Very Low Frequency Heart Rate Variability Predicts the Development of Post-Stroke Infections.

Stroke-induced immunodepression is a major risk factor for severe infectious complications in the immediate post-stroke period. We investigated the predictive value of heart rate variability (HRV) to identify patients at risk of post-stroke infection, systemic inflammatory response syndrome, or severe sepsis during the post-acute interval from days 3 to 5 after stroke onset. A prospective, observational monocentric cohort study was conducted in a university hospital stroke unit of patients with ischemic infarction in the territory of the middle cerebral artery without an ongoing infection at admission. Standard HRV indices were processed from Holter ECG. Recording started within the first day after the onset of stroke. Infection (primary endpoint: pneumonia, urinary tract, unknown localization) was assessed between days 3 and 5. The predictive value of HRV adjusted for clinical data was analyzed by logistic regression models and area under the receiver operating characteristic curve (AUC). From 287 eligible patients, data of 89 patients without event before completion of 24-h Holter ECG were appropriate for prediction of infection (34 events). HRV was significantly associated with incident infection even after adjusting for clinical covariates. Very low frequency (VLF) band power adjusted for both, the National Institutes of Health Stroke Scale (NIHSS) at admission and diabetes predicted infection with AUC = 0.80 (cross-validation AUC = 0.74). A model with clinical data (diabetes, NIHSS at admission, involvement of the insular cortex) performed similarly well (AUC = 0.78, cross-validation AUC = 0.71). Very low frequency HRV, an index of integrative autonomic-humoral control, predicts the development of infectious complications in the immediate post-stroke period. However, the additional predictive value of VLF band power over clinical risk factors such as stroke severity and insular involvement was marginal. The continuous HRV monitoring starting immediately after admission might probably increase the predictive performance of VLF band power. That needs to be clarified in further investigations.

Correction: Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability.

[This corrects the article DOI: 10.1371/journal.pone.0200799.].

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability.

BACKGROUND: Fetal heart rate variability (fHRV) of normal-to-normal (NN) beat intervals provides high-temporal resolution access to assess the functioning of the autonomic nervous system (ANS). AIM: To determine critical periods of fetal autonomic maturation. The developmental pace is hypothesized to change with gestational age (GA). STUDY DESIGN: Prospective longitudinal observational study. SUBJECTS: 60 healthy singleton fetuses were followed up by fetal magnetocardiographic heart rate monitoring 4-11 times (median 6) during the second half of gestation. OUTCOME MEASURE: FHRV parameters, accounting for differential aspects of the ANS, were studied applying linear mixed models over four predefined pregnancy segments of interest (SoI: <27; 27+0-31+0; 31+1-35+0; >35+1 weeks GA). Periods of fetal active sleep and quiescence were accounted for separately. RESULTS: Skewness of the NN interval distribution VLF/LF band power ratio and complexity describe a saturation function throughout the period of interest. A decreasing LF/HF ratio and an increase in pNN5 indicate a concurrent shift in sympathovagal balance. Fluctuation amplitude and parameters of short-term variability (RMSSD, HF band) mark a second acceleration towards term. In contrast, fetal quiescence is characterized by sequential, but low-margin transformations; ascending overall variability followed by an increase of complexity and superseded by fluctuation amplitude. CONCLUSIONS: An increase in sympathetic activation, connected with by a higher ability of parasympathetic modulation and baseline stabilization, is reached during the transition from the late 2nd into the early 3rd trimester. Pattern characteristics indicating fetal well-being saturate at 35 weeks GA. Pronounced fetal breathing efforts near-term mirror in fHRV as respiratory sinus arrhythmia.

Evaluation of standardized, computerized Dawes/Redman heart-rate analysis based on different recording methods and in relation to fetal beat-to-beat heart rate variability.

