Short-term heart rate complexity is reduced in patients with type 1 diabetes mellitus

Heart rate complexity in sinoaortic-denervated mice

NEW FINDINGS

What is the central question of this study? New measurements for cardiovascular complexity, such as detrended fluctuation analysis (DFA) and multiscale entropy (MSE), have been shown to predict cardiovascular outcomes. Given that cardiovascular diseases are accompanied by autonomic imbalance and decreased baroreflex sensitivity, the central question is: do baroreceptors contribute to cardiovascular complexity? What is the main finding and its importance? Sinoaortic denervation altered both DFA scaling exponents and MSE, indicating that both short- and long-term mechanisms of complexity are altered in sinoaortic denervated mice, resulting in a loss of physiological complexity. These results suggest that the baroreflex is a key element in the complex structures involved in heart rate variability regulation. Recently, heart rate (HR) oscillations have been recognized as complex behaviours derived from non-linear processes. Physiological complexity theory is based on the idea that healthy systems present high complexity, i.e. non-linear, fractal variability at multiple scales, with long-range correlations. The loss of complexity in heart rate variability (HRV) has been shown to predict adverse cardiovascular outcomes. Based on the idea that most cardiovascular diseases are accompanied by autonomic imbalance and a decrease in baroreflex sensitivity, we hypothesize that the baroreflex plays an important role in complex cardiovascular behaviour. Mice that had been subjected to sinoaortic denervation (SAD) were implanted with catheters in the femoral artery and jugular vein 5 days prior to the experiment. After recording the baseline arterial pressure (AP), pulse interval time series were generated from the intervals between consecutive values of diastolic pressure. The complexity of the HRV was determined using detrended fluctuation analysis and multiscale entropy. The detrended fluctuation analysis α1 scaling exponent (a short-term index) was remarkably decreased in the SAD mice (0.79 ± 0.06 versus 1.13 ± 0.04 for the control mice), whereas SAD slightly increased the α2 scaling exponent (a long-term index; 1.12 ± 0.03 versus 1.04 ± 0.02 for control mice). In the SAD mice, the total multiscale entropy was decreased (13.2 ± 1.3) compared with the control mice (18.9 ± 1.4). In conclusion, fractal and regularity structures of HRV are altered in SAD mice, affecting both short- and long-term mechanisms of complexity, suggesting that the baroreceptors play a considerable role in the complex structure of HRV.

Decreased complexity of glucose dynamics in diabetes: evidence from multiscale entropy analysis of continuous glucose monitoring system data

Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help in the control of glycemic fluctuations, which is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and, thus, a decreased complexity in this system. No study has investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13), who were matched for sex, age, and body mass index via MSE analysis using the CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 vs. control subjects 93.3 ± 1.5 mg/dl), the standard deviation (51.7 ± 4.3 vs. 11.1 ± 0.5 mg/dl), and the mean amplitude of glycemic excursions (127.0 ± 9.2 vs. 27.7 ± 1.3 mg/dl) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 vs. 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregulation is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes.

An evaluation of heart rate variability and its modifying factors in children with type 1 diabetes

OBJECTIVE

To evaluate heart rate variability by Holter monitoring in type 1 diabetic children compared with a healthy control group and determine the factors modifying heart rate variability.

METHODS

This was designed as a prospective study comparing 28 patients, diagnosed with type 1 diabetes and under follow-up, with 27 healthy control group subjects.

RESULTS

The patients were aged 9.9 ± 4.2 years in the diabetic group, including 13 (46.5%) girls and 15 (53.5%) boys. The healthy control group comprised 20 (74%) girls and seven boys (26%) with an average age of 8.6 ± 3.7 years. The search for factors modifying heart rate variability yielded the following correlations: for the time-dependent variables, negative between age and both average and maximal heart rate (r = -0.263 and -0.460, respectively), negative between haemoglobin A1c and percentage of differences between adjacent RR intervals >50 ms, positive between diabetes duration and square root of the mean of the sum of squares of differences between adjacent NN intervals. The average heart rate and percentage of differences between adjacent RR intervals >50 ms was significantly higher in the girls than the boys in all groups. With regard to the frequency-dependent factors affecting heart rate variability, correlations were found between haemoglobin A1c level and both total power and very low frequency (r = -0.751 and -0.644) and between very low frequency and diabetes duration.

CONCLUSION

A reduction in heart rate variability parameters was observed in type 1 diabetes mellitus patients who had a long disease duration or were poorly controlled, as compared with healthy controls.

