Deceleration and acceleration capacities of heart rate associated with heart failure with high discriminating performance

Short-term deceleration capacity: a novel non-invasive indicator of parasympathetic activity in patients undergoing pulmonary vein isolation

BACKGROUND

Subtypes of atrial fibrillation (AF) can differ, and exact mechanisms in which patients benefit from the pulmonary vein isolation (PVI) remain not fully understood. During PVI, vagal innervation of the heart may also be affected. Thus, non-invasive methods of intraprocedural assessment of such PVI impact are sought.

METHODS

From 1-minute ECG recordings performed before and after PVI, we investigated short-term deceleration capacity (ST-DC) and short-term heart rate variability (ST-HRV) to determine their potential as indicators of parasympathetic activity before and after ablation.

RESULTS

In 24 consecutive patients with paroxysmal AF included in the study, there were a significant differences in ST-DC and ST-HRV parameters measured before and after PVI. After 3 months, patients with baseline ST-DC ≥ 7.5 ms were less likely to experience AF recurrence when compared to patients with baseline ST-DC < 7.5 ms (0% vs 31%, p = 0.0496). There were no differences in AF recurrence after 12 months of follow-up (36% vs 38%, p = 0.52).

CONCLUSION

PVI leads to significant changes in ST-DC and ST-HRV, and these parameters can serve as indicators of vagal denervation after AF ablation. Patients with more prominent baseline ST-DC are less likely to experience AF recurrence during the post-PVI 3-month blanking period.

Enhancing Comprehensive Assessments in Chronic Heart Failure Caused by Ischemic Heart Disease: The Diagnostic Utility of Holter ECG Parameters

Background and Objectives: Chronic heart failure (CHF) caused by ischemic heart disease (IHD) is the leading cause of death worldwide and presents significant health challenges. Effective management of IHD requires prevention, early detection, and treatment to improve patient outcomes. This study aims to expand the diagnostic utility of various 24 h Holter ECG parameters, such as T-wave alternans (TWA), late ventricular potentials (LVPs), and heart rate variability (HRV) in patients with CHF caused by IHD. Additionally, we seek to explore the association between these parameters and other comorbid conditions affecting the prognosis of CHF patients. Materials and Methods: We conducted a prospective case-control study with 150 patients divided into two subgroups: 100 patients with CHF caused by IHD, and 50 patients in the control group. Data included medical history, physical examination, laboratory tests, echocardiography, and 24 h Holter monitoring. Results: Our comparative analysis demonstrated that both TWA and LVPs were significantly higher in patients with CHF compared to the control group (p < 0.01), indicating increased myocardial electrical vulnerability in CHF patients. Both time and frequency-domain HRV parameters were significantly lower in the CHF group. However, the ratio of NN50 to the total count of NN intervals (PNN50) showed a borderline significance (p = 0.06). While the low-frequency (LF) domain was significantly lower in CHF patients, the high-frequency (HF) domain did not differ significantly between groups. Acceleration and deceleration capacities were also significantly altered in CHF patients. Categorizing CHF patients by left ventricular ejection fraction (LVEF) revealed that the mean of the 5-min normal-to-normal intervals over the complete recording (SDNN Index) was significantly higher in patients with LVEF ≥ 50% compared to those with CHF with reduced EF and CHF with mildly reduced EF (p < 0.001), whereas the other HRV parameters showed no significant differences among the groups. Conclusions: Holter ECG parameters can become a reliable tool in the assessment of patients with CHF. The integration of multiple Holter ECG parameters, such as TWA, LVPs, and HRV, can significantly enhance the diagnostic assessment of CHF caused by IHD. This comprehensive approach allows for a more nuanced understanding of the patient's condition and potential outcomes.

How to properly evaluate cardiac vagal tone in oncology studies: a state-of-the-art review

Heart rate variability (HRV) analysis provides an assessment of cardiac vagal tone and consequently global cardiac health as well as systemic condition. In systemic diseases such as cancer and during treatments that affect the whole body, like chemotherapy, the vagus nerve activity is low and deregulated. Some studies focus on using HRV to predict mortality in oncology. However, in cancer patients, systemic alterations substantially increase artifacts during HRV measurement, especially atrial ectopic beats. Moreover, HRV may be altered by various factors (duration and time of measurement, breathing, drugs, and other confounding factors) that alter each metric in different ways. The Standard Deviation of all Normal to Normal intervals (SDNN) is the most commonly used metric to evaluate HRV in oncology, but it does not appear to be specific to the cardiac vagal tone. Thus, cardiac vagal activity diagnosis and vital prognosis of cancer patients can be biased. Our review presents the main HRV metrics that can be currently used in oncology studies and their links with vagus nerve and cancer. We present the influence of external factors and the required duration and time of measurement. Considering all these parameters, this review proposes seven key points for an assessment of HRV and cardiac vagal tone in patients with cancer.

