Autonomic neuronal modulations in cardiac arrhythmias: Current concepts and emerging therapies

The pathophysiology of atrial fibrillation and ventricular tachycardia that result in cardiac arrhythmias is related to the sustained complicated mechanisms of the autonomic nervous system. Atrial fibrillation is when the heart beats irregularly, and ventricular arrhythmias are rapid and inconsistent heart rhythms, which involves many factors including the autonomic nervous system. It's a complex topic that requires careful exploration. Cultivation of speculative knowledge on atrial fibrillation; the irregular rhythm of the heart and ventricular arrhythmias; rapid oscillating waves resulting from mistakenly inconsistent P waves, and the inclusion of an autonomic nervous system is an inconceivable approach toward clinical intricacies. Autonomic modulation, therefore, acquires new expansions and conceptions of appealing therapeutic intelligence to prevent cardiac arrhythmia. Notably, autonomic modulation uses the neural tissue's flexibility to cause remodeling and, hence, provide therapeutic effects. In addition, autonomic modulation techniques included stimulation of the vagus nerve and tragus, renal denervation, cardiac sympathetic denervation, and baroreceptor activation treatment. Strong preclinical evidence and early human studies support the annihilation of cardiac arrhythmias by sympathetic and parasympathetic systems to transmigrate the cardiac myocytes and myocardium as efficient determinants at the cellular and physiological levels. However, the goal of this study is to draw attention to these promising early pre-clinical and clinical arrhythmia treatment options that use autonomic modulation as a therapeutic modality to conquer the troublesome process of irregular heart movements. Additionally, we provide a summary of the numerous techniques for measuring autonomic tone such as heart rate oscillations and its association with cutaneous sympathetic nerve activity appear to be substitute indicators and predictors of the outcome of treatment.

Mindfulness-Based Student Training Improves Vascular Variability Associated With Sustained Reductions in Physiological Stress Response

In today's fast-paced society, chronic stress has become an increasing problem, as it can lead to psycho-physiological health problems. University students are also faced with stress due to the demands of many courses and exams. The positive effects of mindfulness-based stress reduction (MBSR) on stress management and self-regulation have already been studied. We have developed a new mindfulness intervention tailored for students—the Mindfulness-Based Student Training (MBST). In this study, we present longitudinal results of the MBST evaluation. Biosignal analysis methods, including pulse wave variability (PWV), heart rate variability, and respiratory activity, were used to assess participants' state of autonomic regulation during the 12-week intervention and at follow-up. The progress of the intervention group (IGR, N = 31) up to 3 months after the end of MBST was compared with that of a control group (CON, N = 34). In addition, the long-term effect for IGR up to 1 year after intervention was examined. The analysis showed significant positive changes in PWV exclusively for IGR. This positive effect, particularly on vascular function, persists 1 year after the end of MBST. These results suggest a physiologically reduced stress level in MBST participants and a beneficial preventive health care program for University students.

Impact of Meditation-Based Lifestyle Modification on HRV in Outpatients With Mild to Moderate Depression: An Exploratory Study

BACKGROUND

The scientific evaluation of mind-body-interventions (MBI), including yoga and meditation, has increased significantly in recent decades. However, evidence of MBI's efficacy on biological parameters is still insufficient.

OBJECTIVES

In this study, we used HRV analysis to evaluate a novel MBI as a treatment of outpatients with mild to moderate depressive disorder. The Meditation-Based Lifestyle Modification (MBLM) program incorporates all major elements of classical yoga, including ethical principles of yoga philosophy, breathing exercises, postural yoga, and meditation.

METHODS

In this exploratory randomized controlled trial, we compared the changes in HRV indices of a MBLM group (N = 22) and a minimal treatment group (MINIMAL, drugs only, N = 17) with those of a multimodal treatment-as-usual group (TAU, according to best clinical practice, N = 22). Electrocardiogram (ECG) recordings were derived from a Holter monitoring device, and HRV indices have been extracted from nearly stationary 20-min periods.

RESULTS

Short-term HRV analysis revealed statistically significant differences in the pre-to-post changes between MBLM and TAU. In particular, the vagal tone mediating RMSSD and the Rényi entropy of symbolic dynamics indicated HRV gains in MBLM participants compared with TAU. Almost no alterations were observed in the MINIMAL group.

CONCLUSIONS

Our results suggest a benefit in selected HRV parameters for outpatients with mild to moderate depression participating in the MBLM program. For further investigations, we propose analysis of complete 24-h HRV recordings and additional continuous pulse wave or blood pressure analysis to assess long-term modulations and cardiovascular effects.