Dawes and Redman (DR) based their definition of short-term variation (STV) on the successive differences of mean inter-beat intervals dividing 1 min of cardiotocography recordings in 16 epochs of 3.75 s each. In contrast, heart rate variability (HRV) is based on the inter-beat intervals of discrete R peaks, also referred to as normal-to-normal (NN) intervals. Despite the historical achievements of DR in providing a robust method with the equipment available at the time to encourage the widespread use and creation of large databases, one must ask whether the STV (DR) parameter is reproducible using a different method of recording, and how much temporal information is actually lost by applying the averaging algorithm sketched above. We simultaneously performed both standard Oxford cardiotocography and transabdominal fetal electrocardiography recordings in 26 patients with low-risk singletons. In addition, we revisited our database of 418 standard fetal magnetocardiographic recordings, applying the DR algorithm to the fetal NN data and compared them to standard HRV parameters. The correlation between STV (DR) from cardiotocography and fetal electrocardiography was stronger that of either with short term fHRV from NN intervals. The methodological trade-off to gain STV as a robust parameter from heart rate traces of limited temporal resolution is accompanied by a loss of temporal information that, at the moment, only fetal magnetocardiography and, to a lesser extent, fetal electrocardiography may provide.

Fetal autonomic brain age scores, segmented heart rate variability analysis, and traditional short term variability.

Disturbances of fetal autonomic brain development can be evaluated from fetal heart rate patterns (HRP) reflecting the activity of the autonomic nervous system. Although HRP analysis from cardiotocographic (CTG) recordings is established for fetal surveillance, temporal resolution is low. Fetal magnetocardiography (MCG), however, provides stable continuous recordings at a higher temporal resolution combined with a more precise heart rate variability (HRV) analysis. A direct comparison of CTG and MCG based HRV analysis is pending. The aims of the present study are: (i) to compare the fetal maturation age predicting value of the MCG based fetal Autonomic Brain Age Score (fABAS) approach with that of CTG based Dawes-Redman methodology; and (ii) to elaborate fABAS methodology by segmentation according to fetal behavioral states and HRP. We investigated MCG recordings from 418 normal fetuses, aged between 21 and 40 weeks of gestation. In linear regression models we obtained an age predicting value of CTG compatible short term variability (STV) of R (2) = 0.200 (coefficient of determination) in contrast to MCG/fABAS related multivariate models with R (2) = 0.648 in 30 min recordings, R (2) = 0.610 in active sleep segments of 10 min, and R (2) = 0.626 in quiet sleep segments of 10 min. Additionally segmented analysis under particular exclusion of accelerations (AC) and decelerations (DC) in quiet sleep resulted in a novel multivariate model with R (2) = 0.706. According to our results, fMCG based fABAS may provide a promising tool for the estimation of fetal autonomic brain age. Beside other traditional and novel HRV indices as possible indicators of developmental disturbances, the establishment of a fABAS score normogram may represent a specific reference. The present results are intended to contribute to further exploration and validation using independent data sets and multicenter research structures.

Study protocol: prediction of stroke associated infections by markers of autonomic control.

BACKGROUND: Infection is the most important complication after acute stroke. This is substantially based on a stroke-induced immunosuppression. Heart rate variability (HRV) represents the autonomic nervous system activity in connection with stroke-induced immunomodulation and infections. We demonstrated in a feasibility study that HRV indices obtained in patients without acute post-stroke infections can predict infections in the subsequent sub-acute phase. METHODS/DESIGN: The study PRED-SEP is a prospective observational study. Adult patients with acute ischemic infarction in the territory of the middle cerebral artery and severe neurological deficit (National Institutes of Health Stroke Scale: NIHSS ≥ 8) are recruited. Primary endpoint is the development of infections, secondary endpoints are SIRS and severe sepsis in the sub-acute phase (day 3-5) after stroke and the functional outcome after 3 months. Infection is defined according to the PANTHERIS study and comprises pneumonia, urinary tract infection and infections without determined focus. SIRS and severe sepsis are defined according to German Sepsis Society guidelines. Functional outcome is measured by lethality and neurological scores (modified Rankin Scale, Barthel Index). Prognostic factors are HRV risk indices calculated from selected intervals of 24 h ECG measurements within 48 hours after symptom onset. It is planned to recruit 240 patients.HRV risk indices (predictors) will be calculated according to standards and procedures previously developed and published by the authors. The predictive effects of HRV indices on infections will be estimated by fitting logistic regression models and estimating odds ratios with 95% confidence intervals. A prespecified modelling procedure will be applied to estimate unadjusted and confounder adjusted odds ratios. Secondary endpoints will be analysed in the same way. The functional outcome scales will be dichotomized. The association between HRV indices and pro- and anti-inflammatory markers will be quantified by calculating the appropriate correlation coefficients according to scale (Person or Spearman). DISCUSSION: Since a general prophylactic antibiotic treatment after stroke is not recommended, results of this study could have essential implications for an early identification and hence, timely appropriate treating of stroke-induced infections. TRIAL REGISTRATION: Prädiktoren für die Sepsis - Pred Sep, German Clinical Trials Register: DRKS00003392.

