Dirk Hoyer

Altered diurnal autonomic variation and reduced vagal information flow in acute schizophrenia

OBJECTIVE This study aimed to further investigate autonomic function in schizophrenic patients using long-term electrocardiographic (ECG) recordings. METHODS Twenty unmedicated patients suffering from an acute episode of paranoid schizophrenia and 20 matched control subjects were recruited and 24-h ambulatory electrocardiograms were recorded. In order to investigate complexity of heart rate fluctuations related to different physiological time scales, linear heart rate variability (HRV) as well as autonomic information flow (AIF) parameters were calculated from day and night time intervals. RESULTS While heart rates were increased, root mean successive square difference (RMSSD), a measure for vagal function as well as standard deviation of 5-min mean NN-intervals (SDANN), reflecting parasympathetic and sympathetic tone, were decreased in schizophrenia. Furthermore, a decrease of vagal information flow was apparent during night time (decreased mean high frequency peak decay (PD(mHF))). In addition, increased INT(NN) (area under the AIF curve) as well as decreased beat decay (BD(NN)) and mean very low frequency PD (PD(mVLF)) indicated reduced complexity in patients during day and night time. CONCLUSIONS HRV and AIF parameters indicate altered diurnal autonomic variation in schizophrenia. SIGNIFICANCE Reduced vagal modulation and loss of complexity might both contribute to the increased risk for sudden cardiac death in schizophrenia.

Using mutual information to measure coupling in the cardiorespiratory system

Mutual information (MI) analysis represents a general method to detect linear and nonlinear statistical dependencies between time series, and it can be considered as an alternative to the well-known correlation analysis. This article shows how the concept of MI can be used to quantify the coupling between two systems, X and Y. We consider systems as coupled if there are two signals, x(t) and y(t), representing successive measurements of the systems, X and Y, respectively, such that x(t) and y(t) are statistically dependent. Roughly speaking, this means that we can learn anything on x from observations of y, and vice versa. MI represents a measure for the strength of statistical dependencies, hence it could also be used as a measure of coupling. We apply our method to the cardiorespiratory system of a newborn. Here, we find significant changes in the strength of coupling with some characteristic time scales. Typical linear and nonlinear dependencies were found to undergo changes with the sleep states of human newborns. Those changes and scales are also reflected by a correlation analysis. However, we argue that there might be simultaneously rather large correlations, and weak dependencies, quantified by the MI. This can occur because correlation is rather different from M1; correlation describes only linear dependencies, where MI takes into account both linear and nonlinear dependencies.

Mutual information function assesses autonomic information flow of heart rate dynamics at different time scales

The autonomic information flow (AIF) represents the complex communication within the Autonomic Nervous System (ANS). It can be assessed by the mutual information function (MIF) of heart rate fluctuations (HRF). The complexity of HRF is based on several interacting physiological mechanisms operating at different time scales. Therefore one prominent time scale for HRF complexity analysis is not given a priori. The MIF reflects the information flow at different time scales. This approach is defined and evaluated in the present paper. In order to aggregate relevant physiological time scales, the MIF of HRF obtained from eight adult Lewis rats during the awake state, under general anesthesia, with additional vagotomy, and additional beta1-adrenergic blockade are investigated. Physiologically relevant measures of the MIF were assessed with regard to the discrimination of these states. A simulation study of a periodically excited pendulum is performed to clarify the influence of the time scale of MIF in comparison to the Kolmogorov Sinai entropy (KSE) of that well defined system. The general relevance of the presented AIF approach was confirmed by comparing mutual information, approximate entropy, and sample entropy at their respective time scales.

Mutual information and phase dependencies: measures of reduced nonlinear cardiorespiratory interactions after myocardial infarction

The heart rate variability (HRV) is related to several mechanisms of the complex autonomic functioning such as respiratory heart rate modulation and phase dependencies between heart beat cycles and breathing cycles. The underlying processes are basically nonlinear. In order to understand and quantitatively assess those physiological interactions an adequate coupling analysis is necessary. We hypothesized that nonlinear measures of HRV and cardiorespiratory interdependencies are superior to the standard HRV measures in classifying patients after acute myocardial infarction. We introduced mutual information measures which provide access to nonlinear interdependencies as counterpart to the classically linear correlation analysis. The nonlinear statistical autodependencies of HRV were quantified by auto mutual information, the respiratory heart rate modulation by cardiorespiratory cross mutual information, respectively. The phase interdependencies between heart beat cycles and breathing cycles were assessed basing on the histograms of the frequency ratios of the instantaneous heart beat and respiratory cycles. Furthermore, the relative duration of phase synchronized intervals was acquired. We investigated 39 patients after acute myocardial infarction versus 24 controls. The discrimination of these groups was improved by cardiorespiratory cross mutual information measures and phase interdependencies measures in comparison to the linear standard HRV measures. This result was statistically confirmed by means of logistic regression models of particular variable subsets and their receiver operating characteristics.

