Prognostic impact of autonomic information flow in multiple organ dysfunction syndrome patients

Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5-0.7), moderate prognostic ability (0.7-0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63-0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60-0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.

E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures

Wearable technologies and digital phenotyping foster unique opportunities for designing novel intelligent electronic services that can address various well-being issues in patients with mental disorders (i.e., schizophrenia and bipolar disorder), thus having the potential to revolutionize psychiatry and its clinical practice. In this paper, we present e-Prevention, an innovative integrated system for medical support that facilitates effective monitoring and relapse prevention in patients with mental disorders. The technologies offered through e-Prevention include: (i) long-term continuous recording of biometric and behavioral indices through a smartwatch; (ii) video recordings of patients while being interviewed by a clinician, using a tablet; (iii) automatic and systematic storage of these data in a dedicated Cloud server and; (iv) the ability of relapse detection and prediction. This paper focuses on the description of the e-Prevention system and the methodologies developed for the identification of feature representations that correlate with and can predict psychopathology and relapses in patients with mental disorders. Specifically, we tackle the problem of relapse detection and prediction using Machine and Deep Learning techniques on all collected data. The results are promising, indicating that such predictions could be made and leading eventually to the prediction of psychopathology and the prevention of relapses.

Non-linear analysis of the heart rate variability in characterization of manic and euthymic phases of bipolar disorder

BACKGROUND

- Bipolar Disorder (BD) has been associated with autonomic nervous system (ANS) dysregulation, with a consequent increase in mortality. Recent work highlights the non-linear analysis of ANS function. Our objective was to compare ANS modulation using recurrence plots (RP) and symbolic analysis (SA) in manic and euthymic phases of BD to controls.

METHODS

- Eighteen male patients (33.1 ± 12.0 years) were assessed during mania and at discharge in the euthymic phase compared and to a healthy group matched by age (33.9 ± 10.8 years). Electrocardiographic series (1000 RR intervals, at rest, in supine position) were captured using Polar Advantage RS800CX equipment and Heart Rate Variability (HRV) was analysed using RP and SA. Statistical analysis was performed using ANOVA with Tukey's post-test. The threshold for statistical significance was set at P < 0.05 and Cohen's d effect size was also quantified considering d > 0.8 as an important effect. The study was registered into the Clinical Trials Registration (ClinicalTrials.gov: NCT01272518).

RESULTS

Manic group presented significantly higher linearity before treatment (P<0.05) compared to controls considering RP variables. Cohen's d values had a large effect size ranging from 0.888 to 1.227. In the manic phase, SA showed predominance of the sympathetic component (OV%) with reduction of the parasympathetic component (2LV% and 2UV%) with reversion post treatment including higher Shannon Entropy (SE) indicating higher complexity.

LIMITATIONS

- short follow-up (1 month) and small number of patients.

CONCLUSIONS

- Non-linear analyzes may be used as supplementary tools for understanding autonomic function in BD during mania and after drug treatment.

Toward the Existence of a Sympathetic Neuroplasticity Adaptive Mechanism Influencing the Immune Response. A Hypothetical View-Part II

In the preceding work, a hypothesis on the existence of a specific neural plasticity program from sympathetic fibers innervating secondary lymphoid organs was introduced. This proposed adaptive mechanism would involve segmental retraction and degeneration of noradrenergic terminals during the immune system (IS) activation followed by regeneration once the IS returns to the steady-state. Starting from such view, this second part presents clinical and experimental evidence allowing to envision that this sympathetic neural plasticity mechanism is also operative on inflamed non-lymphoid peripheral tissues. Importantly, the sympathetic nervous system regulates most of the physiological bodily functions, ranging from cardiovascular, respiratory and gastro-intestinal functions to endocrine and metabolic ones, among others. Thus, it seems sensible to think that compensatory programs should be put into place during inflammation in non-lymphoid tissues as well, to avoid the possible detrimental consequences of a sympathetic blockade. Nevertheless, in many pathological scenarios like severe sepsis, chronic inflammatory diseases, or maladaptive immune responses, such compensatory programs against noradrenergic transmission impairment would fail to develop. This would lead to a manifest sympathetic dysfunction in the above-mentioned settings, partly accounting for their underlying pathophysiological basis; which is also discussed. The physiological/teleological significance for the whole neural plasticity process is postulated, as well.

Poor oral health in patients with schizophrenia: A systematic review and meta-analysis

Increased rates of comorbid physical illness have been commonly reported in patients with schizophrenia. However, there are fewer data on dental disease in these patients. We systematically evaluated existing data on the oral health survey of schizophrenia patients through meta-analysis. Using the available databases, we performed a systematic search to identify the studies examining the oral health in schizophrenia patients from January 1997 to June 2017, based on the inclusion and exclusion criteria. Two investigators extracted the related data independently. The meta-analysis was performed by using the RevMan 5.3 software after data extraction and quality assessment. We compared the oral health results between the schizophrenia patients and the general population, including the following measures: the mean number of decayed, missing and filled teeth (DMFT). Eight studies comprising 2640 patients with schizophrenia and 19,698 healthy controls were included in the meta-analysis. The patients with schizophrenia had significantly higher scores of dental caries (mean difference [MD] = 7.77, 95% confidence interval [CI] = 3.27 to 12.27), missing teeth (MD = 7.61, 95% CI = 3.44 to 11.77), and decayed teeth (MD = 3.44, 95% CI = 2.06 to 4.82) compared to controls (all p < 0.01). By contrast, the schizophrenia patients had fewer score of filled teeth (MD = -3.06, 95% CI, -4.82 to -1.30) than the controls (p < 0.01), indicating decreased access to dental care. Our systematic review suggests that patients with schizophrenia have worse oral health than the general population, but have received less dental care services. Hence, the oral health services should be taken into account in the patients with schizophrenia.

