Traditional Heart Rate Variability Measures Research Articles

The inter-individual heart rate variability triangular index response to different exercise doses in adults with metabolic syndrome: a randomised trial

Background: Metabolic syndrome (MetS) significantly contributes to the burden of cardiovascular events (CVEs) and mortality worldwide. Non-invasive measures of cardiac autonomic function (CAF) in the form of heart rate variability (HRV) may be a promising tool to monitor disease progression and forecast future CVEs in people with MetS. The HRV triangular index (HRVI) offers superior predictive power of cardiovascular mortality risk in populations with existing cardiovascular complications compared to traditional HRV measures.

Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy.

Objective: Intractable epilepsy and uncontrolled seizures could affect cardiac function and the autonomic nerve system with a negative impact on children's growth. The aim of this study was to investigate the variability and complexity of cardiac autonomic function in pre-school children with pediatric intractable epilepsy (PIE).Methods: Twenty four-hour Holter electrocardiograms (ECGs) from 93 patients and 46 healthy control subjects aged 3–6 years were analyzed by the methods of traditional heart rate variability (HRV), multiscale entropy (MSE), and Kurths–Wessel symbolization entropy (KWSE). Receiver operating characteristic (ROC) curve analysis was used to estimate the overall discrimination ability. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) models were also analyzed.Results: Pre-school children with PIE had significantly lower HRV measurements than healthy controls in time (Mean_RR, SDRR, RMSSD, pNN50) and frequency (VLF, LF, HF, LF/HF, TP) domains. For the MSE analysis, area 1_5 in awake state was lower, and areas 6_15 and 6_20 in sleep state were higher in PIE with a significant statistical difference. KWSE in the PIE group was also inferior to that in healthy controls. In ROC curve analysis, pNN50 had the greatest discriminatory power for PIE. Based on both NRI and IDI models, the combination of MSE indices (wake: area1_5 and sleep: area6_20) and KWSE (m = 2, τ = 1, α = 0.16) with traditional HRV measures had greater discriminatory power than any of the single HRV measures.Significance: Impaired HRV and complexity were found in pre-school children with PIE. HRV, MSE, and KWSE could discriminate patients with PIE from subjects with normal cardiac complexity. These findings suggested that the MSE and KWSE methods may be helpful for assessing and understanding heart rate dynamics in younger children with epilepsy.

Heart rhythm complexity as predictors for the prognosis of end-stage renal disease patients undergoing hemodialysis

BackgroundHeart rhythm complexity, a measure of heart rate dynamics and a risk predictor in various clinical diseases, has not been systematically studied in patients with end-stage renal disease. The aim of this study is to investigate the heart rhythm complexity and its prognostic value for mortality in end-stage renal disease patients undergoing hemodialysis.MethodsTo assess heart rhythm complexity and conventional heart rate variability measures, 4-h continuous electrocardiography for a retrospective cohort of 202 ostensibly healthy control subjects and 51 hemodialysis patients with end-stage renal disease were analyzed. Heart rhythm complexity was quantified by the complexity index from the measurement of the multiscale entropy profile.ResultsDuring a follow-up of 13 months, 8 people died in the patient group. Values of either traditional heart rate variability measurements or complexity indices were found significantly lower in patients than those in healthy controls. In addition, the complexity indices (Area 1–5, Area 6–15 and Area 6–20) in the mortality group were significantly lower than those in the survival group, while there were no significant differences in traditional heart rate variability parameters between the two groups. In receiver operating characteristic curve analysis, Area 6–20 (AUC = 0.895, p < 0.001) showed the strongest predictive power between mortality and survival groups.ConclusionThe results suggest that heart rhythm complexity is impaired for patients with end-stage renal disease. Furthermore, the complexity index of heart rate variability quantified by multiscale entropy may be a powerful independent predictor of mortality in end-stage renal disease patients undergoing hemodialysis.