Harmony in Chaos: Deciphering the Influence of Ischemic Cardiomyopathy and Non-Cardiac Comorbidities on Holter ECG Parameters in Chronic Heart Failure Patients: A Pilot Study

Background and Objective: In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators. Materials and Methods: In this prospective inquiry, a cohort of 60 individuals diagnosed with heart failure underwent stratification into subgroups based on the presence of comorbidities, including diabetes, chronic kidney disease, obesity, or hyperuricemia. Upon admission, a thorough evaluation of all participants encompassed echocardiography, laboratory panel analysis, and 24 h Holter monitoring. Results: Significant associations were uncovered between diabetes and unconventional physiological indicators, specifically the Triangular index (p = 0.035) and deceleration capacity (p = 0.002). Pertaining to creatinine clearance, notable correlations surfaced with RMSSD (p = 0.026), PNN50 (p = 0.013), and high-frequency power (p = 0.026). An examination of uric acid levels and distinctive Holter ECG patterns unveiled statistical significance, particularly regarding the deceleration capacity (p = 0.045). Nevertheless, in the evaluation of the Body Mass Index, no statistically significant findings emerged concerning Holter ECG parameters. Conclusions: The identified statistical correlations between non-cardiac comorbidities and patterns elucidated in Holter ECG recordings underscore the heightened diagnostic utility of this investigative modality in the comprehensive evaluation of individuals grappling with HF. Furthermore, we underscore the critical importance of the thorough analysis of Holter ECG recordings, particularly with regard to subtle and emerging parameters that may be overlooked or insufficiently acknowledged.

Cardiac deceleration capacity is associated with severity of inflammation in COVID-19

PURPOSE

In this pilot study, we investigated the cardiac autonomic activity of coronavirus disease 2019 (COVID-19)-infected hospitalized patients. COVID-19 is characterized by cough, fever, and dyspnea, which in some severe cases can lead to hypoxia, respiratory failure, and shock. Since breathing disorders and pulmonary diseases are tightly linked to autonomic dysfunction, we analyzed the cardiac autonomic activity by measuring the deceleration capacity (DC) in COVID-19 patients.

METHODS

In 14 adults (4 men and 10 women) with a median age of 63.5 years and positive for SARS-CoV-2 by polymerase chain reaction (PCR) with severe symptoms requiring hospital treatment, a high-resolution digital 30 min electrocardiogram (ECG) in Frank leads configuration was performed in a resting supine position within the first 48 h after hospital admission. DC was assessed using validated software and associated with several markers of inflammation and clinical course.

RESULTS

The study revealed a significant association between reduced DC (≤ 2.5 ms) and older age (74 years) in COVID-19 patients, compared to those with a higher DC > 2.5 ms (56.5 years). However, the duration of hospitalization was similar for both groups. There was a nonsignificant trend towards a higher maximum viral load in patients with reduced DC. Further, patients with a DC ≤ 2.5 ms showed higher levels of inflammatory markers such as C-reactive protein (CRP) and procalcitonin (PCT), as well as leukocytosis, compared to patients with a DC > 2.5 ms. Also, the COVID-19-severity marker ferritin was significantly elevated in patients with lower DC. Other markers associated with COVID-19, such as lactate dehydrogenase (LDH) and creatine kinase (CK), exhibited comparable levels in both groups.

CONCLUSIONS

Reduced DC (≤ 2.5 ms) was significantly associated with older age, increased inflammatory markers, and elevated ferritin in patients with COVID-19. These findings suggest that DC might serve as a valuable indicator for predicting the risk of severe inflammation in COVID-19 and possibly complications associated with this disease, such as heart failure. Further studies are needed to confirm these observations and clarify the clinical significance of DC in COVID-19 and other infectious diseases.

Electrophysiological properties and heart rate variability of patients with thalassemia major in Jakarta, Indonesia

Beta thalassemia major (TM) is a common hereditary disease in Indonesia. Iron overload due to regular transfusion may induce myocardial iron deposition leading to electrophysiological dysfunction and functional disorders of the heart. Ventricular arrhythmia is one of the most common causes of sudden cardiac death in thalassemia patients. This cross-sectional study of 62 TM patients aged 10-32 years in Cipto Mangunkusumo General Hospital was done to assess their electrophysiological properties and heart rate variability, including 24- hour Holter monitoring, signal averaged electrocardiogram (SAECG) for detection of ventricular late potential (VLP), and determination of heart rate variability (HRV). We also assessed their 12-lead ECG parameters, such as P wave, QRS complex, QT/ QTc interval, QRS dispersion, and QT/ QTc dispersion. Iron overload was defined by T2-star magnetic resonance (MR-T2*) values of less than 20 ms or ferritin level greater than 2500 ng/mL. Subjects were grouped accordingly. There were significant differences of QTc dispersion (p = 0.026) and deceleration capacity (p = 0.007) between MR-T2* groups. Multivariate analysis showed an inverse correlation between QTc dispersion and MR-T2* values. There was a proportional correlation between heart rate deceleration capacity in the low MR-T2* group (p = 0.058) and the high ferritin group (p = 0.007). No VLPs were detectable in any patients. In conclusion, prolonged QTc dispersion and decreased heart rate deceleration capacity were significantly correlated with greater odds of iron overload among patients with Thalassemia major.