Cardiac dysfunction in critical illness

PURPOSE OF REVIEW

Sepsis and septic shock are prevalent conditions that are likely to increase in prevalence in the future. Given the high mortality and morbidity associated with sepsis and sepsis-induced cardiac dysfunction, we must continue to make advances in knowledge of the complex physiologic interactions and how we may target specific mediators for potential therapeutic options in the future.

RECENT FINDINGS

Multiple biomarkers have been discovered, which when assayed in sepsis-induced cardiomyopathy predict morbidity and mortality. With increased sensitivity of echocardiography, we can diagnose subclinical cardiac dysfunction, which may have future implications for slowing or preventing progressive dysfunction.

SUMMARY

Sepsis-induced cardiomyopathy is the result of complicated interactions between the pathogen, the body's response to infection, and iatrogenic injury. Interplay between inflammatory, metabolic, and adrenergic systems results in direct and indirect myocardial injury leading to decreases in both systolic and diastolic cardiac function. As the interactions are further elucidated with additional research into other proteins and mediators, new treatment options can be researched. VIDEO ABSTRACT.

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning

OBJECTIVE

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning.

APPROACH

Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients.

MAIN RESULTS

HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information.

SIGNIFICANCE

Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

Sepsis-Induced Cardiomyopathy: Mechanisms and Treatments

Sepsis is a lethal syndrome with a high incidence and a weighty economy burden. The pathophysiology of sepsis includes inflammation, immune dysfunction, and dysfunction of coagulation, while sepsis-induced cardiomyopathy (SIC), defined as a global but reversible dysfunction of both sides of the heart induced by sepsis, plays a significant role in all of the aspects above in the pathogenesis of sepsis. The complex pathogenesis of SIC involves a combination of dysregulation of inflammatory mediators, mitochondrial dysfunction, oxidative stress, disorder of calcium regulation, autonomic nervous system dysregulation, and endothelial dysfunction. The treatments for SIC include the signal pathway intervention, Chinese traditional medicine, and other specific therapy. Here, we reviewed the latest literatures on the mechanisms and treatments of SIC and hope to provide further insights to researchers and create a new road for the therapy of sepsis.

Pilot Randomized Study of a Gratitude Journaling Intervention on Heart Rate Variability and Inflammatory Biomarkers in Patients With Stage B Heart Failure

OBJECTIVE

Stage B, asymptomatic heart failure (HF) presents a therapeutic window for attenuating disease progression and development of HF symptoms, and improving quality of life. Gratitude, the practice of appreciating positive life features, is highly related to quality of life, leading to development of promising clinical interventions. However, few gratitude studies have investigated objective measures of physical health; most relied on self-report measures. We conducted a pilot study in Stage B HF patients to examine whether gratitude journaling improved biomarkers related to HF prognosis.

METHODS

Patients (n = 70; mean [standard deviation] age = 66.2 [7.6] years) were randomized to an 8-week gratitude journaling intervention or treatment as usual. Baseline (T1) assessments included the six-item Gratitude Questionnaire, resting heart rate variability (HRV), and an inflammatory biomarker index. At T2 (midintervention), the six-item Gratitude Questionnaire was measured. At T3 (postintervention), T1 measures were repeated but also included a gratitude journaling task.

RESULTS

The gratitude intervention was associated with improved trait gratitude scores (F = 6.0, p = .017, η = 0.10), reduced inflammatory biomarker index score over time (F = 9.7, p = .004, η = 0.21), and increased parasympathetic HRV responses during the gratitude journaling task (F = 4.2, p = .036, η = 0.15), compared with treatment as usual. However, there were no resting preintervention to postintervention group differences in HRV (p values > .10).

CONCLUSIONS

Gratitude journaling may improve biomarkers related to HF morbidity, such as reduced inflammation; large-scale studies with active control conditions are needed to confirm these findings.

TRIAL REGISTRATION

Clinicaltrials.govidentifier:NCT01615094.

Spontaneous breathing trial in T-tube negatively impact on autonomic modulation of heart rate compared with pressure support in critically ill patients

INTRODUCTION

Spontaneous breathing with a conventional T-piece (TT) connected to the tracheal tube orotraqueal has been frequently used in clinical setting to weaning of mechanical ventilation (MV), when compared with pressure support ventilation (PSV). However, the acute effects of spontaneous breathing with TT versus PSV on autonomic function assessed through heart rate variability (HRV) have not been fully elucidated.

OBJECTIVE

The purpose of this study was to examine the acute effects of spontaneous breathing in TT vs PSV in critically ill patients.

