Very high frequency oscillations in the heart rate and blood pressure of heart transplant patients

Autonomic nervous system assessment using heart rate variability

The role of the autonomic nervous system in the onset of supraventricular and ventricular arrhythmias is well established. It can be analysed by the spontaneous behaviour of the heart rate with ambulatory ECG recordings, through heart rate variability measurements. Input of heart rate variability parameters into artificial intelligence models to make predictions regarding the detection or forecast of rhythm disorders is becoming routine and neuromodulation techniques are now increasingly used for their treatment. All this warrants a reappraisal of the use of heart rate variability for autonomic nervous system assessment.Measurements performed over long periods such as 24H-variance, total power, deceleration capacity, and turbulence are suitable for estimating the individual basal autonomic status. Spectral measurements performed over short periods provide information on the dynamics of systems that disrupt this basal balance and may be part of the triggers of arrhythmias, as well as premature atrial or ventricular beats. All heart rate variability measurements essentially reflect the modulations of the parasympathetic nervous system which are superimposed on the impulses of the adrenergic system. Although heart rate variability parameters have been shown to be useful for risk stratification in patients with myocardial infarction and patients with heart failure, they are not part of the criteria for prophylactic implantation of an intracardiac defibrillator, because of their high variability and the improved treatment of myocardial infarction. Graphical methods such as Poincaré plots allow quick screening of atrial fibrillation and are set to play an important role in the e-cardiology networks. Although mathematical and computational techniques allow manipulation of the ECG signal to extract information and permit their use in predictive models for individual cardiac risk stratification, their explicability remains difficult and making inferences about the activity of the ANS from these models must remain cautious.

Autonomic impairment of patients in coma with different Glasgow coma score assessed with heart rate variability

PRIMARY OBJECTIVE

The objective of this study is to assess the functional state of the autonomic nervous system in healthy individuals and in individuals in coma using measures of heart rate variability (HRV) and to evaluate its efficiency in predicting mortality.

DESIGN AND METHODS

Retrospective group comparison study of patients in coma classified into two subgroups, according to their Glasgow coma score, with a healthy control group. HRV indices were calculated from 7 min of artefact-free electrocardiograms using the Hilbert-Huang method in the spectral range 0.02-0.6 Hz. A special procedure was applied to avoid confounding factors. Stepwise multiple regression logistic analysis (SMLRA) and ROC analysis evaluated predictions.

RESULTS

Progressive reduction of HRV was confirmed and was associated with deepening of coma and a mortality score model that included three spectral HRV indices of absolute power values of very low, low and very high frequency bands (0.4-0.6 Hz). The SMLRA model showed sensitivity of 95.65%, specificity of 95.83%, positive predictive value of 95.65%, and overall efficiency of 95.74%.

CONCLUSIONS

HRV is a reliable method to assess the integrity of the neural control of the caudal brainstem centres on the hearts of patients in coma and to predict patient mortality.

Very High Frequency Oscillations of Heart Rate Variability in Healthy Humans and in Patients with Cardiovascular Autonomic Neuropathy

Literature reports on the very high frequency (VHF) range of 0.4-0.9 Hz in heart rate variability (HRV) are scanty. The VHF presence in cardiac transplant patients and other conditions associated with reduced vagal influence on the heart encouraged us to explore this spectral band in healthy subjects and in patients diagnosed with cardiac autonomic neuropathy (CAN), and to assess the potential clinical value of some VHF indices. The study included 80 healthy controls and 48 patients with spinocerebellar ataxia type 2 (SCA2) with CAN. The electrocardiographic recordings of short 5-min duration were submitted to three different spectral analysis methods, including the most generally accepted procedure, and the two novel methods using the Hilbert-Huang transform. We demonstrated the presence of VHF activity in both groups of subjects. However, VHF power spectral density, expressed in relative normalized units, was significantly greater in the SCA2 patients than that in healthy subjects, amounting to 36.1 ± 17.4% vs. 22.9 ± 14.1%, respectively, as also was the instantaneous VHF spectral frequency, 0.58 ± 0.05 vs. 0.64 ± 0.07 Hz, respectively. These findings were related to the severity of CAN. We conclude that VHF activity of HRV is integral to the cardiovascular autonomic control.

