Reduced ventricular response irregularity is associated with increased mortality in patients with chronic atrial fibrillation

Heart rate variability in patients with atrial fibrillation of sinus rhythm or atrial fibrillation: chaos or merit?

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia characterized by consistently irregular atrial and ventricular contractions. Heart rate variability (HRV) refers to the changes in the intervals between consecutive ventricular heartbeats. In sinus rhythm, HRV may be subtle and is quantitatively reflecting the dynamic interplay of the cardiac autonomic nervous system, which plays a crucial role in the onset, development, and maintenance of AF. HRV metrics, consisting of time-domain, frequency-domain, and nonlinear parameters, have been verified to vary significantly before and after AF episodes, and AF treatment-related procedures such as electrical cardioversion, ablation, and surgery of AF. Therefore, HRV may serve as a digital biomarker in predicting AF risk in long-term and acute risk period, identification of patients with AF risk in sinus rhythm and recurrence risk stratification after procedures. HRV in AF rhythm, predominantly influenced by dynamic atrioventricular node conduction under the onslaught of irregular atrial impulses, shows a huge disparity compared to that in sinus rhythm. Despite this, HRV in AF rhythm still provides valuable prognostic information, as reduced HRV may indicate a poor heart function and outcomes in patients with AF. Despite being influenced by lots of variables, HRV can still serve as an independent digital biomarker in the clinical management of AF throughout its entire lifecycle.

Complexity AF score as a novel marker of atrial fibrillation instability

Atrial fibrillation (AF) is a heart disease affecting millions of Americans. Clinicians evaluate AF-related risk by assessing the temporal pattern, variation, and severity of AF episodes through AF burden (AFB). However, existing prognostic tools based on these metrics are suboptimal, as they do not account for electrical complexity of AF signals. This study introduced Electrical Burden (EB) as a new marker to assess electrical instability and complexity of AF. We also developed a Complexity AF score that incorporates AFB, EB, and Poincaré analysis to assess the severity of AF. Electrocardiogram (ECG) from 50 AF patients in the Long-term AF database were analyzed. EB was calculated using four metrics and combined with AFB and Poincaré metrics to derive the Complexity AF score for each patient. Our results show that AFB, EB, and Poincaré metrics are independent markers, each describing different aspects of AF complexity. The Complexity AF score effectively distinguished between terminated (2.82 ± 1.29, 17 patients) and non-terminated AF groups (4 ± 1.46, 33 patients) (p-value < 0.05). This study emphasizes the importance of EB and Poincaré analysis as an indicator of electrical complexity of AF and highlights the utility of the Complexity AF score in accurately characterizing and stratifying AF to guide management.

Does obstructive sleep apnoea modulate cardiac autonomic function in paroxysmal atrial fibrillation?

PURPOSE

The autonomic nervous system may mediate acute apnoea-induced atrial fibrillation (AF). We compared cardiac autonomic function in paroxysmal atrial fibrillation (PAF) patients with and without obstructive sleep apnoea (OSA).

METHODS

Case control study of 101 patients with PAF recruited at two tertiary centres. All patients underwent in-laboratory polysomnography. ECG signal demonstrating "steady state" sinus rhythm (i.e. with arrhythmic beats and respiratory events excluded) was included in the analysis. Cardiac autonomic function was assessed via measures of heart rate variability (HRV) and reported by sleep stage (REM vs Non-REM) for patients with and without OSA.

RESULTS

Sixty-five (66.3%) of patients were male, mean age 61.5 ± 11.6 years, mean BMI 27.1 ± 4.3 kg/m². Global measures of HRV (triangular index, total power) did not differ between PAF patients with and without OSA in either REM or non-REM sleep. Frequency-domain analysis during non-REM sleep in PAF patients with OSA showed increased cardiac parasympathetic modulation (HF-nu: 39.1 ± 15.7 vs 48.0 ± 14.6, p = 0.008) and reduced cardiac sympathetic modulation (LF-nu 54.1 ± 19.7 vs 43.7 ± 18.0, p = 0.012, LF/HF ratio: 2.1 ± 2.0 vs 1.2 ± 1.0, p = 0.007). Results remained significant after adjusting for age, sex, and BMI (adjusted p values 0.024, 0.045 and 0.018 respectively). There were no differences in HRV parameters during REM sleep.

CONCLUSIONS

This is the first study of HRV in PAF patients with and without OSA. Our results indicate limited differences in HRV between groups. However, this work suggests a chronic increase in parasympathetic nervous modulation and relative reduction in sympathetic modulation in PAF patients with OSA during steady-state non-REM sleep.

Is the Median Hourly Ambulatory Heart Rate Range Helpful in Stratifying Mortality Risk among Newly Diagnosed Atrial Fibrillation Patients?

Background: The application of heart rate variability is problematic in patients with atrial fibrillation (AF). This study aims to explore the associations between all-cause mortality and the median hourly ambulatory heart rate range (AHRR˜24hr) compared with other parameters obtained from the Holter monitor in patients with newly diagnosed AF. Material and Methods: A total of 30 parameters obtained from 521 persistent AF patients’ Holter monitor were analyzed retrospectively from 1 January 2010 to 31 July 2014. Every patient was followed up to the occurrence of death or the end of 30 June 2017. Results:AHRR˜24hr was the most feasible Holter parameter. Lower AHRR˜24hr was associated with increased risk of all-cause mortality (adjusted hazard ratio [aHR] for every 10-bpm reduction: 2.70, 95% confidence interval [CI]: 1.75–4.17, p < 0.001). The C-statistic of AHRR˜24hr alone was 0.707 (95% CI: 0.658–0.756), and 0.697 (95% CI: 0.650–0.744) for the CHA2DS2-VASc score alone. By combining AHRR˜24hr with the CHA2DS2-VASc score, the C-statistic could improve to 0.764 (95% CI: 0.722–0.806). While using 20 bpm as the cut-off value, the aHR was 3.66 (95% CI: 2.05–6.52) for patients with AHRR˜24hr < 20 bpm in contrast to patients with AHRR˜24hr ≥ 20 bpm. Conclusions:AHRR˜24hr could be helpful for risk stratification for AF in addition to the CHA2DS2-VASc score.