How to Calculate Renyi Entropy from Heart Rate Variability, and Why it Matters for Detecting Cardiac Autonomic Neuropathy

Cardiac autonomic neuropathy (CAN) is a disease that involves nerve damage leading to an abnormal control of heart rate. An open question is to what extent this condition is detectable from heart rate variability (HRV), which provides information only on successive intervals between heart beats, yet is non-invasive and easy to obtain from a three-lead ECG recording. A variety of measures may be extracted from HRV, including time domain, frequency domain, and more complex non-linear measures. Among the latter, Renyi entropy has been proposed as a suitable measure that can be used to discriminate CAN from controls. However, all entropy methods require estimation of probabilities, and there are a number of ways in which this estimation can be made. In this work, we calculate Renyi entropy using several variations of the histogram method and a density method based on sequences of RR intervals. In all, we calculate Renyi entropy using nine methods and compare their effectiveness in separating the different classes of participants. We found that the histogram method using single RR intervals yields an entropy measure that is either incapable of discriminating CAN from controls, or that it provides little information that could not be gained from the SD of the RR intervals. In contrast, probabilities calculated using a density method based on sequences of RR intervals yield an entropy measure that provides good separation between groups of participants and provides information not available from the SD. The main contribution of this work is that different approaches to calculating probability may affect the success of detecting disease. Our results bring new clarity to the methods used to calculate the Renyi entropy in general, and in particular, to the successful detection of CAN.

Effects of first-time overnight CPAP therapy for increasing the complexity of the patient's physiological system

Studies regarding the effects of short-term continuous positive airway pressure (CPAP) therapy are not sufficient. A total of 35 patients with moderate to severe untreated OSA were divided into 2 groups. Group 1 comprised 22 patients who underwent polysomnography (PSG) for one night, and Group 2 comprised 13 patients who received PSG combined with CPAP therapy. To evaluate the influence of receiving CPAP therapy for one night, we measured 5 min wrist pulse signals before and after the experiment to assess heart rate variability, as well as novel short time multiscale entropy (sMSE) indicator that examines complexity in physiological signals. The results show that the participants in Group 1 exhibited significant changes in normalized low-frequency power/normalized high-frequency power (nLF/nHF) (0.72 ± 0.09 versus 1.11 ± 0.11, P = 0.006) values before and after the PSG study. By contrast, the participants in Group 2 showed no significant changes in the 3 indicators. Regarding the sMSE indicator, Group 2 patients exhibited significant increases in the sMSE. CPAP therapy administered for one night can reduce the sympathovagal imbalance in patients with moderate to severe untreated OSA and increase the complexity of the patient's physiological system, thereby reflecting their overall improved health.

Heart rate variability in children with type 1 diabetes mellitus

OBJECTIVE

To gather current information about the effects of type 1 diabetes mellitus on children's cardiac autonomic behavior.

DATA SOURCES

The search of articles was conducted on PubMed, Ibecs, Medline, Cochrane, Lilacs, SciELO and PEDro databases using the MeSH terms: "autonomic nervous system", "diabetes mellitus", "child", "type 1 diabetes mellitus", "sympathetic nervous system" and "parasympathetic nervous system", and their respective versions in Portuguese (DeCS). Articles published from January 2003 to February 2013 that enrolled children with 9-12 years old with type 1 diabetes mellitus were included in the review.

DATA SYNTHESIS

The electronic search resulted in four articles that approached the heart rate variability in children with type 1 diabetes mellitus, showing that, in general, these children present decreased global heart rate variability and vagal activity. The practice of physical activity promoted benefits for these individuals.

CONCLUSIONS

Children with type 1 diabetes mellitus present changes on autonomic modulation, indicating the need for early attention to avoid future complications in this group.

Effect of age on complexity and causality of the cardiovascular control: comparison between model-based and model-free approaches

The proposed approach evaluates complexity of the cardiovascular control and causality among cardiovascular regulatory mechanisms from spontaneous variability of heart period (HP), systolic arterial pressure (SAP) and respiration (RESP). It relies on construction of a multivariate embedding space, optimization of the embedding dimension and a procedure allowing the selection of the components most suitable to form the multivariate embedding space. Moreover, it allows the comparison between linear model-based (MB) and nonlinear model-free (MF) techniques and between MF approaches exploiting local predictability (LP) and conditional entropy (CE). The framework was applied to study age-related modifications of complexity and causality in healthy humans in supine resting (REST) and during standing (STAND). We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia.

