Exponential distribution of long heart beat intervals during atrial fibrillation and their relevance for white noise behaviour in power spectrum

The statistical properties of heart beat intervals of 130 long-term surface electrocardiogram recordings during atrial fibrillation (AF) are investigated. We find that the distribution of interbeat intervals exhibits a characteristic exponential tail, which is absent during sinus rhythm, as tested in a corresponding control study with 72 healthy persons. The rate of the exponential decay lies in the range 3-12 Hz and shows diurnal variations. It equals, up to statistical uncertainties, the level of the previously uncovered white noise part in the power spectrum, which is also characteristic for AF. The overall statistical features can be described by decomposing the intervals into two statistically independent times, where the first one is associated with a correlated process with 1/f noise characteristics, while the second one belongs to an uncorrelated process and is responsible for the exponential tail. It is suggested to use the rate of the exponential decay as a further parameter for a better classification of AF and for the medical diagnosis. The relevance of the findings with respect to a general understanding of AF is pointed out

A Comparison of Patient History- and EKG-based Cardiac Risk Scores.

Patient-specific risk scores are used to identify individuals at elevated risk for cardiovascular disease. Typically, risk scores are based on patient habits and medical history - age, sex, race, smoking behavior, and prior vital signs and diagnoses. We explore an alternative source of information, a patient's raw electrocardiogram recording, and develop a score of patient risk for various outcomes. We compare models that predict adverse cardiac outcomes following an emergency department visit, and show that a learned representation (e.g. deep neural network) of raw EKG waveforms can improve prediction over traditional risk factors. Further, we show that a simple model based on segmented heart beats performs as well or better than a complex convolutional network recently shown to reliably automate arrhythmia detection in EKGs. We analyze a large cohort of emergency department patients and show evidence that EKG-derived scores can be more robust to patient heterogeneity

Automatic Mode Switching in Atrial Fibrillation

Automatic mode switching (AMS) algorithms were designed to prevent tracking of atrial tachyarrhythmias (ATA) or other rapidly occurring signals sensed by atrial channels, thereby reducing the adverse hemodynamic and symptomatic consequences of a rapid ventricular response. The inclusion of an AMS function in most dual chamber pacemaker now provides optimal management of atrial arrhythmias and allows the benefit of atrioventricular synchrony to be extended to a population with existing atrial fibrillation. Appropriate AMS depends on several parameters: a) the programmed parameters; b) the characteristics of the arrhythmia; c) the characteristics of the AMS algorithm. Three qualifying aspects constitute an AMS algorithm: onset, AMS response, and resynchronization. Since AMS programs also provide data on the time of onset and duration of AMS episodes, AMS data may be interpreted as a surrogate marker of ATAs recurrence. Recently, stored electrograms corresponding to episodes of ATAs have been introduced, thus clarifying the accuracy of AMS in detecting ATAs Clinically this information may be used to assess the efficacy of an antiarrhythmic intervention or the risk of thromboembolic events, and it may serve as a valuable research tool for evaluating the natural history and burden of ATAs

P-wave Variability and Atrial Fibrillation

The analysis of P-wave template has been widely used to extract indices of Atrial Fibrillation (AF) risk stratification. The aim of this paper was to assess the potential of the analysis of the P-wave variability over time in patients suffering from atrial fibrillation. P-wave features extracted from P-wave template together with novel indices of P-wave variability have been estimated in a population of patients suffering from persistent AF and compared to those extracted from control subjects. We quantify the P-wave variability over time using three algorithms and we extracted three novel indices: one based on the cross-correlation coefficients among the P-waves (Cross-Correlation Index, CCI), one associated to variation in amplitude of the P-waves (Amplitude Dispersion Index, ADI), one sensible to the phase shift among P-waves (Warping Index, WI). The control group resulted to be characterized by shorter P-wave duration and by a less amount of fragmentation and variability, respect to AF patients. The parameter CCI shows the highest sensitivity (97.3%) and a good specificity (95%)

International criteria for electrocardiographic interpretation in athletes: Consensus statement.

Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly, advanced by a growing body of scientific data and investigations that both examine proposed criteria sets and establish new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington (USA), to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD

Incidence and predictors of premature ventricular complexes following catheter ablation for atrial fibrillation

