Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data

Objective. The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor. We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.Approach. The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57 ± 12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.Main results. The mixed-effect models had a better fit to the data than fixed-effect models showing h.c. of determination (R2 = 0.49 versusR2 = 0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2 = 0.04). AFR was found to be significantly affected by previous catheter ablations (p< 0.05), episode duration (p< 0.05), and irregularity of theRRinterval series (p< 0.05).Significance. Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organizedRRintervals and after several ablation procedures.

Machine learning based potentiating impacts of 12-lead ECG for classifying paroxysmal versus non-paroxysmal atrial fibrillation

Background

Conventional modality requires several days observation by Holter monitor to differentiate atrial fibrillation (AF) between Paroxysmal atrial fibrillation (PAF) and Non-paroxysmal atrial fibrillation (Non-PAF). Rapid and practical differentiating approach is needed.

Objective

To develop a machine learning model that observes 10-s of standard 12-lead electrocardiograph (ECG) for real-time classification of AF between PAF versus Non-PAF.

Methods

In this multicenter, retrospective cohort study, the model training and cross-validation was performed on a dataset consisting of 741 patients enrolled from Severance Hospital, South Korea. For cross-institutional validation, the trained model was applied to an independent data set of 600 patients enrolled from Ewha University Hospital, South Korea. Lasso regression was applied to develop the model.

Results

In the primary analysis, the Area Under the Receiver Operating Characteristic Curve (AUC) on the test set for the model that predicted AF subtype only using ECG was 0.72 (95% CI 0.65–0.80). In the secondary analysis, AUC only using baseline characteristics was 0.53 (95% CI 0.45–0.61), while the model that employed both baseline characteristics and ECG parameters was 0.72 (95% CI 0.65–0.80). Moreover, the model that incorporated baseline characteristics, ECG, and Echocardiographic parameters achieved an AUC of 0.76 (95% CI 0.678–0.855) on the test set.

Conclusions

Our machine learning model using ECG has potential for automatic differentiation of AF between PAF versus Non-PAF achieving high accuracy. The inclusion of  Echocardiographic parameters further increases model performance. Further studies are needed to clarify the next steps towards clinical translation of the proposed algorithm.

Respiratory Induced Modulation in f-Wave Characteristics During Atrial Fibrillation

The autonomic nervous system (ANS) is an important factor in cardiac arrhythmia, and information about ANS activity during atrial fibrillation (AF) may contribute to personalized treatment. In this study we aim to quantify respiratory modulation in the f-wave frequency trend from resting ECG. First, an f-wave signal is extracted from the ECG by QRST cancelation. Second, an f-wave model is fitted to the f-wave signal to obtain a high resolution f-wave frequency trend and an index for signal quality control ( S ). Third, respiratory modulation in the f-wave frequency trend is extracted by applying a narrow band-pass filter. The center frequency of the band-pass filter is determined by the respiration rate. Respiration rate is estimated from a surrogate respiration signal, obtained from the ECG using homomorphic filtering. Peak conditioned spectral averaging, where spectra of sufficient quality from different leads are averaged, is employed to obtain a robust estimate of the respiration rate. The envelope of the filtered f-wave frequency trend is used to quantify the magnitude of respiratory induced f-wave frequency modulation. The proposed methodology is evaluated using simulated f-wave signals obtained using a sinusoidal harmonic model. Results from simulated signals show that the magnitude of the respiratory modulation is accurately estimated, quantified by an error below 0.01 Hz, if the signal quality is sufficient ( S > 0 . 5 ). The proposed method was applied to analyze ECG data from eight pacemaker patients with permanent AF recorded at baseline, during controlled respiration, and during controlled respiration after injection of atropine, respectively. The magnitude of the respiratory induce f-wave frequency modulation was 0.15 ± 0.01, 0.18 ± 0.02, and 0.17 ± 0.03 Hz during baseline, controlled respiration, and post-atropine, respectively. Our results suggest that parasympathetic regulation affects the magnitude of respiratory induced f-wave frequency modulation.

Atrial fibrillation frequency tracking in ambulatory ECG signals: The significance of signal quality assessment

An approach to atrial fibrillation (AF) frequency tracking in long-term ambulatory ECG recordings is presented, comprising f-wave extraction, dominant atrial frequency (DAF) tracking, and signal quality assessment. Since poor signal quality is commonly encountered in ambulatory monitoring, a recently proposed index is employed to assess f-wave signal quality in a database containing 38 patients with permanent AF. The index ensures that DAF outliers, typically associated with poor-quality segments, are excluded from further analysis. 40% of all 5-s signal segments were excluded from the database due to poor quality. The exclusion of DAF outliers significantly reduces the standard deviation of the frequency estimates (p≤0.01), allowing more reliable evaluation of the difference between day- and night-time DAF. The results show that signal quality assessment plays a central role in DAF tracking, and therefore should be employed in ambulatory monitoring.