METHOD

Twenty-one patients who had received MV for ≥ 48 h and who met the study inclusion criteria for weaning were assessed. Eligible patients were randomized to TT and PSV. Cardiorespiratory responses (respiratory rate -ƒ, tidal volume-V_T , mean blood pressure (MBP) and diastolic blood pressure (DBP), end tidal dioxide carbone (P_ET CO₂ ), peripheral oxygen saturation (SpO₂ ) and HRV indices in frequency domain (low-LF, high frequency (HF) and LF/HF ratio were evaluated.

RESULTS

TT increased ƒ (20 ± 5 vs 25 ± 4 breaths/min, P<0.05), MBP (90 ± 14 vs 94 ± 18 mmHg, P<0.05), HR (90 ± 17 vs 96 ± 12 beats/min, P<0.05), P_ET CO₂ (33 ± 8 vs 48 ± 10 mmHg, P<0.05) and reduced SpO₂ (98 ± 1.6 vs 96 ± 1.6%, P<0.05). In addition, LF increased (47 ± 18 vs 38 ± 12 nu, P<0.05) and HF reduced (29 ± 13 vs 32 ± 16 nu, P<0.05), resulting in higher LF/HF ratio (1.62 ± 2 vs 1.18 ± 1, P<0.05) during TT. Conversely, V_T increased with PSV (0.58 ± 0.16 vs 0.50 ± 0.15 L, P<0.05) compared with TT.

CONCLUSION

Acute effects of TT mode may be closely linked to cardiorespiratory mismatches and cardiac autonomic imbalance in critically ill patients.

Heart rate variability in horses with acute gastrointestinal disease requiring exploratory laparotomy

OBJECTIVE

To describe heart rate variability (HRV) in horses with acute gastrointestinal disease that undergo exploratory laparotomy. We hypothesized that horses with ischemic gastrointestinal disease will have reduced HRV compared to horses with nonischemic lesions. We further hypothesized that a reduction in HRV will be associated with nonsurvival.

DESIGN

Prospective, clinical, observational study.

SETTING

University veterinary teaching hospital.

ANIMALS

Horses presented for acute colic (n = 57) or elective surgical procedures (n = 10) were enrolled.

INTERVENTIONS

Admission heart rate (HR) was recorded and within 2 hours of recovery from general anesthesia continuous telemetry was placed, monitored and recorded for 48-52 hours postoperatively. Stored electrocardiograms were manually inspected and R-to-R intervals were extracted and uploaded into HRV software for analysis. Time domain and frequency spectral analysis were investigated at Times 1 (2-10 h), 2 (16-24 h), 3 (30-38 h), and 4 (44-52 h) postoperatively. A two-way ANOVA for repeated measures was used for group comparisons. Logistic regression analysis was used to detect potential associations between admission HR, time and frequency domain variables, and nonsurvival.

MEASUREMENTS AND MAIN RESULTS

Horses diagnosed with an ischemic gastrointestinal lesion (n = 22) at the time of surgery had significantly higher postoperative heart rates and reduced time domain-derived measures of HRV than horses with nonischemic gastrointestinal lesions (n = 35) or control horses (n = 10). Horses that survived to discharge had significantly lower postoperative HRs, higher time domain, and lower low frequency spectral measures of HRV compared to nonsurvivors. The multivariable logistic regression model had a receiver operating characteristic area under the curve (AUC) of 0.95 and was significantly better at predicting nonsurvival than admission HR (P = 0.0124).

CONCLUSIONS

Reduced HRV was strongly associated with ischemic gastrointestinal disease and nonsurvival. HRV analysis is a noninvasive technique that may provide diagnostic and prognostic information pertinent to the management of postoperative horses with severe gastrointestinal disease.

Study protocol: prediction of stroke associated infections by markers of autonomic control

Background

Infection is the most important complication after acute stroke. This is substantially based on a stroke-induced immunosuppression. Heart rate variability (HRV) represents the autonomic nervous system activity in connection with stroke-induced immunomodulation and infections. We demonstrated in a feasibility study that HRV indices obtained in patients without acute post-stroke infections can predict infections in the subsequent sub-acute phase.

Methods/Design

The study PRED-SEP is a prospective observational study. Adult patients with acute ischemic infarction in the territory of the middle cerebral artery and severe neurological deficit (National Institutes of Health Stroke Scale: NIHSS ≥ 8) are recruited. Primary endpoint is the development of infections, secondary endpoints are SIRS and severe sepsis in the sub-acute phase (day 3–5) after stroke and the functional outcome after 3 months. Infection is defined according to the PANTHERIS study and comprises pneumonia, urinary tract infection and infections without determined focus. SIRS and severe sepsis are defined according to German Sepsis Society guidelines. Functional outcome is measured by lethality and neurological scores (modified Rankin Scale, Barthel Index). Prognostic factors are HRV risk indices calculated from selected intervals of 24 h ECG measurements within 48 hours after symptom onset. It is planned to recruit 240 patients.

HRV risk indices (predictors) will be calculated according to standards and procedures previously developed and published by the authors. The predictive effects of HRV indices on infections will be estimated by fitting logistic regression models and estimating odds ratios with 95% confidence intervals. A prespecified modelling procedure will be applied to estimate unadjusted and confounder adjusted odds ratios. Secondary endpoints will be analysed in the same way. The functional outcome scales will be dichotomized. The association between HRV indices and pro- and anti-inflammatory markers will be quantified by calculating the appropriate correlation coefficients according to scale (Person or Spearman).