Comparison among random forest, logistic regression, and existing clinical risk scores for predicting outcomes in patients with atrial fibrillation: A report from the J-RHYTHM registry

Background

Machine learning (ML) has emerged as a promising tool for risk stratification. However, few studies have applied ML to risk assessment of patients with atrial fibrillation (AF).

Hypothesis

We aimed to compare the performance of random forest (RF), logistic regression (LR), and conventional risk schemes in predicting the outcomes of AF.

Methods

We analyzed data from 7406 nonvalvular AF patients (median age 71 years, female 29.2%) enrolled in a nationwide AF registry (J‐RHYTHM Registry) and who were followed for 2 years. The endpoints were thromboembolisms, major bleeding, and all‐cause mortality. Models were generated from potential predictors using an RF model, stepwise LR model, and the thromboembolism (CHADS₂ and CHA₂DS₂‐VASc) and major bleeding (HAS‐BLED, ORBIT, and ATRIA) scores.

Results

For thromboembolisms, the C‐statistic of the RF model was significantly higher than that of the LR model (0.66 vs. 0.59, p = .03) or CHA₂DS₂‐VASc score (0.61, p < .01). For major bleeding, the C‐statistic of RF was comparable to the LR (0.69 vs. 0.66, p = .07) and outperformed the HAS‐BLED (0.61, p < .01) and ATRIA (0.62, p < .01) but not the ORBIT (0.67, p = .07). The C‐statistic of RF for all‐cause mortality was comparable to the LR (0.78 vs. 0.79, p = .21). The calibration plot for the RF model was more aligned with the observed events for major bleeding and all‐cause mortality.

Conclusions

The RF model performed as well as or better than the LR model or existing clinical risk scores for predicting clinical outcomes of AF.

Heart Rate Variability Triangular Index as a Predictor of Cardiovascular Mortality in Patients With Atrial Fibrillation

Background

Impaired heart rate variability (HRV) is associated with increased mortality in sinus rhythm. However, HRV has not been systematically assessed in patients with atrial fibrillation (AF). We hypothesized that parameters of HRV may be predictive of cardiovascular death in patients with AF.

Methods and Results

From the multicenter prospective Swiss‐AF (Swiss Atrial Fibrillation) Cohort Study, we enrolled 1922 patients who were in sinus rhythm or AF. Resting ECG recordings of 5‐minute duration were obtained at baseline. Standard parameters of HRV (HRV triangular index, SD of the normal‐to‐normal intervals, square root of the mean squared differences of successive normal‐to‐normal intervals and mean heart rate) were calculated. During follow‐up, an end point committee adjudicated each cause of death. During a mean follow‐up time of 2.6±1.0 years, 143 (7.4%) patients died; 92 deaths were attributable to cardiovascular reasons. In a Cox regression model including multiple covariates (age, sex, body mass index, smoking status, history of diabetes mellitus, history of hypertension, history of stroke/transient ischemic attack, history of myocardial infarction, antiarrhythmic drugs including β blockers, oral anticoagulation), a decreased HRV index ≤ median (14.29), but not other HRV parameters, was associated with an increase in the risk of cardiovascular death (hazard ratio, 1.7; 95% CI, 1.1–2.6; P=0.01) and all‐cause death (hazard ratio, 1.42; 95% CI, 1.02–1.98; P=0.04).

Conclusions

The HRV index measured in a single 5‐minute ECG recording in a cohort of patients with AF is an independent predictor of cardiovascular mortality. HRV analysis in patients with AF might be a valuable tool for further risk stratification to guide patient management.

Registration

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.

Sinus node dysfunction in patients with Fontan circulation: could heart rate variability be a predictor for pacemaker implantation?

Sinus node dysfunction (SND) causes significant morbidity in patients after Fontan surgery. Heart rate variability (HRV) reflects the autonomic regulation of the heart, and changes in HRV have been associated with SND in adults. We aimed to study whether changes in HRV could be detected in 24-h electrocardiographic (ECG) recordings in Fontan patients with SND. We compared HRV results from two patient groups; patients with Fontan circulation who later required a pacemaker due to severe SND (n = 12) and patients with Fontan circulation and SND, without indication for pacemaker treatment (n = 11), with two control groups; patients with Fontan circulation without SND (n = 90) and healthy controls (n = 66). The Poincaré plot index SD2 (representing changes in heart rate over 24-h) and the very low-frequency (VLF) HRV component were significantly higher in both SND groups, both compared with healthy controls and patients with Fontan circulation without SND. In SND patients with pacemakers, SD2 and VLF were slightly reduced compared to SND patients without pacemaker (p = 0.06). In conclusion, in Fontan patients with SND the HRV is significantly higher compared to healthy controls and Fontan patients without SND. However, in patients with severe SND requiring pacemaker, SD2 and VLF tended to be lower than in patients with SND without pacemaker, which could indicate a reduced diurnal HRV in addition to the severe bradycardia. This is a small study, but our results indicate that HRV analysis might be a useful method in the follow-up of Fontan patients regarding development of SND.

The effect of head-up tilt upon markers of heart rate variability in patients with atrial fibrillation

BACKGROUND

Heart rate variability (HRV) analysis is uncommonly undertaken in patients with atrial fibrillation (AF) due to an assumption that ventricular response is random. We sought to determine the effects of head-up tilt (HUT), a stimulus known to elicit an autonomic response, on HRV in patients with AF; we contrasted the findings with those of patients in sinus rhythm (SR).

