Circadian rhythm of spectral indices of heart rate variability in healthy subjects

Does psychological treatment of major depression reduce cardiac risk biomarkers? An exploratory randomized controlled trial

BACKGROUND

Depression is associated with an increased risk for cardiovascular disease (CVD). Biological cardiac risk factors are already elevated in depressed patients without existing CVD. The purpose of this exploratory trial was to examine whether treating Major Depression (MD) with cognitive behavioral therapy (CBT) is associated with improvements in cardiac risk biomarkers and whether depressive symptom severity at baseline moderates treatment effects.

METHODS

Eighty antidepressant-free patients with MD were randomly assigned to CBT or waiting list (WL). Biological outcomes included long-term recordings (24-h, daytime, nighttime) of heart rate, heart rate variability (HRV), and blood pressure, as well as inflammatory markers such as C-reactive protein (CRP), interleukin (IL)-6, and tumor necrosis factor (TNF)-α. A sample of 40 age- and sex-matched non-clinical controls was also involved to verify biological alterations in MD at study entry.

RESULTS

Compared to WL, CBT was associated with a significant increase in overall HRV, as indexed by the 24-h and daytime HRV triangular index, as well as trend improvements in 24-h low-frequency HRV and daytime systolic blood pressure. Self-rated depressive symptom severity moderated (or tended to moderate) improvements in CBT for 24-h and daytime heart rate and several indices of HRV (especially daytime measures). Inflammatory treatment effects were not observed.

CONCLUSIONS

CBT increased overall HRV in patients with MD. Initially more depressed patients showed the most pronounced cardiovascular improvements through CBT. These exploratory findings may provide new insights into the biological effects of psychological treatment against depression and must be confirmed through future research.

Effect of low frequency sound vibration on acute stress response in university students-Pilot randomized controlled trial

Background

Low frequency sound (LFS, combined with music listening) is applied by practitioners in vibroacoustic therapy who report a positive effect of this intervention on acute stress response. However, there is a lack of research on this topic and studies with mainly objective measurements are scarce.

Materials and methods

In this pilot double-blinded Randomized Controlled Trial we used a multimodal approach to measurement of acute stress response in 54 international university students attending a university summer school in Olomouc, the Czech Republic who were individually randomized into a group receiving LFS vibration and a control group. In both groups, the acute stress response was measured by heart rate variability (HRV), visual analogue scales (VAS) for stress and muscle relaxation.

Results

Differences were found in pre-test post-test measures, however, between groups differences occurred only for HRV, with statistically significant improvement in the experimental group (parameter LF/HF and pNN50).

Conclusion

Vibroacoustic therapy has the potential to contribute to the stress management of university students. Further research is needed to explore the effect of LFS on stress response, especially when applied without additional music listening.

Presleep Heart-Rate Variability Biofeedback Improves Mood and Sleep Quality in Chinese Winter Olympic Bobsleigh Athletes

PURPOSE

To evaluate the effectiveness of heart-rate variability (HRV) biofeedback in improving autonomic function, mood, and sleep in elite bobsleigh athletes.

METHODS

Eight Chinese Winter Olympic bobsleigh athletes (age: 24 [2] y, body mass: 89 [15] kg, and height: 184 [5] cm) completed a randomized crossover study with and without HRV biofeedback before a single night's sleep. HRV biofeedback was provided 35 minutes prior to bedtime in the experimental condition. The assessment of HRV took place 45 and 10 minutes before bedtime. The Profile of Mood States questionnaire was completed 50 and 15 minutes prior to bedtime. Sleep duration and quality were measured through an air-mattress sleep-monitoring system.

RESULTS

Sleep efficiency (P = .020; F = 7.831; CI, 0.008 to 0.072) and the percentage of deep sleep duration increased (P = .013; F = 10.875; CI, 0.006 to 0.035), while the percentage of light sleep decreased (P = .034; F = 6.893; CI, -0.038 to -0.002). Presleep HRV biofeedback increased parasympathetic and decreased sympathetic activity. Mood states of anger (P = .006, F = 7.573), panic (P = .031, F = 4.288), tension (P = .011, F = 6.284), depression (P = .010, F = 6.016), fatigue (P = .000, F = 16.901), and total mood disturbance (P = .001, F = 11.225) were reduced before sleep.

CONCLUSION

Presleep HRV biofeedback improved some measures of autonomic function, mood, and sleep quality in Chinese Olympic bobsleigh athletes. Presleep HRV biofeedback provides a practical strategy that may help reduce sleep disturbances during periods of training and competition.

Neurobehavioral Symptoms and Heart Rate Variability: Feasibility of Remote Collection Using Mobile Health Technology

OBJECTIVES

To determine the covariance of heart rate variability (HRV) and self-reported neurobehavioral symptoms after traumatic brain injury (TBI) collected using mobile health (mHealth) technology.

SETTING

Community.

PARTICIPANTS

Adults with lifetime history of TBI (n = 52) and adults with no history of brain injury (n = 12).

DESIGN

Two-week prospective ecological momentary assessment study.

MAIN MEASURES

Behavioral Assessment Screening Tool (BASTmHealth) subscales (Negative Affect, Fatigue, Executive Dysfunction, Substance Abuse, and Impulsivity) measured frequency of neurobehavioral symptoms via a RedCap link sent by text message. Resting HRV (root mean square of successive R-R interval differences) was measured for 5 minutes every morning upon waking using a commercially available heart rate monitor (Polar H10, paired with Elite HRV app).

RESULTS

Data for n = 48 (n = 38 with TBI; n = 10 without TBI) participants were included in covariance analyses, with average cross-correlation coefficients (0-day lag) varying greatly across participants. We found that the presence and direction of the relationship between HRV and neurobehavioral symptoms varied from person to person. Cross-correlation coefficients r ≤ -0.30, observed in 27.1% to 29.2% of participants for Negative Affect, Executive Dysfunction, and Fatigue, 22.9% of participants for Impulsivity, and only 10.4% of participants for Substance Abuse, supported our hypothesis that lower HRV would covary with more frequent symptoms. However, we also found 2.0% to 20.8% of participants had positive cross-correlations (r ≥ 0.30) across all subscales, indicating that higher HRV may sometimes correlate with more neurobehavioral symptoms, and 54.2% to 87.5% had no significant cross-correlations.