Fetal functional brain age assessed from universal developmental indices obtained from neuro-vegetative activity patterns.

Fetal brain development involves the development of the neuro-vegetative (autonomic) control that is mediated by the autonomic nervous system (ANS). Disturbances of the fetal brain development have implications for diseases in later postnatal life. In that context, the fetal functional brain age can be altered. Universal principles of developmental biology applied to patterns of autonomic control may allow a functional age assessment. The work aims at the development of a fetal autonomic brain age score (fABAS) based on heart rate patterns. We analysed n = 113 recordings in quiet sleep, n = 286 in active sleep, and n = 29 in active awakeness from normals. We estimated fABAS from magnetocardiographic recordings (21.4-40.3 weeks of gestation) preclassified in quiet sleep (n = 113, 63 females) and active sleep (n = 286, 145 females) state by cross-validated multivariate linear regression models in a cross-sectional study. According to universal system developmental principles, we included indices that address increasing fluctuation range, increasing complexity, and pattern formation (skewness, power spectral ratio VLF/LF, pNN5). The resulting models constituted fABAS. fABAS explained 66/63% (coefficient of determination R(2) of training and validation set) of the variance by age in quiet, while 51/50% in active sleep. By means of a logistic regression model using fluctuation range and fetal age, quiet and active sleep were automatically reclassified (94.3/93.1% correct classifications). We did not find relevant gender differences. We conclude that functional brain age can be assessed based on universal developmental indices obtained from autonomic control patterns. fABAS reflect normal complex functional brain maturation. The presented normative data are supplemented by an explorative study of 19 fetuses compromised by intrauterine growth restriction. We observed a shift in the state distribution towards active awakeness. The lower WGA dependent fABAS values found in active sleep may reflect alterations in the universal developmental indices, namely fluctuation amplitude, complexity, and pattern formation that constitute fABAS.

Development of multiscale complexity and multifractality of fetal heart rate variability.

During fetal development a complex system grows and coordination over multiple time scales is formed towards an integrated behavior of the organism. Since essential cardiovascular and associated coordination is mediated by the autonomic nervous system (ANS) and the ANS activity is reflected in recordable heart rate patterns, multiscale heart rate analysis is a tool predestined for the diagnosis of prenatal maturation. The analyses over multiple time scales requires sufficiently long data sets while the recordings of fetal heart rate as well as the behavioral states studied are themselves short. Care must be taken that the analysis methods used are appropriate for short data lengths. We investigated multiscale entropy and multifractal scaling exponents from 30 minute recordings of 27 normal fetuses, aged between 23 and 38 weeks of gestational age (WGA) during the quiet state. In multiscale entropy, we found complexity lower than that of non-correlated white noise over all 20 coarse graining time scales investigated. Significant maturation age related complexity increase was strongest expressed at scale 2, both using sample entropy and generalized mutual information as complexity estimates. Multiscale multifractal analysis (MMA) in which the Hurst surface h(q,s) is calculated, where q is the multifractal parameter and s is the scale, was applied to the fetal heart rate data. MMA is a method derived from detrended fluctuation analysis (DFA). We modified the base algorithm of MMA to be applicable for short time series analysis using overlapping data windows and a reduction of the scale range. We looked for such q and s for which the Hurst exponent h(q,s) is most correlated with gestational age. We used this value of the Hurst exponent to predict the gestational age based only on fetal heart rate variability properties. Comparison with the true age of the fetus gave satisfying results (error 2.17±3.29 weeks; p<0.001; R(2)=0.52). In addition, we found that the normally used DFA scale range is non-optimal for fetal age evaluation. We conclude that 30 min recordings are appropriate and sufficient for assessing fetal age by multiscale entropy and multiscale multifractal analysis. The predominant prognostic role of scale 2 heart beats for MSE and scale 39 heart beats (at q=-0.7) for MMA cannot be explored neither by single scale complexity measures nor by standard detrended fluctuation analysis.

Fetal development of complex autonomic control evaluated from multiscale heart rate patterns.