METHODS

Consecutive, clinically indicated tilt tests were examined for 207 patients: 176 in SR, 31 in AF. Patients in AF were compared to an age-matched SR cohort (n = 69). Five minute windows immediately before and after tilting were analyzed using time-domain, frequency-domain and nonlinear HRV parameters. Continuous, noninvasive assessment of blood pressure, heart rate and stroke volume were available in the majority of patients.

RESULTS

There were significant differences at baseline in all HRV parameters between AF and age matched SR. HUT produced significant hemodynamic changes, regardless of cardiac rhythm. Coincident with these hemodynamic changes, patients in AF had a significant increase in median [quartile 1, 2] DFA-α2 (+0.14 [-0.03, 0.32], p < .005) and a decrease in sample entropy (-0.17 [-0.50, -0.01], p < .005).

CONCLUSION

In the SR cohort, increasing age was associated with fewer HRV changes on tilting. Patients with AF had blunted HRV responses to tilting, mirroring those seen in an age matched SR group. It is feasible to measure HRV in patients with AF and the changes observed on HUT are comparable to those seen in patients in sinus rhythm.

Hidden Signals-The History and Methods of Heart Rate Variability

The understanding of heart rate variability (HRV) has increased parallel with the development of modern physiology. Discovered probably first in 1847 by Ludwig, clinical applications evolved in the second part of the twentieth century. Today HRV is mostly used in cardiology and research settings. In general, HRV can be measured over shorter (e.g., 5-10 min) or longer (12 or 24 h) periods. Since 1996, most measurements and calculations are made according to the standard of the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. As the first step, the series of times between successive R-peaks in the ECG are in milliseconds. It is crucial, however, to identify and remove extrasystoles and artifacts according to standard protocols. The series of QRS distances between successive heartbeats can be analyzed with simple or more sophisticated algorithms, beginning with standard deviation (SDNN) or by the square root of the mean of the sum of squares of differences between adjacent normal RR (rMSSD). Short-term HRV is frequently analyzed with the help of a non-parametric fast Fourier transformation quantifying the different frequency bands during the measurement period. In the last decades, various non-linear algorithms have been presented, such as different entropy and fractal measures or wavelet analysis. Although most of them have a strong theoretical foundation, their clinical relevance is still debated.

Relationship between HRV measurements and demographic and clinical variables in a population of patients with atrial fibrillation

Little is known about the role of HRV in atrial fibrillation (AF) patients. Aim of our study was to assess the relationship between HRV measurements and demographic and clinical variables in a population of 274 AF patients. We selected all consecutive patients with persistent/permanent AF among whom had performed a Holter ECG in our Department from April 2010 to April 2015. Time-domain analysis of HRV was evaluated. Demographic and clinical variables were collected for each patient. At multivariable logistic regression, a higher pNN50 was associated with ACE inhibitors/ARBs (p = 0.016) and a lower pNN50 with obesity (p = 0.037) and higher heart rate (HR) (p < 0.0005). A higher RMSSD was associated with ACE inhibitors/ARBs (p = 0.001), digitalis (p < 0.0005) and beta-blockers (p = 0.002) and a lower RMSSD with a higher HR (p < 0.0005). A higher SDNNi was associated with ACE inhibitors/ARBs (p < 0.0005), digitalis (p < 0.0005) and beta-blockers (p = 0.002) and a lower SDNNi with dysthyroidism (p = 0.048) and higher HR (p < 0.0005). A higher SDANN was associated with non-dihydropyiridine calcium-channel-blockers (p = 0.002) and ACE inhibitors/ARBs (p = 0.002) and a lower SDANN with hypertension (p = 0.034), obesity (p = 0.011), stroke (p = 0.031), pneumonia (p = 0.005) and higher HR (p < 0.0005). A higher SDNN was associated with ACE inhibitors/ARBs (p < 0.0005), digitalis (p < 0.0005) and beta-blockers (p = 0.022) and a lower SDNN with obesity (p = 0.012), pneumonia (p = 0.049) and higher HR (p < 0.0005). Our study showed that, in AF patients, there is a direct relationship between some clinical variables and HRV measurements; as for patients with sinus rhythm, even in AF patients this relationship seemed to reflect the autonomic nervous system activity.

Is 10-second electrocardiogram recording enough for accurately estimating heart rate in atrial fibrillation

BACKGROUND

At present, the estimation of rest heart rate (HR) in atrial fibrillation (AF) is obtained by apical auscultation for 1min or on the surface electrocardiogram (ECG) by multiplying the number of RR intervals on the 10second recording by six. But the reasonability of 10second ECG recording is controversial.

METHODS

ECG was continuously recorded at rest for 60s to calculate the real rest HR (HR60s). Meanwhile, the first 10s and 30s ECG recordings were used for calculating HR10s (sixfold) and HR30s (twofold). The differences of HR10s or HR30s with the HR60s were compared. The patients were divided into three sub-groups on the HR60s <80, 80-100 and >100bpm.

RESULTS

No significant difference among the mean HR10s, HR30s and HR60s was found. A positive correlation existed between HR10s and HR60s or HR30s and HR60s. Bland-Altman plot showed that the 95% reference limits were high as -11.0 to 16.0bpm for HR10s, but for HR30s these values were only -4.5 to 5.2bpm. Among the three subgroups with HR60s <80, 80-100 and >100bpm, the 95% reference limits with HR60s were -8.9 to 10.6, -10.5 to 14.0 and -11.3 to 21.7bpm for HR10s, but these values were -3.9 to 4.3, -4.1 to 4.6 and -5.3 to 6.7bpm for HR30s.