Assessing rheoencephalography dynamics through analysis of the interactions among brain and cardiac networks during general anesthesia

Cerebral blood flow (CBF) reflects the rate of delivery of arterial blood to the brain. Since no nutrients, oxygen or water can be stored in the cranial cavity due to space and pressure restrictions, a continuous perfusion of the brain is critical for survival. Anesthetic procedures are known to affect cerebral hemodynamics, but CBF is only monitored in critical patients due, among others, to the lack of a continuous and affordable bedside monitor for this purpose. A potential solution through bioelectrical impedance technology, also known as rheoencephalography (REG), is proposed, that could fill the existing gap for a low-cost and effective CBF monitoring tool. The underlying hypothesis is that REG signals carry information on CBF that might be recovered by means of the application of advanced signal processing techniques, allowing to track CBF alterations during anesthetic procedures. The analysis of REG signals was based on geometric features extracted from the time domain in the first place, since this is the standard processing strategy for this type of physiological data. Geometric features were tested to distinguish between different anesthetic depths, and they proved to be capable of tracking cerebral hemodynamic changes during anesthesia. Furthermore, an approach based on Poincaré plot features was proposed, where the reconstructed attractors form REG signals showed significant differences between different anesthetic states. This was a key finding, providing an alternative to standard processing of REG signals and supporting the hypothesis that REG signals do carry CBF information. Furthermore, the analysis of cerebral hemodynamics during anesthetic procedures was performed by means of studying causal relationships between global hemodynamics, cerebral hemodynamics and electroencephalogram (EEG) based-parameters. Interactions were detected during anesthetic drug infusion and patient positioning (Trendelenburg positioning and passive leg raise), providing evidence of the causal coupling between hemodynamics and brain activity. The provided alternative of REG signal processing confirmed the hypothesis that REG signals carry information on CBF. The simplicity of the technology, together with its low cost and easily interpretable outcomes, should provide a new opportunity for REG to reach standard clinical practice. Moreover, causal relationships among the hemodynamic physiological signals and brain activity were assessed, suggesting that the inclusion of REG information in depth of anesthesia monitors could be of valuable use to prevent unwanted CBF alterations during anesthetic procedures.

Classification of ischemic and dilated cardiomyopathy patients based on the analysis of the pulse transit time

Cardiomyopathies diseases affects a great number of the elderly population. An adequate identification of the etiology of a cardiomyopathy patient is still a challenge. The aim of this study was to classify patients by their etiology in function of indexes extracted from the characterization of the pulse transit time (PTT). This time series represents the time taken by the pulse pressure to propagate through the length of the arterial tree and corresponding to the time between R peak of ECG and the mid-point of the diastolic to systolic slope in the blood pressure signal. For each patient, the PTT time series was extracted. Thirty cardiomyopathy patients (CMP) classified as ischemic (ICM - 15 patients) and dilated (DCM - 15 patients) were analyzed. Forty-three healthy subjects (CON) were used as a reference. The PTT time series was characterized through statistical descriptive indices and the joint symbolic dynamics method. The best indices were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 89.6% accuracy, 78.5% sensitivity, and 100% specificity. When comparing CMP patients and CON subjects, the best model achieved 91.3% accuracy, 91.3% sensitivity, and 88.3% specificity. Our results suggests a significantly lower pulse transit time in ischemic patients.Clinical relevance- This study analyzed the suitability of the pulse transit time for the classification of ICM and DCM patients.

Autonomic Modulation of Cardiac Arrhythmias: Methods to Assess Treatment and Outcomes

The autonomic nervous system plays a central role in the pathogenesis of multiple cardiac arrhythmias, including atrial fibrillation and ventricular tachycardia. As such, autonomic modulation represents an attractive therapeutic approach in these conditions. Notably, autonomic modulation exploits the plasticity of the neural tissue to induce neural remodeling and thus obtain therapeutic benefit. Different forms of autonomic modulation include vagus nerve stimulation, tragus stimulation, renal denervation, baroreceptor activation therapy, and cardiac sympathetic denervation. This review seeks to highlight these autonomic modulation therapeutic modalities, which have shown promise in early preclinical and clinical trials and represent exciting alternatives to standard arrhythmia treatment. We also present an overview of the various methods used to assess autonomic tone, including heart rate variability, skin sympathetic nerve activity, and alternans, which can be used as surrogate markers and predictors of the treatment effect. Although the use of autonomic modulation to treat cardiac arrhythmias is supported by strong preclinical data and preliminary studies in humans, in light of the disappointing results of a number of recent randomized clinical trials of autonomic modulation therapies in heart failure, the need for optimization of the stimulation parameters and rigorous patient selection based on appropriate biomarkers cannot be overemphasized.