Measuring piglet castration pain using linear and non-linear measures of heart rate variability

AbstractThe purpose of this study was to evaluate whether linear and non-linear measures of heart rate variability (HRV) could be used as indicators of piglet castration pain. Thirty piglets were allocated to 1 of 4 treatments: i) sham castrated HRV (SHRV; n = 8); ii) surgical castrated HRV (CHRV; n = 7); iii) sham castrated blood collection (SBC; n = 7); or iv) surgical castrated blood collection (CBC; n = 8). Piglets in the SHRV and CHRV treatment groups underwent a 1-h HRV and postural behaviour evaluation on day-1, day 0 (castration treatment), day 1 and day 3 of the experimental procedure. Piglets in the SBC and CBC groups underwent blood collection for serum cortisol analysis at -0.5, 1, 2, 3, 24, 48 and 72 h relative to castration treatment. Castrated piglets (CHRV) exhibited greater low to high frequency ratio, lower sample entropy and greater percent determinism compared to SHRV piglets, indicating greater pain-related stress due to the surgical castration procedure. Serum cortisol was greater in CBC pigs at 1 h post-castration compared to SBC piglets. No effect of treatment was found for amount of time spent lying post-castration. In conclusion, surgically castrated pigs exhibited greater pain-related stress than their sham castrated counterparts. Additionally, non-linear HRV measures seem to complement traditional linear HRV measures and may be valuable for assessing pain-related stress in future studies investigating swine welfare.

Early identification of cardiac autonomic neuropathy using complexity analysis in children with type 1 diabetes.

In children and adolescents, there are significant limitations to detecting cardiac autonomic neuropathy (CAN), an important contributor to morbidity and mortality in adults with type 1 diabetes (T1D). The analysis of heart rate variability (HRV) is one method available to detect CAN. Some evidence shows traditional linear HRV measures detect abnormalities in youth with T1D. In this study, we aimed to assess whether non-linear complexity analysis of HRV would assist identification of CAN in youth with T1D and to assess contributory factors. We studied 19 youth with T1D and 17 healthy controls. Each had an electrocardiogram recorded continuously for 10 min, at a sampling frequency of 1000 Hz. Using Labview software and an algorithm for complexity analysis, along with standard time-domain and spectral analysis, recordings of the electrocardiogram were analysed to detect differences in HRV between groups. Youth with T1D had significantly higher sample entropy than controls (P = 0.015) suggesting increased complexity in HRV, but similar detrended fluctuation analysis (P = 0.68). Youth with T1D also had increased % high frequency power (P = 0.017) and reduced mid-frequency power (P = 0.019) on spectral analysis. There were no differences in heart rate or blood pressure responses to standing, or time-domain analysis of HRV. Within the T1D group, sample entropy correlated strongly with triglycerides (r = 0.76, P = 0.001) and detrended fluctuation analysis correlated strongly with serum potassium (r = -0.86, P < 0.001). Complexity analysis of HRV, particularly using sample entropy, may aid detection of CAN in youth with T1D.

Prediction of PAF Attacks using Time-Domain Measures of Heart Rate Variability

Paroxysmal atrial fibrillation (PAF) is the mainly encountered type of arrhythmia and there is no validated method to predict a PAF attack before it occurs. In this study, predicting the PAF event was aimed using time-domain heart rate variability (HRV) measures in k- nearest neighbor (k-nn) classifier. Traditional time-domain HRV measures were analyzed in every 5-minute segments from 49 normal subjects, 25 patients with PAF attack and 25 patients with no attack within 45 minutes. All features were investigated whether they showed statistically significance. Significant features were classified by k-nn for odd numbers of neighbors between 1 and 19. This setup was run with two different configurations as study 1 to discriminate patients with PAF attack from normals and patients with no attack, and study 2 to discriminate patients with PAF attack from patients with no attack. SDNN, RMSSD and pNN50 measures were found to show statistically significant differences with p less than 0.05 in segments of 0-5 min, 2.5-7.5 min and 5-10 min intervals only. The maximum classification accuracy was obtained in the time interval of 2.5-7.5 minutes with %79 for Study 1 and just before attack with %80 for Study 2 in the time interval of 0-5 minutes. Results showed that the prediction of PAF events was possible when the classification between normal subjects from PAF patients was accurate. PAF attack can be determined 2.5 minutes earlier by simple classifier algorithms.

Deceleration and acceleration capacities of heart rate in patients with drug-resistant epilepsy.