CONCLUSIONS

It is generally feasible for community-dwelling adults with and without TBI to use a commercially available wearable device to capture daily HRV measures and to complete a short, electronic self-reported neurobehavioral symptom measure for a 2-week period. The covariance of HRV and neurobehavioral symptoms over time suggests that HRV could be used as a relevant physiological biomarker of neurobehavioral symptoms, though how it would be interpreted and used in practice would vary on a person-by-person and symptom domain basis and requires further study.

Acute Cardiovascular Effects of Hydrotreated Vegetable Oil Exhaust

Ambient air pollution is recognized as a key risk factor for cardiovascular morbidity and mortality contributing to the global disease burden. The use of renewable diesel fuels, such as hydrotreated vegetable oil (HVO), have increased in recent years and its impact on human health are not completely known. The present study investigated changes in cardiovascular tone in response to exposure to diluted HVO exhaust. The study participants, 19 healthy volunteers, were exposed in a chamber on four separate occasions for 3 h and in a randomized order to: (1) HVO exhaust from a wheel loader without exhaust aftertreatment, (2) HVO exhaust from a wheel loader with an aftertreatment system, (3) clean air enriched with dry NaCl salt particles, and (4) clean air. Synchronized electrocardiogram (ECG) and photoplethysmogram (PPG) signals were recorded throughout the exposure sessions. Pulse decomposition analysis (PDA) was applied to characterize PPG pulse morphology, and heart rate variability (HRV) indexes as well as pulse transit time (PTT) indexes were computed. Relative changes of PDA features, HRV features and PTT features at 1, 2, and 3 h after onset of the exposure was obtained for each participant and exposure session. The PDA index A₁₃, reflecting vascular compliance, increased significantly in both HVO exposure sessions but not in the clean air or NaCl exposure sessions. However, the individual variation was large and the differences between exposure sessions were not statistically significant.

Does the Heart Fall Asleep?—Diurnal Variations in Heart Rate Variability in Patients with Disorders of Consciousness

The current study investigated heart rate (HR) and heart rate variability (HRV) across day and night in patients with disorders of consciousness (DOC). We recorded 24-h electrocardiography in 26 patients with DOC (i.e., unresponsive wakefulness syndrome (UWS; n = 16) and (exit) minimally conscious state ((E)MCS; n = 10)). To examine diurnal variations, HR and HRV indices in the time, frequency, and entropy domains were computed for periods of clear day- (forenoon: 8 a.m.–2 p.m.; afternoon: 2 p.m.–8 p.m.) and nighttime (11 p.m.–5 a.m.). The results indicate that patients’ interbeat intervals (IBIs) were larger during the night than during the day, indicating HR slowing. The patients in UWS showed larger IBIs compared to the patients in (E)MCS, and the patients with non-traumatic brain injury showed lower HRV entropy than the patients with traumatic brain injury. Additionally, higher HRV entropy was associated with higher EEG entropy during the night. Thus, cardiac activity varies with a diurnal pattern in patients with DOC and can differentiate between patients’ diagnoses and etiologies. Moreover, the interaction of heart and brain appears to follow a diurnal rhythm. Thus, HR and HRV seem to mirror the integrity of brain functioning and, consequently, might serve as supplementary measures for improving the validity of assessments in patients with DOC.

ECG and Heart Rate Variability in Sleep-Related Breathing Disorders

Here we discuss the current perspectives of comprehensive heart rate variability (HRV) analysis in electrocardiogram (ECG) signals as a non-invasive and reliable measure to assess autonomic function in sleep-related breathing disorders (SDB). It is a tool of increasing interest as different facets of HRV can be implemented to screen and diagnose SDB, monitor treatment efficacy, and prognose adverse cardiovascular outcomes in patients with sleep apnea. In this context, the technical aspects, pathophysiological features, and clinical applications of HRV are discussed to explore its usefulness in better understanding SDB.

Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy

Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices. Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model. Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1). Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

Cardiac circadian rhythms in time and space: The future is in 4D

The circadian clock synchronizes the body into 24-h cycles, thereby anticipating variations in tissue-specific diurnal tasks, such as response to increased cardiac metabolic demand during the active period of the day. As a result, blood pressure, heart rate, cardiac output, and occurrence of fatal cardiovascular events fluctuate in a diurnal manner. The heart contains different cell types that make up and reside in an environment of biochemical, mechanical, and topographical signaling. Cardiac architecture is essential for proper heart development as well as for maintenance of cell homeostasis and tissue repair. In this review, we describe the possibilities of studying circadian rhythmicity in the heart by using advanced in vitro systems that mimic the native cardiac 3D microenvironment which can be tuned in time and space. Harnessing the knowledge that originates from those in vitro models could significantly improve innovative cardiac modeling and regenerative strategies.

Heart Rate Variability Responses to a Training Cycle in Female Youth Rowers

Heart rate variability (HRV) is a reputable estimate of cardiac autonomic function used across multiple athletic populations to document the cardiac autonomic responses to sport demands. However, there is a knowledge gap of HRV responses in female youth rowers. Thus, the purpose of this study was to measure HRV weekly, over a 15-week training period, covering pre-season and up to competition in youth female rowers, in order to understand the physiological response to long-term training and discern how fluctuations in HRV may relate to performance in this population. Measures of heart rate and heart rate variability were recorded before training each Friday over the monitoring period in seven athletes. Analysis of heart rate variability focused on time domain indices, the standard deviation of all normal to normal R-R wave intervals, and the root mean square of successive differences as markers of cardiac parasympathetic modulation. Training load was quantified by multiplying the rating of perceived exertion of the weeks training and training duration. A decrease was identified in cardiac parasympathetic modulation as the season progressed (Effect Size (Cohen's d) = -0.34 to -0.8, weeks 6 and 11-15), despite no significant relationship between training load and heart rate variability. Factors outside of training may further compound the reduction in heart rate variability, with further monitoring of external stressors (e.g., school) in adolescent athletes.