Mindfulness-Based Student Training Leads to a Reduction in Physiological Evaluated Stress

Background and Objective

In today’s fast-paced modern lifestyle, chronic stress has become a serious issue with potential consequences for our physical and mental health. The concept of mindfulness and its derived Mindfulness-Based Stress Reduction (MBSR) program is considered to be an effective stress management technique for patients as well as for healthy persons. The effects of MBSR interventions on their participants have been subject of previous research, especially with regard to psychological or social science approaches using self-reports and questionnaires. In contrast, medical investigations in this field have been less frequent and often somehow limited, for example, addressing only absolute (discrete) mean values for heart rate or blood pressure.

Methods

In this study, we have evaluated a Mindfulness Based Student Training program (MBST) by applying methods of biosignal analysis to examine its impact on the training participants’ autonomic regulation. This intervention program included classical MBSR elements but was adapted to suit the normal daily needs of university students. We obtained the electrocardiogram, finger-pulse plethysmography, and respiration activity from students participating in either the intervention group (IGR, 38 subjects) or a passive control group (CON, 35 subjects) prior to and after 8 weeks of MBST intervention.

Results

When comparing various indices from heart rate variability, pulse wave variability, and respiration in linear and nonlinear domains, significant changes in the autonomic regulation were observed for the IGR group after 8 weeks of MBST.

Conclusion

The results indicate a reduced stress level exclusively for the intervention participants, and therefore, we assume a health benefit from the MBST program.

Yoga in school sports improves functioning of autonomic nervous system in young adults: A non-randomized controlled pilot study

Background

Yoga in school is a beneficial tool to promote the good health and well-being of students by changing the way they react to stress. The positive effects of yoga—taught in schools—on children, youth and young adults have been demonstrated in former studies using mostly subjective psychometric data.

Aim

The present trial aims to evaluate the potential effects of yoga on autonomic regulation in young adults by analyzing heart rate variability (HRV).

Methods

This study is a non-randomized, explorative, two-arm-pilot study with an active control group. Fourteen healthy young adults took part in a 10-week yoga program (90 min once a week) in school and were compared to a control group of 11 students who participated in conventional school sports (90 min once a week over 10 weeks). 24-hour electrocardiograms (ECGs) were recorded at baseline and following the 10-week intervention. From 20-minute of nocturnal sleep phases, HRV parameters were calculated from linear (time and frequency domain) and nonlinear dynamics (such as symbolic dynamics and Poincaré plot analysis). Analyses of variance (ANOVA) followed by t-tests as post-hoc tests estimating both statistical significance and effect size were used to compare pre-post-intervention for the two groups.

Results

The statistical analysis of the interaction effects did not reveal a significant group and time interaction for the individual nocturnal HRV indices. Almost all indices revealed medium and large effects regarding the time main effects. The changes in the HRV indices following the intervention were more dramatic for the yoga group than for the control group which is reflected in predominantly higher significances and stronger effect sizes in the yoga group.

Conclusion

In this explorative pilot trial, an increase of HRV (more parasympathetic dominance and overall higher HRV) after ten weeks of yoga in school in comparison to regular school sports was demonstrated, showing an improved self-regulation of the autonomic nervous system.

Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone

The application of Poincaré plot analysis to characterize inter-beat interval dynamics has been successfully proposed in the scientific literature for the assessment of humans' physiological states and related aberrations. In this study, we proposed novel descriptors to trace the evolution of Poincaré plot shape over the lags. Their reliability in ultra-short cardiovascular series analysis was validated on synthetic inter-beat series generated through a physiologically plausible integral pulse frequency modulation model. Furthermore, we used the proposed approach for the investigation of the direct relationship between autonomic nervous system (ANS) dynamics and hedonic olfactory elicitation, in a group of 30 healthy subjects. Participants with a similar olfactory threshold were selected, and were asked to score 5-s stimuli in terms of arousal and valence levels according to the Russell's circumflex model of affect. Their ANS response was investigated in 35-s windows after the elicitation. Experimental results showed a gender-specific, high discriminant power of the proposed approach, discerning between pleasant and unpleasant odorants with an accuracy of 83.33% and 73.33% for men and for women, respectively. Graphical Abstract Olfaction plays a crucial role in our life and is strictly related to the Autonomic Nervous System (ANS) activity, which can be monitored studying Heart Rate Variability. We used the Lagged Poincare Plot approach to recognize gender-specific ANS response in 35-second windows after the elicitation through pleasant/unpleasant odorants.

