB, LTI indices and bandwidth, were higher during periods C2F compared to periods C1F. Lowest values of all four parameters were found at 20 weeks gestation. The ID index, which is a measure of short-term variability increased significantly between 32 to 38 (C2F). The absolute values of ID, ABB and LTI were lower for ultrasound recordings than for the fetal ECG.

Influences on heart rate variability in spontaneously breathing preterm infants

To investigate the influence of maturational and physiological factors on heart rate variability in spontaneously breathing very preterm infants (n = 29) a multiparametric study was performed during the first 3 days of life in infants born at a gestational age below 33 weeks. Four times a day, RR-intervals, respiration curve and rate, transcutaneously measured blood gases and observed body movements were recorded while the infants were asleep. All data were stored simultaneously in a micro-computer. Non-invasively measured blood pressure and patency of the ductus arteriosus were documented as well. Four sets of short- (STV) and long term variability (LTV) indices were calculated. Both STV and LTV appeared to be significantly influenced by conceptional and postnatal age in the appropriate for gestational age infants. LTV was influenced by the behavioural state and body movements. During state coincidence 2 ('active sleep') LTV was influenced by respiratory rate and the variations in transcutaneous PO2. An effect of blood pressure or ductus patency could not be demonstrated.

Fetal heart rate variability and cerebral oxygen consumption in fetal sheep during asphyxia

This study was designed to examine the relationship between fetal heart rate variability and fetal cerebral oxygen uptake. Fetal sheep were chronically prepared with catheters and electrodes to determine cerebral blood flow (microsphere method), cerebral arteriovenous oxygen difference, and the electrocardiogram. An adjustable occluder was placed on the maternal common internal iliac artery to induce fetal asphyxia by reducing uterine blood flow. Fetal heart rate variability tended to decrease in the first 11 min of asphyxia, when cerebral oxygen consumption was approximately 53% of control. Despite stable cerebral oxygen consumption and worsening metabolic acidosis, however, fetal heart rate variability progressively returned towards normal by 36 min. There was no relationship between the depression of FHR variability and the degree of reduction of cerebral oxygen consumption. Nor was there any relationship between an alteration in regional cerebral blood flow or myocardial blood flow and the return of FHR variability with increasing duration of asphyxia. We conclude that there is an association between loss of fetal heart rate variability and reduced cerebral oxygen consumption, but the reduced variability does not persist with time at this degree of reduced cerebral metabolism in fetal sheep. This appears to be at variance with human clinical experience. Among the explanations for this may be insufficiently severe asphyxia, a species difference, removal of an inhibitor to FHR variability, or progressive use of other substrates for metabolism.

The properties of V in newborns across repeated measures

It has been argued that a recently developed measure, vagal tone (V), is a significant advancement over other existing methods of assessing the periodic variation in heart rate associated with respiration (respiratory sinus arrhythmia). It has been further suggested that, as a noninvasive measure of vagal nerve efferent activity, V may facilitate the early identification of infants at risk for developmental disabilities. This study addressed the relationship between V and other measures of cardiac activity and behavioral state and the stability of V across repeated measures. Twelve samples of cardiac activity were collected from each of 20 full term infants, 6 samples on each of two consecutive days. V values were derived using a spectral analysis program comparable to Porges' patented MXedit process. Measures of behavioral states were collected by continuous observation. Heart period and heart period variability were highly correlated with V. Variation in V between behavioral states was also detected. Repeated assessments revealed that average V values collected in the same state were not significantly correlated across successive days. This short-term variability both between and within individuals does not support the notion that a single assessment of V can, by itself, be used to identify at-risk infants or predict developmental outcome.

Heart rate variability

Reduced heart rate variability carries an adverse prognosis in patients who have survived an acute myocardial infarction. This article reviews the physiology, technical problems of assessment, and clinical relevance of heart rate variability. The sympathovagal influence and the clinical assessment of heart rate variability are discussed. Methods measuring heart rate variability are classified into four groups, and the advantages and disadvantages of each group are described. Concentration is on risk stratification of postmyocardial infarction patients. The evidence suggests that heart rate variability is the single most important predictor of those patients who are at high risk of sudden death or serious ventricular arrhythmias.

Spectral analysis of fetal heart rhythm in relation to fetal regular mouthing

Fetal heart rate variation during fetal regular mouthing in behavioural state 1F was investigated applying spectral analysis. Periods with and without fetal regular mouthing movements were compared. The power spectrum of the periods with regular mouthing movements showed a peak at the frequency of the clusters of mouthing movements which was absent in the power spectrum of the corresponding periods without movements. The oscillations in the fetal heart rate associated with this peak in the power spectrum were detectable both in the heart rate tracings obtained from the abdominal electrocardiogram and those recorded by means of wide range Doppler ultrasound.

Long-term spectral analysis of heart rate variability--an algorithm based on segmental frequency distributions of beat-to-beat intervals

Reduced heart rate variability has been reported as a predictor of long-term mortality in recent myocardial infarction patients. However, it has not been systematically investigated whether the reduction in heart rate variability in those post myocardial infarction patients who later suffer death or severe arrhythmias is caused by a reduction of short-term variability of heart rate (such as respiratory arrhythmia) or whether the differences in long term variability (such as diurnal rhythm) are involved. In order to perform such an evaluation, a new algorithm has been developed which permits different wavelength components (including the long-term components due to diurnal rhythm) of heart rate variability to be approximated. In general, the method uses segmental frequency distributions of durations of intervals between successive normal cardiac beats. To assess the spectral components of heart rate variability, a scale of wavelength limits is used and for each limit of this scale, the algorithm excludes the rate changes of wavelength longer than the given bound. The method was applied to the analysis of electrocardiograms recorded in 14 post myocardial infarction patients who later suffered death or ventricular tachycardia, and in 14 other randomly selected patients with an uncomplicated course following acute myocardial infarction. The rate variability spectra obtained for both groups of patients were compared statistically and the results showed that the groups of positive and negative cases were most significantly distinguished when including both short- and long-term components of heart rate variability. Separate evaluation of different wavelength components showed that the very long-term components of heart rate variability were more powerful in distinguishing between positive and negative cases than the short term components.