Autonomic responses to Dohsa therapy and progressive muscle relaxation: a case-based HRV study with student-athletes

As reports show cardiovascular (CV) risks in first-degree relatives (FDR) of type2 diabetics, and autonomic imbalance predisposing to CV risks, in the present study we have assessed the contribution of sympathovagal imbalance (SVI) to CV risks in these subjects. Body mass index (BMI), waist-to-hip ratio (WHR), basal heart rate (BHR), blood pressure (BP), rate pressure product (RPP), and spectral indices of heart rate variability (HRV) were reordered and analyzed in FDR of type2 diabetics (study group, n=293) and in subjects with no family history of diabetes (control group, n=405). The ratio of low-frequency (LF) to high-frequency (HF) power of HRV (LF-HF), a sensitive marker of SVI, was significantly increased (P<0.001) in the study group compared with the control group. The SVI in the study group was due to concomitant sympathetic activation (increased LF) and vagal inhibition (decreased HF). In the study group, the LF-HF ratio was significantly correlated with BMI, WHR, BHR, BP and RPP. Multiple regression analysis showed an independent contribution of LF-HF to hypertension status (P=0.000), and bivariate logistic regression showed significant prediction (odds ratio 2.16, confidence interval 1.130-5.115) of LF-HF to increased RPP, the marker of CV risk, in the study group. Sympathovagal imbalance in the form of increased sympathetic and decreased parasympathetic activity is present in FDR of type2 diabetics. Increased resting heart rate, elevated hypertension status, decreased HRV and increased RPP in these subjects make them vulnerable to CV risks. SVI in these subjects contributes to CV risks independent of the degree of adiposity.

Fractal analysis and time- and frequency-domain measures of heart rate variability as predictors of mortality in patients with heart failure

We investigated whether TNFα‐coupled mitogen‐activated protein kinases (MAPKs) in central neurons modulate the early hemodynamic responses evoked by endotoxemia in rats. Changes in blood pressure (BP), heart rate (HR), and HR variability (HRV) caused by i.v. lipopolysaccharide (LPS, 10 mg/kg) were assessed in absence and presence of pharmacologic inhibitors of TNFα, inducible nitric oxide synthase (iNOS), MAPKERK1/2, MAPKp38, or MAPKJNK. Compared with saline, LPS caused significant falls in BP and increases in HR that appeared 30 min post treatment and continued for the following 60 min. The time (standard deviation of beat‐to‐beat intervals, SDNN, and the root mean square of successive beat‐to‐beat differences in R‐R intervals, rMSSD) and frequency domain indices (total power and spectral bands of low and high‐frequency) of HRV were all reduced by LPS. The inhibition of TNFα (pentoxifylline) or iNOS (aminoguanidine) abolished the hemodynamic and HRV effects of LPS. Intracisternal (i.c.) injection of ODQ (guanylate cyclase inhibitor), wortmannin (PI3K inhibitor), SP600125 (MAPKJNK inhibitor) mitigated the LPS‐evoked reductions in BP and HR, but failed to affect the associated decreases in HRV. MAPKp38 inhibition by i.c. SB203580 produced exactly the opposite effects. The reduction in BP or HRV caused by LPS remained unaltered after i.c. PD98059, suggesting no role for MAPKERK1/2 in the LPS responses. Together, the data suggest that central TNFα/iNOS/GC/PI3K pathways linked to MAPKp38 and MAPKJNK are pivotal for provoking the reductions in BP and HRV, respectively, seen during endotoxic shock.

Blood Pressure, Heart Rate Variability, and Renal Function in Nonsmoker and Smoker Hypertensive Patients.