Permutation entropy improves fetal behavioural state classification based on heart rate analysis from biomagnetic recordings in near term fetuses.

The relevance of the complexity of fetal heart rate fluctuations with regard to the classification of fetal behavioural states has not been satisfyingly clarified so far. Because of the short behavioural states, the permutation entropy provides an advantageous complexity estimation leading to the Kullback–Leibler entropy (KLE). We test the hypothesis that parameters derived from KLE can improve the classification of fetal behaviour states based on classical heart rate fluctuation parameters (SDNN, RMSSD, ln(LF), ln(HF)). From measured heartbeat sequences (35 healthy fetuses at a gestational age between 35 and 40 completed weeks) representative intervals of 256 heartbeats were visually preclassified into fetal behavioural states. Employing discriminant analysis to separate the states 1F, 2F and 4F, the best classification result by classical parameters was 80.0% (SDNN). After additionally considering KLE parameters it was improved significantly (p<0.0005) to 94.3% (ln(LF), KLE_Mean). It could be confirmed that KLE can improve the state classification. This might reflect the consideration of different physiological aspects by classical and complexity measures.

Estimation of nonlinear couplings on the basis of complexity and predictability-a new method applied to cardiorespiratory coordination

Nonlinear coordination is an essential property of the complex functioning of the autonomic nervous system. Therefore, the coupled behavior of heart rate fluctuations (HRF) and respiratory movements (RM) was analyzed on the basis of their joint reconstruction in phase space. Independence measures of complexity and predictability were approximated from the correlation integrals which enabled the strength of cardiorespiratory couplings to be quantified. These measures were validated in a simulation study of two coupled nonlinear oscillators in dependence on their coupling strength and respective synchronization effects. The cardiorespiratory coordination during quiet sleep and active sleep of newborn piglets was quantified by means of the proposed independence measures of complexity and predictability. The difference of those measures between the sleep states investigated was more significant than the difference of the respective linear coherence peaks.

Nonlinear broad band dynamics are less complex in major depression.

OBJECTIVES Cardiac mortality is known to be increased in depressive patients. However, the underlying mechanisms remain elusive to date. Decreased heart rate variability (HRV) has been discussed as contributing to increased cardiac mortality, but studies examining patients suffering from major depressive disorder (MDD) have revealed inconsistent results. This study aimed to investigate long-term and broad band parameters of heart rate regulation in MDD, which have been shown to be more sensitive for the assessment of autonomic dysfunction. METHODS A total of 18 non-medicated patients suffering from MDD and 18 matched control subjects without cardiac disease were recruited and 24-h ambulatory electrocardiograms were recorded. Data were recorded during three distinct time intervals linear and nonlinear parameters as well as autonomic information flow (AIF) were calculated. RESULTS The power law slope was significantly reduced in the patient group for all intervals investigated and correlated with symptom severity, whereas standard deviation of the 5-min NN intervals (SDANN) and area under the AIF curve (INT(NN)) showed significant differences between groups in the morning hours only. Analysis of standard HRV parameters in the time and frequency domain revealed no significant differences between groups. CONCLUSIONS The evidence for decreased complexity of cardiac regulation in depressed patients presented here might be useful as an indicator of the increased cardiac mortality known in depression, especially since these parameters are capable of predicting cardiac mortality in other diseases. The importance of these parameters for patients at risk should be evaluated in future prospective studies.

Deterministic-chaotic and periodic properties of heart rate and arterial pressure fluctuations and their mediation in piglets