CONCLUSION

As 10s ECG recording could not provide clinically accepted estimation HR, ECG should be recorded at least for 30s in the patients with AF. It is better to record ECG for 60s when the HR is rapid.

Circadian variation of variability and irregularity of heart rate in patients with permanent atrial fibrillation: relation to symptoms and rate control drugs

The aim of the present study was to evaluate diurnal variations of the variability and irregularity of heart rate (HR) in patients with permanent atrial fibrillation (AF) with and without rate control drugs. Thirty-eight patients with permanent AF were part of an investigator-blind crossover study comparing diltiazem, verapamil, metoprolol, and carvedilol. We analyzed five Holter recordings per patient: at baseline (no rate control drug) and with each of the four drug regimens. HR, variability (SD; percentages of interval differences of successive RR intervals of >20, 50, and 80 ms; and root of the mean squared differences of successive RR intervals), and irregularity (approximate and sample entropy) parameters were computed in 20-min long nonoverlapping segments. Circadian rhythmicity was evaluated using cosinor analysis to each parameter series, which is characterized by the 24-h mean [midline statistic of rhythm (MESOR)] and excursion over the mean (amplitude). Arrhythmia-related symptoms were assessed by a questionnaire measuring symptom severity and frequency. HR and variability parameters showed a significant circadian variation in most patients, whereas only a small minority of the patients had circadian variations of irregularity parameters. Patients with circadian approximate entropy n at baseline had more severe symptoms (symptom severity: 9 ± 4 vs. 6 ± 5, P < 0.05, circadian vs. noncircadian variations). All drugs decreased the MESOR of HR and increased the MESOR of variability parameters. Only carvedilol and metoprolol decreased the normalized amplitude over 24 h of all parameters and HR. In conclusion, HR and RR variability parameters present a circadian variation in patients with permanent AF, whereas few patients demonstrated circadian fluctuations in irregularity parameters, suggesting different physiological mechanisms.

Reduced Irregularity of Ventricular Response During Atrial Fibrillation and Long-term Outcome in Patients With Heart Failure

Reduced heart rate variability (HRV) is associated with poor outcome in patients with heart failure (HF). However, the data on predictive value of RR variability during atrial fibrillation (AF) are limited. Therefore, the aim of this study was to evaluate the association between ventricular response characteristics and long-term clinical outcome in the population of ambulatory patients with mild-to-moderate HF and AF at baseline. The study included 155 patients (mean age 69 ± 10 years) with AF at 20-minute Holter electrocardiographic (ECG) recordings at enrollment. HRV analysis included SDNN, rMSSD, and pNN50, whereas irregularity indexes included 2 nonlinear parameters: approximate entropy (ApEn) and Shannon entropy. After median 41 months of follow-up, 54 patients died, including 21 HF related and 16 sudden deaths. Patients with ApEn ≤1.68 (lower tertile) had 40% mortality versus 12% in others (p <0.001) at 2 years of follow-up. Only nonlinear HRV parameters (irregularity but not variability indexes) identified patients at higher risk during follow-up. Decreased ApEn ≤1.68 was an independent predictor of total mortality (hazard ratio [HR] 2.81, 95% confidence interval [CI] 1.61 to 4.89, p <0.001), sudden cardiac death (HR 3.83, 95% CI 1.31 to 11.25, p = 0.014), and HF death (HR 3.45, 95% CI 1.42 to 8.38, p = 0.006) in a multivariate Cox analysis. In conclusion, in a post hoc analysis of Muerte Subita en Insufficiencia Cardiaca study AF cohort, reduced irregularity of RR intervals during AF, likely caused by autonomic dysfunction, was an independent predictor of all-cause mortality and sudden death and HF progression in patients with mild-to-moderate HF, whereas traditional HRV indexes did not predict outcome.

Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is a significant risk factor for ischemic strokes, and making a robust risk stratification scheme would be important. Few studies have examined whether nonlinear dynamics of the heart rate could predict ischemic strokes in AF. We examined whether a novel complexity measurement of the heart rate variability called multiscale entropy (MSE) was a useful risk stratification measure of ischemic strokes in patients with permanent AF.

METHODS AND RESULTS

We examined 173 consecutive patients (age 69 ± 11 years) with permanent AF who underwent 24-hour Holter electrocardiography from April 2005 to December 2006. We assessed several frequency ranges of the MSE and CHA2DS2-VASc score (1 point for congestive heart failure, hypertension, diabetes, vascular disease, an age 65 to 74 years, and a female sex and 2 points for an age ≥ 75 years and a stroke or transient ischemic attack). We found 22 (13%) incident ischemic strokes during a mean follow up of 3.8-years. The average value of the MSE in the very-low frequency subrange (90-300 s, MeanEnVLF2) was significantly higher in patients who developed ischemic strokes than in those who did not (0.68 ± 0.15 vs. 0.60±0.14, P<0.01). There was no significant difference in the C-statistic between the CHA2DS2-VASc score and MeanEnVLF2 (0.56; 95% confidence interval, 0.43-0.69 vs. 0.66; 95% confidence interval, 0.53-0.79). After an adjustment for the age, CHA2DS2-VASc score, and antithrombotic agent, a Cox hazard regression model revealed that the MeanEnVLF2 was an independent predictor of an ischemic stroke (hazard ratio per 1-SD increment, 1.80; 95% confidence interval, 1.17-2.07, P<0.01).

CONCLUSION

The MeanEnVLF2 in 24-hour Holter electrocardiography is a useful risk stratification measure of ischemic strokes during the long-term follow-up in patients with permanent AF.