Autonomic Dysfunction during Acute SARS-CoV-2 Infection: A Systematic Review

Although autonomic dysfunction (AD) after the recovery from Coronavirus disease 2019 (COVID-19) has been thoroughly described, few data are available regarding the involvement of the autonomic nervous system (ANS) during the acute phase of SARS-CoV-2 infection. The primary aim of this review was to summarize current knowledge regarding the AD occurring during acute COVID-19. Secondarily, we aimed to clarify the prognostic value of ANS involvement and the role of autonomic parameters in predicting SARS-CoV-2 infection. According to the PRISMA guidelines, we performed a systematic review across Scopus and PubMed databases, resulting in 1585 records. The records check and the analysis of included reports’ references allowed us to include 22 articles. The studies were widely heterogeneous for study population, dysautonomia assessment, and COVID-19 severity. Heart rate variability was the tool most frequently chosen to analyze autonomic parameters, followed by automated pupillometry. Most studies found ANS involvement during acute COVID-19, and AD was often related to a worse outcome. Further studies are needed to clarify the role of autonomic parameters in predicting SARS-CoV-2 infection. The evidence emerging from this review suggests that a complex autonomic nervous system imbalance is a prominent feature of acute COVID-19, often leading to a poor prognosis.

Heart rate variability comparison between young males after 4-6 weeks from the end of SARS-CoV-2 infection and controls

Due to the prolonged inflammatory process induced by infection of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), indices of autonomic nervous system dysfunction may persist long after viral shedding. Previous studies showed significant changes in HRV parameters in severe (including fatal) infection of SARS-CoV-2. However, few studies have comprehensively examined HRV in individuals who previously presented as asymptomatic or mildly symptomatic cases of COVID-19. In this study, we examined HRV in asymptomatic or mildly symptomatic individuals 5–7 weeks following positive confirmation of SARS-CoV-2 infection. Sixty-five ECG Holter recordings from young (mean age 22.6 ± 3.4 years), physically fit male subjects 4–6 weeks after the second negative test (considered to be the start of recovery) and twenty-six control male subjects (mean age 23.2 ± 2.9 years) were considered in the study. Night-time RR time series were extracted from ECG signals. Selected linear as well as nonlinear HRV parameters were calculated. We found significant differences in Porta’s symbolic analysis parameters V0 and V2 (p < 0.001), α₂ (p < 0.001), very low-frequency component (VLF; p = 0.022) and respiratory peak (from the PRSA method; p = 0.012). These differences may be caused by the changes of activity of the parasympathetic autonomic nervous system as well as by the coupling of respiratory rhythm with heart rate due to an increase in pulmonary arterial vascular resistance. The results suggest that the differences with the control group in the HRV parameters, that reflect the functional state of the autonomic nervous system, are measurable after a few weeks from the beginning of the recovery even in the post-COVID group—a young and physically active population. We indicate HRV sensitive markers which may be used in long-term monitoring of patients after recovery.

Chaotic and stochastic dynamics of epileptiform-like activities in sclerotic hippocampus resected from patients with pharmacoresistant epilepsy

The types of epileptiform activity occurring in the sclerotic hippocampus with highest incidence are interictal-like events (II) and periodic ictal spiking (PIS). These activities are classified according to their event rates, but it is still unclear if these rate differences are consequences of underlying physiological mechanisms. Identifying new and more specific information related to these two activities may bring insights to a better understanding about the epileptogenic process and new diagnosis. We applied Poincaré map analysis and Recurrence Quantification Analysis (RQA) onto 35 in vitro electrophysiological signals recorded from slices of 12 hippocampal tissues surgically resected from patients with pharmacoresistant temporal lobe epilepsy. These analyzes showed that the II activity is related to chaotic dynamics, whereas the PIS activity is related to deterministic periodic dynamics. Additionally, it indicates that their different rates are consequence of different endogenous dynamics. Finally, by using two computational models we were able to simulate the transition between II and PIS activities. The RQA was applied to different periods of these simulations to compare the recurrences between artificial and real signals, showing that different ranges of regularity-chaoticity can be directly associated with the generation of PIS and II activities.

Temporal lobe epilepsy (TLE) is the most prevalent type of epilepsy in adults and hippocampal sclerosis is the major pathophysiological substrate of pharmaco-refractory TLE. Different patterns of epileptiform-like activity have been described in human hippocampal sclerosis, but the standard analysis applied to characterize the activities usually do not consider the nonlinear features that epileptiform patterns exhibit. Here, using Poincaré map and Recurrence Quantitative Analysis we characterized the most prevalent type of epileptiform-like activities—interictal-like events (II) and periodic ictal spiking (PIS), recorded in vitro from resected hippocampi of pharmacoresistant patients with TLE—according to their levels of stochasticity, chaoticity and determinism. The II activities showed to be more chaotic with complex rhythmicity than PIS activities. The nonlinear dynamic differences between II and PIS leads us to conjecture that they are expressions of different seizure susceptibility. We also identified that each hippocampal subfield expresses II and PIS activities in a specific and different way. Finally, from the modulation of internal parameters of two computational models, we show the conversion of one type of activity into the other, showing how specific neuron networks synchronize over time, leading to II and PIS activities and then into a generalized seizure.