Cardiovascular Coupling-Based Classification of Ischemic and Dilated Cardiomyopathy Patients

Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response. A total of thirty-eight cardiomyopathy patients (CMP) classified as ischemic (ICM, 25 patients) and dilated (DCM, 13 patients) were analyzed. Thirty elderly control subjects (CON) were used as reference. Their electrocardiographic (ECG) and blood pressure (BP) signals were studied. To characterize the cardiovascular activity, the following temporal series were extracted: beat-to-beat intervals (from the ECG signal), and end- systolic and diastolic blood pressure amplitudes (from the BP signal). Non-linear characterization techniques like high resolution joint symbolic dynamics, segmented Poincaré plot analysis, normalized shorttime partial directed coherence, and dual sequence method were used to characterize these times series. The best indices were used to build support vector machine models for classification. The optimal model for ICM versus DCM patients achieved 84.2% accuracy, 76.9% sensitivity, and 88% specificity. When CMP patients and CON subjects were compared, the best model achieved 95.5% accuracy, 97.3% sensitivity, and 93.3% specificity. These results suggest a disfunction in the baroreflex mechanism in cardiomyopathies patients.

Risk Stratification in Idiopathic Dilated Cardiomyopathy Patients Using Cardiovascular Coupling Analysis

Cardiovascular diseases are one of the most common causes of death; however, the early detection of patients at high risk of sudden cardiac death (SCD) remains an issue. The aim of this study was to analyze the cardio-vascular couplings based on heart rate variability (HRV) and blood pressure variability (BPV) analyses in order to introduce new indices for noninvasive risk stratification in idiopathic dilated cardiomyopathy patients (IDC). High-resolution electrocardiogram (ECG) and continuous noninvasive blood pressure (BP) signals were recorded in 91 IDC patients and 49 healthy subjects (CON). The patients were stratified by their SCD risk as high risk (IDC_HR) when after two years the subject either died or suffered life-threatening complications, and as low risk (IDC_LR) when the subject remained stable during this period. Values were extracted from ECG and BP signals, the beat-to-beat interval, and systolic and diastolic blood pressure, and analyzed using the segmented Poincaré plot analysis (SPPA), the high-resolution joint symbolic dynamics (HRJSD) and the normalized short time partial directed coherence methods. Support vector machine (SVM) models were built to classify these patients according to SCD risk. IDC_HR patients presented lowered HRV and increased BPV compared to both IDC_LR patients and the control subjects, suggesting a decrease in their vagal activity and a compensation of sympathetic activity. Both, the cardio -systolic and -diastolic coupling strength was stronger in high-risk patients when comparing with low-risk patients. The cardio-systolic coupling analysis revealed that the systolic influence on heart rate gets weaker as the risk increases. The SVM IDC_LR vs. IDC_HR model achieved 98.9% accuracy with an area under the curve (AUC) of 0.96. The IDC and the CON groups obtained 93.6% and 0.94 accuracy and AUC, respectively. To simulate a circumstance in which the original status of the subject is unknown, a cascade model was built fusing the aforementioned models, and achieved 94.4% accuracy. In conclusion, this study introduced a novel method for SCD risk stratification for IDC patients based on new indices from coupling analysis and non-linear HRV and BPV. We have uncovered some of the complex interactions within the autonomic regulation in this type of patient.

ECG based human identification using Second Order Difference Plots

BACKGROUND AND OBJECTIVE

ECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. It has a common use on cardiac diseases with high rates of classification performances by integrating it with signal analysis methods. The aim of the study is to utilize the ECG for human identification.

METHODS

Second Order Difference Plot (SODP) is a non-linear time-series analysis method that allows determining the features using the statistical analysis of the wave distributions. The SODP features were extracted using different quantification methods for ECG-based human identification. A new quantification approach has been proposed on the SODP for ECG-based human identification. The proposed method, Logarithmic Grid Analysis, was compared with the existing quantification methods on the SODP. The region of the SODP was divided into sub-regions with logarithmically increasing distances and the numbers of data points in each logarithmic sub regions were calculated in the proposed method. Three different databases were used to test the validity of the method. These records have been tested with the conventional feature extraction methods on the SODP. The long-term ECG signals were divided into 5-s short-term ECG signals.

RESULTS

The Logarithmic Grid Analysis features that were counted from short-time ECG signals were classified with k-Nearest Neighbor algorithm using 10-fold cross validation, and the identification performance of the proposed model was evaluated. Consequently, high accuracy rates of 91.96%, 99.86% and 95.12% were achieved on ECG-based human identification using the Logarithmic Grid Analysis method on the SODP.

CONCLUSIONS

The density score of data points at the center of the SODP is too high. This case increases the importance of the regions close the center in order to find the detailed and significant features from the SODP. The number of data points at the center has been extracted in more detail and the vertex areas of the major axes of the SODP can be interpreted in the aggregate sub-regions by using logarithmically increasing distances with a small number of feature size.

Poincaré plot analysis of cerebral blood flow signals: Feature extraction and classification methods for apnea detection

OBJECTIVE

Rheoencephalography is a simple and inexpensive technique for cerebral blood flow assessment, however, it is not used in clinical practice since its correlation to clinical conditions has not yet been extensively proved. The present study investigates the ability of Poincaré Plot descriptors from rheoencephalography signals to detect apneas in volunteers.