Heart rate variability improvement in children using transcatheter atrial septal defect closure

Objective:

We evaluated autonomic behavior by examining heart rate variability (HRV) in the time domain and frequency domain in pediatric patients who underwent transcatheter closure of atrial septal defect (ASD).

Methods:

A prospective study design was used. Holter ECG was performed in a control group of 30 healthy subjects and a group of 47 patients who underwent transcatheter ASD closure. ECG was taken one day before, one day after, and six months after the procedure to evaluate changes in the time domain [SDNN, rMSSD, NN, pNN50(%), and SDANN] and frequency domain (VLF, LF, HF, VHF, and LF/HF) in the patient group. Student’s t-test was used to evaluate changes prior to and after the procedure.

Results:

There were 28 females (60%) in the patient group and 21 females (70%) in the control group. The mean age and weight of the participants in the patient group were 9.61±4.72 years and 32.40±19.60 kg, respectively; the mean age and weight of the control subjects were 10.43±5.31 years and 32.83±13.00 kg, respectively. In both the time domain and frequency domain analyses, the patient group values were found to be lower than those in the control group prior to the procedure; the values in the patient group were found to approach the values in the control group following the procedure. By the sixth month, the values in the patient group reached the control levels with no statistically significant difference (SDNN: 145±0.84, 137.50±42.50; r MSSD: 72.18±48.22, 58.14±28.49; SDANN: 125.13±13.50, 122.40±41.06; VLF: 112.85±29.07, 114.41±98.39; LF: 50.40±24.09, 45.69±15.13; HF: 39.28±19.86, 44.29±13.14; VHF: 10.29±4.24, 9.99±6.47; LF/HF: 1.90±1.44, 1.24±0.81; p>0.05).

Conclusion:

The transcatheter closure of secundum ASDs was found to have a positive effect on HRV. Consequently, it may contribute to reduced mortality and morbidity. We can conclude that in children, HRV recovers approximately six months after transcatheter ASD closure.

The matching of sinus arrhythmia to respiration: are trauma patients without serious injury comparable to healthy laboratory subjects?

We sought to better understand the physiology underlying the metrics of heart rate variability (HRV) in trauma patients without serious injury, compared to healthy laboratory controls. In trauma patients without serious injury (110 subjects, 470 2-min data segments), we studied the correlation between sinus arrhythmia (SA) rate, heart rate (HR), and respiratory rate (RR). Most segments with 2.4 < HR/RR < 4.8 exhibited SA-RR matching, whereas rate matching was absent in 81% of the segments with HR/RR < 2.4 and in 86% of the segments with HR/RR > 4.8. The findings were comparable, in some cases remarkably so, to previous reports from healthy laboratory subjects. The presence (or absence) of SA-RR matching, when SA is largely controlled by respiration, can be anticipated in this trauma population. This work provides a valuable step towards the definition of patterns of HRV found in trauma patients with and without life-threatening injury.

Noisy fluctuation of heart rate indicates cardiovascular system instability

Heart rate spontaneously fluctuates despite homeostatic regulatory mechanisms to stabilize it. Harmonic and fractal fluctuations have been described. Non-harmonic non-fractal fluctuation has not been studied because it is usually thought that it is caused by apparatus noise. We hypothesized that this fluctuation looking like apparatus noise (that we call "noisy fluctuation") is linked to challenged blood pressure stabilization and not to apparatus noise. We assessed noisy fluctuation by quantifying the small and fastest beat-to-beat fluctuation of RR-interval by means of spectral analysis (Nyquist power of heart rate variability: nyHRV) after filtering out its fractal component. We observed nyHRV in healthy supine subjects and in patients with vasovagal symptoms. We challenged stabilization of blood pressure by upright posture (by means of a head-up tilt table test). Head-up position on the tilt table dramatically decreased nyHRV (0.128 ± 0.063 vs. 0.004 ± 0.002, p < 0.01) in healthy subjects (n = 12). Head-up position also decreased nyHRV in patients without vasovagal symptoms (n = 24; 0.220 ± 0.058 vs. 0.034 ± 0.015, p < 0.05), but not in patients with vasovagal symptoms during a head-up tilt table test (age and sex paired, 0.103 ± 0.041 vs. 0.122 ± 0.069, not significant). Heart rate variability includes a physiological non-harmonic non-fractal noisy fluctuation. This noisy fluctuation indicates low engagement of regulatory mechanisms because it disappears when the cardiovascular system is challenged (upright posture). It also indicates cardiovascular instability because it does not disappear in upright patients before vasovagal syncope, a transient failure of cardiovascular regulation.