The Efficacy of Heart Rate Variability in Tracking Travel and Training Stress in Youth Female Rowers: A Preliminary Study

Egan-Shuttler, JD, Edmonds, R, and Ives, SJ. The efficacy of heart rate variability in tracking travel and training stress in youth female rowers: A preliminary study. J Strength Cond Res 34(11): 3293-3300, 2020-Heart rate variability (HRV) is a reliable indicator of cardiac parasympathetic activity and has been used in athletic populations to measure training adaptations. To date, there is limited research showing whether HRV is practical in youth female athletes and rowers during short periods of overload training. The purpose of this study was to evaluate the practicality of HRV in documenting training responses during a period of overload training in youth female rowers. Time-domain (SD of N-N intervals, SDNN; root mean square of successive differences, RMSSD) and nonlinear (SD1) indices of HRV were recorded during baseline training, daily during the 6-day training camp, and 1 week after the camp in 5 athletes from an elite, high-school, rowing team. Training duration and rate of perceived exertion were recorded to document training load. Training load during the camp was 76% above the athlete's normal workload (2,258 ± 459 vs. 1,280 ± 356 arbitrary units (a.u.)). Using progressive statistics, cardiac vagal activity (RMSSD and SD1) was very likely reduced during each day of the camp when compared with baseline training, although returned to baseline within a week of the training camp. Interestingly, SDNN was reduced throughout the training camp and remained reduced up to a week after the training camp (78% likely; effect size = -0.32). These insights add value to HRV's use in youth sport and provides coaches with an easy, cost-effective means to monitor the physiological response to training, allowing fine-tuning of training, potentially enhancing performance.

Aircraft Pilots Workload Analysis: Heart Rate Variability Objective Measures and NASA-Task Load Index Subjective Evaluation

Workload and fatigue of aircraft pilots represent an argument of great interest in the framework of human factors and a pivotal point to be considered in aviation safety. 75% of aircraft accidents are related to human errors that, in most cases, are due to high level of mental workload and fatigue. There exist several subjective or objective metrics to quantify the pilots’ workload level, with both linear and nonlinear relationships reported in the literature. The main research objective of the present work is to analyze the relationships between objective and subjective workload measurements by looking for a correlation between metrics belonging to the subjective and biometric rating methods. More particularly, the Heart Rate Variability (HRV) is used for the objective analysis, whereas the NASA-TLX questionnaire is the tool chosen for the subjective evaluation of the workload. Two different flight scenarios were considered for the studies: the take-off phase with the initial climb and the final approach phase with the landing. A Maneuver Error Index (MEI) is also introduced to evaluate the pilot flight performance according to mission requirements. Both qualitative and quantitative correlation analyses were performed among the MEI, subjective and objective measurements. Monotonic relationships were found within the HRV indexes, and a nonlinear relationship is proposed among NASA-TLX and HRV indexes. These findings suggest that the relationship between workload, biometric data, and performance indexes are characterized by intricate patterns of nonlinear relationships.

Reliability of short-term measurements of heart rate variability: Findings from a longitudinal study

Research on heart rate variability (HRV) received increasing attention. This study analysed the reliability of the most common HRV parameters for baseline measurements. 103 healthy students (83 women, M = 21.72 ± 3.31 years) participated in five short-term HRV sessions, each including supine, sitting, and standing positions, respectively, spanning a time interval of eleven months. Relative reliability was evaluated by intraclass correlation coefficients, and absolute reliability by standard errors of measurement, smallest real differences, and 95 % limits of random variation. No systematic mean differences between measurements emerged. Intraclass correlation coefficients were quite low (supine: .49-.64, sitting: .40-.57, standing: .35-.56). Absolute reliability indicators revealed pronounced variations between test and retest. Influences of posture and time between measurements on reliability were small and unsystematic. We conclude that such high levels of within-subjects variability in HRV measurements (a) hamper the detection of changes over time, and (b) should be considered carefully in future analyses.

Effectiveness of an 8-Week Aerobic Exercise Program on Autonomic Function in People Living with HIV Taking Anti-Retroviral Therapy: A Pilot Randomized Controlled Trial

This study assessed the effectiveness of an 8-week aerobic exercise program on heart rate variability (HRV) in people living with HIV taking antiretroviral therapy. Twenty-six participants were randomly assigned to a control group or an aerobic exercise group. Resting HRV was measured for 5 min in supine position using an electrocardiogram. Estimated maximal oxygen uptake (VO_2max) was assessed through a treadmill 6-min walk test. The training program consisted of aerobic exercise thrice per week at 65%-75% of heart rate max for 45 min per session. Repeated measures ANOVA was used to test for differences between groups, and Spearman's rho was used to assess for the correlation between HRV measures and estimated VO_2max. There was no significant group by time interactions for any of the HRV indices. However, the standard deviation of normal-to-normal (NN) R-R intervals increased significantly in the aerobic exercise group (pre: 46.97 ± 32.70 ms vs. post: 59.49 ± 37.20 ms, p = .045). There was a strong correlation between the VO_2max and the standard deviation of NN intervals (SDNN) (r = 0.617; p = .002). There was a moderate correlation between VO_2max and the square root of the mean squared differences of successive normal-to-normal intervals (rMSSD) (r = 0.424; p = .049), the low frequency power (r = 0.506; p = .016), and the standard deviation of differences between successive differences of normal-to-normal intervals (SDSD) (r = 0.424; p = .049). While differences in HRV were not observed between groups, our data suggest that overall autonomic function can improve across time with aerobic exercise, and these changes are associated with greater levels of VO_2max. These results advocate the importance of improvements in HRV given their association with lower risk of cardiovascular disease and mortality.