Altered Heart Rate Variability Early in ICU Admission Differentiates Critically Ill Coronavirus Disease 2019 and All-Cause Sepsis Patients

IMPORTANCE

Altered heart rate variability has been associated with autonomic dysfunction in a number of disease profiles, in this work we elucidate differences in the biomarker among patients with all-cause sepsis and coronavirus disease 2019.

OBJECTIVES

To measure heart rate variability metrics in critically ill coronavirus disease 2019 patients with comparison to all-cause critically ill sepsis patients.

DESIGN SETTING AND PARTICIPANTS

Retrospective analysis of coronavirus disease 2019 patients admitted to an ICU for at least 24 hours at any of Emory Healthcare ICUs between March 2020 and April 2020 up to 5 days of ICU stay. The comparison group was a cohort of all-cause sepsis patients prior to coronavirus disease 2019 pandemic.

MAIN OUTCOMES AND MEASURES

Continuous waveforms were captured from the patient monitor. The electrocardiogram was then analyzed for each patient over a 300 seconds observational window that was shifted by 30 seconds in each iteration from admission till discharge. A total of 23 heart rate variability metrics were extracted in each iteration. We use the Kruskal-Wallis and Steel-Dwass tests (p < 0.05) for statistical analysis and interpretations of heart rate variability multiple measures.

RESULTS

A total of 141 critically ill coronavirus disease 2019 patients met inclusion criteria, who were compared with 208 patients with all-cause sepsis. Three nonlinear markers, including the ratio of standard deviation derived from the Poincaré plot, sample entropy, and approximate entropy and four linear features, including mode of beat-to-beat interval, acceleration capacity, deceleration capacity, and the proportion of consecutive RR intervals that differ by more than 50 ms, were all statistically significant (p < 0.05) between the coronavirus disease 2019 and all-cause sepsis cohorts. The three nonlinear features and acceleration capacity, deceleration capacity, and beat-to-beat interval (mode) were statistically significant (p < 0.05) when comparing pairwise analysis among the combinations of survivors and nonsurvivors between the coronavirus disease 2019 and sepsis cohorts. Temporal analysis of the main markers showed low variability across the 5 days of analysis compared with sepsis patients.

CONCLUSIONS AND RELEVANCE

In this descriptive statistical study, heart rate variability measures were found to be statistically different across critically ill patients infected with severe acute respiratory syndrome coronavirus 2 and distinct from bacterial sepsis.

Quantifying the Autonomic Response to Stressors-One Way to Expand the Definition of "Stress" in Animals

Quantifying how whole organisms respond to challenges in the external and internal environment ("stressors") is difficult. To date, physiological ecologists have mostly used measures of glucocorticoids (GCs) to assess the impact of stressors on animals. This is of course too simplistic as Hans Seyle himself characterized the response of organisms to "noxious stimuli" using multiple physiological responses. Possible solutions include increasing the number of biomarkers to more accurately characterize the "stress state" of animal or just measuring different biomarkers to more accurately characterize the degree of acute or chronic stressors an animal is experiencing. We focus on the latter and discuss how heart rate (HR) and heart rate variability (HRV) may be better predictors of the degree of activation of the sympathetic-adrenal-medullary system and complement or even replace measures of GCs as indicators of animal health, welfare, fitness, or their level of exposure to stressors. The miniaturization of biological sensor technology ("bio-sensors" or "bio-loggers") presents an opportunity to reassess measures of stress state and develop new approaches. We describe some modern approaches to gathering these HR and HRV data in free-living animals with the aim that heart dynamics will be more integrated with measures of GCs as bio-markers of stress state and predictors of fitness in free-living animals.

Anticipation of ventricular tachyarrhythmias by a novel mathematical method: Further insights towards an early warning system in implantable cardioverter defibrillators

Implantable cardioverter defibrillators (ICD) are the most effective therapy to terminate malignant ventricular arrhythmias (VA) and therefore to prevent sudden cardiac death. Until today, there is no way to predict the onset of such VA. Our aim was to develop a mathematical model that could predict VA in a timely fashion. We analyzed the time series of R-R intervals from 3 groups. Two groups from the Spontaneous Ventricular Tachyarrhythmia Database (v 1.0) were analyzed from a set of 81 pairs of R-R interval time series records from patients, each pair containing one record before the VT episode (Dataset 1A) and one control record which was obtained during the follow up visit (Dataset 1B). A third data set was composed of the R-R interval time series of 54 subjects without a significant arrhythmia heart disease (Dataset 2). We developed a new method to transform a time series into a network for its analysis, the ε-regular graphs. This novel approach transforms a time series into a network which is sensitive to the quantitative properties of the time series, it has a single parameter (ε) to be adjusted, and it can trace long-range correlations. This procedure allows to use graph theory to extract the dynamics of any time series. The average of the difference between the VT and the control record graph degree of each patient, at each time window, reached a global minimum value of -2.12 followed by a drastic increase of the average graph until reaching a local maximum of 5.59. The global minimum and the following local maxima occur at the windows 276 and 393, respectively. This change in the connectivity of the graphs distinguishes two distinct dynamics occurring during the VA, while the states in between the 276 and 393, determine a transitional state. We propose this change in the dynamic of the R-R intervals as a measurable and detectable "early warning" of the VT event, occurring an average of 514.625 seconds (8:30 minutes) before the onset of the VT episode. It is feasible to detect retrospectively early warnings of the VA episode using their corresponding ε-regular graphs, with an average of 8:30 minutes before the ICD terminates the VA event.