Influence of type 2 diabetes on symbolic analysis and complexity of heart rate variability in men

BACKGROUND

Individuals with diabetes may develop cardiac autonomic dysfunction that may be evaluated by heart rate variability (HRV). The aim was evaluated heart rate variability (HRV) of individuals with type 2 diabetes, without cardiovascular autonomic neuropathy (CAN), in response to active postural maneuver by means of nonlinear analysis (symbolic analysis, Shannon and conditional entropy) and correlate HRV parameters between them, glycated hemoglobin and diabetes duration.

METHODS

Nineteen men with type 2 diabetes without CAN (T2D) and nineteen healthy men (CG), age-range from 40 to 60 years were studied. We assessed HRV in supine and orthostatic position using symbolic analysis (0V%, 1V%, 2LV% and 2UV%), Shannon and conditional entropy (SE and NCI).

RESULTS

In supine position T2D presented higher sympathetic modulation (0V%) than CG. However, there was not any difference between groups for indexes of complexity (SE and NCI). Furthermore, T2D presented a preserved response of cardiac autonomic modulation after active postural maneuver.

CONCLUSIONS

The present study showed that individuals with type 2 diabetes without CAN presented higher cardiac sympathetic modulation. However, the complexity of HRV was not influenced by imbalance of the autonomic modulation in individuals with type 2 diabetes. In addition, the response of autonomic nervous system in the heart remains preserved after active postural maneuver in individuals with type 2 diabetes, possibly due to the lack of CAN in this group.

Visualization methods for assisting detection of cardiovascular neuropathy

Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN. Indications from the new visualization technique are compared to the results of established diagnostic measures using the Ewing battery of tests. We find the proposed method to offer useful insights into this disease, as rather than relying upon a binary yes/no decision, it offers a comprehensive picture of the complexity of this disease.

Entropy-based complexity of the cardiovascular control in Parkinson disease: comparison between binning and k-nearest-neighbor approaches

Entropy-based approaches are frequently used to quantify complexity of short-term cardiovascular control from spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP). Among these tools the ones optimizing a critical parameter such as the pattern length are receiving more and more attention. This study compares two entropy-based techniques for the quantification of complexity making use of completely different strategies to optimize the pattern length. Comparison was carried out over HP and SAP variability series recorded from 12 Parkinson's disease (PD) patients without orthostatic hypotension or symptoms of orthostatic intolerance and 12 age-matched healthy control (HC) subjects. Regardless of the method, complexity of cardiovascular control increased in PD group, thus suggesting the early impairment of cardiovascular function.

Risk stratification of cardiac autonomic neuropathy based on multi-lag Tone-Entropy

Cardiac autonomic neuropathy (CAN) is an irreversible condition affecting the autonomic nervous system, which leads to abnormal functioning of the visceral organs and affects critical body functions such as blood pressure, heart rate and kidney filtration. This study presents multi-lag Tone-Entropy (T-E) analysis of heart rate variability (HRV) at multiple lags as a screening tool for CAN. A total of 41 ECG recordings were acquired from diabetic subjects with definite CAN (CAN+) and without CAN (CAN-) and analyzed. Tone and entropy values of each patient were calculated for different beat sequence lengths (len: 50-900) and lags (m: 1-8). The CAN- group was found to have a lower mean tone value compared to that of CAN+ group for all m and len, whereas the mean entropy value was higher in CAN- than that in CAN+ group. Leave-one-out (LOO) cross-validation tests using a quadratic discriminant (QD) classifier were applied to investigate the performance of multi-lag T-E features. We obtained 100 % accuracy for tone and entropy with len = 250 and m = {2, 3} settings, which is better than the performance of T-E technique based on lag m = 1. The results demonstrate the usefulness of multi-lag T-E analysis over single lag analysis in CAN diagnosis for risk stratification and highlight the change in autonomic nervous system modulation of the heart rate associated with cardiac autonomic neuropathy.

Heart rate complexity and cardiac sympathetic dysinnervation in patients with type 2 diabetes mellitus

Cardiovascular autonomic neuropathy (CAN) is one of the most severe complications of type 2 diabetes mellitus (T2DM). The aim of this study was to investigate associations of cardiac sympathetic dysinnervation (CSD; by (123)I-MIBG scintigraphy) with short-term heart rate variability (HRV) measured by traditional vs. complexity markers. ECG was measured in 31 diabetic patients during rest over a period of 5 minutes and HRV quantified in different domains (time and frequency domain, scaling properties, symbolic dynamics). (123)I-MIBG scintigraphy identified 16 patients with CSD. Resting heart rate was increased and HRV reduced in these patients. In a subgroup of 16 patients ECG was also measured during standing. Changes in several HRV measures upon standing demonstrated cardiac responsiveness to orthostatic stress. Strong correlations between HRV, measured during standing, and CSD were observed with metrics based on symbolic dynamics. In conclusion, HRV assessment during standing may be useful for assessing cardiac sympathetic dysinnervation in patients with type 2 diabetes mellitus.