A Systematic Review and Meta-Analysis of Within-Person Changes in Cardiac Vagal Activity across the Menstrual Cycle: Implications for Female Health and Future Studies

Interest in cardiac vagal activity (CVA; e.g., parasympathetically-mediated heart rate variability) as a biomarker of physical and mental health has increased exponentially in recent years. However, the understanding of sources of within-person change (i.e., intra-individual variance) in CVA is lagging behind. This systematic review and meta-analysis summarizes and quantifies current empirical evidence of within-person changes in measures of CVA across the menstrual cycle in naturally-cycling premenopausal females. We conducted an extensive literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement in five databases to identify observational studies with repeated measures of CVA in at least two menstrual cycle phases. A broad meta-analysis (n_studies = 37; n_individuals = 1,004) revealed a significant CVA decrease from the follicular to luteal phase (d = −0.39, 95% CI (−0.67, −0.11)). Furthermore, 21 studies allowed for finer-grained comparisons between each of two cycle phases (menstrual, mid-to-late follicular, ovulatory, early-to-mid luteal, and premenstrual). Significant decreases in CVA were observed from the menstrual to premenstrual (n_studies = 5; n_individuals = 200; d = −1.17, 95% CI (−2.18, −0.17)) and from the mid-to-late follicular to premenstrual phases (n_studies = 8; n_individuals = 280; d = −1.32, 95% CI (−2.35, −0.29)). In conclusion, meta-analyses indicate the presence of CVA fluctuations across the menstrual cycle. Future studies involving CVA should control for cycle phase. Recommendations for covarying or selecting cycle phase are provided.

Cardiac autonomic activity during sleep in high-altitude resident children compared with lowland residents

Study Objectives

We aimed to characterize heart-rate variability (HRV) during sleep in Andean children native to high altitude (HA) compared with age, gender, and genetic ancestry-similar low-altitude (LA) children. We hypothesized that the hypoxic burden of sleep at HA could induce variation in HRV. As children have otherwise healthy cardiovascular systems, such alterations could provide early markers of later cardiovascular disease.

Methods

Twenty-six LA (14F) and 18 HA (8F) children underwent a single night of attended polysomnography. Sleep parameters and HRV indices were measured. Linear mixed models were used to assess HRV differences across sleep stage and altitude group.

Results

All children showed marked fluctuations in HRV parameters across sleep stages, with higher vagal activity during nonrapid eye movement sleep and greater variability of the heart rate during rapid eye movement (REM). Moreover, HA children showed higher very low-frequency HRV in REM sleep and, after adjusting for heart rate, higher low-to-high frequency ratio in REM sleep compared with children living at lower altitude.

Conclusions

We confirmed previous findings of a stage-dependent modulation of HRV in Andean children living at both HA and LA. Moreover, we showed subtle alteration of HRV in sleep in HA children, with intriguing differences in the very low-frequency domain during REM sleep. Whether these differences are the results of an adaptation to high-altitude living, or an indirect effect of differences in oxyhemoglobin saturation remains unclear, and further research is required to address these questions.

Circadian Rhythms and Measures of CNS/Autonomic Interaction

The physiological role and relevance of the mechanisms sustaining circadian rhythms have been acknowledged. Abnormalities of the circadian and/or sleep-wakefulness cycles can result in major metabolic disorders or behavioral/professional inadequacies and stand as independent risk factors for metabolic, psychiatric, and cerebrovascular disorders and early markers of disease. Neuroimaging and clinical evidence have documented functional interactions between autonomic (ANS) and CNS structures that are described by a concept model (Central Autonomic Network) based on the brain-heart two-way interplay. The circadian rhythms of autonomic function, ANS-mediated processes, and ANS/CNS interaction appear to be sources of variability adding to a variety of environmental factors, and may become crucial when considering the ANS major role in internal environment constancy and adaptation that are fundamental to homeostasis. The CNS/ANS interaction has not yet obtained full attention and systematic investigation remains overdue.

Measures of CNS-Autonomic Interaction and Responsiveness in Disorder of Consciousness

Neuroimaging studies have demonstrated functional interactions between autonomic (ANS) and brain (CNS) structures involved in higher brain functions, including attention and conscious processes. These interactions have been described by the Central Autonomic Network (CAN), a concept model based on the brain-heart two-way integrated interaction. Heart rate variability (HRV) measures proved reliable as non-invasive descriptors of the ANS-CNS function setup and are thought to reflect higher brain functions. Autonomic function, ANS-mediated responsiveness and the ANS-CNS interaction qualify as possible independent indicators for clinical functional assessment and prognosis in Disorders of Consciousness (DoC). HRV has proved helpful to investigate residual responsiveness in DoC and predict clinical recovery. Variability due to internal (e.g., homeostatic and circadian processes) and environmental factors remains a key independent variable and systematic research with this regard is warranted. The interest in bidirectional ANS-CNS interactions in a variety of physiopathological conditions is growing, however, these interactions have not been extensively investigated in DoC. In this brief review we illustrate the potentiality of brain-heart investigation by means of HRV analysis in assessing patients with DoC. The authors' opinion is that this easy, inexpensive and non-invasive approach may provide useful information in the clinical assessment of this challenging patient population.

Spectral Analysis of Heart Rate Variability: Time Window Matters

Spectral analysis of heart rate variability (HRV) is a valuable tool for the assessment of cardiovascular autonomic function. Fast Fourier transform and autoregressive based spectral analysis are two most commonly used approaches for HRV analysis, while new techniques such as trigonometric regressive spectral (TRS) and wavelet transform have been developed. Short-term (on ECG of several minutes) and long-term (typically on ECG of 1–24 h) HRV analyses have different advantages and disadvantages. This article reviews the characteristics of spectral HRV studies using different lengths of time windows. Short-term HRV analysis is a convenient method for the estimation of autonomic status, and can track dynamic changes of cardiac autonomic function within minutes. Long-term HRV analysis is a stable tool for assessing autonomic function, describe the autonomic function change over hours or even longer time spans, and can reliably predict prognosis. The choice of appropriate time window is essential for research of autonomic function using spectral HRV analysis.