Dynamics of AV coupling during human atrial fibrillation: role of atrial rate

The causal relationship between atrial and ventricular activities during human atrial fibrillation (AF) is poorly understood. This study analyzed the effects of an increase in atrial rate on the link between atrial and ventricular activities during AF. Atrial and ventricular time series were determined in 14 patients during the spontaneous acceleration of the atrial rhythm at AF onset. The dynamic relationship between atrial and ventricular activities was quantified in terms of atrioventricular (AV) coupling by AV synchrogram analysis. The technique identified n: m coupling patterns ( n atrial beats in m ventricular cycles), quantifying their percentage, maximal length, and conduction ratio (= m/ n). Simulations with a difference-equation AV model were performed to correlate the observed dynamics to specific atrial/nodal properties. The atrial rate increase significantly affected AV coupling and ventricular response during AF. The shortening of atrial intervals from 185 ± 32 to 165 ± 24 ms ( P < 0.001) determined transitions toward AV patterns with progressively decreasing m/ n ratios (from conduction ratio = 0.34 ± 0.09 to 0.29 ± 0.08, P < 0.01), lower occurrence (from percentage of coupled beats = 27.1 ± 8.0 to 21.8 ± 6.9%, P < 0.05), and higher instability (from maximal length = 3.9 ± 1.5 to 2.8 ± 0.7 s, P < 0.01). Advanced levels of AV block and coupling instability at higher atrial rates were associated with increased ventricular interval variability (from 123 ± 52 to 133 ± 55 ms, P < 0.05). AV pattern transitions and coupling instability in patients were predicted, assuming the filtering of high-rate irregular atrial beats by the slow recovery of nodal excitability. These results support the role of atrial rate in determining AV coupling and ventricular response and may have implications for rate control in AF.

Increased systemic inflammation is associated with cardiac and vascular dysfunction over the first 12 weeks of antiretroviral therapy among undernourished, HIV-infected adults in Southern Africa

INTRODUCTION

Persistent systemic inflammation is associated with mortality among undernourished, HIV-infected adults starting antiretroviral therapy (ART) in sub-Saharan Africa, but the etiology of these deaths is not well understood. We hypothesized that greater systemic inflammation is accompanied by cardiovascular dysfunction over the first 12 weeks of ART.

METHODS

In a prospective cohort of 33 undernourished (body mass index <18.5 kg/m²) Zambian adults starting ART, we measured C-reactive protein (CRP), tumor necrosis factor-α receptor 1 (TNF-α R1), and soluble CD163 and CD14 at baseline and 12 weeks. An EndoPAT device measured the reactive hyperemia index (LnRHI; a measure of endothelial responsiveness), peripheral augmentation index (AI; a measure of arterial stiffness), and heart rate variability (HRV; a general marker of autonomic tone and cardiovascular health) at the same time points. We assessed paired changes in inflammation and cardiovascular parameters, and relationships independent of time point (adjusted for age, sex, and CD4+ T-cell count) using linear mixed models.

RESULTS

Serum CRP decreased (median change -3.5 mg/l, p=0.02), as did TNF-α R1 (-0.31 ng/ml, p<0.01), over the first 12 weeks of ART. A reduction in TNF-α R1 over 12 weeks was associated with an increase in LnRHI (p=0.03), and a similar inverse relationship was observed for CRP and LnRHI (p=0.07). AI increased in the cohort as a whole over 12 weeks, and a reduction in sCD163 was associated with a rise in the AI score (p=0.04). In the pooled analysis of baseline and 12 week data, high CRP was associated with lower HRV parameters (RMSSD, p=0.01; triangular index, p<0.01), and higher TNF- α R1 accompanied lower HRV (RMSSD, p=0.07; triangular index, p=0.06).

CONCLUSIONS

Persistent inflammation was associated with impaired cardiovascular health over the first 12 weeks of HIV treatment among undernourished adults in Africa, suggesting cardiac events may contribute to high mortality in this population.

Association between atrial fibrillatory rate and heart rate variability in patients with atrial fibrillation and congestive heart failure

BACKGROUND

Even if atrial fibrillatory rate (AFR) has been related to clinical outcome in patients with atrial fibrillation (AF), its relation with ventricular response has not been deeply studied. The aim of this study was to investigate the relation between AFR and RR series variability in patients with AF.

METHODS

Twenty-minute electrocardiograms in orthogonal leads were processed to extract AFR, using spatiotemporal QRST cancellation and time frequency analysis, and RR series in 127 patients (age 69 ± 11 years) with congestive heart failure (NYHA II-III) enrolled in the MUSIC study (MUerte Subita en Insufficiencia Cardiaca). Heart rate variability and irregularity were assessed by time domain parameters and entropy-based indices, respectively and their correlation with AFR investigated.

RESULTS

Variability measures seem not to be related to AFR, while irregularity measures do. A significant correlation between AFR and variability parameters of heart rate variability during AF was found only in patients not treated with antiarrhythmics drugs (correlation = 0.56 P < 0.05 for pNN50), while this correlation was lost in patients taking rate- or rhythm-control drugs. A significant positive correlation between AFR and indices of RR irregularity was found, showing that a higher AFR is related to a less organized RR series (correlation = 0.33 P < 0.05 for regularity index for all patients, correlation increased in subgroups of patients treated with the same drug).

CONCLUSIONS

These results suggest that a higher AFR is associated with a higher degree of irregularity of ventricular response that is observed regardless of the use of rate-controlling drugs.

Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score

Introduction

A key aim of triage is to identify those with high risk of cardiac arrest, as they require intensive monitoring, resuscitation facilities, and early intervention. We aim to validate a novel machine learning (ML) score incorporating heart rate variability (HRV) for triage of critically ill patients presenting to the emergency department by comparing the area under the curve, sensitivity and specificity with the modified early warning score (MEWS).