METHODS

A group of 16 subjects participated in the study. Rheoencephalography data from baseline and apnea periods were recorded and Poincaré Plot descriptors were extracted from the reconstructed attractors with different time lags (τ). Among the set of extracted features, those presenting significant differences between baseline and apnea recordings were used as inputs to four different classifiers to optimize the apnea detection.

RESULTS

Three features showed significant differences between apnea and baseline signals: the Poincaré Plot ratio (SDratio), its correlation (R) and the Complex Correlation Measure (CCM). Those differences were optimized for time lags smaller than those recommended in previous works for other biomedical signals, all of them being lower than the threshold established by the position of the inflection point in the CCM curves. The classifier showing the best performance was the classification tree, with 81% accuracy and an area under the curve of the receiver operating characteristic of 0.927. This performance was obtained using a single input parameter, either SDratio or R.

CONCLUSIONS

Poincaré Plot features extracted from the attractors of rheoencephalographic signals were able to track cerebral blood flow changes provoked by breath holding. Even though further validation with independent datasets is needed, those results suggest that nonlinear analysis of rheoencephalography might be a useful approach to assess the correlation of cerebral impedance with clinical changes.

Delta space plot analysis of cardiovascular coupling in vasovagal syncope during orthostatic challenge

In this work, a graphical method to study cardiovascular coupling, called delta space plot analysis (DSPA), was introduced. The graphical representation is susceptible to be parameterized in shape and orientation. The usefulness of this technique was studied on cardiovascular data from patients with vasovagal syncope (VVS) and from controls. The study included 15 female patients diagnosed with VVS and 11 age-matched healthy female subjects. All subjects were enrolled in a head-up tilt (HUT) test, breathing normally, including 5 minutes of supine position (baseline) and 18 minutes of 70° orthostatic phase. The DSPA parameters were obtained at different times during the HUT test, i.e., at baseline, early (first 5 min) and late (10-15 min) orthostatic phases. In baseline there were no considerable differences between female controls and female patients. During the late orthostatic phase, parameters from DSPA showed highly significantly (p=0.000003) reduced cardiovascular coupling in patients. Findings indicated a loss of control on cardiovascular coupling in female patients susceptible to vasovagal syncope during orthostatic challenge. In addition, this study provided promising results for a new graphical method to investigate cardiovascular coupling.

Identifying glaucoma patients by applying multivariate analyses of cardiovascular signals

Glaucoma is a disease that damages the eye's optic nerve. However, the exact cause of this optic nerve damage is not yet fully understood. Besides the factors of age, genetics and others, such as obesity, medication and migraines, a vascular dysfunction is believed to be a significant factor leading to glaucoma. This study's objective was to investigate whether these vascular dysfunctions could be recognized by analyzing cardiovascular regulation in glaucoma patients. Linear and nonlinear methods were applied to the extracted heart rate (HR), and systolic/ diastolic blood pressure (DBP) time series to discriminate between 35 healthy controls and 20 glaucoma patients. The combination of indices from 30-min analysis of time domain (Renyi entropy of systolic blood pressure) and nonlinear dynamics (segmented Poincare plot analysis of DBP, high-resolution joint symbolic dynamics of DBP/ HR) were able to differentiate between controls and patients with a specificity and sensitivity of > 95%. Since changes in short-term blood pressure regulation patterns and heart-rate coupling are clear signs of a vascular dysfunction, this approach could be useful for providing an earlier diagnosis of glaucoma in clinical practice.

Altered autonomic regulation as a cardiovascular risk marker for patients with sudden sensorineural hearing loss

OBJECTIVES

To measure autonomic nervous system function after idiopathic sudden sensorineural hearing loss (ISSHL).

STUDY DESIGN

Diagnostic prospective cohort single-center study.

SETTING

Tertiary referral university hospital.

PATIENTS

Twenty-three adult patients with ISSHL and 10 normal-hearing control patients without ISSHL (CON) matched with respect to age, sex, hypertension, and medication.

MAIN OUTCOME MEASURES

Bivariate analysis of autonomic regulation (ISSHL versus CON) using 30-minute heart rate (HR) and systolic and diastolic blood pressure (BP) time series at baseline, based on cardiovascular coupling, HR and BP regulatory patterns, high-resolution coupling analysis based on joint symbolic dynamics (High-Resolution Joint Symbolic Dynamics).

INTERVENTION

No intervention.