Changes in heart rate variability of patients with delirium in intensive care unit

Delirium is an important syndrome in intensive care unit (ICU) patients, however, its characteristics are still unclear. Many evidences showed that this syndrome can be related to the autonomic instability. In this study, we aimed to investigate the possible alterations of autonomic nervous system (ANS) in delirium patients in ICU. Electrocardiography (ECG) of every ICU patient was measured during routine daily ICU care, and the data were gathered to evaluate the heart rate variability (HRV). HRV of total 60 patients were analyzed in time, frequency and non-linear domains. As a result, we found that heart rates of delirium patients were more variable and irregular than non-delirium patients. These findings may facilitate early detection and prevention of delirium in ICU.

Validity of spectral analysis based on heart rate variability from 1-minute or less ECG recordings

BACKGROUND

To broaden the utility of heart rate variability (HRV) in clinical medicine and mass screening, results based on shorter electrocardiogram (ECG) recordings require validation with those based on standard 5-minute recordings. We investigated the association between HRV variables obtained from 5-minute ECGs with those obtained from ECGs shorter than 5 minutes.

METHODS

Twenty-two participants aged 20-69 years underwent 5-minute resting ECG recordings in the supine position with natural breathing. Spectral analysis using MemCalc method was performed to calculate high-frequency (HF, which required at least 10 seconds) and low-frequency (LF, which required at least 30 seconds) components. Participants were not strictly preconditioned as in previous experimental studies in order to simulate a setting similar to that of a general health checkup. Associations of each variable between the 5-minute ECG recordings and those for shorter recordings were examined by Pearson's correlation coefficients and Bland-Altman plots.

RESULTS

HF and LF components were log-transformed based on their distributions. Correlation coefficients between 5-minute data and shorter recordings in the supine position with natural breathing ranged from 0.80 to 0.91 (HF by 10-second recording, 0.80; LF by 30-second recording, 0.83, respectively). Bland-Altman plots showed that gaps between the values from both methods slightly increased as the HF and LF component values increased.

CONCLUSIONS

Although slight proportional errors were possible, values from standard 5-minute and shorter recordings in the supine position were strongly correlated. Our findings suggest that shorter ECG data without strict preconditioning can be reliably used for spectral analysis.

Fluctuations in heart rate variability of health care workers during four consecutive extended work shifts and recovery during rest and sleep

The aim of this study was to investigate fluctuations in heart rate variability (HRV), which reflect autonomic nervous system (ANS) function and potential psychological and physical strain, among 24 health care workers during work and sleep during four consecutive extended work shifts. Data included 24/36/12 h of HRV measurements, two logbooks, and a questionnaire. A cross-shift/cross-week design was applied. HRV was measured during work, leisure time, and sleep. The HRV data included time-domain [mean RR, SD of normal to normal R-R intervals (SDNN), and root mean square of the successive differences (RMSSD)] and frequency-domain [low frequency (LF)/high frequency (HF) ratio] parameters. HRV parameters revealed significant differences among work, leisure time, and sleep. Mean RR, RMSSD, and SDNN values were lower and the LF/HF ratio was higher on the first versus last day of the work period; however, the differences were most prominent in the morning hours. The results indicate higher levels of cardiovascular stress on the first versus fourth day of the working period, and measurements at night indicate a satisfactory recovery from the extended shifts.

Grip on health: A complex systems approach to transform health care

This article addresses the urgent need for a transition in health care to deal with the increasing prevalence of chronic diseases and associated rapid rise of health care costs. Chronic diseases evolve and are predominantly related to lifestyle and environment. A shift is needed from a reductionist repair mode of thinking, toward a more integrated biopsychosocial way of thinking about health. The aim of this article is to discuss the opportunities that complexity science offer for transforming health care toward optimal treatment and prevention of chronic lifestyle diseases. Health and health care is discussed from a complexity science perspective. The benefits of concepts developed in the field of complexity science for stimulating transitions in health care are explored. Complexity science supports the elucidation of the essence of health processes. It provides a unique perspective on health with a focus on the relationships within networks of dynamically interacting factors and the emergence of health out of the organization of those relationships. Novel types of complexity science-based intervention strategies are being developed. The first application in practice is the integrated obesity treatment program currently piloted in the Netherlands, focusing on health awareness and healing relationships. Complexity science offers various theories and methods to capture the path toward unhealthy and healthy states, facilitating the development of a dynamic integrated biopsychosocial perspective on health. This perspective offers unique insights into health processes for patients and citizens. In addition, dynamic models driven by personal data provide simulations of health processes and the ability to detect transitions between health states. Such models are essential for aligning and reconnecting the many institutions and disciplines involved in the health care sector and evolve toward an integrated health care ecosystem.

Spectro-Temporal Electrocardiogram Analysis for Noise-Robust Heart Rate and Heart Rate Variability Measurement

The last few years has seen a proliferation of wearable electrocardiogram (ECG) devices in the market with applications in fitness tracking, patient monitoring, athletic performance assessment, stress and fatigue detection, and biometrics, to name a few. The majority of these applications rely on the computation of the heart rate (HR) and the so-called heart rate variability (HRV) index via time-, frequency-, or non-linear-domain approaches. Wearable/portable devices, however, are highly susceptible to artifacts, particularly those resultant from movement. These artifacts can hamper HR/HRV measurement, thus pose a serious threat to cardiac monitoring applications. While current solutions rely on ECG enhancement as a pre-processing step prior to HR/HRV calculation, existing artifact removal algorithms still perform poorly under extremely noisy scenarios. To overcome this limitation, we take an alternate approach and propose the use of a spectro-temporal ECG signal representation that we show separates cardiac components from artifacts. More specifically, by quantifying the rate-of-change of ECG spectral components over time, we show that heart rate estimates can be reliably obtained even in extremely noisy signals, thus bypassing the need for ECG enhancement. With such HR measurements in hands, we then propose a new noise-robust HRV index termed MD-HRV (modulation-domain HRV) computed as the standard deviation of the obtained HR values. Experiments with synthetic ECG signals corrupted at various different signal-to-noise levels, as well as recorded noisy signals show the proposed measure outperforming several HRV benchmark parameters computed post wavelet-based enhancement. These findings suggest that the proposed HR measures and derived MD-HRV metric are well-suited for ambulant cardiac monitoring applications, particularly those involving intense movement (e.g., elite athletic training).