Epilepsy and seizures can have dramatic effects on cardiac function. The aim of the present study was to investigate deceleration capacity, acceleration capacity and their 24-h fluctuations of heart rate variability in patients with drug-resistant epilepsy. Deceleration capacity, acceleration capacity of heart rate and their 24-h dynamics derived from the phase rectified signal averaging method as well as traditional measures were analyzed in 39 patients with drug-resistant epilepsy and 33 healthy control subjects using 24-h electrocardiogram recordings. The discriminatory power of heart rate variability measures were validated by assessment of the area under the receiver operating characteristic curve. Net reclassification improvement and integrated discrimination improvement models were also estimated. Both deceleration capacity and absolute values of acceleration capacity were significantly lower in patients with drug-resistant epilepsy. The abnormal suppression of absolute deceleration capacity and acceleration capacity values were observed throughout the 24-h recording time (peaked at about 3 to 5 A.M.). Deceleration capacity had the greatest discriminatory power to differentiate the patients from the healthy controls. Moreover, in both net reclassification improvement and integrated discrimination improvement models, the combination of acceleration capacity or deceleration capacity with traditional heart rate variability measures has greater discriminatory power than any of the single heart rate variability features. Drug-resistant epilepsy was associated with a significant inhibition of vagal modulation of heart rate, which was more pronounced during the night than during the day. These findings indicate that phase rectified signal averaging method may serve as a complementary approach for characterizing and understanding the neuro-pathophysiology in epilepsy, and may provide a new clue to sudden unexpected death in epilepsy.

Residual heart rate variability measures can better differentiate patients with acute myocardial infarction from patients with patent coronary artery.

PurposeIt has been shown that the power spectral density (PSD) of heart rate variability (HRV) can be decomposed into a power-law function and a residual PSD (rPSD) with a more prominent high-frequency component than that in traditional PSD. This study investigated whether the residual HRV (rHRV) measures can better discriminate patients with acute myocardial infarction (AMI) from patients with patent coronary artery (PCA) than traditional HRV measures.Materials and methodsThe rHRV and HRV measures of 48 patients with AMI and 69 patients with PCA were compared.ResultsThe high-frequency power of rHRV spectrum was significantly enhanced while the low-frequency and very low-frequency powers of rHRV spectrum were significantly suppressed, as compared to their corresponding traditional HRV spectrum in both groups of patients. The normalized residual high-frequency power (nrHFP = residual high-frequency power/residual total power) was significantly greater than the corresponding normalized high-frequency power in both groups of patients. Between-groups comparison showed that the nrHFP in AMI patients was significantly smaller than that in PCA patients. Receiver operating characteristic curve analysis showed that the nrHFP or nrHFP + normalized residual very low-frequency power (residual very low-frequency power/rTP) had better discrimination capability than the corresponding HRV measures for predicting AMI.ConclusionsCompared with traditional HRV measures, the rHRV measures can slightly better differentiate AMI patients from PCA patients, especially the nrHFP or nrHFP + normalized residual very low-frequency power.

Fractal analysis of heart rate variability as a predictor of mortality: A systematic review and meta-analysis.

Previous studies have suggested benefits of applying fractal analysis to intervals between R waves in electrocardiography as an additional prognostic marker. The aim of this study was to investigate whether fractal analysis can provide an independent predictor of cardiac mortality or all-cause mortality. Prognostic cohort studies reporting fractal heart rate variability results from 24-h Holter monitor recordings were selected for comparison. Populations were subdivided into four groups-post-myocardial infarction, left ventricular dysfunction, other cardiac, and non-cardiac patients-and analysed using ANOVA, Forest plots (using pooled mean difference), and Funnel plots. The most significant mean differences were recorded in short-term fractal self-similarity (α1) (-0.17, 95% CI [-0.21, -0.13], p < 0.00001) and the traditional measure called standard deviation of NN intervals (SDNN) (-13.31, 95% CI [-18.89, -7.73], p < 0.00001) between the deceased and survivor groups. Fractal measures of long-term fractal self-similarity (α2), 1/f scaling (β), and traditional heart rate variability measures of high frequency to low frequency ratio show promise. This review indicated that fractal measure α1 and traditional measure SDNN could be potential predictors of mortality, but require further assessment to determine appropriate thresholds for clinical significance and additional targeted prognostic studies to properly define their applicability as prognostic markers. Therefore, clinicians should interpret fractal and traditional measures with caution since such measures have yet to be fully described as biomarkers for clinical application.

High Altitude Affects Nocturnal Non-linear Heart Rate Variability: PATCH-HA Study.