Heart rate (HR) variability (HRV) during ambulatory recordings may be affected by individual differences in daily physical activity (PA). However, the influence of various levels of PA on different measures of HRV is not exactly known. We examined the association between simultaneously measured HRV and objective PA data obtained with an accelerometer during waking hours among 45 healthy adults. Bouts of PA were identified from minute-by-minute accelerometer data as metabolic equivalent (METs) values and calculated as mean METs for 30 min. HRV was analyzed concurrently. Within-individual correlation analyses and sign tests were performed to study the relationships between various HRV indexes and PA. The mean PA time was 15:44 +/- 1:01 h, and the mean MET was 1.91 +/- 0.14. HR and sample entropy, but not the other measures of HRV, had a significant relationship with PA, as shown by both correlation analyses (r = 0.64, P = 0.021, and r = -0.55, P = 0.022, respectively) and sign tests (P < 0.0001 for both). Beat-to-beat R-R interval fluctuation expressed as SD1 also demonstrated a significant relation to PA according to the sign test (P = 0.037) and a trend of association according to the correlation analysis (r = -0.40, P = 0.129). The complexity measure of HRV, in addition to average HR and the short-term index of HRV (SD1), is significantly influenced by the level of PA during ambulatory conditions. Long-term HRV indexes remained relatively stable at various activity levels, making them the most robust indexes for the assessment of cardiac autonomic function during free-running ambulatory conditions.

BackgroundVarious relaxation procedures have been proposed to reduce fatigue in multiple sclerosis (MS). However, it is unknown, which type of relaxation has the largest effect on fatigue reduction and on autonomic nervous system (ANS) activity.ObjectiveWe aimed to compare two biofeedback-supported relaxation exercises: a deep breathing (DB) exercise and progressive muscle relaxation (PMR), which may ameliorate MS fatigue and alter ANS activity.MethodsWe performed a single-blind randomized clinical trial, introducing MS patients (n = 34) to the DB or PMR exercise. We first tested cardiovagal integrity, reflected by changes in heart rate variability (HRV) in response to DB. Participants then performed a fatigue-inducing vigilance task, followed by the DB or PMR. State fatigue was recorded consecutively at baseline, after the vigilance task, and after the relaxation exercise, along with HRV reflecting ANS activity.ResultsOnly patients assigned to the PMR group experienced a significant drop in fatigue, whereas both relaxation exercises changed ANS activity. MS patients showed the expected autonomic response during the cardiovagal reflex test. The vigilance task elevated short-term feelings of fatigue and significantly reduced HRV parameters of parasympathetic activity. Trait fatigue was negatively correlated with HRV during the second half of the vigilance task.ConclusionPMR alleviates short-term feelings of fatigue in persons with MS. The vigilance task in combination with HRV measurements may be helpful for evaluating relaxation procedures as a treatment of fatigue. Hereby, future studies should ensure longer and more frequent relaxation exercises and focus on patients with weak to moderate fatigue.Trial registrationTrial Registry: DRKS00024358.

To the Editor: We have read the article by Barthel et al1 describing the first prospective trial to determine the predictive value of heart rate turbulence (HRT) in patients after acute myocardial infarction. In previous studies, the ability of HRT to predict risk was only determined retrospectively.2 We would like to critically discuss here the uniqueness of the emerging risk factor, HRT, in comparison with other parameters. Interestingly, Barthel et al1 found that HRT was the strongest ECG-based risk predictor. This conclusion is surprising for 2 reasons, as follows. First, in an editorial comment3 on the original article by Schmidt et al,2 it was noted that the positive predictive value of HRT is only moderately higher than other ECG risk parameters, and it was suggested that …