Discussion

Since a general prophylactic antibiotic treatment after stroke is not recommended, results of this study could have essential implications for an early identification and hence, timely appropriate treating of stroke-induced infections.

Trial registration

Prädiktoren für die Sepsis - Pred Sep, German Clinical Trials Register: DRKS00003392.

Development of multiscale complexity and multifractality of fetal heart rate variability

During fetal development a complex system grows and coordination over multiple time scales is formed towards an integrated behavior of the organism. Since essential cardiovascular and associated coordination is mediated by the autonomic nervous system (ANS) and the ANS activity is reflected in recordable heart rate patterns, multiscale heart rate analysis is a tool predestined for the diagnosis of prenatal maturation. The analyses over multiple time scales requires sufficiently long data sets while the recordings of fetal heart rate as well as the behavioral states studied are themselves short. Care must be taken that the analysis methods used are appropriate for short data lengths. We investigated multiscale entropy and multifractal scaling exponents from 30 minute recordings of 27 normal fetuses, aged between 23 and 38 weeks of gestational age (WGA) during the quiet state. In multiscale entropy, we found complexity lower than that of non-correlated white noise over all 20 coarse graining time scales investigated. Significant maturation age related complexity increase was strongest expressed at scale 2, both using sample entropy and generalized mutual information as complexity estimates. Multiscale multifractal analysis (MMA) in which the Hurst surface h(q,s) is calculated, where q is the multifractal parameter and s is the scale, was applied to the fetal heart rate data. MMA is a method derived from detrended fluctuation analysis (DFA). We modified the base algorithm of MMA to be applicable for short time series analysis using overlapping data windows and a reduction of the scale range. We looked for such q and s for which the Hurst exponent h(q,s) is most correlated with gestational age. We used this value of the Hurst exponent to predict the gestational age based only on fetal heart rate variability properties. Comparison with the true age of the fetus gave satisfying results (error 2.17±3.29 weeks; p<0.001; R(2)=0.52). In addition, we found that the normally used DFA scale range is non-optimal for fetal age evaluation. We conclude that 30 min recordings are appropriate and sufficient for assessing fetal age by multiscale entropy and multiscale multifractal analysis. The predominant prognostic role of scale 2 heart beats for MSE and scale 39 heart beats (at q=-0.7) for MMA cannot be explored neither by single scale complexity measures nor by standard detrended fluctuation analysis.

Heart rate variability - a potential early marker of sub-acute post-stroke infections

OBJECTIVE

Infection is the most relevant complication after acute ischemic stroke. Activity of the autonomic nervous system seems to control post-stroke immunodepression. We investigated heart rate variability (HRV) indices that reflect autonomic readjustments as predictors of post-stroke infection.

MATERIALS AND METHODS

Forty-three patients with acute ischemic stroke were enrolled in a prospective study. The predictability of sub-acute infections (day 4 ± 1 after admission) was investigated in 34 patients without acute infection by means of HRV indices obtained in the acute period (48 h after admission).

RESULTS

Sub-acute infection could be predicted in patients without clinical or paraclinical (white blood cell count and C-reactive protein) signs of infection in the acute period at (i) day: increased HFnorm, reduced LFnorm and LF/HF; (ii) night: reduced LF and VLF (P < 0.05).

CONCLUSIONS

HRV indices are candidates for early markers of developing post-stroke infections, preceding routine blood samples. Thus, HRV-based early diagnosis of post-stroke infection should be investigated in more detail as it may have implications as a novel tool for timely and appropriate treatment. A corresponding continuous HRV-based risk assessment using the ECG provided by the routine stroke monitoring system would be possible without any additional burden for patients and staff.

Heart rate variability: a diagnostic and prognostic tool in anesthesia and intensive care

The autonomic nervous system (ANS) plays an important role in the human response to various internal and external stimuli, which can modify homeostasis, and exerts a tight control on essential functions such as circulation, respiration, thermoregulation and hormonal secretion. ANS dysfunction may complicate the perioperative course in the surgical patient undergoing anesthesia, increasing morbidity and mortality, and, therefore, it should be considered as an additional risk factor during pre-operative evaluation. Furthermore, ANS dysfunction may complicate the clinical course of critically ill patients admitted to intensive care units, in the case of trauma, sepsis, neurologic disorders and cardiovascular diseases, and its occurrence adversely affects the outcome. In the care of these patients, the assessment of autonomic function may provide useful information concerning pathophysiology, risk stratification, early prognosis prediction and treatment strategies. Given the role of ANS in the maintenance of systemic homeostasis, anesthesiologists and intensivists should recognize as critical the evaluation of ANS function. Measurement of heart rate variability (HRV) is an easily accessible window into autonomic activity. It is a low-cost, non-invasive and simple to perform method reflecting the balance of the ANS regulation of the heart rate and offers the opportunity to detect the presence of autonomic neuropathy complicating several illnesses. The present review provides anesthesiologists and intensivists with a comprehensive summary of the possible clinical implications of HRV measurements, suggesting that autonomic dysfunction testing could potentially represent a diagnostic and prognostic tool in the care of patients both in the perioperative setting as well as in the critical care arena.