Background: High altitude (HA) exposure can lead to changes in resting heart rate variability (HRV), which may be linked to acute mountain sickness (AMS) development. Compared with traditional HRV measures, non-linear HRV appears to offer incremental and prognostic data, yet its utility and relationship to AMS have been barely examined at HA. This study sought to examine this relationship at terrestrial HA.Methods: Sixteen healthy British military servicemen were studied at baseline (800 m, first night) and over eight consecutive nights, at a sleeping altitude of up to 3600 m. A disposable cardiac patch monitor was used, to record the nocturnal cardiac inter-beat interval data, over 1 h (0200–0300 h), for offline HRV assessment. Non-linear HRV measures included Sample entropy (SampEn), the short (α1, 4–12 beats) and long-term (α2, 13–64 beats) detrend fluctuation analysis slope and the correlation dimension (D2). The maximal rating of perceived exertion (RPE), during daily exercise, was assessed using the Borg 6–20 RPE scale.Results: All subjects completed the HA exposure. The average age of included subjects was 31.4 ± 8.1 years. HA led to a significant fall in SpO2 and increase in heart rate, LLS and RPE. There were no significant changes in the ECG-derived respiratory rate or in any of the time domain measures of HRV during sleep. The only notable changes in frequency domain measures of HRV were an increase in LF and fall in HFnu power at the highest altitude. Conversely, SampEn, SD1/SD2 and D2 all fell, whereas α1 and α2 increased (p < 0.05). RPE inversely correlated with SD1/SD2 (r = -0.31; p = 0.002), SampEn (r = -0.22; p = 0.03), HFnu (r = -0.27; p = 0.007) and positively correlated with LF (r = 0.24; p = 0.02), LF/HF (r = 0.24; p = 0.02), α1 (r = 0.32; p = 0.002) and α2 (r = 0.21; p = 0.04). AMS occurred in 7/16 subjects (43.8%) and was very mild in 85.7% of cases. HRV failed to predict AMS.Conclusion: Non-linear HRV is more sensitive to the effects of HA than time and frequency domain indices. HA leads to a compensatory decrease in nocturnal HRV and complexity, which is influenced by the RPE measured at the end of the previous day. HRV failed to predict AMS development.

Preoperative Heart Rate Variability as Predictors of Vagus Nerve Stimulation Outcome in Patients with Drug-resistant Epilepsy

Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders0 had significantly lower preoperative CI including Area 1–5, Area 6–15 and Area 6–20 than those in the responders0 while those of the non-responders50 had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders50. In receiver operating characteristic (ROC) curve analysis, Area 6–20 and RMSSD had the greatest discriminatory power for the responders0 and non-responders0, responders50 and non-responders50, respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.

Novel measure of autonomic remodeling associated with sudden cardiac arrest in diabetes

Diabetes is independently associated with an increased risk of sudden cardiac arrest (SCA), with a need to identify novel methods for risk stratification. Diabetic patients can develop autonomic dysfunction that has been associated with an increased risk of ventricular arrhythmogenesis and manifests as reduced heart rate variability (HRV). However, previously published studies have not accounted for resting heart rate (HR), important from both pathophysiological and prognosticating standpoints. We sought to evaluate autonomic remodeling of the sinus node response in SCA and diabetes while accounting for HR. We performed a case-control study in SCA cases (age 35-59 years; 2002-2014) from the ongoing Oregon Sudden Unexpected Death Study (catchment population ∼1 million), and archived 12-lead electrocardiograms recorded prior to the SCA event werecompared with those of geographic controls. Short-term HRV was calculated from digitized 10-second electrocardiograms by using established methods. We analyzed 313 subjects (mean age 52.0 ± 5.5 years; 216 men, 69.0%) and compared 4 groups: 111 diabetic (49 cases, 62 controls) and 202 nondiabetic (80 cases, 122 controls) subjects. Analysis of covariance showed an absence of the expected interaction between HRV and HR (HRV-HR) in diabetic patients with SCA (regression slope -0.008; 95% confidence interval -0.023 to 0.0071; P = .26). This finding, unique to this population of diabetic patients with SCA, was not detected using traditional HRV measures. By incorporating resting HR in this analysis, we observed that this population of diabetic patients with SCA had loss of the expected HRV-HR relationship. This potentially novel noninvasive risk measurement warrants further investigation, especially at the level of the individual patient.