Methods

We conducted a prospective observational study of critically ill patients (Patient Acuity Category Scale 1 and 2) in an emergency department of a tertiary hospital. At presentation, HRV parameters generated from a 5-minute electrocardiogram recording are incorporated with age and vital signs to generate the ML score for each patient. The patients are then followed up for outcomes of cardiac arrest or death.

Results

From June 2006 to June 2008 we enrolled 925 patients. The area under the receiver operating characteristic curve (AUROC) for ML scores in predicting cardiac arrest within 72 hours is 0.781, compared with 0.680 for MEWS (difference in AUROC: 0.101, 95% confidence interval: 0.006 to 0.197). As for in-hospital death, the area under the curve for ML score is 0.741, compared with 0.693 for MEWS (difference in AUROC: 0.048, 95% confidence interval: -0.023 to 0.119). A cutoff ML score ≥ 60 predicted cardiac arrest with a sensitivity of 84.1%, specificity of 72.3% and negative predictive value of 98.8%. A cutoff MEWS ≥ 3 predicted cardiac arrest with a sensitivity of 74.4%, specificity of 54.2% and negative predictive value of 97.8%.

Conclusion

We found ML scores to be more accurate than the MEWS in predicting cardiac arrest within 72 hours. There is potential to develop bedside devices for risk stratification based on cardiac arrest prediction.

Determinants of a reduced heart rate variability in chronic atrial fibrillation

BACKGROUND

We aimed to evaluate whether clinical factors, which influence heart rate variability (HRV) in the presence of undisturbed sinus rhythm, have any associations with HRV in patients with permanent atrial fibrillation (AF).

METHODS

One hundred ninety-seven consecutive patients with permanent AF were included (122 males, 75 females, aged 64 ± 11 years, range 25-85). In each patient a 24-hour electrocardiographic recording was performed and an HRV fraction (HRVF)-the index based on scatter plot numerical processing-was calculated. Additionally, standard HRV measures were analyzed. Reduced HRVF was defined as its value lower than lower normal limit. Demographic and clinical factors were examined for their association with a reduced HRVF by means of a univariate and multivariate logistic regression analysis.

RESULTS

The reduced HRVF was associated with advanced age, clinical diagnosis of a previous MI or dilated cardiomyopathy, presence of diabetes, depressed left ventricular function, NYHA class > II, treatment regimen, use of digoxin, diuretics or antiarrhythmic agents, nonuse of beta-blockers, and increased heart rate. The independent determinants that sustained after multivariate analysis were: heart rate (per 10 bpm increase, odds ratio 2.77 [1.88-4.07]), age (per 5 years increase 1.43 [1.1-1.85]), depressed left ventricular EF (<30% vs higher 2.26 [1.19-4.31]), and presence of diabetes (3.45 [1.1-10.85]). The HRVF correlated moderately with standard HRV measures. This index showed also the strongest correlation with left ventricular ejection fraction.

CONCLUSION

We concluded that advanced age, left ventricular systolic dysfunction, increased heart rate, and presence of diabetes are cofactors of a reduced HRV in AF patients. Thus, the determinants of heart rate variability in the presence of atrial fibrillation are the same as those in sinus rhythm.

Atrial fibrillatory rate and irregularity of ventricular response as predictors of clinical outcome in patients with atrial fibrillation

Atrial fibrillation (AF) remains the most common arrhythmia encountered in clinical practice. Electrocardiogram (ECG)-based predictors of clinical outcome, however, have mostly been studied during sinus rhythm, whereas noninvasive risk stratification of patients with AF remains largely unexplored. Advances in ECG signal processing have led to the development of noninvasive methods of atrial fibrillatory rate (AFR) assessment using spatiotemporal QRST cancellation and time frequency analysis that demonstrated its predictive value for the outcome of pharmacologic and catheter-based interventions for AF. Recently, the prognostic value of AFR was evaluated in patients with congestive heart failure and indicated that reduced AFR may be an independent predictor of total and congestive heart failure-related mortality. A high degree of irregularity of the RR intervals during AF and its dependence on the modulation of the atrioventricular conduction rather than sinus node automaticity hampers the use of conventional heart rate variability approach in patients with AF. However, RR irregularity measures that can be applied to short-time ECG recordings appear to be promising predictors of clinical outcome.

Oscillatory vagal maneuvers produce ventricular entrainment in patients with atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common sustained dysrhythmia and appears to be an independent predictor of sudden cardiac death. The irregular ventricular rhythm contains both linear and non-linear patterns; however, it remains unclear whether vagally mediated effects are present within these patterns.

OBJECTIVE

We sought to determine if (1) power spectral analysis of heart rate can detect changes in vagal activity in patients with AF and (2) if the vagus modulates ventricular response during AF.

METHODS

Time and frequency domain parameters of heart rate variability (HRV) were calculated during forced vagal oscillations at 0.125 and 0.25 Hz imposed by neck suction and deep breathing in five AF patients.

RESULTS

There was a significant increase in SDRRI during deep breathing/neck suction combined compared to baseline (p=0.01) and deep breathing (p=0.03). Neck suction significantly increased SDRRI compared to baseline (p=0.03). Deep breathing/neck suction significantly increased spectral power compared to baseline (p=0.02) and deep breathing (p=0.03). Neck suction significantly increased spectral power compared to baseline (p=0.03). Deep breathing did not significantly increase HRV compared to baseline (p>0.20). In addition, SDRRI and spectral power were significantly correlated during deep breathing (r=0.91, p=0.03) and deep breathing/neck suction combined (r=0.92, p=0.02).

INTERPRETATION

These data suggest that (1) power spectral analysis can detect vagal influences on heart rate in AF patients, and (2) oscillatory vagal maneuvers produce ventricular entrainment during AF.