Objectives: Heart rate variability (HRV) provides insight into autonomic modulation of the heart rate. HRV indices – classified as time domain, frequency domain and non-linear indices – are computed using software tools. While the calculation of time domain indices is relatively straightforward, there exists heterogeneity in the methodology of spectral analysis of HRV parameters across different platforms. We compared HRV indices derived from electrocardiogram (ECG) data recorded in healthy adults using Kubios ™ (‘K’), LabChart ™ (‘L’) and Nevrokard ™ (‘N’) software solutions. Materials and Methods: A single observer analysed HRV indices from 5-min Lead II ECG epochs using ‘K’, ‘L’ and ‘N’ software. Time domain and frequency domain indices were computed and compared. Bias between the software was assessed using Bland–Altman analysis by choosing ‘N’ as the reference method. Mean bias and limits of agreement were compared. Results: Data of 53 healthy adults (40 males, 13 females; mean age = 29.89 ± 6.94 years) were analysed. Time domain indices, while exhibiting statistically significant differences, had slight differences between ‘K’, ‘L’ and ‘N’. Median frequency domain indices derived from ‘K’, ‘L’ and ‘N’ demonstrated statistically significant differences, especially low frequency (LF), high frequency (HF) and normalised powers of LF and HF. Furthermore, they demonstrated reasonable bias between tools. Conclusion: HRV indices, especially frequency domain indices, may be affected by the analytical methodology adopted by the software tool. While we cannot establish superiority of one software over another, we recommend detailed documentation of analytical approach of HRV data in scientific literature. In addition, comparison of HRV indices using different analytical tools merits a cautious approach.

Heart rate variability, but not heart rate, is associated with handgrip strength and mortality in older Africans at very low cardiovascular risk: A population-based study

Interplay between heart rate and its variability: a prognostic game

Real-world data from wearable devices has the potential to understand mental health status in everyday life. We aimed to investigate the feasibility of estimating mental health status using a wrist-worn wearable device (Fitbit Sense) that measures movement using a 3D accelerometer and optical pulse photoplethysmography (PPG). Participants were 110 patients with mental illnesses from different diagnostic groups. The study was undertaken between 1 October 2020 and 31 March 2021. Participants wore a Fitbit Sense on their wrist and also completed the State-Trait Anxiety Inventory (STAI), Positive and Negative Affect Schedule (PANAS), and EuroQol 5 dimensions 5-level (EQ-5D-5L) during the study period. To determine heart rate (HR) variability (HRV), we calculated the sdnn (standard deviation of the normal-to-normal interval), coefficient of variation of R-R intervals, and mean HR separately for each sleep stage and the daytime. The association between mental health status and HR and HRV was analyzed. The following significant correlations were found in the wake after sleep onset stage within 3 days of mental health status assessment: sdnn, HR and STAI scores, HR and PANAS scores, HR and EQ-5D-5L scores. The association between mental health status and HR and HRV was stronger the closer the temporal distance between mental health status assessment and HR measurement. A wrist-worn wearable device that measures PPG signals was feasible for use with patients with mental illness. Resting state HR and HRV could be used as an objective assessment of mental health status within a few days of measurement.

Relation of High Heart Rate Variability to Healthy Longevity

Even at rest, blood pressure and heart fluctuate continuously around their mean values. Considerable interest has recently focused on the assessment of spontaneous in fluctuations in heart rate and blood pressure, i.e., heart rate and blood pressure variability, using time or frequency domain indexes. Heart rate variability has been extensively studied in cardiovascular disease and has emerged as a valuable parameter for detecting abnormalities in autonomic cardiovascular control, evaluating the prognosis and assessing the impact of drug therapy on the autonomic nervous system in patients with myocardial infarction, congestive heart failure or a heart transplant. In contrast, until the recent development of noninvasive methods for continuous blood pressure recording, blood pressure variability received little attention, and this parameter remains to be evaluated in cardiovascular disease.