K-nearest-neighbor conditional entropy approach for the assessment of the short-term complexity of cardiovascular control

Complexity analysis of short-term cardiovascular control is traditionally performed using entropy-based approaches including corrective terms or strategies to cope with the loss of reliability of conditional distributions with pattern length. This study proposes a new approach aiming at the estimation of conditional entropy (CE) from short data segments (about 250 samples) based on the k-nearest-neighbor technique. The main advantages are: (i) the control of the loss of reliability of the conditional distributions with the pattern length without introducing a priori information; (ii) the assessment of complexity indexes without fixing the pattern length to an arbitrary low value. The approach, referred to as k-nearest-neighbor conditional entropy (KNNCE), was contrasted with corrected approximate entropy (CApEn), sample entropy (SampEn) and corrected CE (CCE), being the most frequently exploited approaches for entropy-based complexity analysis of short cardiovascular series. Complexity indexes were evaluated during the selective pharmacological blockade of the vagal and/or sympathetic branches of the autonomic nervous system. We found that KNNCE was more powerful than CCE in detecting the decrease of complexity of heart period variability imposed by double autonomic blockade. In addition, KNNCE provides indexes indistinguishable from those derived from CApEn and SampEn. Since this result was obtained without using strategies to correct the CE estimate and without fixing the embedding dimension to an arbitrary low value, KNNCE is potentially more valuable than CCE, CApEn and SampEn when the number of past samples most useful to reduce the uncertainty of future behaviors is high and/or variable among conditions and/or groups.

Short-term complexity indexes of heart period and systolic arterial pressure variabilities provide complementary information

It is unclear whether the complexity of the variability of the systolic arterial pressure (SAP) provides complementary information to that of the heart period (HP). The complexity of HP and SAP variabilities was assessed from short beat-to-beat recordings (i.e., 256 cardiac beats). The evaluation was made during a pharmacological protocol that induced vagal blockade with atropine or a sympathetic blockade (beta-adrenergic blockade with propranolol or central sympathetic blockade with clonidine) alone or in combination, during a graded head-up tilt, and in patients with Parkinson's disease (PD) without orthostatic hypotension undergoing orthostatic challenge. Complexity was quantified according to the mean square prediction error (MSPE) derived from univariate autoregressive (AR) and multivariate AR (MAR) models. We found that: 1) MSPEMAR did not provide additional information to that of MSPEAR; 2) SAP variability was less complex than that of HP; 3) because HP complexity was reduced by either vagal blockade or vagal withdrawal induced by head-up tilt and was unaffected by beta-adrenergic blockade, HP was under vagal control; 4) because SAP complexity was increased by central sympathetic blockade and was unmodified by either vagal blockade or vagal withdrawal induced by head-up tilt, SAP was under sympathetic control; 5) SAP complexity was increased in patients with PD; and 6) during orthostatic challenge, the complexity of both HP and SAP variabilities in patients with PD remained high, thus indicating both vagal and sympathetic impairments. Complexity indexes derived from short HP and SAP beat-to-beat series provide complementary information and are helpful in detecting early autonomic dysfunction in patients with PD well before circulatory symptoms become noticeable.

NONLINEAR ANALYSIS OF PHYSIOLOGICAL SIGNALS: A REVIEW

This paper reviews various nonlinear analysis methods for physiological signals. The assessment is based on a discussion of chaos-inspired methods, such as fractal dimension (FD), correlation dimension (D2), largest Lyapunov exponet (LLE), Renyi's entropy (REN), Shannon spectral entropy (SEN), and approximate entropy (ApEn). We document that these methods are used to extract discriminative features from electroencephalograph (EEG) and heart rate variability (HRV) signals by reviewing the relevant scientific literature. EEG features can be used to support the diagnosis of epilepsy and HRV features can be used to support the diagnosis of cardiovascular diseases as well as diabetes. Documenting the widespread use of these and other nonlinear methods supports our thesis that the study of feature extraction methods, based on the chaos theory, is an important subject which has been gaining more and significance in biomedical engineering. We adopt the position that pursuing research in the field of biomedical engineering is ultimately a progmatic activity, where it is necessary to engage in features that work. In this case, the nonlinear features are working well, even if we do not have conclusive evidence that the underlying physiological phenomena are indeed chaotic.