Is heart rate variability affected by distinct motor imagery strategies?

Although some studies have reported significant changes in autonomic responses according to the perspective-taking during motor imagery [first person perspective (1P) and third person perspective (3P)], investigations on how the strategies adopted to mentally simulate a given movement affect the heart rate variability (HRV) seem so far unexplored. Twenty healthy subjects mentally simulated the movement of middle-finger extension in 1P and 3P, while electrocardiogram was recorded. After each task, the level of easiness was self-reported. Motor imagery ability was also assessed through the revised version of Movement Imagery Questionnaire (MIQ-R) and a mental chronometry index. The traditional measures of HRV in the time- and frequency-domain were compared between 1P and 3P tasks by using Student's t-test for dependent samples. The MIQ-R results showed that subjects had the same facility to imagine movements in 1P or 3P. The mental chronometry index revealed a similar temporal course only between 1P and execution, while the 3P strategy had a shorter duration. Additionally, the subjective report was similar between the experimental tasks. Regarding the HRV measures, the low frequency component, in log-transformed unit, was significantly higher (p=0.017) in 1P than 3P, suggesting a higher activity of the sympathetic system during 1P. This log-transformed HRV parameter seems to be more sensitive than normalized values for the assessment of the motor imagery ability, together with questionnaires, scales and mental chronometry.

Executive Cognitive Functioning and Cardiovascular Autonomic Regulation in a Population-Based Sample of Working Adults.

Objective: Executive cognitive functioning is essential in private and working life and is sensitive to stress and aging. Cardiovascular (CV) health factors are related to cognitive decline and dementia, but there is relatively few studies of the role of CV autonomic regulation, a key component in stress responses and risk factor for cardiovascular disease (CVD), and executive processes. An emerging pattern of results from previous studies suggest that different executive processes may be differentially associated with CV autonomic regulation. The aim was thus to study the associations between multiple measures of CV autonomic regulation and measures of different executive cognitive processes.Method: Participants were 119 healthy working adults (79% women), from the Swedish Longitudinal Occupational Survey of Health. Electrocardiogram was sampled for analysis of heart rate variability (HRV) measures, including the Standard Deviation of NN, here heart beats (SDNN), root of the mean squares of successive differences (RMSSD), high frequency (HF) power band from spectral analyses, and QT variability index (QTVI), a measure of myocardial repolarization patterns. Executive cognitive functioning was measured by seven neuropsychological tests. The relationships between CV autonomic regulation measures and executive cognitive measures were tested with bivariate and partial correlational analyses, controlling for demographic variables, and mental health symptoms.Results: Higher SDNN and RMSSD and lower QTVI were significantly associated with better performance on cognitive tests tapping inhibition, updating, shifting, and psychomotor speed. After adjustments for demographic factors however (age being the greatest confounder), only QTVI was clearly associated with these executive tests. No such associations were seen for working memory capacity.Conclusion: Poorer CV autonomic regulation in terms of lower SDNN and RMSSD and higher QTVI was associated with poorer executive cognitive functioning in terms of inhibition, shifting, updating, and speed in healthy working adults. Age could largely explain the associations between the executive measures and SDNN and RMSSD, while associations with QTVI remained. QTVI may be a useful measure of autonomic regulation and promising as an early indicator of risk among otherwise healthy adults, compared to traditional HRV measures, as associations between QTVI and executive functioning was not affected by age.

Comparison of Baseline Heart Rate Variability in Stable Ischemic Heart Disease Patients with and without Stroke in Long-Term Observation