RESULTS

Multivariate discrimination between ISSHL and CON achieved values of area under the receiver operator characteristic curve = 95.5, sensitivity = 90.9%, and specificity = 88.9%. Independent from medication and hypertension increased the complexity of nonlinear HR regulation and reduced cardiovascular coupling of ISSHL patients and independent from hypertension altered nonlinear systolic and diastolic BP regulation. Coupling patterns are characterized by a less pronounced strong and fast decrease of systolic BP when HR increases and rapidly changes in ISSHL patients. Disturbed BP modulation and complexity by impaired baroreflex activities resulting in short-term BP fluctuations, altered peripheral resistance, and reduced cochlear blood flow. Increased values for the pulse wave velocity in the aorta and carotid-femoral were early indicators that the elasticity of the arteries might be restricted in ISSHL patients.

CONCLUSION

ISSHL patients show an altered autonomic regulation. At least a subgroup of ISSHL patients seems to exist where a vascular impairment might play an important role in the pathogenesis of this disease.

Influence of age and gender on complexity measures for short term heart rate variability analysis in healthy subjects

Short-term heart rate variability (HRV) analyses (less than 30 min) are suitable for ambulatory care and patient monitoring and can provide an almost immediate test result. Short-term 5 min HRV indices from nonlinear dynamics were determined from 782 females and 1124 males from the KORA S4 database. We applied various fractal and complexity measures with focus on entropies and investigated the influence of age in terms of five age decades (25-34, 35-44, 45-54, 55-64 and 65-74 years) and gender on these HRV indices. The analyses revealed significant modifications of the indices especially by age but partly also by gender especially in the younger groups. These results should be considered in future studies applying nonlinear dynamics, especially if major age and gender differences between the investigated groups are expected.

Altered cardiovascular coupling in patients with sudden sensorineural hearing loss in comparison to healthy subjects

The causes of idiopathic sudden sensorineural hearing loss (SSNHL) are still unclear while SSNHL seems to be a multicausal disease. To date limited information about autonomic regulation and, especially, cardiovascular coupling (CVC) are available for those patients. The objective of this study was to characterize short-term (30 min) CVC in 23 SSNHL patients in comparison to 23 healthy age and gender matched normal hearing control subjects (CON). Further on, the results from CVC should be compared with those from standard heart rate variability (HRV) and blood pressure variability (BPV) analyses. The results showed that HRV is not affected by the disease whereas BPV analysis revealed significant differences between both groups (p<0.01) whereby SSNHL exhibit a decreased short-term BPV. Results from CVC analysis demonstrated that especially the applied nonlinear methods exhibit an increased short-term CVC in SSNHL patients (p<0.01) indicating more complex interactions of short-term HR and BP regulatory processes. In conclusion, this study was the first to show a changed and decreased short-term BPV and increased nonlinear CVC in SSNHL patients. Our findings might help to improve diagnostic strategies for hearing loss caused by vascular factors.

Short-term heart rate variability--influence of gender and age in healthy subjects

In the recent years, short-term heart rate variability (HRV) describing complex variations of beat-to-beat interval series that are mainly controlled by the autonomic nervous system (ANS) has been increasingly analyzed to assess the ANS activity in different diseases and under various conditions. In contrast to long-term HRV analysis, short-term investigations (<30 min) provide a test result almost immediately. Thus, short-term HRV analysis is suitable for ambulatory care, patient monitoring and all those applications where the result is urgently needed. In a previous study, we could show significant variations of 5-min HRV indices according to age in almost all domains (linear and nonlinear) in 1906 healthy subjects from the KORA S4 cohort. Based on the same group of subjects, general gender-related influences on HRV indices are to be determined in this study. Short-term 5-min HRV indices from linear time and frequency domain and from nonlinear methods (compression entropy, detrended fluctuation analysis, traditional and segmented Poincaré plot analysis, irreversibility analysis, symbolic dynamics, correlation and mutual information analysis) were determined from 782 females and 1124 males. First, we examined the gender differences in two age clusters (25-49 years and 50-74 years). Secondly, we investigated the gender-specific development of HRV indices in five age decade categories, namely for ages 25-34, 35-44, 45-54, 55-64 and 65-74 years. In this study, significant modifications of the indices according to gender could be obtained, especially in the frequency domain and correlation analyses. Furthermore, there were significant modifications according to age in nearly all of the domains. The gender differences disappeared within the last two age decades and the age dependencies disappeared in the last decade. To summarize gender and age influences need to be considered when performing HRV studies even if these influences only partly differ.