Heart rate time irreversibility is impaired in adolescent major depression

We aimed to study heart rate time irreversibility--a nonlinear qualitative characteristics of heart rate variability indicating complexity of cardiac autonomic control at rest and in response to physiological stress (orthostasis) in never-treated major depressive disorder (MDD) adolescent female patients.

METHODS

We studied 20 MDD girls and 20 healthy age-matched girls at the age of 15 to 18 years. The ECG was recorded in supine position and in response to position change from lying to standing (orthostasis). Time irreversibility analysis was performed using Porta's (P%), Guzik's (G%) and Ehlers' (E) index. The depressive disorder severity was evaluated using Montgomery-Asberg Depression Rating Scale (MADRS) and Children's Depression Inventory (CDI).

RESULTS

Resting heart rate time irreversibility indices (logG%, logP%, Ehlers' index) were significantly reduced in MDD female patients without significant differences in response to orthostasis in MDD girls compared to controls. No significant correlations between time irreversibility and MDD severity were observed.

CONCLUSION

This study revealed the impaired heart rate asymmetry pattern indicating an altered complexity of cardiac autonomic regulation in adolescent female patients suffering from MDD.

The effect of orthostatic stress on multiscale entropy of heart rate and blood pressure

Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.

Multiscale entropy of laser Doppler flowmetry signals in healthy human subjects

PURPOSE

The cardiovascular system (CVS) regulation can be studied from a central viewpoint, through heart rate variability (HRV) data, and from a peripheral viewpoint, through laser Doppler flowmetry (LDF) signals. Both the central and peripheral CVSs are regulated by several interacting mechanisms, each having its own temporal scale. The central CVS has been the subject of many multiscale studies. By contrast, these studies at the level of the peripheral CVS are very recent. Among the multiscale studies performed on the central CVS data, multiscale entropy has been proven to give interesting physiological information for diagnostic purposes. However, no multiscale entropy analysis has been performed on LDF signals. The authors' goal is therefore to propose a first multiscale entropy study of LDF data recorded in healthy subjects.

METHODS

The LDF signals recorded in the forearm of seven healthy subjects are processed. Their period sampling is T=50 ms, and coarse-graining scales from T to 23T are studied. Also, for validation, the algorithm is first tested on synthetic signals of known theoretical multiscale entropy.

RESULTS

The results reveal nonmonotonic evolution of the multiscale entropy of LDF signals, with a maximum at small scales around 7T and a minimum at longer scales around 18T, singling out in this way two distinctive scales where the LDF signals undergo specific changes from high to low complexity. This also marks a strong contrast with the HRV signals that usually display a monotonic increase in the evolution of the multiscale entropy.

CONCLUSIONS

Multiscale entropy of LDF signals in healthy subjects shows variation with scales. Moreover, as the variation pattern observed appears similar for all the tested signals, multiscale entropy could potentially be a useful stationary signature for LDF signals, which otherwise are probe-position and subject dependent. Further work could now be conducted to evaluate possible diagnostic purposes of the multiscale entropy of LDF signals.

Acute increase of complexity in the neurocardiovascular dynamics following carotid stenting

OBJECTIVE

Percutaneous carotid angioplasty and stenting (CAS) has been used to improve cerebral circulation and autoregulation. However, whether CAS ameliorates the autonomic regulatory dynamics remains unclear. This prospective study examines the neurocardiovascular dynamics following carotid stenting.

METHODS

Thirty minutes electrocardiograms were recorded at three different time points (pre-operative, 1-h post-operative, 1-day post-operative) on twelve male patients (mean age 70.8 ± 9.6 years) receiving unilateral primary CAS. The HR data were analyzed by the conventional heart rate variability (HRV) and the multiscale entropy (MSE) methods; the former associates with autonomic activities and the latter quantifies the regulatory complexity of heart beat intervals. Loss of complexity at multiple scales has been associated with decoupled regulatory network in vivo.

RESULTS

Conventional HRV indices showed no difference after CAS. Complexity indices increased significantly on scales 2-8 at 1-h and on scales 2-3 1-day post-treatment. The lower scale MSE (1-5) correlated with the frequency components of conventional HRV indices. The increased complexity could imply a restoration of the neurocardiovascular dynamics on the path to a healthier state.