Autonomic dysfunction and risk stratification assessed from heart rate pattern

The modulation of the autonomic nervous system (ANS) under physiological and pathophysiological conditions is in focus of recent research. Many patients with cardio- and cerebrovascular diseases display features of sympathovagal dysregulation. Measuring specific ANS parameters could improve risk stratification. Thus, the early diagnosis of ANS dysfunction in these patients poses a great challenge with high prognostic relevance.The most relevant methods and measures of Heart Rate Variability (HRV) analysis and HRV monitoring will be described in detail in this chapter. The grown importance of these easily obtainable heart rate patterns in stratifying the risk of patients with myocardial infarction and heart failure as well as ischemic stroke will be demonstrated based on recent clinical studies. In order to perspectively improve clinical management of these patients further large scale clinical investigations on the role of ANS dysfunction will be useful.

Heart rate variability in bipolar mania and schizophrenia

BACKGROUND

Autonomic nervous system (ANS) dysfunction and reduced heart rate variability (HRV) have been reported in a wide variety of psychiatric disorders, but have not been well characterized in bipolar mania. We recorded cardiac activity and assessed HRV in acutely hospitalized manic bipolar (BD) and schizophrenia (SCZ) patients compared to age- and gender-matched healthy comparison (HC) subjects.

METHOD

HRV was assessed using time domain, frequency domain, and nonlinear analyses in 23 manic BD, 14 SCZ, and 23 HC subjects during a 5min rest period. Psychiatric symptoms were assessed by administration of the Brief Psychiatric Rating Scale (BPRS) and the Young Mania Rating Scale (YMRS).

RESULTS

Manic BD patients demonstrated a significant reduction in HRV, parasympathetic activity, and cardiac entropy compared to HC subjects, while SCZ patients demonstrated a similar, but non-significant, trend towards lower HRV and entropy. Reduction in parasympathetic tone was significantly correlated with higher YMRS scores and the unusual thought content subscale on the BPRS. Decreased entropy was associated with increased aggression and diminished personal hygiene on the YMRS scale.

CONCLUSION

Cardiac function in manic BD individuals is characterized by decreased HRV, reduced vagal tone, and a decline in heart rate complexity as assessed by linear and nonlinear methods of analysis. Autonomic dysregulation is associated with more severe psychiatric symptoms, suggesting HRV dysfunction in this disorder may be dependent on the phase of the illness.

Indices of fetal development derived from heart rate patterns

BACKGROUND

The fetal precursors of mental and cardiovascular disease caused by adverse prenatal environmental influences and manifesting in later age are an important issue of developmental medicine. However the number of measurable functional parameters of a fetus is limited. Evaluation of key parameters involving fetal autonomic control could permit an earlier detection of developmental problems and improved therapeutic strategies. Thus far, however, even the maturation of normal autonomic control has not been sufficiently assessed.

AIM

The objective of the present work is to describe normal fetal maturation based on indices of autonomic heart rate modulation.

STUDY DESIGN

Heart beat interval series were magnetocardiographically recorded with 1 kHz sampling rate over 30 min in 78 normal fetuses, gestational age (GA) 23-40 weeks. Indices considered were: number of accelerations (AC) and decelerations (DC), RMSSD, SDNN, and short-term/long-term autonomic information flows (AIF_NN, AIF_fVLF). These were measured from the entire 30 min data sets and from activity-specific subsets (10 min).

RESULTS

In the 30 min recordings: the number of AC increased, number of DC decreased, rMSSD and SDNN increased and AIF_fVLF increased with GA, but AIF_NN remained constant. In the 10 min subsets: SDNN increased in the active state but remained constant in the quiet state and AIF_NN decreased with GA in the quiet state.

CONCLUSION

Heart rate patterns from 30 min biomagnetic recordings may provide new indices with which to assess the normal and abnormal maturation of fetal autonomic control and to identify risk of possible disorders in later life.

Multiscale, multiorgan and multivariate complexity analyses of cardiovascular regulation

Cardiovascular system complexity is confirmed by both its generally variegated structure of physiological modelling and the richness of information detectable from processing of the signals involved in it, with strong linear and nonlinear interactions with other biological systems. In particular, this behaviour may be accordingly described by means of what we call MMM paradigm (i.e. multiscale, multiorgan and multivariate). Such an approach to the cardiovascular system emphasizes where the genesis of its complexity is potentially allocated and how it is possible to detect information from it. No doubt that processing signals from multi-leads of the same system (multivariate), from the interaction of different physiological systems (multiorgan) and integrating all this information across multiple scales (from genes, to proteins, molecules, cells, up to the whole organ) could really provide us with a more complete look at the overall phenomenon of cardiovascular system complexity, with respect to the one which is obtainable from its single constituent parts. In this paper, some examples of approaches are discussed for investigating the cardiovascular system in different time and spatial scales, in studying a different organ involvement (such as sleep, depression and multiple organ dysfunction) and in using a multivariate approach via various linear and nonlinear methods for cardiovascular risk stratification and pathology assessment.