QT variability improves risk stratification in patients with dilated cardiomyopathy

Recently it could be demonstrated that systolic and diastolic blood pressure variability (BPV) as well as segmented Poincare plot analysis (SPPA) contribute to risk stratification in patients suffering from dilated cardiomyopathy (DCM). The aim of this study was to improve the risk stratification applying a multivariate technique including QT variability (QTV). We enrolled and significantly separated 56 low risk and 13 high risk DCM patients by nearly all applied BPV and QTV methods, but not with traditional heart rate variability analysis. The optimum set of two indices calculating the multivariate discriminate analysis (DA) included one BPV index calculated by symbolic dynamics method (DBP(Shannon)) and one index calculated from QTV (QTV(log)) achieving an area under the receiver operating characteristics curve (AUC) of 92%, sensitivity of 92.3% and specificity of 89.3%. Performing only electrocardiogram analysis, the optimum multivariate approach including indices from segmented Poincaré plot analysis and QTV still achieved a remarkable AUC of 88.3%. Increasing the number of indices for multivariate DA up to three, we achieved an AUC of 95.7%, sensitivity of 100% and specificity of 85.7% including one clinical, one BPV and one QTV index. Summarizing, we identified DCM patients with an increased risk of sudden cardiac death applying QTV analysis in a multivariate approach.

Three-dimensional segmented poincare plot analysis - A new approach of cardiovascular and cardiorespiratory regulation analysis

Hypertensive pregnancy disorders affect 6 to 8 percent of all pregnancies which can cause severe complications for the mother and the fetus. The aim of this study was to develop a new method suitable for a three dimensional coupling analysis. Therefore, the three-dimensional segmented Poincaré plot analysis (SPPA3) is introduced that represents the Poincare analysis based on a cubic box model representation. The box representing the three dimensional phase space is (based on the SPPA method) subdivided into 12×12×12 equal cubelets according to the predefined range of signals and all single probabilities of occurring points in a specific cubelet related to the total number of points are calculated. From 10 healthy non-pregnant women, 66 healthy pregnant women and 56 hypertensive pregnant women suffering from chronic hypertension, gestational hypertension and preeclampsia, 30 minutes of beat-to-beat intervals (BBI), noninvasive blood pressure and respiration (RESP) were continuously recorded and analyzed. Couplings between the different signals were analyzed. The ability of SPPA3 for a screening could be confirmed by multivariate discriminant analysis differentiating between all pregnant woman and preeclampsia (index BBI3_SBP9_RESP6/ BBI8_SBP11_RESP4 leads to an area under the ROC curve of AUC=91.2%). In conclusion, SPPA3 could be a useful method for enhanced risk stratification in pregnant women.

A multi-scale feedback ratio analysis of heartbeat interval series in healthy vs. cardiac patients

The second-order difference plot, as a modified Poincaré plot, is one of the important approaches for assessing the dynamics of heart rate variability. However, corresponding quantitative analysis methods are relatively limited. Based on the second-order difference plot, we propose a novel method, called the multi-scale feedback ratio analysis, which can measure the feedback properties of heart rate fluctuations on different temporal scales. The index [R(TF([τ(1), τ(2)]) is then defined to quantify the average feedback ratio through a definite scale range. Analysis of Gaussian white, 1/f and Brownian noises show that the feedback ratios are indeed on different levels. The method is then applied to heartbeat interval series derived from healthy subjects, subjects with congestive heart failure and subjects with atrial fibrillation. Results show that, for all groups, the feedback ratios vary with increasing time scales, and gradually reach relatively stable states. The R(TF)([10,20]) values of the three groups are significantly different. Thus, R(TF)([10,20]) becomes an effective parameter for distinguishing healthy and pathologic states. In addition, RTF([10,20]) for healthy, congestive failure and atrial fibrillation subjects are close to those of the 1/f, Brownian and white noises respectively, indicating different intrinsic dynamics.

Three-Dimensional Segmented Poincaré Plot Analyses SPPA3 Investigates Cardiovascular and Cardiorespiratory Couplings in Hypertensive Pregnancy Disorders

Hypertensive pregnancy disorders affect 6-8% of gestations representing the most common complication of pregnancy for both mother and fetus. The aim of this study was to introduce a new three-dimensional coupling analysis methods - the three-dimensional segmented Poincaré plot analyses (SPPA3) - to establish an effective approach for the detection of hypertensive pregnancy disorders and especially pre-eclampsia (PE). A cubic box model representing the three-dimensional phase space is subdivided into 12 × 12 × 12 equal predefined cubelets according to the range of the SD of each investigated signal. Additionally, we investigated the influence of rotating the cloud of points and the size of the cubelets (adapted or predefined). All single probabilities of occurring points in a specific cubelet related to the total number of points are calculated. In this study, 10 healthy non-pregnant women, 66 healthy pregnant women, and 56 hypertensive pregnant women (chronic hypertension, pregnancy-induced hypertension, and PE) were investigated. From all subjects, 30 min of beat-to-beat intervals (BBI), respiration (RESP), non-invasive systolic (SBP), and diastolic blood pressure (DBP) were continuously recorded and analyzed. Non-rotated adapted SPPA3 discriminated best between hypertensive pregnancy disorders and PE concerning coupling analysis of two or three different systems (BBI, DBP, RESP and BBI, SBP, DBP) reaching an accuracy of up to 82.9%. This could be increased to an accuracy of up to 91.2% applying multivariate analysis differentiating between all pregnant women and PE. In conclusion, SPPA3 could be a useful method for enhanced risk stratification in pregnant women.