Predictive value of heart rate deceleration capacity on coronary artery lesion in acute phase of Kawasaki disease

This study was to investigate the correlation of vagal activity with coronary artery lesion (CAL) in Kawasaki disease (KD) children, and assess the predictive value of heart rate deceleration capacity (DC) for CAL in acute phase of KD.50 KD children with CAL, 130 KD children without CAL, 30 children with acute upper respiratory infection and 100 healthy children were recruited and indicators reflecting vagal activity including DC were measstuogram. KD children with CAL showed decreased vagal activity with significantly lower values of DC. DC was negatively correlated with levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and C-reactive protein (CRP) in KD children. DC was a usable cardiac electrophysiological index to predict CAL in children with KD, with an area under the receiver operating characteristic curve (AUC) of 0.741. The cut-off value of DC for predicting CAL in KD children was 4.37 ms. DC was an independent predictor of CAL in children with KD, evaluated by multiple logistic regression analysis, KD children with DC ≤ 4.37 ms had an increased risk of CAL, with odds ratios (OR) of 5.94. Our study illustrates DC could be used to predict CAL in acute phase of KD.

Heart Rhythm Complexity Predicts Long-Term Cardiovascular Outcomes in Peritoneal Dialysis Patients: A Prospective Cohort Study

Background Cardiovascular disease is the leading cause of morbidity and mortality in patients with end-stage renal disease. Heart rhythm complexity analysis has been shown to be useful in predicting outcomes in various diseases; however, data on patients with end-stage renal disease are limited. In this study, we analyzed the association between heart rhythm complexity and long-term cardiovascular outcomes in patients with end-stage renal disease receiving peritoneal dialysis. Methods and Results We prospectively enrolled 133 patients receiving peritoneal dialysis and analyzed linear heart rate variability and heart rhythm complexity variables including detrended fluctuation analysis (DFA) and multiscale entropy. The primary outcome was cardiovascular mortality, and the secondary outcome was the occurrence of major adverse cardiovascular events. After a median of 6.37 years of follow-up, 21 patients (22%) died from cardiovascular causes. These patients had a significantly lower low-frequency band of heart rate variability, low/high-frequency band ratio, total power band of heart rate variability, heart rate turbulence slope, deceleration capacity, short-term DFA (DFAα1); and multiscale entropy slopes 1 to 5, scale 5, area 1 to 5, and area 6 to 20 compared with the patients who did not die from cardiovascular causes. Time-dependent receiver operating characteristic curve analysis showed that DFAα1 had the greatest discriminatory power for cardiovascular mortality (area under the curve: 0.763) and major adverse cardiovascular events (area under the curve: 0.730). The best cutoff value for DFAα1 was 0.98 to predict both cardiovascular mortality and major adverse cardiovascular events. Multivariate Cox regression analysis showed that DFAα1 (hazard ratio: 0.076; 95% CI, 0.016-0.366; P=0.001) and area 1 to 5 (hazard ratio: 0.645; 95% CI, 0.447-0.930; P=0.019) were significantly associated with cardiovascular mortality. Conclusions Heart rhythm complexity appears to be a promising noninvasive tool to predict long-term cardiovascular outcomes in patients receiving peritoneal dialysis.

Theoretical Value of Deceleration Capacity Points to Deceleration Reserve of Fetal Heart Rate

OBJECTIVE

The interpretation of Average Acceleration and Deceleration Capacities (AC/DC), computed through Phase-Rectified Signal Averaging (PRSA), in intrapartum fetal heart rate (FHR) monitoring is still matter of investigation. We aimed to elucidate some behaviors of AC/DC.

METHODS

We derived the theoretical value of PRSA for stationary stochastic Gaussian processes and proved that for these time series AC and DC are necessarily identical in absolute value. The difference between DC and AC, termed Deceleration Reserve (DR), was introduced to detect signal's asymmetric trends. DR was tested on FHR signals from: near-term pregnant sheep model of labor consisting of chronically hypoxic and normoxic fetuses with both groups developing acidemia due to umbilical cord occlusions (UCO); and the CTU-UHB dataset containing fetal CTG recordings collected during labor of newborns that resulted acidotic and non-acidotic, respectively. DR was compared with AC and DC in terms of discriminatory power (AUC), between the groups, after correcting for signal power or deceleration area, respectively.