Modulation of Cardiac Autonomic Function by Fingolimod Initiation and Predictors for Fingolimod Induced Bradycardia in Patients with Multiple Sclerosis

Objective: It is well-known that initiation of fingolimod induces a transient decrease of heart rate. However, the underlying cardiac autonomic regulation is poorly understood. We aimed to investigate the changes of autonomic activity caused by the first dose of fingolimod using a long-term multiple trigonometric spectral analysis for the first time. In addition, we sought to use the continuous Holter ECG recording to find predictors for fingolimod induced bradycardia.

Methods: Seventy-eight patients with relapsing-remitting multiple sclerosis (RRMS) were included. As a part of the START study (NCT01585298), continuous electrocardiogram was recorded before fingolimod initiation, and until no <6 h post medication. Time domain and frequency domain heart rate variability (HRV) parameters were computed hourly to assess cardiac autonomic regulation. A long-term multiple trigonometric regressive spectral (MTRS) analysis was applied on successive 1-h-length electrocardiogram recordings. Decision tree analysis was used to find predictors for bradycardia following fingolimod initiation.

Results: Most of the HRV parameters representing parasympathetic activities began to increase since the second hour after fingolimod administration. These changes of autonomic regulations were in accordance with the decline of heart rate. Baseline heart rate was highly correlated with nadir heart rate, and was the only significant predicting factor for fingolimod induced bradycardia among various demographic, clinical and cardiovascular variables in the decision tree analysis.

Conclusions: The first dose application of fingolimod enhances the cardiac parasympathetic activity during the first 6 h post medication, which might be the underlying autonomic mechanism of reduced heart rate. Baseline heart rate is a powerful predictor for bradycardia caused by fingolimod.

The end effector of circadian heart rate variation: the sinoatrial node pacemaker cell

Cardiovascular function is regulated by the rhythmicity of circadian, infradian and ultradian clocks. Specific time scales of different cell types drive their functions: circadian gene regulation at hours scale, activation-inactivation cycles of ion channels at millisecond scales, the heart's beating rate at hundreds of millisecond scales, and low frequency autonomic signaling at cycles of tens of seconds. Heart rate and rhythm are modulated by a hierarchical clock system: autonomic signaling from the brain releases neurotransmitters from the vagus and sympathetic nerves to the heart’s pacemaker cells and activate receptors on the cell. These receptors activating ultradian clock functions embedded within pacemaker cells include sarcoplasmic reticulum rhythmic spontaneous Ca²⁺ cycling, rhythmic ion channel current activation and inactivation, and rhythmic oscillatory mitochondria ATP production. Here we summarize the evidence that intrinsic pacemaker cell mechanisms are the end effector of the hierarchical brain-heart circadian clock system. [BMB Reports 2015; 48(12): 677-684]

Cardiac autonomic activity has a circadian rhythm in summer but not in winter in non-lactating pregnant dairy cows

This investigation was conducted to examine circadian and seasonal rhythms of heart rate and heart rate variability (HRV) by means of hour-by-hour recordings over 24h in a large population of non-lactating Holstein-Friesian pregnant cows [N=56, summer (June-July); N=61, winter (November-December)]. Data were collected during a 5-day period from each animal. Besides parameters of cardiac autonomic function [the high-frequency (HF) component of HRV and the ratio between the low-frequency (LF) and the HF components (LF/HF ratio)], the RR triangular index and Lmax were calculated. A clear circadian profile was observed for every parameter in summer. Heart rate elevated gradually with the course of the day from 7:00 to 17:00 o'clock and then slightly decreased from 18:00 to 6:00. Sympathovagal balance shifted towards sympathetic dominance during the daytime (increased LF/HF ratio), whereas parasympathetic activity was predominant during the night (increased HF). Lmax reflected a chaotic behavior of heart rate fluctuations during the afternoon in summer. Decreased values of RR triangular index indicated a sensitive period for cows between 14:00 and 16:00 o'clock in summer. During winter, except for the RR triangular (RRtri) index reflecting a high overall variability in R-R intervals between 12:00 and 23:00 o'clock, heart rate and HRV showed no periodicity over the 24-h period. The results suggest an impaired cardiac autonomic function during daytime in summer. HF, Lmax and RRtri index showed seasonal differences for both daytime and nighttime. Heart rate was higher in summer than in winter during the daytime, whereas the LF/HF ratio was higher in winter during the nighttime. Circadian and seasonal rhythms of cardiovascular function are presumably related to the differing temperature, and animal activity associated with summer and winter. As all of the investigated parameters are commonly used in bovine HRV research, these findings have practical implications for behavioral, physiological and welfare studies on dairy cattle.

The circadian pattern of cardiac autonomic modulation and obesity in adolescents

PURPOSE

To assess the impact of obesity and population attributes on the circadian pattern of cardiac autonomic modulation (CAM) in a population-based sample of adolescents.

METHODS

We used data from 421 adolescents who completed the follow-up exam in the Penn State Children Cohort study. CAM was assessed by heart rate variability (HRV) analysis of beat-to-beat, normal R-R intervals from a 24-hour ECG, on a 30-minute basis. The HRV indices included frequency-domain (HF, LF, and LF/HF ratio) and time-domain (SDNN, RMSSD, and HR) variables. Nonlinear mixed-effect models were used to calculate a cosine periodic curve, each having three parameters quantifying its circadian period: M (mean levels of the HRV variables), Â (amplitude of the oscillation), and θ (the time of the highest oscillation).

RESULTS

The mean (SD) age was 16.9 (2.2) years, with 54 % male and 77 % white. The mean BMI percentile was 66, with 16 % obese (BMI percentile ≥ 95). Overall, HF (a marker of parasympathetic modulation) gradually increased from the late afternoon, reached peak amplitude around 3 a.m., and then decreased throughout the daytime until late afternoon. In contrast, obesity had adverse effects on all circadian parameters. The age, sex and race showed varying differences on the CAM circadian parameters. The adjusted means (95 %Cls) of M, Â, and θ for HF were 5.99 (5.79-6.19), 0.77 (0.66-0.89), 3:15 (2:15-4:15) a.m., and 6.21 (6.13-6.29), 0.66 (0.61-0.70), 2:45 (2:30-3:15) a.m. for obese and non-obese subjects, respectively.