Coupling of heart rate and systolic blood pressure in hypertensive pregnancy

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems".

BACKGROUND

Hypertensive pregnancy disorders affect 6 - 8 percent of all pregnancies and can result in severe complications for both the mother and the fetus.

OBJECTIVES

The aim of this study was to improve risk stratification of pregnant women suffering from hypertension and pre-eclampsia (PE) by applying bivariate Segmented Poincaré plot analysis (BSPPA).

METHODS

From 35 pregnant women suffering from chronic hypertension, gestational hypertension and PE, 30 minutes of noninvasive systolic blood pressure and beat- to-beat intervals were continuously recorded and analyzed by applying BSPPA to quantify their couplings.

RESULTS

We revealed significant different couplings between chronic hypertension (CH), gestational hypertension and PE, indicating that cardiovascular regulation can be considerably altered depending on the type of hypertensive disorder. The optimal multivariate set of two BSPPA indices was determined which distinguish best between CH and PE. It achieved a sensitivity of 100%, a specificity of 77.8% and an area under the receiver operator characteristic curve of 90.8%.

CONCLUSIONS

The BSPPA method a) provides improved risk stratification for pregnant women suffering from hypertension and PE, b) increases the ability to diagnose pathological changes, and c) could contribute substantially to the differential diagnosis of hypertensive pregnancy disorders.

Short-term vs. long-term heart rate variability in ischemic cardiomyopathy risk stratification

In industrialized countries with aging populations, heart failure affects 0.3–2% of the general population. The investigation of 24 h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV) for enhanced risk stratification in patients with ischemic heart failure (IHF). However, long-term analyses are time-consuming, expensive, and delay the initial diagnosis. The objective of this study was to investigate whether 30 min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24 h-HRV analysis. From 256 IHF patients [221 at low risk (IHF_LR) and 35 at high risk (IHF_HR)] (a) 24 h beat-to-beat time series (b) the first 30 min segment (c) the 30 min most stationary day segment and (d) the 30 min most stationary night segment were investigated. We calculated linear (time and frequency domain) and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 h and for each 30 min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p < 0.01) discriminating between IHF_LR and IHF_HR. For multivariate risk stratification, optimal mixed parameter sets consisting of 5 indices (clinical and nonlinear) achieved 80.4% AUC (area under the curve of receiver operating characteristics) from 24 h HRV analysis, 84.3% AUC from first 30 min, 82.2 % AUC from daytime 30 min and 81.7% AUC from nighttime 30 min. The optimal parameter set obtained from the first 30 min showed nearly the same classification power when compared to the optimal 24 h-parameter set. As results from stationary daytime and nighttime, 30 min segments indicate that short-term analyses of 30 min may provide at least a comparable risk stratification power in IHF in comparison to a 24 h analysis period.

Quantification of compensatory processes of postnatal hypoxia in newborn piglets applying short-term nonlinear dynamics analysis

Background

Newborn mammals suffering from moderate hypoxia during or after birth are able to compensate a transitory lack of oxygen by adapting their vital functions. Exposure to hypoxia leads to an increase in the sympathetic tone causing cardio-respiratory response, peripheral vasoconstriction and vasodilatation in privileged organs like the heart and brain. However, there is only limited information available about the time and intensity changes of the underlying complex processes controlled by the autonomic nervous system.

Methods

In this study an animal model involving seven piglets was used to examine an induced state of circulatory redistribution caused by moderate oxygen deficit. In addition to the main focus on the complex dynamics occurring during sustained normocapnic hypoxia, the development of autonomic regulation after induced reoxygenation had been analysed. For this purpose, we first introduced a new algorithm to prove stationary conditions in short-term time series. Then we investigated a multitude of indices from heart rate and blood pressure variability and from bivariate interactions, also analysing respiration signals, to quantify the complexity of vegetative oscillations influenced by hypoxia.

Results

The results demonstrated that normocapnic hypoxia causes an initial increase in cardiovascular complexity and variability, which decreases during moderate hypoxia lasting one hour (p < 0.004). After reoxygenation, cardiovascular complexity parameters returned to pre-hypoxic values (p < 0.003), however not respiratory-related complexity parameters.

Conclusions

In conclusion, indices from linear and nonlinear dynamics reflect considerable temporal changes of complexity in autonomous cardio-respiratory regulation due to normocapnic hypoxia shortly after birth. These findings might be suitable for non-invasive clinical monitoring of hypoxia-induced changes of autonomic regulation in newborn humans.