Autonomic dysfunction predicts both 1- and 2-month mortality in middle-aged patients with multiple organ dysfunction syndrome

OBJECTIVE

Multiple organ dysfunction syndrome (MODS) is a disease entity that carries a high mortality rate. It is characterized by a sequential failure of several organ systems after a trigger event, most commonly sepsis. There is increasing evidence that autonomic dysfunction may substantially contribute to the development of MODS. We recently characterized the spectrum of autonomic dysfunction by using heart rate variability in critically ill MODS patients and were able to show that autonomic dysfunction predicts 28-day mortality in MODS. The aim of the present study was evaluate whether autonomic dysfunction is also a predictor of 180-day and 365-day mortalities.

DESIGN

Prospective cohort study.

SETTING

Twelve-bed medical intensive care unit in a university center.

PATIENTS

Ninety consecutively admitted score-defined MODS patients.

INTERVENTIONS

We assessed heart rate variability as a marker of autonomic dysfunction. The patients were followed for 180- and 365-day mortalities.

MEASUREMENTS AND MAIN RESULTS

We prospectively used the heart rate variability variable lnVLF, which predicted 28-day mortality best in the entire cohort of patients, for analysis of longer term mortality. The variable lnVLF was found to be useful for risk prediction for about 60 days, and then the survival curves became nearly parallel.

CONCLUSIONS

Autonomic function of critically ill MODS patients is blunted, and this attenuation has prognostic implications not merely concerning 28-day mortality but also concerning longer term (about 2-month) mortality.

Autonomic response to cardiac dysfunction in chronic heart failure: a risk predictor based on autonomic information flow

BACKGROUND

Chronic heart failure (CHF) is associated with a complex dysfunction of cardiac, cardiovascular, autonomic, and other mechanisms. Autonomic information flow (AIF) characteristics calculated from heart rate patterns were recently found as promising predictors of outcome in several cardiovascular diseases.

AIM

To assess the prognostic value of AIF indices in CHF patients.

METHODS

We analyzed 24-hour Holter recordings from 200 consecutive CHF patients in sinus rhythm and computed AIF over the shortest possible interval of an interbeat series, namely over one heart beat interval (BDnn), and over longer intervals (12.5-166.7 seconds, PDmVLF), which reflect slower heart rate modulations. End-point for survival analysis over three years (Cox model) was total cardiac death. A prognostic model was built (backward elimination) considering known clinical and functional risk factors, and the ability of AIF indices to add prognostic information to this model assessed.

RESULTS

Out of candidate predictors, New York Heart Association class, left ventricular ejection fraction, peak VO(2,) and systolic pressure were selected as the variables with the highest joint predictive value. When entered into this model, both BDnn and PDmVLF added prognostic information (HR (95%CI): 1.76 (1.00-3.09), P = 0.05, 1.73 (1.05-2.85), P = 0.031 respectively). High risk was associated with reduced fast AIF and increased slower AIF.

CONCLUSION

In CHF patients, AIF indices provide prognostic information independent of known risk factors.

The alteration of autonomic function in multiple organ dysfunction syndrome

Autonomic dysfunction is associated with the severity of illness and mortality in patients with multiple organ dysfunction syndrome (MODS) and may contribute significantly to the pathogenesis of this syndrome. Several treatment approaches may possibly restore autonomic function in MODS and thus cause the survival benefit.

Nonlinear broad band dynamics are less complex in major depression

OBJECTIVES

Cardiac mortality is known to be increased in depressive patients. However, the underlying mechanisms remain elusive to date. Decreased heart rate variability (HRV) has been discussed as contributing to increased cardiac mortality, but studies examining patients suffering from major depressive disorder (MDD) have revealed inconsistent results. This study aimed to investigate long-term and broad band parameters of heart rate regulation in MDD, which have been shown to be more sensitive for the assessment of autonomic dysfunction.

METHODS

A total of 18 non-medicated patients suffering from MDD and 18 matched control subjects without cardiac disease were recruited and 24-h ambulatory electrocardiograms were recorded. Data were recorded during three distinct time intervals linear and nonlinear parameters as well as autonomic information flow (AIF) were calculated.

RESULTS

The power law slope was significantly reduced in the patient group for all intervals investigated and correlated with symptom severity, whereas standard deviation of the 5-min NN intervals (SDANN) and area under the AIF curve (INT(NN)) showed significant differences between groups in the morning hours only. Analysis of standard HRV parameters in the time and frequency domain revealed no significant differences between groups.

CONCLUSIONS

The evidence for decreased complexity of cardiac regulation in depressed patients presented here might be useful as an indicator of the increased cardiac mortality known in depression, especially since these parameters are capable of predicting cardiac mortality in other diseases. The importance of these parameters for patients at risk should be evaluated in future prospective studies.