CONCLUSION

The circadian pattern of CAM can be quantified by the three cosine parameters. Obesity is associated with lower HRV even in young individuals like children/adolescents.

Childhood obesity and autonomic dysfunction: risk for cardiac morbidity and mortality

OPINION STATEMENT

The epidemic of childhood obesity is becoming a major predictor for risk of cardiovascular diseases (CVD) and mortality during adulthood. Alterations in the morphology of the heart due to obesity could be a predictor for the dysfunction of cardiac autonomic modulation (CAM). A number of epidemiologic studies have evaluated the effect of obesity and CAM in children, finding that obesity impaired the balance of CAM toward a sympathetic overflow and reduced parasympathetic modulation, a significant predictor of CVD morbidity and mortality in adults. Lifestyle modifications, for example long-term exercise programs, have been shown to improve CAM in the obese. This review discusses the recent evidence on childhood and adolescent obesity and its impact on CAM, as well as how early lifestyle changes could help improve CAM, which may in turn reduce the burden of CVD in adults.

Influences of age, gender, and circadian rhythm on deceleration capacity in subjects without evident heart diseases

Background

Deceleration capacity (DC) is a newly found predictor of mortality after myocardial infarction. Age‐, gender‐, and circadian rhythm–related differences in DC may limit its predictive value, which should be considered in clinical settings.

Methods

DC, average heart rate, and HRV parameters, including 24 hours, awaking state (15:00–20:00) and sleeping mode (00:00–05:00) strips from 24 hours Holter recordings in 636 subjects without heart diseases were examined. Heart rate variability was analyzed in time domains (standard deviation of all normal‐to‐normal intervals [SDNN], normal‐to‐normal RR intervals in all 5‐minute segments [SDANN], and root mean square successive difference [RMSSD]).

Results

The DC, SDNN, SDANN, RMSSD, and heart rate decreased with age. Deceleration capacity was significantly lower in patients greater than 50 years of age. The largest decrease of SDNN, SDANN, and RMSSD occurred in patients 30–39 years of age. The values of SDNN, SDANN, and DC of women were lower than that of men in the young and middle‐aged groups, but age‐related decrease of DC in men was greater than that in women. Heart rate of women was significantly higher than that of men in younger subjects, especially in a sleeping mode. There were higher values of DC and RMSSD during sleeping than that during a waking state.

Conclusions

The age, gender, and circadian rhythm may be useful when evaluating cardiac autonomic function and need to be considered when evaluating DC and HRV in clinical and scientific researches.

Heart rate and heart rate variability modification in chronic insomnia patients

Chronic insomnia is highly prevalent in the general population, provoking personal distress and increased risk for psychiatric and medical disorders. Autonomic hyper-arousal could be a pathogenic mechanism of chronic primary insomnia. The aim of this study was to investigate autonomic activity in patients with chronic primary insomnia by means of heart rate variability (HRV) analysis. Eighty-five consecutive patients affected by chronic primary insomnia were enrolled (38 men and 47 women; mean age: 53.2 ± 13.6). Patients were compared with a control group composed of 55 healthy participants matched for age and gender (23 men and 32 women; mean age: 54.2 ± 13.9). Patients underwent an insomnia study protocol that included subjective sleep evaluation, psychometric measures, and home-based polysomnography with evaluation of HRV in wake before sleep, in all sleep stages, and in wake after final awakening. Patients showed modifications of heart rate and HRV parameters, consistent with increased sympathetic activity, while awake before sleep and during Stage-2 non-REM sleep. No significant differences between insomniacs and controls could be detected during slow-wave sleep, REM sleep, and post-sleep wake. These results are consistent with the hypothesis that autonomic hyper-arousal is a major pathogenic mechanism in primary insomnia, and confirm that this condition is associated with an increased cardiovascular risk.

Human circadian phase estimation from signals collected in ambulatory conditions using an autoregressive model

Phase estimation of the human circadian rhythm is a topic that has been explored using various modeling approaches. The current models range from physiological to mathematical, all attempting to estimate the circadian phase from different physiological or behavioral signals. Here, we have focused on estimation of the circadian phase from unobtrusively collected signals in ambulatory conditions using a statistically trained autoregressive moving average with exogenous inputs (ARMAX) model. Special attention has been given to the evaluation of heart rate interbeat intervals (RR intervals) as a potential circadian phase predictor. Prediction models were trained using all possible combinations of RR intervals, activity levels, and light exposures, each collected over a period of 24 hours. The signals were measured without any behavioral constraints, aside from the collection of saliva in the evening to determine melatonin concentration, which was measured in dim-light conditions. The model was trained and evaluated using 2 completely independent datasets, with 11 and 19 participants, respectively. The output was compared to the gold standard of circadian phase: dim-light melatonin onset (DLMO). The most accurate model that we found made use of RR intervals and light and was able to yield phase estimates with a prediction error of 2 ± 39 minutes (mean ± SD) from the DLMO reference value.

Autonomic regulation, physical activity and perceived stress in subjects with musculoskeletal pain: 24-hour ambulatory monitoring

The aim of the study was to investigate autonomic nervous system regulation, physical activity (PA) and perceived stress and energy during daily activities in subjects with chronic muscle pain in the neck-shoulders (trapezius myalgia) (n=23) and symptom-free controls (n=22). Subjects underwent 24-hour objective ambulatory monitoring of heart rate variability (HRV) and PA, and reported their perceived stress and energy in a diary. Standard HRV measures were extracted in time and frequency domains. The volume and pattern of different types of activities were quantified in terms of intensity and duration of walking, and time spent sitting, standing and lying during the 24-hour measurement. Results showed shortened inter-beat-intervals (higher heart rate) and reduced HRV in the pain group, most pronounced during sleep (p<0.05). For overall PA, the pain group showed increased lying time, compared to controls (p<0.05). A different activity pattern was found in the pain group, with reduced leisure time PA and increased PA during morning hours, in comparison with controls (p<0.05). Both groups demonstrated low levels of perceived stress, whereas reduced energy was observed in the pain group (p<0.05). In conclusion, monitoring of 24-hour HRV demonstrated diminished HRV among persons with chronic neck-shoulder pain. This reflected aberration in autonomic regulation, suggesting reduced parasympathetic activation and increased sympathetic tone as an element in maintenance of chronic muscle pain.