Individual Time-Dependent Spectral Boundaries for Improved Accuracy in Time-Frequency Analysis of Heart Rate Variability

Heart rate variability (HRV) is a major noninvasive technique for evaluating the autonomic nervous system (ANS). Use of time-frequency approach to analyze HRV allows investigating the ANS behavior from the power integrals, as a function of time, in both steady-state and non steady-state. Power integrals are examined mainly in the low-frequency and the high-frequency bands. Traditionally, constant boundaries are chosen to determine the frequency bands of interest. However, these ranges are individual, and can be strongly affected by physiologic conditions (body position, breathing frequency). In order to determine the dynamic boundaries of the frequency bands more accurately, especially during autonomic challenges, we developed an algorithm for the detection of individual time-dependent spectral boundaries (ITSB). The ITSB was tested on recordings from a series of standard autonomic maneuvers with rest periods between them, and the response to stand was compared to the known physiological response. A major advantage of the ITSB is the ability to reliably define the mid-frequency range, which provides the potential to investigate the physiologic importance of this range.

Effects of RR segment duration on HRV spectrum estimation

Although patterns of heart rate variability (HRV) hold considerable promise for clarifying issues in clinical applications, the inappropriate quantification and interpretation of these patterns may obscure critical issues or relationships and may impede rather than foster the development of clinical applications. The duration of the RR interval series is not a matter of convenience but a fine balance between two important issues: acceptable variance and stationarity of the time series on one hand, and acceptable resolution of the spectral estimate and reduced spectral leakage on the other. Further, in the standard short-term HRV analysis, it has been observed that the previous studies in HRV spectral analysis use a wide range of RR interval segment duration for spectral estimation by Welch's algorithm. The standardization of RR interval segment duration is also important for comparisons among studies and is essential for within-study experimental contrasts. In the present study, a comparative analysis for RR interval segment durations has been made to propose an optimal RR interval segment duration. Firstly a simulated signal was analyzed with Hann window and zero padding for the segment lengths of 1024, 512, 256 and 128 samples resampled at 4 Hz with 50% overlapping. Again, the above procedure was applied to RR interval series and it was concluded that segment length of 256 samples with 50% overlapping provides a smoothed spectral estimate with clearly outlined peaks in low- and high-frequency bands. This easily understandable and interpretable spectral estimate leads to a better visual and automated analysis, which is not only desirable in basic physiology studies, but also a prerequisite for a widespread utilization of frequency domain techniques in clinical studies, where simplicity and effectiveness of information are of primary importance.

Bicoherence analysis of new cardiovascular spectral components observed in heart-transplant patients: statistical approach for bicoherence thresholding

Following heart transplant (HT), the patient's heart functions under complete cardiac denervation. As a result, the variability in physiologic signals is extremely reduced. We have previously reported that in addition to the typical spectral components (of very low amplitude), part of the HT patients (above 50%) demonstrated unexpected additional peaks in their heart rate and blood pressure spectra. These peaks may be a result of the development of compensatory mechanism induced by loss of parasympathetic control, or of increased importance of nonlinear control interactions. It is important to quantify these strange, unexpected very-high frequency (VHF) peaks, to understand their origin and their contribution to cardiac control in transplant patients. In this paper, we chose to examine these VHF peaks by applying the bicoherence approach. The reduced signal to noise ratio, occurring in these patients, results, however, in an extremely noisy bicoherence. We, therefore, developed several statistical tools in order to distinguish between "true" bicoherence peaks (reflecting true phase coupling) and spurious peaks. The outcome of these methods was an efficient and sensitive bicoherence thresholding procedure, able to identify most of the spurious peaks. Applying these tools to the bicoherence of cardiovascular signals which display VHF peaks, revealed several significant bicoherence peaks. Interestingly, these peaks consisted of two different types. The first type of VHF peaks simply reflects nonlinear cardiac-respiratory coupling, imposed by nonsinusoidal breathing. The second type, however, is clearly not induced by the respiratory system. We believe that these type-2 VHF peaks reflect the evolution of a new, yet unexplained, compensatory mechanism.