Association between short term and long term communication in pathological autonomic control

Autonomic Information Flow (AIF) reflects the time scale dependence of autonomic communications such as vagal, sympathetic, and slower rhythms and their complex interplay. We investigated the hypothesis that pathologically disturbed short term control is associated with simplified complex long term control. This particular characteristic of altered autonomic communication was evaluated in different medical patient groups. Holter recordings were assessed in patients with multiple organ dysfunction (MODS) (26 survivors, 10 non-survivors); with heart failure (14 low risk-without history of aborted cardiac arrest (CA), 13 high risk--with history of CA); with idiopathic dilated cardiomyopathy (IDC) (26 low risk, 11 high risk of CA), after myocardial infarction (MI) (1221 low risk--survivors, 55 high risk--non-survivors); after abdominal aorta surgery (AAS, 32 length of stay in hospital LOS>7 days, 62 LOS < or =7 days). AIF of short and long time scales was investigated. We found a fundamental association of increased short term randomness and decreased long term randomness due to pathology. Concerning risk, high risk patients were characterized by increased short term complexity and decreased long term complexity in all patients groups with the exception of the IDC patients. We conclude that different time scales of AIF represent specific pathophysiological aspects of altered autonomic communication and control. The association of altered short term control with simplified long term behavior might be a pathophysiologically relevant compensation mechanism in the case of a disturbed fastest actuator. This knowledge might be useful for the development of comprehensive therapeutic strategies besides the predictive implications.

Effect of age and sex on heart rate variability in healthy subjects

OBJECTIVE

The study aimed to investigate the effect of age and sex on the heart rate variability (HRV) analysis and to explore the normal range of HRV in different age and sex groups for potential health care applications.

METHOD

Baseline HRV, age, and sex data were collected from 470 subjects without cardiovascular conditions. Short-term HRV was recorded using Biocom Active ECG units (Biocom, Seattle, Wash). Subjects were divided by age into 10-year intervals and by sex for HRV analysis.

RESULTS

Total power, representing the overall autonomic activity, decreased consistently from the age groups 10+ to 80+ years (P < .001). Both the low frequency (sympathetic activity) and high frequency (parasympathetic activity) declined (P < .05) as age increased. Sex had a significant effect on heart rate, R-R interval, high frequency, normalized low frequency, normalized high frequency, and low frequency-high frequency ratio. Sex did not seem to affect the SD of the normal-to-normal heartbeats and total power (P > .05) despite the significant heart rate changes (P < .05).

CONCLUSION

This study demonstrated that age had a greater impact on HRV than sex. The older age group had consistently lower HRV than younger people. The values generated in this study may be useful in health care settings to determine abnormal ranges of HRV under different clinical and experimental conditions.

Non-linear complexity measures of heart rate variability in acute schizophrenia

OBJECTIVE

Cardiovascular mortality is significantly increased in patients suffering from schizophrenia. The mechanisms currently discussed contain unhealthy lifestyle with obesity and smoking, increased incidence of diabetes, adverse pro-arrhythmic effects of antipsychotic medication and altered autonomic function. It is therefore likely that the adaptation of the heart rate to different requirements is faulty in schizophrenia. One way to detect adaptive capabilities and thus stability of regulation is to measure complexity of heart rate fluctuations, with more complex heart rate fluctuations indicating better adaptability of the underlying system.

METHODS

We calculated novel non-linear measures for beat-to-beat interval complexity from short-term ECG recordings in 20 unmedicated patients suffering from acute schizophrenia and compared them to those obtained from matched controls.

RESULTS

Data from all mathematical models applied, i.e. joint symbolic dynamics, compression entropy, fractal dimension and approximate entropy, revealed significantly reduced complexity of heart rate time series in acute schizophrenia. When using heart rate as a covariate, only fractal dimension remained significantly altered, thus appearing to be a relatively more important heart rate independent parameter.

CONCLUSIONS

Complexity of heart rate modulation is significantly reduced in acute, untreated schizophrenia, thus indicating an increased risk for cardiovascular events in these patients.

SIGNIFICANCE

These data might eventually add to the currently discussed monitoring of physical health in patients with schizophrenia, possibly providing a promising tool for cardio-arrhythmic risk stratification.

Changes of autonomic information flow due to idiopathic dilated cardiomyopathy

Risk stratification of patients with idiopathic dilated cardiomyopathy (IDC) is an epidemiologically relevant question. But the results based on conventional heart rate variability (HRV) analysis are still unsatisfactory. The adjustments within the cardiovascular system incorporate nonlinear and complex mechanisms of information exchange which may have additional prognostic value. It is an objective of the present work to evaluate the prognostic value of autonomic information flow (AIF) measures in IDC patients compared to conventional HRV measures in a first explorative study. Holter recordings of 32 patients with idiopathic dilated cardiomyopathy (IDC) and 12 normal subjects (NRM) were analyzed. The IDC patients consisted of two groups: 10 high risk (HR) patients, after aborted sudden cardiac death (SCD); 22 low risk (LR) patients, without SCD. Sensitivity, specificity, positive predictive value, negative predictive value and ROC characteristics of a comprehensive set of AIF measures, organized according to the conventional HRV standards, and conventional HRV measures were investigated. The significant risk predictors were evaluated by Spearman's rank correlation. While the only traditional HRV measure discriminating IDC patients from NRM was ln(LF) most of the AIF measures had a discriminatory value. Concerning the prognosis of the IDC patients by conventional HRV we found that SDNN and all frequency band measures (lnHF, lnLF, lnVLF) significantly discriminated HR from LR. Among the AIF measures the time shift related peak decay (PD(dHF)) reflecting the HF band information flow had a prognostic value. PD(dHF) was identified as a promising candidate which might improve the predictive value of traditional HRV analysis, predominantly represented by SDNN. A subsequent comprehensive clinical study is necessary to validate this hypothesis.