Decreased heart rate variability (HRV) has predictive value in postinfarction as well as in ischemic stroke patients. However, it is unknown if ischemic heart disease (IHD) patients who are at high risk of stroke have different HRV profile. The goal of this study was to compare baseline HRV (traditional and novel indices) in stable IHD patients with and without stroke in long-term observation. A total of 139 consecutive patients with stable IHD scheduled for coronary angiography were enrolled. Five-minute electrocardiogram readings were taken. Traditional and novel HRV measures were calculated. After 70.06 ± 4.297 months of follow-up, baseline HRV indices in patients who had had a stroke were compared with indices in patients without the aforementioned cerebrovascular event. During follow-up, 6 patients developed stroke. Compared to patients without such a cerebrovascular event, these patients with stroke had lower values for the following HRV indices: de Hann long-term irregularity (30,521 ± 32,767 versus 46,678 ± 25,328; P < .05), Yeh interval index (.0207 ± .0208 versus .0326 ± .0157; P < .05), Organ BAND (3.0563 ± 3.328 versus 4.515 ± 2.276; P < .05), Dalton standard deviation (SD) (17,887 ± 17,636 versus 29,859 ± 16,478; P < .05), Zugaib short-term variability (.004 ± .00416 versus .00622 ± .00418; P < .05), Zugaib long-term variability (.0161 ± .0151 versus .0247 ± .0115; P < .05), standard deviation of all NN intervals (8,954 ± 8,812 versus 16,724 ± 11,594; P < .05), total power (2,616 ± 4,855 versus 4,678 ± 4,653; P < .05), w2 (.71 ± .338 versus 1.719 ± 1.08; P < .05), w3 (1.399 ± .924 versus 2.552 ± 1.609; P < .05), and w4 (1.367 ± 1.705 versus 2.824 ± 2.027; P < .05). No significant differences in other analyzed indices were observed. Patients with IHD and stroke in long-term observation have different baseline profiles of HRV indices. Further investigations are needed to assess the usefulness of HRV analysis in stroke risk assessment.

Decomposition of Heart Rate Variability Spectrum into a Power-Law Function and a Residual Spectrum.

The power spectral density (PSD) of heart rate variability (HRV) contains a power-law relationship that can be obtained by plotting the logarithm of PSD against the logarithm of frequency. The PSD of HRV can be decomposed mathematically into a power-law function and a residual HRV (rHRV) spectrum. Almost all rHRV measures are significantly smaller than their corresponding HRV measures except the normalized high-frequency power (nrHFP). The power-law function can be characterized by the slope and Y-intercept of linear regression. Almost all HRV measures except the normalized low-frequency power have significant correlations with the Y-intercept, while almost all rHRV measures except the total power [residual total power (rTP)] do not. Though some rHRV measures still correlate significantly with the age of the subjects, the rTP, high-frequency power (rHFP), nrHFP, and low-/high-frequency power ratio (rLHR) do not. In conclusion, the clinical significances of rHRV measures might be different from those of traditional HRV measures. The Y-intercept might be a better HRV measure for clinical use because it is independent of almost all rHRV measures. The rTP, rHFP, nrHFP, and rLHR might be more suitable for the study of age-independent autonomic nervous modulation of the subjects.

Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction.

The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV. In the Nordic ICD pilot study, patients with an acute MI were screened with 2D echocardiography and 24-hour Holter recordings. The study was designed to assess the power of several HRV measures to predict mortality. Dyx was tested in a subset of 206 consecutive Danish patients with analysable Holter recordings. After a median follow-up of 8.5 years 70 patients had died. Of all traditional and multipole HRV parameters, reduced Dyx was the most powerful predictor of all-cause mortality (HR 2.4; CI 1.5 to 3.8; P < 0.001). After adjustment for known risk markers, such as age, diabetes, ejection fraction, previous MI and hypertension, Dyx remained an independent predictor of mortality (P = 0.02). Reduced Dyx also predicted cardiovascular death (P < 0.01) and sudden cardiovascular death (P = 0.05). In Kaplan-Meier analysis, Dyx significantly predicted mortality in patients both with and without impaired left ventricular systolic function (P < 0.0001). The new nonlinear HRV measure Dyx is a promising independent predictor of mortality in a long-term follow-up study of patients surviving a MI, irrespectively of left ventricular systolic function.

Effects of breathing patterns and light exercise on linear and nonlinear heart rate variability.