CONCLUSIONS

Primary CAS can induce a recovery in the neurocardiovascular regulatory dynamics in patients with high-grade carotid stenosis.

Nonlinear PD2i heart rate complexity algorithm detects autonomic neuropathy in patients with type 1 diabetes mellitus

OBJECTIVE

The aim of this study was to test whether a new heart rate variability (HRV) complexity measure, the Point Correlation Dimension (PD2i), provides diagnostic information regarding early subclinical autonomic dysfunction in diabetes mellitus (DM). We tested the ability of PD2i to detect diabetic autonomic neuropathy (DAN) in asymptomatic young DM patients without overt neuropathy and compared them to age- and gender-matched controls.

METHODS

HRV in DM type 1 patients (n=17, 10 female, 7 male) aged 12.9-31.5 years (duration of DM 12.4±1.2 years) was compared to that in a control group of 17 healthy matched probands. The R-R intervals were measured over 1h using a telemetric ECG system.

RESULTS

PD2i was able to detect ANS dysfunction with p=0.0006, similar to the best discriminating MSE scale, with p=0.0002.

CONCLUSIONS

The performance of PD2i to detect DAN in asymptomatic DM patients is similar to the best discriminative power of previously published complexity measures.

SIGNIFICANCE

The PD2i algorithm may prove to be an easy to perform and clinically useful tool for the early detection of autonomic neuropathy in DM type 1 patients, especially given its minimal data requirements.

Cardiorespiratory phase-coupling is reduced in patients with obstructive sleep apnea

Cardiac and respiratory rhythms reveal transient phases of phase-locking which were proposed to be an important aspect of cardiorespiratory interaction. The aim of this study was to quantify cardio-respiratory phase-locking in obstructive sleep apnea (OSA). We investigated overnight polysomnography data of 248 subjects with suspected OSA. Cardiorespiratory phase-coupling was computed from the R-R intervals of body surface ECG and respiratory rate, calculated from abdominal and thoracic sensors, using Hilbert transform. A significant reduction in phase-coupling was observed in patients with severe OSA compared to patients with no or mild OSA. Cardiorespiratory phase-coupling was also associated with sleep stages and was significantly reduced during rapid-eye-movement (REM) sleep compared to slow-wave (SW) sleep. There was, however, no effect of age and BMI on phase coupling. Our study suggests that the assessment of cardiorespiratory phase coupling may be used as an ECG based screening tool for determining the severity of OSA.

The altered complexity of cardiovascular regulation in depressed patients

Major depressive disorders (MDD) are associated with an increased risk for cardiovascular morbidity and mortality. Even if it is known that MDD are accompanied by an autonomic dysbalance with increased sympathetic and/or reduced parasympathetic activity, to date only limited information is available about the degree and complexity of cardiovascular regulation. The aim of this study was to investigate the influence of MDD on the autonomous nervous system and cardiovascular complexity by means of linear and nonlinear indices from heart rate and blood pressure variability (HRV, BPV). From 57 non-medicated patients and 57 matched healthy controls with respect to age and gender HRV and BPV in time and frequency domain, symbolic dynamics, compression entropy, multiscale entropy, detrended fluctuation analysis, Poincaré plot analysis and baroreflex sensitivity were analysed from 30 min short-term recordings. Complexity indices from nonlinear dynamics demonstrated considerable changes in autonomous regulation due to MDD. For the first time we could show that non-medicated depressed patients who were matched with respect to age and gender reveal a significantly changed short-term as well as long-term complexity of cardiovascular regulation. These results suggest substantial changes in autonomic control probably due to a change of interactions between different physiological control loops in MDD.

Methods derived from nonlinear dynamics for analysing heart rate variability

Methods from nonlinear dynamics (NLD) have shown new insights into heart rate (HR) variability changes under various physiological and pathological conditions, providing additional prognostic information and complementing traditional time- and frequency-domain analyses. In this review, some of the most prominent indices of nonlinear and fractal dynamics are summarized and their algorithmic implementations and applications in clinical trials are discussed. Several of those indices have been proven to be of diagnostic relevance or have contributed to risk stratification. In particular, techniques based on mono- and multifractal analyses and symbolic dynamics have been successfully applied to clinical studies. Further advances in HR variability analysis are expected through multidimensional and multivariate assessments. Today, the question is no longer about whether or not methods from NLD should be applied; however, it is relevant to ask which of the methods should be selected and under which basic and standardized conditions should they be applied.