Review and classification of variability analysis techniques with clinical applications

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Circadian Patterns of Heart Rate Turbulence, Heart Rate Variability and Their Relationship

Background

Heart rate variability (HRV) is an established tool for studying cardiac autonomic activity over time, while heart rate turbulence (HRT) is a recent method used to assess autonomic dysfunction. However, there are different autonomic tones at different times of a day. This study aimed to examine the effect of circadian change of autonomic tone on heart rate turbulence and variability, and determine any relationship between them based on circadian variations.

Methods

Twenty-four-hour Holter recordings from 35 subjects with structurally normal heart were done, and HRV and HRT parameters of turbulence onset (TO) and turbulence slope (TS) were calculated. The 24-hour circadian patterns of these parameters and correlation analysis between them were performed.

Results

There were conspicuous diurnal oscillations in TS and HRV parameters, with less prominent variation in TO. TS and high frequency power (HF) shared the similar oscillation patterns in a day. Comparing HRT and HRV based on circadian variation, TS showed positive correlations with HF and low frequency power (LF) to a reasonable degree, while there was an inverse correlation between TS and LF/HF.

Conclusions

Circadian change of TS values throughout the day is more prominent than TO. It also presents as an autonomic activity more than TO. The relationships between HRV and HRT persist independently on the time of a day.

Heart rate variability on 7-day Holter monitoring using a bootstrap rhythmometric procedure

Heart rate variability (HRV) markers have been widely used to characterize the autonomous regulation state of the heart from 24-h Holter monitoring, but long-term evolution of HRV indexes is mostly unknown. A dataset of 7-day Holter recordings of 22 patients with congestive heart failure was studied. A rhythmometric procedure was designed to characterize the infradian, circadian, and ultradian components for each patient, as well as circadian and ultradian fluctuations. Furthermore, a bootstrap test yielded automatically the rhythmometric model for each patient. We analyzed the temporal evolution of relevant time-domain (AVNN, SDNN, and NN50), frequency-domain (LF, HF, HFn, and LF/HF), and nonlinear (alpha(1) and SampEn) HRV indexes. Circadian components were the most significant for all HRV indexes, but the infradian ones were also strongly present in NN50, HFn, LF/HF, alpha(1), and SampEn indexes. Among ultradian components that one corresponding to 12 h, was the most relevant. Long-term monitoring of HRV conveys new potentially relevant rhythmometric information, which can be analyzed by using the proposed automatic procedure.

Prediction of early secondary complications in patients with spontaneous subarachnoid hemorrhage based on accelerated sympathovagal ratios

PURPOSE

The development of secondary complications following spontaneous subarachnoid hemorrhage (SAH) largely depends on sympathetic overexcitation. The roles of vagal activities, however, are poorly defined. Because both components of the autonomic nervous system can be explored in the frequency domain of heart rate variability (HRV), the present study aimed to determine the dynamic evolution of autonomic activities and to identify patients at high risk for complications following hemorrhage.

METHODS

Thirty patients with SAH were enrolled in our study. Those who suffered from symptomatic vasospasm, cerebral infarction, neurogenic pulmonary edema, or early mortality within 1 week of ictus were categorized into the complication group. Spectral analysis of HRV explored three important indices of sympathetic and vagal modulations: low-frequency (LF), high-frequency (HF), and LF/HF ratios. Patterns of HRV dynamics within the first 3 days were compared between complication and non-complication groups. The group trends, estimated by the slopes of HRV changes, were determined for further univariate and multivariate analysis.

RESULTS

Our study showed that daily HRV in the complication group exhibited an approximately 2.7-fold increase of sympathovagal ratio (denoted by LF/HF). This resulted from reciprocal changes of sympathoexcitation (LF) and vagal withdrawal (HF). Multivariate analysis revealed that LF/HF slope, an indicator of the trend of sympathovagal change, was an independent variable significantly associated with the development of complications.

CONCLUSIONS

This study confirmed that during early SAH period, patients with and without complications presented different patterns of sympathovagal changes. LF/HF slope during the first 3 days was a significant predictor of secondary complications after SAH.

Chaotic signatures of heart rate variability and its power spectrum in health, aging and heart failure

A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a ‘litmus test’ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative ‘HF chaos’ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF.

Autonomic nervous system function and depth of sedation in adults receiving mechanical ventilation

BACKGROUND

The effect of the depth of sedation on the function of the autonomic nervous system is not well known.

OBJECTIVES

To describe the effect of level of sedation on heart rate variability as a marker of the function of the autonomic nervous system in patients receiving mechanical ventilation.

METHODS

This pilot study was part of a larger study in which sedation level was measured continuously for up to 24 hours. The sample consisted of 14 patients receiving mechanical ventilation. The R-R interval was measured continuously via electrocardiography. Sedation level was determined by using the Patient State Index and was categorized as deep (<60) or light (=60). Continuous heart rate data of 5 to 10 minutes for each sedation level for each patient were analyzed.

RESULTS

Parasympathetic activity as indicated by root mean square of successive difference of the R-R interval, the high-frequency component, and the percentage of differences of successive N-N intervals (intervals due to normal sinus depolarization) that differed more than 50 milliseconds was significantly lower for deep sedation than for light sedation. The markers indicating sympathetic activity, including the low-frequency component and the ratio of the low-frequency component to the high-frequency component, did not differ significantly between the 2 levels of sedation. Most patients were receiving benzodiazepines.

CONCLUSIONS

Deep sedation may be associated with depression of parasympathetic function in patients receiving mechanical ventilation. Use of benzodiazepines most likely contributed to this finding.