Despite their use in cardiac risk stratification, the physiological meaning of nonlinear heart rate variability (HRV) measures is not well understood. The aim of this study was to elucidate effects of breathing frequency, tidal volume, and light exercise on nonlinear HRV and to determine associations with traditional HRV indices. R-R intervals, blood pressure, minute ventilation, breathing frequency, and respiratory gas concentrations were measured in 24 healthy male volunteers during 7 conditions: voluntary breathing at rest, and metronome guided breathing (0.1, 0.2 and 0.4 Hz) during rest, and cycling, respectively. The effect of physical load was significant for heart rate (HR; p < 0.001) and traditional HRV indices SDNN, RMSSD, lnLFP, and lnHFP (p < 0.01 for all). It approached significance for sample entropy (SampEn) and correlation dimension (D2) (p < 0.1 for both), while HRV detrended fluctuation analysis (DFA) measures DFAα1 and DFAα2 were not affected by load condition. Breathing did not affect HR but affected all traditional HRV measures. D2 was not affected by breathing; DFAα1 was moderately affected by breathing; and DFAα2, approximate entropy (ApEn), and SampEn were strongly affected by breathing. DFAα1 was strongly increased, whereas DFAα2, ApEn, and SampEn were decreased by slow breathing. No interaction effect of load and breathing pattern was evident. Correlations to traditional HRV indices were modest (r from -0.14 to -0.67, p < 0.05 to <0.01). In conclusion, while light exercise does not significantly affect short-time HRV nonlinear indices, respiratory activity has to be considered as a potential contributor at rest and during light dynamic exercise.

Heart rate variability density analysis (Dyx) for identification of appropriate implantable cardioverter defibrillator recipients among elderly patients with acute myocardial infarction and left ventricular systolic dysfunction.

Dyx is a new heart rate variability (HRV) density analysis specifically designed to identify patients at high risk for malignant ventricular arrhythmias. The aim of this study was to test if Dyx can improve risk stratification for malignant ventricular tachyarrhythmias and to test if the previously identified cut-off can be reproduced. This study included 248 patients from the CARISMA study with ejection fraction ≤40% after an acute myocardial infarction and an analysable 24 h Holter recording. All patients received an implantable cardiac monitor, which was used to diagnose the primary endpoint of near-fatal or fatal ventricular tachyarrhythmias likely preventable by an implantable cardioverter defibrillator (ICD), during a period of 2 years. A Dyx ≤ 1.96 was considered abnormal. The secondary endpoint was cardiovascular death. At enrolment 59 patients (24%) had a Dyx ≤ 1.96 and 20 experienced a primary endpoint. A Dyx ≤ 1.96 was associated with a significantly increased risk for malignant arrhythmias [hazards ratio (HR) = 4.36 (1.81-10.52), P = 0.001] and cardiovascular death [HR = 3.47 (1.38-8.74), P = 0.008]. Compared with important clinical risk parameters (age >70 years and QRS > 120 ms), Dyx ≤ 1.96 significantly added predictive value (P = 0.0066). Dyx was a better predictor of ventricular tachyarrhythmias than the traditional measures of HRV and heart rate turbulence, particularly in the elderly. Dyx might be a useful tool for better selection of ICD candidates in the elderly population, since a normal Dyx in this group was associated with a very low risk for malignant ventricular arrhythmias.ClinicalTrials.gov Identifier NCT00145119.

Sample Entropy and Traditional Measures of Heart Rate Dynamics Reveal Different Modes of Cardiovascular Control During Low Intensity Exercise

Nonlinear parameters of heart rate variability (HRV) have proven their prognostic value in clinical settings, but their physiological background is not very well established. We assessed the effects of low intensity isometric (ISO) and dynamic (DYN) exercise of the lower limbs on heart rate matched intensity on traditional and entropy measures of HRV. Due to changes of afferent feedback under DYN and ISO a distinct autonomic response, mirrored by HRV measures, was hypothesized. Five-minute inter-beat interval measurements of 43 healthy males (26.0 ± 3.1 years) were performed during rest, DYN and ISO in a randomized order. Blood pressures and rate pressure product were higher during ISO vs. DYN (p &lt; 0.001). HRV indicators SDNN as well as low and high frequency power were significantly higher during ISO (p &lt; 0.001 for all measures). Compared to DYN, sample entropy (SampEn) was lower during ISO (p &lt; 0.001). Concluding, contraction mode itself is a significant modulator of the autonomic cardiovascular response to exercise. Compared to DYN, ISO evokes a stronger blood pressure response and an enhanced interplay between both autonomic branches. Non-linear HRV measures indicate a more regular behavior under ISO. Results support the view of the reciprocal antagonism being only one of many modes of autonomic heart rate control. Under different conditions; the identical “end product” heart rate might be achieved by other modes such as sympathovagal co-activation as well.