Vagal modulation of heart rate variability during atrial fibrillation in pigs

Atrial fibrillation (AF) is the most common sustained cardiac dysrhythmia and is associated with an increased risk for sudden cardiac death. The ventricular rhythm is irregular and displays both non-linear and linear patterns; however, it has not been determined whether vagally derived patterns are manifest within the irregular rhythm. Moreover, indices of increased vagal control are associated with reduced risk of sudden cardiac death. In this study, we sought to determine whether the ventricular rhythm pattern during AF is, in part, modulated by vagal activity. Vagal oscillations were forced at 0.15 Hz by neck suction in 12 pigs with sustained AF with and without glycopyrrolate (0.15 microg/kg, intravenously) vagal blockade. Vagal activity was evaluated using time- and frequency-domain heart rate variability measures. The standard deviation of RR intervals (SDRRI) was significantly increased during vagal activation compared with baseline (P = 0.006). Moreover, SDRRI correlated significantly with spectral power at 0.15 Hz during baseline (r = 0.90, P < .001) and vagal activation (r = 0.86, P < 0.05). Glycopyrrolate blocked the increase in SDRRI (P < 0.001) and blunted spectral power at 0.15 Hz (P < 0.05). These results indicate that: (1) power spectral analysis may be used to assess parasympathetic regulation during AF, and (2) vagal oscillations produce an entrainment of the ventricular rhythm during AF in pigs.

Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value

AIMS

We aimed to assess the mutual interrelationships and to compare the prognostic value of a comprehensive set of nonlinear indices of heart rate variability (HRV) in a population of chronic heart failure (CHF) patients.

METHODS AND RESULTS

Twenty nonlinear HRV indices, representative of symbolic dynamics, entropy, fractality-multifractality, predictability, empirical mode decomposition, and Poincaré plot families, were computed from 24-hour Holter recordings in 200 stable CHF patients in sinus rhythm (median age [interquartile range]: 54 [47-58] years, LVEF: 23 [19-28]%, NYHA class II-III: 88%). End point for survival analysis (Cox model) was cardiac death or urgent transplantation. Homogeneous variables were grouped by cluster analysis, and in each cluster redundant variables were discarded. A prognostic model including only known clinical and functional risk factors was built and the ability of each selected HRV variable to add prognostic information to this model assessed. Bootstrap resampling was used to test the models stability. Four nonlinear variables showed a correlation >0.90 with classical linear ones and were discarded. Correlations >0.80 were found between several nonlinear variables. Twelve clusters were obtained and from each cluster a candidate predictor was selected. Only two variables (from empirical mode decomposition and symbolic dynamics families) added prognostic information to the clinical model.

CONCLUSION

This exploratory study provides evidence that, despite some redundancies in the informative content of nonlinear indices and strong differences in their prognostic power, quantification of nonlinear properties of HRV provides independent information in risk stratification of CHF patients.

The assessment of autonomic function in chronic atrial fibrillation: description of a non-invasive technique based on circadian rhythm of atrioventricular nodal functional refractory periods

AIMS

Heart rate variability (HRV) parameters can be used to assess autonomic function and to predict outcome, but this has been done exclusively in patients with sinus rhythm. Atrial fibrillation (AF) is the commonest sustained arrhythmia and is particularly prevalent in heart failure. We have developed a simple index to assess autonomic function in patients with chronic AF.

METHODS AND RESULTS

Forty patients with chronic AF (>1 month) and symptoms of heart failure underwent ambulatory 24 h electrocardiography recording as well as evaluation of symptoms, exercise capacity (6 min walk distance), ventricular function (echocardiography and radionuclide ventriculography), and neuroendocrine activation. A number of standard HRV parameters shown to have prognostic significance in sinus rhythm were also determined. A modified in-house HRV statistical programme was used to filter labelled QRS intervals and to compute the 5th percentile RR interval in each hour. This parameter has been shown to approximate the functional refractory period (FRP) of the atrioventricular node (AVN). A cosine curve was fitted to hourly 5th percentile RR intervals for each patient and from this was estimated the diurnal change in hourly 5th percentile RR interval (approximating DeltaFRP of the AVN) and, by inference, diurnal variation in sympathovagal input to the AVN. Digoxin was the sole agent permitted for control of ventricular rate. DeltaFRP of the AVN varied and revealed a significant correlation, on multivariate analysis, with mean RR interval (P<0.001), SDARR (SD of 5-min average RR intervals during 24 h, P<0.001), and NYHA class of heart failure (classes III and IV heart failure vs. classes I and II, P=0.02). SDARR has previously been shown independently to predict mortality in patients with chronic AF and heart failure.

CONCLUSION

This analysis describes a novel non-invasive method for assessing autonomic function in chronic AF. Whether DeltaFRP in chronic AF patients can independently predict adverse prognosis or sudden death requires further study.

The role of heart rate variability in prognosis for different modes of death in chronic heart failure

Classic risk factors for mortality due to chronic heart failure (CHF), such as low left ventricular ejection fraction, NYHA functional stage, and increased heart rate perform well in the prediction of death from pump failure. The prediction of sudden cardiac death (SCD) remains somewhat problematic. Numerous studies have analyzed the potential contribution heart rate variability (HRV) can make to risk assessment in CHF. The aim of this review was to summarize the literature and identify the role HRV might play in identifying mode of death, as well as overall mortality risk. In studies where all-cause mortality or cardiac events were the clinical end point(s), global and slow oscillatory measures of HRV were the strongest risk predictors. In the fewer studies that used SCD as an end point, the strongest risk factors were HRV measures of short-term oscillations and sympathovagal interaction. We concluded from these findings that different HRV measurements predict different modes of death in CHF.Additionally, further studies using short-term analysis of HRV and non-linear analyses are warranted. Furthermore, studies with multiple end points, which clearly delineate pump failure from SCD, may be useful to identify more clearly the role HRV measures can play in the prediction of SCD.