RESULTS

DR displayed higher discriminatory power on the animal model during severe acidemia, with respect to AC/DC ( ) but also distinguished correctly all chronically hypoxic from normoxic fetuses at baseline prior to UCO. DR also outperformed AC/DC on the CTU-UHB dataset in distinguishing acidemic fetuses at birth (AUC: 0.65).

CONCLUSION

Theoretical results motivated the introduction of DR, that proved to be superior than AC/DC for risk stratification during labor.

SIGNIFICANCE

DR, measured during labor, might permit to distinguish acidemic fetuses due to their different autonomic regulation, paving the way for new monitoring strategies.

A refined method of quantifying deceleration capacity index for heart rate variability analysis

Background

Phase-rectified signal averaging (PRSA) was often applied to assess the cardiac vagal modulation. Despite its broad use, this method suffers from the confounding effects of anomalous variants of sinus rhythm. This study aimed to improve the original PRSA method in deceleration capacity (DC) quantification.

Methods

The refined deceleration capacity (DC_ref) was calculated by excluding from non-vagally mediated abnormal variants of sinus rhythms. Holter recordings from 202 healthy subjects and 51 patients with end-stage renal disease (ESRD) have been used for validity. The DC_ref was compared to original DC (DC_org) by the area under receiver operating characteristic curve.

Results

Experimental results demonstrate that the original and refined DCs calculated from 24-h, 2-h, and 30-min Holter recordings are significantly lower in patients with ESRD than those in the healthy group. In receiver operating characteristic curve analysis, the DC_ref provides better performance than the DC_org in distinguishing between the patients with ESRD and healthy control subjects. Furthermore, the refined PRSA technique enhances the low frequency and attenuates high frequency components for spectral analysis in ESRD patients.

Conclusions

The DC_ref appears to reduce the influence of non-vagally mediated abnormal variants of sinus rhythm and highlighting the pathological influence. DC_ref, especially assessed from short-term electrocardiography recordings, may be complementary to existing autonomic function assessment, risk stratification, and efficacy prediction strategies.

Male Patients With Dilated Cardiomyopathy Exhibiting a Higher Heart Rate Acceleration Capacity or a Lower Deceleration Capacity Are at Higher Risk of Cardiac Death

The effects of dilated cardiomyopathy (DCM) on cardiac autonomic regulation and electrophysiology, and the consequences of such changes, remain unclear. We evaluated the associations between heart rate acceleration capacity (AC) and deceleration capacity (DC), heart structural and functional changes, and cardiac death in 202 healthy controls and 100 DCM patients. The DC was lower and the AC was higher in DCM patients (both males and females). Multivariable, linear, logistic regression analyses revealed that in males, age was positively associated with AC in healthy controls (N = 85); the left atrial diameter (LAD) was positively and the left ventricular ejection fraction (LVEF) was negatively associated with AC in DCM patients (N = 65); age was negatively associated with DC in healthy controls (N = 85); and the LAD was negatively and the LVEF was positively associated with DC in DCM patients (N = 65). In females, only age was associated with either AC or DC in healthy controls (N = 117). Kaplan–Meier analysis revealed that male DCM patients with greater LADs (≥46.5 mm) (long-rank chi-squared value = 11.1, P = 0.001), an elevated AC (≥-4.75 ms) (log-rank chi-squared value = 6.8, P = 0.009), and a lower DC (≤4.72 ms) (log-rank chi-squared value = 9.1, P = 0.003) were at higher risk of cardiac death within 60 months of follow-up. In conclusion, in males, DCM significantly affected both the AC and DC; a higher AC or a lower DC increased the risk of cardiac death.

Model Selection for Body Temperature Signal Classification Using Both Amplitude and Ordinality-Based Entropy Measures

Many entropy-related methods for signal classification have been proposed and exploited successfully in the last several decades. However, it is sometimes difficult to find the optimal measure and the optimal parameter configuration for a specific purpose or context. Suboptimal settings may therefore produce subpar results and not even reach the desired level of significance. In order to increase the signal classification accuracy in these suboptimal situations, this paper proposes statistical models created with uncorrelated measures that exploit the possible synergies between them. The methods employed are permutation entropy (PE), approximate entropy (ApEn), and sample entropy (SampEn). Since PE is based on subpattern ordinal differences, whereas ApEn and SampEn are based on subpattern amplitude differences, we hypothesized that a combination of PE with another method would enhance the individual performance of any of them. The dataset was composed of body temperature records, for which we did not obtain a classification accuracy above 80% with a single measure, in this study or even in previous studies. The results confirmed that the classification accuracy rose up to 90% when combining PE and ApEn with a logistic model.

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

OBJECTIVE

Epilepsy and seizures can have dramatic effects on cardiac function. The aim of the present study was to investigate deceleration capacity, acceleration capacity and their 24-h fluctuations of heart rate variability in patients with drug-resistant epilepsy.

METHODS

Deceleration capacity, acceleration capacity of heart rate and their 24-h dynamics derived from the phase rectified signal averaging method as well as traditional measures were analyzed in 39 patients with drug-resistant epilepsy and 33 healthy control subjects using 24-h electrocardiogram recordings. The discriminatory power of heart rate variability measures were validated by assessment of the area under the receiver operating characteristic curve. Net reclassification improvement and integrated discrimination improvement models were also estimated.