Spectral Analysis of Baseline Electrocardiogram During Atrial Fibrillation Predicts Response to Antiarrhythmic Drug Therapy in Patients With Persistent Atrial Fibrillation

BACKGROUND

We evaluated the ability of spectral analysis of the baseline ECG during atrial fibrillation (AF) to predict the response of persistent AF to antiarrhythmic drug therapy.

METHODS

Patients with persistent AF who were admitted for dofetilide loading were prospectively enrolled in the study. Atrial activity was extracted from the ECG using an Independent Component Analysis method and then subjected to a Modified Periodogram. The regularity index was computed as the ratio of the power in the dominant frequency and all its harmonics to the total power in the spectrum. Patients were followed at 1 month, 3 months and every 3 months thereafter.

RESULTS

Of 28 patients enrolled in the study, 14 (50%) converted acutely to sinus rhythm during the 3-day hospital loading period. The clinical and echocardiographic characteristics of patients with and without acute pharmacologic conversion were similar. The regularity index was significantly higher in those who converted to sinus rhythm compared to those who did not (0.71 ± 0.20 vs. 0.38 ± 0.13, respectively; P < 0.0001). A regularity index ≥0.44 had a 79% sensitivity and 93% specificity to predict acute conversion and was associated with a nearly 5-fold increase in the acute conversion rate (odds ratio = 4.89; 95% confidence interval 1.74-13.75; P = 0.003). The regularity index was the only independent predictor of acute conversion. Neither acute conversion, nor the regularity index predicted sinus rhythm maintenance, after a median follow-up of 10 months.

CONCLUSION

Increased regularity index predicts acute conversion of persistent AF during dofetilide loading, but does not predict long-term sinus rhythm maintenance.

Inverse Correlation between the Atrial Fibrillatory Rate and the Ventricular Repolarization Time: Observations at Baseline and after an Intravenous Infusion of a Combined Potassium and Sodium Current Blocker

BACKGROUND

The atrial fibrillatory rate (AFR) and the ventricular rate and repolarization (QTcF) were studied at baseline and under the influence of the combined potassium and sodium current blocker AZD7009.

METHODS

Ninety-two patients with atrial fibrillation (AF) were randomized to an intravenous infusion of AZD7009 or placebo. The atrial fibrillatory activity in lead V1 was extracted using spatiotemporal QRST cancellation. The exponential decay (ED) characterized the degree of atrial signal organization.

RESULTS

The mean (SD) AFR at baseline was 396  ±  57 (range 253-584) and 410 ± 33 (range 363-469) bpm in patients randomized to AZD7009 and placebo, respectively. The AFR decreased within the first minutes of the AZD7009 infusion and reached its minimum of 235 ± 34 bpm after 18 minutes. On placebo, the AFR was unchanged. On AZD7009, the ED decreased from 1.2 ± 0.3 to reach its lowest level at 0.7 ± 0.2 after 14 minutes. The ventricular rate did not change significantly over time. The AFR was statistically significantly related to the ventricular repolarization at baseline, the QTcF being longer at lower AFR values, and this relationship remained during and after AZD7009. In the full multivariate linear regression model, including age, sex, left ventricular ejection fraction, QRS duration, heart rate, QTcF, AF episode duration, AF history duration, and right atrial or left atrial size, only QTcF and age were statistically significantly correlated with the AFR. The correlation remained when the uncorrected QT interval was used.

CONCLUSIONS

The QTcF was inversely correlated with AFR, both at baseline and during administration of AZD7009. The AFR was not correlated with the ventricular rate.

The Role Of Renin Angiotensin System In Atrial Fibrillation

Atrial fibrillation (AF) is the most prevalent arrhythmia and its incidence is on the rise. AF causes significant morbidity and mortality leading to rising AF-related health care costs. There is experimental and clinical evidence from animal and human studies that suggests a role for the renin angiotensin system (RAS) in the etiopathogenesis of AF. This review appraises the current understanding of RAS antagonism, using angiotensin converting enzyme inhibitors (ACE-I), angiotensin receptor blockers (ARB) and aldosterone antagonists (AA), for prevention of AF. RAS antagonism has proven to be effective for primary and secondary prevention of AF in subjects with heart failure and left ventricular (LV) dysfunction.However, most of the evidence for the protective effect of RAS antagonism is from clinical trials that had AF as a secondary outcome or from unspecified post-hoc analyses. The evidence for prevention in subjects without heart failure and with normal LV function is not as clear. RAS antagonism, in the absence of concomitant antiarrhythmic therapy, was not shown to reduce post cardioversion AF recurrences. RAS antagonism in subjects undergoing catheter ablation has also been ineffective in preventing AF recurrences.

Low atrial fibrillatory rate is associated with spontaneous conversion of recent-onset atrial fibrillation

AIMS

Atrial fibrillatory rate (AFR) is considered a non-invasive index of atrial remodelling. Low AFR has been associated with favourable outcome of interventions in patients with persistent atrial fibrillation (AF). However, AFR has never been studied in unselected patients with short duration of AF, prone to regain sinus rhythm (SR) spontaneously. The aim of the study was to assess if AFR can predict spontaneous conversion in patients with recent-onset AF.