Making sense of multiple organ dysfunction syndrome

Despite recent advances in critical care medicine, caring for patients with MODS remains one of the most challenging experience a critical care can encounter. New therapies that current exist and continue to be developed contribute to successful outcomes for patients with MODS, but there is no substitute for prevention and early intervention for persons at risk for developing MODS. Early and subtle changes in the patient who is at risk and has endured an initial insult can make a great difference in the patient's outcome and chances of mortality. Goal-directed therapy, supportive management, as well as an understanding of the inflammatory process are key to decreasing the mortality rate among patients with MODS.

Interactions between short-term and long-term cardiovascular control mechanisms

The cardiovascular system incorporates several controlling mechanisms acting as feedback loops over different time horizons. Because of their complex interrelationships, information-based methods such as autonomic information flow (AIF) functions promise to be useful in identifying normal and pathological behavior. Optimal adjustment between those controllers is necessary for healthy global behavior of the organism. We investigated the question as to whether there are typical relationships between short-term and long-term AIF by means of a meta-analysis of several of our own clinical studies of the mortality of patients with multiple organ dysfunction syndrome, heart failure, idiopathic dilated cardiomyopathy, and the length of stay in hospital after abdominal aorta surgery. We found a fundamental association of increased short-term randomness (decreased AIF) and decreased long-term randomness (increased AIF) due to pathology. A systems theoretic validation of this fundamental type of association was done by an appropriate mathematical model using a dissipative system with two feedback loops over different time horizons. The systematic simulation of an increasing collapse of the short feedback loop confirmed the inverse association between short-term and long-term information flow as a fundamental, system inherent type of readjustment that occurs under pathological conditions.

Complex autonomic dysfunction in cardiovascular, intensive care, and schizophrenic patients assessed by autonomic information flow

BACKGROUND

The cardiovascular control system is mediated by mechanisms acting at different time scales, such as heart period, vagal, sympathetic, and other slower controllers. Since these elements are interrelated in a complex manner, classical control theory fails and information-based description, based on autonomic information flow (AIF) functions, is appropriate. We investigated the hypothesis that AIF functions of typical time scales specifically characterize autonomic dysfunction and prognosis.

MATERIALS AND METHODS

Holter recordings of patients with multiple organ dysfunction syndrome (MODS) (26 survivors, 10 non-survivors), heart failure (13 low risk, 13 high risk of cardiac arrest), idiopathic dilated cardiomyopathy (IDC) (26 low risk, 11 high risk), after abdominal aorta surgery (AAS) [32 with length of stay in hospital (LOS) >7 days; 62 with LOS < or =7 days] or with schizophrenia (n=20) were assessed and compared to 20 control subjects.

RESULTS

We found different AIF time scales discriminating risk. AIF measures of heart beat period had predominant prognostic value in heart failure patients, those of vagal communication in MODS and IDC, and those of long-term communication after AAS. Schizophrenic patients were discriminated from controls by vagally mediated communication.

CONCLUSION

Different time scales of AIF represent specific pathophysiological aspects of altered complex autonomic control (communication) and consequently have predictive implications.

Analysis of complex physiological systems by information flow: a time scale-specific complexity assessment

In the last two decades conventional linear methods for biosignal analysis have been substantially extended by non-stationary, non-linear, and complexity approaches. So far, complexity is usually assessed with regard to one single time scale, disregarding complex physiology organised on different time scales. This shortcoming was overcome and medically evaluated by information flow functions developed in our research group in collaboration with several theoretical, experimental, and clinical partners. In the present work, the information flow is introduced and typical information flow characteristics are demonstrated. The prognostic value of autonomic information flow (AIF), which reflects communication in the cardiovascular system, was shown in patients with multiple organ dysfunction syndrome and in patients with heart failure. Gait information flow (GIF), which reflects communication in the motor control system during walking, was introduced to discriminate between controls and elderly patients suffering from low back pain. The applications presented for the theoretically based approach of information flow confirm its value for the identification of complex physiological systems. The medical relevance has to be confirmed by comprehensive clinical studies. These information flow measures substantially extend the established linear and complexity measures in biosignal analysis.

Permutation entropy improves fetal behavioural state classification based on heart rate analysis from biomagnetic recordings in near term fetuses

The relevance of the complexity of fetal heart rate fluctuations with regard to the classification of fetal behavioural states has not been satisfyingly clarified so far. Because of the short behavioural states, the permutation entropy provides an advantageous complexity estimation leading to the Kullback-Leibler entropy (KLE). We test the hypothesis that parameters derived from KLE can improve the classification of fetal behaviour states based on classical heart rate fluctuation parameters (SDNN, RMSSD, ln(LF), ln(HF)). From measured heartbeat sequences (35 healthy fetuses at a gestational age between 35 and 40 completed weeks) representative intervals of 256 heartbeats were visually preclassified into fetal behavioural states. Employing discriminant analysis to separate the states 1F, 2F and 4F, the best classification result by classical parameters was 80.0% (SDNN). After additionally considering KLE parameters it was improved significantly (p<0.0005) to 94.3% (ln(LF), KLE_Mean). It could be confirmed that KLE can improve the state classification. This might reflect the consideration of different physiological aspects by classical and complexity measures.