Analysis of surface electrocardiograms in atrial fibrillation: techniques, research, and clinical applications

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice. Neither the natural history of AF nor its response to therapy is sufficiently predictable by clinical and echocardiographic parameters. The purpose of this article is to describe technical aspects of novel electrocardiogram (ECG) analysis techniques and to present research and clinical applications of these methods for characterization of both the fibrillatory process and the ventricular response during AF. Atrial fibrillatory frequency (or rate) can reliably be assessed from the surface ECG using digital signal processing (extraction of atrial signals and spectral analysis). This measurement shows large inter-individual variability and correlates well with intra-atrial cycle length, a parameter which appears to have primary importance in AF maintenance and response to therapy. AF with a low fibrillatory rate is more likely to terminate spontaneously and responds better to antiarrhythmic drugs or cardioversion, whereas high-rate AF is more often persistent and refractory to therapy. Ventricular responses during AF can be characterized by a variety of methods, which include analysis of heart rate variability, RR-interval histograms, Lorenz plots, and non-linear dynamics. These methods have all shown a certain degree of usefulness, either in scientific explorations of atrioventricular (AV) nodal function or in selected clinical questions such as predicting response to drugs, cardioversion, or AV nodal modification. The role of the autonomic nervous system for AF sustenance and termination, as well as for ventricular rate responses, can be explored by different ECG analysis methods. In conclusion, non-invasive characterization of atrial fibrillatory activity and ventricular response can be performed from the surface ECG in AF patients. Different signal processing techniques have been suggested for identification of underlying AF pathomechanisms and prediction of therapy efficacy.

Recombinant nematode anticoagulant protein c2 and other inhibitors targeting blood coagulation factor VIIa/tissue factor

Originally isolated from a haematophagous hookworm, recombinant nematode anticoagulant protein c2 (rNAPc2) is an 85-amino acid protein with potent anticoagulant properties. Unlike conventional anticoagulants that attenuate blood coagulation via inhibition of thrombin or activated factor X (FXa) at the downstream portion of the cascade, rNAPc2 is a potent inhibitor of the activated factor VII/tissue factor complex (FVIIa/TF), the key physiological initiator of blood coagulation. Its mechanism of action requires prerequisite binding to circulating FXa or zymogen factor X (FX) to form a binary complex prior to its interaction and inhibition of membrane-bound FVIIa/TF. The binding of rNAPc2 to FX results in an elimination half-life of longer than 50 h following either subcutaneous or intravenous administration. Recombinant NAPc2, like other inhibitors of FVIIa/TF including tissue factor pathway inhibitor (TFPI) and active site-blocked FVIIa (ASIS, FFR-rFVIIa or FVIIai), may have a promising role in the prevention and treatment of venous and arterial thrombosis, as well as potential efficacy in the management of disseminated intravascular coagulopathies because of their potent and selective inhibition of FVIIa/TF.

Prognostic value of nonlinear heart rate dynamics in hemodialysis patients with coronary artery disease

BACKGROUND

Although altered nonlinear heart rate dynamics predicts death in patients with coronary artery disease (CAD), its prognostic value in chronic hemodialysis patients with CAD is unknown.

METHODS

We analyzed 24-hour electrocardiogram for nonlinear heart rate dynamics and heart rate variability in a retrospective cohort of 81 chronic hemodialysis patients with CAD.

RESULTS

During a follow-up period of 31 +/- 20 months, 19 cardiac and 8 noncardiac deaths were observed. Cox hazards model, including diabetes, left ventricular ejection fraction, and the number of diseased coronary arteries, revealed that abnormal alpha2 (defined as both increase and decrease in alpha2 because of its J curve relationship with cardiac mortality), decreased approximate entropy and decreased heart rate variability (triangular index and ultra-low frequency power) were significant and independent predictors of cardiac death. No significant and independent predictive power for noncardiac death was observed in either the heart rate dynamics or the heart rate variability measures. The predictive power of alpha2 and approximate entropy was independent of that of triangular index and ultra-low frequency power. Combinations of two categories of measures improved the predictive accuracy; overall accuracy of approximate entropy + ultra-low frequency power for cardiac death was 87%.

CONCLUSION

Altered nonlinear heart rate dynamics are independent predictors of cardiac death in chronic hemodialysis patients with CAD and their combinations with decreased heart rate variability provide clinically useful markers for risk stratification.

Frequency distribution, variance, and moving average of left ventricular rhythm and contractility during atrial fibrillation in dog

Mean levels of left ventricular rhythm and contractility averaged over arrhythmic beats would characterize the average cardiac performance during atrial fibrillation (AF). However, no consensus exists on the minimal number of beats for their reliable mean values. We analyzed their basic statistics to find out such a minimal beat number in canine hearts. We produced AF by electrically stimulating the atrium and measured left ventricular arrhythmic beat interval (RR) and peak isovolumic pressure (LVP). From these, we calculated instantaneous heart rate (HR = 60,000/RR), contractility (E(max) = LVP/isovolumic volume above unstressed volume), and beat interval ratio (RR1/RR2). We found that all their frequency distributions during AF were variably nonnormal with skewness and kurtosis. Their means +/- standard deviations alone cannot represent their nonnormal distributions. A 90% reduction of variances of E(max) and RR1/RR2 required a moving average of 15 and 24, respectively, arrhythmic beats on the average, whereas that of RR and HR required 60 beats on the average. These results indicate that a statistical characterization of arrhythmic cardiodynamic variables facilitates better understanding of cardiac performance during AF.