RESULTS

Both deceleration capacity and absolute values of acceleration capacity were significantly lower in patients with drug-resistant epilepsy. The abnormal suppression of absolute deceleration capacity and acceleration capacity values were observed throughout the 24-h recording time (peaked at about 3 to 5 A.M.). Deceleration capacity had the greatest discriminatory power to differentiate the patients from the healthy controls. Moreover, in both net reclassification improvement and integrated discrimination improvement models, the combination of acceleration capacity or deceleration capacity with traditional heart rate variability measures has greater discriminatory power than any of the single heart rate variability features.

INTERPRETATION

Drug-resistant epilepsy was associated with a significant inhibition of vagal modulation of heart rate, which was more pronounced during the night than during the day. These findings indicate that phase rectified signal averaging method may serve as a complementary approach for characterizing and understanding the neuro-pathophysiology in epilepsy, and may provide a new clue to sudden unexpected death in epilepsy.

Autonomic function as indicated by heart rate deceleration capacity and deceleration runs in type 2 diabetes patients with or without essential hypertension

Purpose

Sympathovagal imbalance is a common underlying disorder in hypertension and diabetes. This study characterized autonomic nervous system function, indicated by heart rate deceleration capacity (DC) and deceleration runs (DRs), in patients with type 2 diabetes mellitus (T2DM), with or without concomitant essential hypertension.

Subjects and methods

We recruited 50 healthy subjects, 50 patients with T2DM, and 95 with T2DM and essential hypertension. DC, DRs (DR₂, DR₄, and DR₈, ie, episodes of 2, 4, or 8 consecutive beat-to-beat heart rate decelerations, respectively), and heart rate variability were determined by dynamic electrocardiogram. Biochemical markers of glucose and lipid metabolism, including glycated hemoglobin (HbA1c) and high-density lipoprotein cholesterol (HDL-C), were measured from blood samples.

Results

Both T2DM groups featured lower DC, SD of all normal-to-normal sinus RR intervals over 24 h (SDNN), root mean square of the successive normal sinus RR interval difference, and all DR values, but higher average heart rate (AHR) and acceleration capacity (AC), than healthy subjects. There were significant associations between the following: DC and HbA1c, systolic blood pressure (SBP), AHR, age, and HDL-C; DR₂ and AHR, SBP, and HbA1c; DR₄ and HbA1c, age, SBP, and HDL-C; and DR₈ and HbA1c, AHR, and age. In both T2DM groups, HbA1c correlated negatively with DC, DR₂, and SDNN, and positively with AC and AHR; homeostasis model assessment-insulin resistance index correlated negatively with DC, all DRs, and SDNN, and positively with AC.

Conclusion

Compared with healthy subjects, T2DM patients with or without essential hypertension have lower DC and DRs. DC and DRs correlate negatively with blood glucose and insulin resistance index.

Low heart deceleration capacity imply higher atrial fibrillation-free rate after ablation

How deceleration capacity (DC) and acceleration capacity (AC) of heart rate associated with atrial fibrillation (AF) and ablation is still not clear. The dynamic changes of AC, DC and conventional heart rate variability (HRV) parameters were characterized in 154 subjects before circumferential pulmonary veins isolation (CPVI) and three days, 3 months and 6 months after CPVI. The DCs of the recurrent group decreased significantly at each time point after CPVI; the DCs of the recurrence-free group before CPVI and three days, 3 months and 6 months after CPVI were 7.06 ± 1.77, 3.79 ± 1.18, 4.22 ± 1.96 and 3.97 ± 0.98 ms respectively, which also decreased significantly at each time point and were significantly lower than these of recurrent group. Conversely, the AC of recurrent and recurrence-free groups increased significantly at each time point after CPVI; the ACs of recurrence-fee group were significantly higher than these of recurrent group at each time point. No stable difference trend of HRV parameters was found between two groups. Further Kaplan–Meier analysis showed that DC < 4.8 ms or AC ≥ −5.1 ms displayed significant higher recurrence-free rates. In conclusion, high AC and low DC imply higher AF-free rate after ablation.