The aim of this study was to investigate the autonomic drive to the heart in cardiac transplant patients (CTP) using heart rate (HR) and HR variability (HRV) analysis during non-rapid eye movement (NREM)-rapid eye movement (REM) sleep cycles, in particular during arousal associated with the emergence from slow wave sleep (SWS). In healthy subjects, this arousal is characterized by a pronounced HR surge, and HRV is lower during SWS than during the subsequent "active" sleep stage 2 and REM sleep. The participants were 24 adults, 14 CTP (men, n = 11; women, n = 3; mean age, 62.2 +/- 2.2 years; time after transplantation, 4-14 years) and 10 control subjects (men, n = 7; women, n = 3; mean age, 61.0 +/- 1.8 years). The subjects underwent polygraphic sleep, cardiac, and respiratory recordings during an experimental night. HR was measured during the arousal. HRV was estimated from the R-R intervals in 5-minute stationary segments preceding and following arousal, ie, during SWS and active sleep stage 2 from the first 2 complete NREM-REM sleep cycles. In controls, HR increased during arousal associated with the emergence from SWS during the 2 sleep cycles (P < .05). Sleep-stage-dependent increases of all HRV indexes were observed in the 2 sleep cycles. Concerning CTP, 5 of them displayed a smaller HR increase at arousal, whereas 9 other patients had no HR variation. This distinction between the 2 groups of CTP was confirmed by HRV analysis. The patients with HR reactivity to arousal presented significant sleep-stage-dependent increases in global HRV and sympathetic HRV indexes, whereas the nonreactive group was characterized by an inability of HRV to change with sleep-stage alternation. Sympathetic HRV indexes were significantly higher in the reactive patients than in nonreactive patients, but high frequency power reflecting parasympathetic activity did not differ. However, the absolute HRV indexes were greatly decreased in both groups of patients compared to controls. HR reactivity during arousal associated with the emergence from SWS, corroborated by HRV surrounding arousal, may suggest a partial improvement of the sympathetic drive to the heart in some CTP, with no indication of increased parasympathetic activity. Other signs of reinnervation have to be identified to validate this hypothesis.

The aim of this study was to determine the minimal sampling rate (SR) required for blood pressure (BP) waveform recordings to accurately determine BP and heart rate (HR) variability indices and baroreceptor reflex sensitivity in rats and mice. We also determined if an 8-bit (versus 12-bit) analog-to-digital converter (ADC) resolution is sufficient to accurately determine these hemodynamic parameters and if spline interpolation to 1000 Hz of BP waveforms sampled at lower SRs can improve accuracy. BP and ECG recordings (1000 Hz SR, 12-bit ADC resolution) from two strains of rats and BP recordings (1000 Hz SR, 12-bit ADC resolution) from two strains of mice were mathematically converted to lower SRs and/or 8-bit ADC resolution. Time-domain HR variability and frequency-domain HR and BP variability indices and baroreflex sensitivity (using the sequence technique) were determined and the results obtained from the original files were compared to the results obtained from the mathematically altered files. Our results demonstrate that an ADC resolution of 8 bit is not sufficient to determine HR and BP variability in rats and mice and baroreceptor reflex sensitivity in mice. Average values for systolic, mean and diastolic BP and HR can be accurately derived from BP waveforms recorded at a minimal SR of 200 Hz in rats and mice. Spline interpolation of BP waveforms to 1000 Hz prior to extracting derived parameters reduces this minimal SR to 50 Hz in rats but still requires 200 Hz in mice. Frequency-domain BP variability (very low and low frequency spectral powers) can be estimated accurately at a minimum SR of 100 Hz in rats and mice and spline interpolation of BP waveforms to 1000 Hz reduces this minimal SR to 50 Hz in rats but does not reduce the minimal SR in mice. Time- and frequency-domain HR variability parameters require at least a SR of 1000 Hz in rats and mice. Spline interpolation of BP waveforms to 1000 Hz reduces this minimal SR to 100 Hz in rats and to 200 Hz in mice. Estimation of baroreflex sensitivity using the sequence technique requires a SR of at least 1000 Hz in rats and mice. Spline interpolation of BP waveforms to 1000 Hz reduces this minimal SR to 100 Hz in rats but does not reduce the minimum SR in mice. Finally, our results indicate that HR time series derived from BP waveforms are not totally consistent with HR time series derived from the ECG in rats. In conclusion, accurate assessment of HR variability and baroreflex sensitivity from BP waveform recordings requires a SR of at least 1000 Hz in rats and mice. If lower SRs are used for BP waveform recordings, a cubic spline interpolation to 1000 Hz (or an even higher SR) prior to extracting derived parameters significantly improves accuracy.