Development of the fetal autonomic nervous system's integrative capacity in relation to gestational age and emerging behavioral pattern is reflected in fetal heart rate patterns. Conventional indices of vagal and sympathetic rhythms cannot sufficiently reflect their complex interrelationship. Universal behavioral indices of developing complex systems may provide additional information regarding the maturating complex autonomic control. We investigated fetal magnetocardiographic recordings undertaken at 10-min intervals in active (n = 248) and quiet (n = 111) states between 22 and 39 wk gestational age. Standard deviation of heartbeat intervals, skewness, contribution of particular rhythms to the total power, and multiscale entropy were analyzed. The multiscale entropy methodology was validated for 10-min data sets. Age dependence was analyzed by linear regression. In the quiet state, contribution of sympathovagal rhythms and their complexity over a range of corresponding short scales increased with rising age, and skewness shifted from negative to positive values. In the active state, age dependencies were weaker. Skewness as the strongest parameter shifted in the same direction. Fluctuation amplitude and the complexity of scales associated with sympathovagal rhythms increased. We conclude that in the quiet state, stable complex organized rhythms develop. In the active state, however, increasing behavioral variability due to multiple internal coordinations, such as movement-related heart rate accelerations, and external influences develop. Hence, the state-selective assessment in association with developmental indices used herein may substantially improve evaluation of maturation age and early detection and interpretation of developmental problems in prenatal diagnosis.

Development of integrative autonomic nervous system function: an investigation based on time correlation in fetal heart rate patterns.

OBJECTIVE: To describe the development of the integrative capacity of the fetal autonomic nervous system (ANS) according to gestational age and emerging behavioral states, assuming that developing integrative ANS functions are reflected in increasing autocorrelation of fetal heart rate and fetal heart rate variability markers. METHODS: Magnetocardiograms of 114 healthy fetuses (21-40 weeks of gestation) were recorded. Level of fetal activity (quiet/active sleep) was estimated according to characteristic heart rate patterns. Autocorrelation functions of (i) fetal heart rate and (ii) time patterns of SDNN (standard deviation of normal-to-normal intervals) and RMSSD (root mean square of successive differences in normal-to-normal intervals) were calculated and autocorrelation was determined over different time scales. Age and activity related changes were examined using linear regression and non-parametric tests. RESULTS: During pregnancy, autocorrelation increased in fetal heart rate signals and time patterns of SDNN and RMSSD. Short-time correlation (0-20 s) changed between 21 and 31 gestational weeks. Long-time correlation (75-300 s) accelerated later in pregnancy and did not increase in quiet heart rate patterns. Strong state-dependent changes were found with time patterns of SDNN. CONCLUSIONS: Emerging integrative ANS functions are reflected in increasing autocorrelation of fetal heart rate fluctuations over increasing time scales. The period from 21 to 31 gestational weeks seems to be critical to ANS development. Increasing long-time correlation is specific to active sleep states.

Fetal development assessed by heart rate patterns--time scales of complex autonomic control.

The increasing functional integrity of the organism during fetal maturation is connected with increasing complex internal coordination. We hypothesize that time scales of complexity and dynamics of heart rate patterns reflect the increasing inter-dependencies within the fetal organism during its prenatal development. We investigated multi-scale complexity, time irreversibility and fractal scaling from 73 fetal magnetocardiographic 30min recordings over the third trimester. We found different scale dependent complexity changes, increasing medium scale time irreversibility, and increasing long scale fractal correlations (all changes p<0.05). The results confirm the importance of time scales to be considered in fetal heart rate based developmental indices.

Multi-scale characteristics of resampled fetal heart rate pattern provide novel fetal developmental indices.

The increasing functional integrity of the organism during fetal maturation is connected with increasing complex internal coordination mediated by the autonomic nervous system. We hypothesize that time scales of complex and dynamic inter-dependencies over more than one heart beat interval reflect the increasing complex adjustments within the fetal organism during its prenatal development. We investigated multi-scale complexity and time irreversibility from equidistantly resampled heart rate time series of 73 fetal magnetocardiographic recordings over the third trimester. We found scale dependent changes in complexity and time irreversibility. The functions obtained from equidistantly resampled heart rate time series showed qualitatively similar curves compared to those obtained from heart beat intervals series previously reported. Time scales of fetal heart rate characteristics may provide novel information for the identification of developmental disorders in prenatal diagnosis.