Bidirectional Cardio-Respiratory Interactions in Heart Failure

We investigated cardio-respiratory coupling in patients with heart failure by quantification of bidirectional interactions between cardiac (RR intervals) and respiratory signals with complementary measures of time series analysis. Heart failure patients were divided into three groups of twenty, age and gender matched, subjects: with sinus rhythm (HF-Sin), with sinus rhythm and ventricular extrasystoles (HF-VES), and with permanent atrial fibrillation (HF-AF). We included patients with indication for implantation of implantable cardioverter defibrillator or cardiac resynchronization therapy device. ECG and respiratory signals were simultaneously acquired during 20 min in supine position at spontaneous breathing frequency in 20 healthy control subjects and in patients before device implantation. We used coherence, Granger causality and cross-sample entropy analysis as complementary measures of bidirectional interactions between RR intervals and respiratory rhythm. In heart failure patients with arrhythmias (HF-VES and HF-AF) there is no coherence between signals (p < 0.01), while in HF-Sin it is reduced (p < 0.05), compared with control subjects. In all heart failure groups causality between signals is diminished, but with significantly stronger causality of RR signal in respiratory signal in HF-VES. Cross-sample entropy analysis revealed the strongest synchrony between respiratory and RR signal in HF-VES group. Beside respiratory sinus arrhythmia there is another type of cardio-respiratory interaction based on the synchrony between cardiac and respiratory rhythm. Both of them are altered in heart failure patients. Respiratory sinus arrhythmia is reduced in HF-Sin patients and vanished in heart failure patients with arrhythmias. Contrary, in HF-Sin and HF-VES groups, synchrony increased, probably as consequence of some dominant neural compensatory mechanisms. The coupling of cardiac and respiratory rhythm in heart failure patients varies depending on the presence of atrial/ventricular arrhythmias and it could be revealed by complementary methods of time series analysis.

Collaborative care model improves self-care ability, quality of life and cardiac function of patients with chronic heart failure

Chronic heart failure (CHF) is a common chronic disease that requires much care. This study aimed to explore the effects of collaborative care model (CCM) on patients with CHF. A total of 114 CHF patients were enrolled in this study, and were randomly and equally divided into two groups: control and experimental. Patients in the two groups received either usual care or CCM for 3 continuous months. The impacts of CCM on the self-care ability and quality of life were assessed using self-care of heart failure index and short form health survey 12, respectively. Further, cardiac function was assessed by measuring left ventricular ejection fraction (LVEF) and the level of N-terminal pro-B-type natriuretic peptide (NT-proBNP), and by the 6-min walking test. Clinical and demographic characteristics of patients in the control and CCM groups were statistically equivalent. Compared with usual care, CCM significantly enhanced self-care abilities of patients with CHF, including self-care maintenance, self-care management and self-care confidence (all P<0.05). The physical and mental quality of life was also significantly improved by CCM (P<0.01 or P<0.05). Compared with usual care, CCM significantly increased the LVEF (P<0.01), decreased the NT-proBNP level (P<0.01), and enhanced exercise capacity (P<0.001). In conclusion, CCM improved the self-care, quality of life and cardiac function of patients with CHF compared with usual care.

Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks

Ventricular tachycardia (VT) is a potentially fatal tachyarrhythmia, which causes a rapid heartbeat as a result of improper electrical activity of the heart. This is a potentially life-threatening arrhythmia because it can cause low blood pressure and may lead to ventricular fibrillation, asystole, and sudden cardiac death. To prevent VT, we developed an early prediction model that can predict this event one hour before its onset using an artificial neural network (ANN) generated using 14 parameters obtained from heart rate variability (HRV) and respiratory rate variability (RRV) analysis. De-identified raw data from the monitors of patients admitted to the cardiovascular intensive care unit at Asan Medical Center between September 2013 and April 2015 were collected. The dataset consisted of 52 recordings obtained one hour prior to VT events and 52 control recordings. Two-thirds of the extracted parameters were used to train the ANN, and the remaining third was used to evaluate performance of the learned ANN. The developed VT prediction model proved its performance by achieving a sensitivity of 0.88, specificity of 0.82, and AUC of 0.93.

Maternal cardiac deceleration capacity: a novel insight into maternal autonomic function in pregnancies complicated by hypertensive disorders and intrauterine growth restriction

OBJECTIVE

To explore maternal cardiac deceleration capacity (DC), a marker of autonomic function derived from electrocardiographic (ECG) signals, in pregnancies complicated by intrauterine growth restriction (IUGR) and hypertensive disorders of pregnancy (HDP) associated to IUGR (HDP-IUGR) or to appropriate for gestational age fetal growth (HDP-AGAf).

METHODS

Prospective single center case-control study conducted at Buzzi Children's Hospital, Milan. Maternal ECGs were analyzed by Phase Rectified Signal Averaging (PRSA) method to obtain cardiac DC in women with: HDP-IUGR, HDP-AGAf, severe-IUGR, mild-IUGR and uncomplicated pregnancies. IUGR was defined as abdominal circumference <5th centile; severe-IUGR was associated with umbilical artery Doppler pulsatility index >2 standard deviations. Non-parametric tests were adopted.

RESULTS

269 women were recruited. Women with HDP-IUGR (n=35) showed significantly higher cardiac DC compared both to controls (n=141) (p=0.003) and women with HDP-AGAf (n=18) (p=0.01). Women with severe-IUGR (n=14) showed significantly higher DC than controls (p=0.01). Women with mild-IUGR (n=61) as well as women with HDP-AGAf showed no differences in DC compared to controls (both p=0.3).

CONCLUSIONS

Women with pregnancy complicated by severe placental failure, such as HDP-IUGR and severe IUGR, show significant autonomic alterations, as indicated by elevated cardiac DC. On the contrary, pregnancy complications such as HDP-AGAf and mild IUGR show no impact on maternal autonomic balance. We present a new approach to explore maternal autonomic cardiovascular regulation that might reflect the severity of placental vascular insufficiency.