OBJECTIVE Only the simultaneous analysis of periodic and nonlinear properties of heart rate fluctuations (HRF) can describe completely this complex physiological process. Up to now there is, apart from a study of our own, no systematic and correlative investigation using both parameter groups, also not in early development. Thus, we tried to describe in this manner these properties of HRF, the corresponding mean arterial pressure fluctuations (MAPF) and respiratory movements (RM) and their mutual relations in neonatal pig. METHODS In 6 term newborn piglets, periodic properties of HRF, RM, and MAPF were analyzed by spectral and coherence analysis, and deterministic-chaotic properties by calculation of correlation dimension (CD), Lyapunov exponent (LE), and construction of phase space plots. The assumption of deterministic chaotic components was supported by Theilers test for nonlinearity, by always positive leading LEs, and by the results of a nonlinear deterministic model. These analyses were done in sleep states, general anaesthesia, hypoxic hypoxia, in ventilated state, and during cholinergic and additional beta-adrenergic blockade. RESULTS In all experimental states, HRF and MAPF have periodic and nonlinear, very probably deterministic-chaotic properties, but in different relations. In anaesthetized piglets, periodic properties of HRF and MAPF dominate. In hypoxia the decreasing LE and CD of HRF and CD of MAPF were connected with increasing MAPF power density. Cholinergic blockade caused a decreased overall HRF and MAPF power and a decreasing LE and CD, but beta-adrenergic blockade decreased a small part of power density of both in 0.02-0.08 Hz only. The results of CD, LE, Theilers test and the low dimensional deterministic model data suggested mainly deterministic-chaotic properties in the nonlinear part of HRF and MAPF. CONCLUSIONS Already in neonatal piglets, both periodic and nonlinear, very probably deterministic chaotic properties of HRF and MAPF exist which change both during hypoxia and cholinergic blockade. They are partly cholinergically and--to a small extent--also beta-adrenergically mediated. The decrease of nonlinear complexity of HRF and MAPF during hypoxia suggests characteristic pathological change even in early development.

Fetal heart rate variability reveals differential dynamics in the intrauterine development of the sympathetic and parasympathetic branches of the autonomic nervous system

The aim of this study was to investigate the hypothesis that fetal beat-to-beat heart rate variability (fHRV) displays the different time scales of sympatho-vagal development prior to and after 32 weeks of gestation (wks GA). Ninety-two magnetocardiograms of singletons with normal courses of pregnancy between 24 + 1 and 41 + 6 wks GA were studied. Heart rate patterns were either quiet/non-accelerative (fHRP I) or active/accelerative (fHRP II) and recording quality sufficient for fHRV. The sample was divided into the GA groups <32 wks GA/>32 wks GA. Linear parameters of fHRV were calculated: mean heart rate (mHR), SDNN and RMSSD of normal-to-normal interbeat intervals, power in the low (0.04-0.15 Hz) and high frequency range (0.15-0.4 Hz) and the ratios SDNN/RMSSD and LF/HF as markers for sympatho-vagal balance. fHRP I is characterized by decreasing SDNN/RMSSD, LF/HF and mHR. The decrease is more pronounced <32 wks GA. Beyond that GA SDNN/RMSSD is predominantly determined by RMSSD during fHRP I and by SDNN during fHRP II. In contrast to fHRP I, during fHRP II, mHR is positively correlated to SDNN/RMSSD instead of SDNN >32 wks GA. LF/HF increases in fHRP II during the first half of the third trimester. Non-accelerative fHRP are indicative of parasympathetic dominance >32 wks GA. In contrast, the sympathetic accentuation during accelerative fHRP is displayed in the interrelations between mHR, SDNN and SDNN/RMSSD. Prior to 32 wks GA, fHRV reveals the increasing activity of the respective branches of the autonomic nervous system differentiating the types of fHRP.

Autonomic dysfunction predicts both 1- and 2-month mortality in middle-aged patients with multiple organ dysfunction syndrome.

Objective:Multiple organ dysfunction syndrome (MODS) is a disease entity that carries a high mortality rate. It is characterized by a sequential failure of several organ systems after a trigger event, most commonly sepsis. There is increasing evidence that autonomic dysfunction may substantially contribute to the development of MODS. We recently characterized the spectrum of autonomic dysfunction by using heart rate variability in critically ill MODS patients and were able to show that autonomic dysfunction predicts 28-day mortality in MODS. The aim of the present study was evaluate whether autonomic dysfunction is also a predictor of 180-day and 365-day mortalities. Design:Prospective cohort study. Setting:Twelve-bed medical intensive care unit in a university center. Patients:Ninety consecutively admitted score-defined MODS patients. Interventions:We assessed heart rate variability as a marker of autonomic dysfunction. The patients were followed for 180- and 365-day mortalities. Measurements and Main Results:We prospectively used the heart rate variability variable lnVLF, which predicted 28-day mortality best in the entire cohort of patients, for analysis of longer term mortality. The variable lnVLF was found to be useful for risk prediction for about 60 days, and then the survival curves became nearly parallel. Conclusions:Autonomic function of critically ill MODS patients is blunted, and this attenuation has prognostic implications not merely concerning 28-day mortality but also concerning longer term (about 2-month) mortality.