METHODS AND RESULTS

Files of consecutive patients with AF < 48 h seeking emergency room care during a 12-month period were screened (n = 225). Patients with thyroid illness, acute ischaemic heart disease (IHD) or acute congestive heart failure, significant valvular heart disease, congenital heart disease, history of cardiac surgery or catheter ablation, or on class I/III antiarrhythmics were excluded. Atrial fibrillatory rate was obtained by QRST cancellation and time frequency analysis of electrocardiogram at admission. The study population comprised 148 patients (age 64 ± 13 years, 52 men), of whom 48 converted to SR within 18 h. Those converting spontaneously comprised more women, had a higher prevalence of first-ever AF episode, IHD, and a lower AFR. The multivariate analysis revealed: AFR < 350 fibrillations per minute [odds ratio (OR) 3.7, 95% confidence interval (CI) 1.3-10.5, P = 0.016], IHD (OR 5.7, 95% CI 1.5-22.4, P = 0.012) and first-ever AF episode (OR 4.1, 95% CI 1.3-13.0, P = 0.015) as independent predictors of spontaneous conversion.

CONCLUSION

A low AFR was predictive of spontaneous conversion in patients with recent-onset AF. Along with first-ever AF episode and IHD, AFR can be used in assessing likelihood of spontaneous conversion, if proven in prospective studies.

The role of the renin-angiotensin system blocking in the management of atrial fibrillation

OBJECTIVE

To review current available evidence for the role of renin-angiotensin system blockade in the management of atrial fibrillation.

METHOD

We conducted a PubMed and Medline literature search (January 1980 through July 2011) to identify all clinical trials published in English concerning the use of angiotensin converting enzyme inhibitors or angiotensin II receptor blockers for primary and secondary prevention of atrial fibrillation. We also discussed renin-angiotensin system and its effects on cellular electrophysiology.

CONCLUSION

The evidence from the current studies discussed does not provide a firm definitive indication for the use of angiotensin converting enzyme inhibitors or angiotensin II receptor blockers in the primary or secondary prevention of atrial fibrillation. Nevertheless, modest benefits were observed in patients with left ventricular dysfunction. In view of the possible benefits and the low incidence of side-effects with angiotensin converting enzyme inhibitors and angiotensin II receptor blockers, they can be given to patients with recurrent AF, specifically those with hypertension, heart failure and diabetes mellitus.

Low atrial fibrillatory rate is associated with poor outcome in patients with mild to moderate heart failure

BACKGROUND

Atrial fibrillatory rate (AFR) is a measure of atrial remodeling caused by atrial fibrillation (AF), and its acceleration negatively affects outcome of interventions for persistent AF. However, the prognostic value of AFR in patients with congestive heart failure (CHF) has not been studied. We sought to evaluate whether AFR can predict outcome in patients with mild to moderate (New York Health Association II-III) CHF.

METHODS AND RESULTS

High-resolution 20-minute long Holter ECGs obtained from 169 CHF patients with AF at enrollment were analyzed. AFR was estimated using spatiotemporal QRST cancellation and time-frequency analysis. The patients were followed for a median of 44 months, with primary end point defined as total mortality and secondary end points as sudden death and heart failure death. Atrial signal quality was sufficient for AFR estimation in 142 patients (mean age 69±11 years, 101 male). Of those, 48 patients died during follow-up, including 18 because of CHF progression. Mean AFR was 390±60 fpm and decreased with age (r=-0.3, P<0.001). Patients with AFR ≤371 fpm (lower tertile) had 44% 3-year mortality as compared with 26% with higher AFR. Lower AFR was an independent predictor of all cause mortality (HR=1.99, 95% CI=1.09-3.63, P=0.025) and CHF death (HR=3.74, 95% CI=1.38-10.14, P=0.010) after adjustment for significant clinical covariates in multivariable Cox analysis.

CONCLUSIONS

In CHF patients with AF, reduced AFR assessed using noninvasive approach is associated with increased risk of death because of heart failure progression, and may be considered a predictor of outcome.

Inhibition of the renin-angiotensin system for prevention of atrial fibrillation

Atrial fibrillation (AF) is a source of considerable morbidity and mortality. There has been compelling evidence supporting the role of renin-angiotensin system (RAS) in the genesis and perpetuation of AF through atrial remodeling, and experimental studies have validated the utilization of RAS inhibition for AF prevention. This article reviews clinical trials on the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) for the prevention of AF. Results have been variable, depending on the clinical background of treated patients. ACEIs and ARBs appear beneficial for primary prevention of AF in patients with heart failure, whereas they are not equally effective in hypertensive patients with normal left ventricular function. Furthermore, the use of ACEIs or ARBs for secondary prevention of AF has been found beneficial only after electrical cardioversion. Additional data are needed to establish the potential clinical role of renin-angiotensin inhibition for prevention of AF.