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and previous studies have focused on the epidemiology, mechanisms and risk factors for this global disease (Ryder and Benjamin 1999). Various studies have examined the mechanism, epidemiology, and risk factors for AF. One of the most common triggers for AF is believed to be premature atrial contractions (PACs) usually arising from the pulmonary veins of the left atrium, but the relationship between AF and premature ventricular complexes (PVCs) is not well understood. Studies investigating the triggers of premature beats in both the atria and ventricles are similar, so it is possible that treatment for one arrhythmia may affect the incidence of another. It is hypothesized that due to commonly shared mechanisms of triggered activity or automaticity between PACs and PVCs, and shared risk factors, that patients with AF undergoing treatment with catheter ablation may be prone to develop PVCs. OBJECTIVE: To investigate the incidence of clinically detected PVCs among patients undergoing catheter ablation for AF, and clinical predictors of PVC development in this cohort of patients. We also aim to evaluate if incident PVC detection is associated with recurrent AF following AF ablation in a cohort of 317 patients receiving treatment at a single academic medical center. METHODS: A total of 375 patients undergoing AF ablation from 2009-2012 were reviewed, and patients that underwent repeat ablations were excluded, yielding 317 patients for analysis. T-tests and Chi-squared analyses were used in univariate analyses to test for significance between characteristics of AF patients who did and did not develop PVCs. Kaplan-Meier analyses and Cox proportional hazards models were used for univariate and multivariate survival analyses, respectively, to assess the risks of incident PVC development. RESULTS: Of 317 patients with AF undergoing pulmonary vein isolation (PVI) ablation, 36.3% developed clinically detectable PVCs following ablation. A history of clinically evident PVC prior to catheter ablation for AF was associated with an 80% increase in risk of incident PVC development (HR=1.83, 95% CI 1.02-3.26, p=0.041). Additionally, a history of prior angioplasty, stent, or percutaneous coronary intervention (PCI) was associated with a 73% decreased risk of incident PVCs (HR=0.27, 95% CI 0.08-0.88, p=0.03). In patients with a history of PVC prior to ablation, or who developed PVCs after ablation, there was no significant difference in the risk of AF recurrence (HR=1.01, 95% CI 0.70-1.46, p=0.96; and HR=1.09, 95% CI 0.78-1.53, p=0.60, respectively). CONCLUSIONS: Over 1 in 3 patients develop clinically detected PVCs following catheter ablation. Predictors of incident PVC development include a history of PVC, whereas a history of angioplasty, stent, or PCI was associated with less incident PVC development. Furthermore, there was no significant association between both a history of PVC or incident PVC and risk of recurrent AF following ablation

Recent Advances in the Noninvasive Study of Atrial Conduction Defects Preceding Atrial Fibrillation

The P-wave represents the electrical activity in the electrocardiogram (ECG) associated with the heart\u27s atrial contraction. This wave has merited significant research efforts in recent years with the aim to characterize atrial depolarization from the ECG. Indeed, the alterations of the P-wave main time, frequency, and wavelet features have been widely studied to predict the onset of atrial fibrillation (AF), both spontaneously and after a specific treatment, such as pharmacological or electrical cardioversion, catheter ablation, as well as cardiac surgery. To this respect, the P-wave prolongation is today a clinically accepted marker of high risk of suffering AF. However, given the relatively low P-wave amplitude in the ECG, its analysis has been most widely carried out from signal-averaged ECG signals. Unfortunately, these kind of recordings are uncommon in routine clinical practice and, moreover, they obstruct the possibility of studying the information carried by each single P-wave as well as its variability over time. These limitations have motivated the recent development of the beat-to-beat P-wave analysis, which has proven to be very useful in revealing interesting information about the altered atrial conduction preceding the onset of AF. Within this context, the main goal of this chapter is to review the most recent advances reached by this kind of analysis in the noninvasive assessment of atrial conduction alterations. Thus, the chapter will introduce and discuss the existing methods of the beat-to-beat P-wave analysis and their application to predict the onset of AF as well as its advantages and disadvantages compared with the signal-averaged P-wave analysis

QUest for the Arrhythmogenic Substrate of Atrial fibRillation in Patients Undergoing Cardiac Surgery (QUASAR Study): Rationale and Design

The heterogeneous presentation and progression of atrial fibrillation (AF) implicate the existence of different pathophysiological processes. Individualized diagnosis and therapy of the arrhythmogenic substrate underlying AF may be required to improve treatment outcomes. Therefore, this single-center study aims to identify t

Blood pressure in atrial fibrillation

Introduction: Hypertension is a leading risk factor for cardiovascular morbidity and premature death. Prevalence of hypertension in the adult population in Sweden has been estimated to 27%. Atrial fibrillation (AF) is the most prevalent sustained arrhythmia of clinical relevance with an estimated prevalence of at least 2.9% among adults in Sweden. Similarly to hypertension, AF is independently associated with an increased risk for cardiovascular morbidity and with a two-fold increased risk of death. The underlying mechanisms responsible for this association however, are not fully known. Both conditions may impose a heavy burden upon affected patients as well as on the health care system. AF and hypertension are closely intertwined and often coexist. Hypertension is the major risk factor for AF development and conversely, AF affects blood pressure (BP). The irregular heart rhythm in AF is one factor influencing BP, but also other factors may play a part. Furthermore, the presence of AF has implications for conventional BP measurement. AF-related effects on BP are studied to a very limited extent. Possibly, AF-induced BP effects may have pathophysiological consequences and may also influence BP measurement accuracy. Consequently, these factors may negatively influence risk assessment and prognosis in patients with AF. The aims of this thesis were 1) to systematically quantify beat-to-beat BP variability in patients with AF compared to sinus rhythm (SR); 2) to study how BP, as measured with different techniques, is affected by the presence of AF; 3) to investigate the relationship between peripheral and central intra-arterial BP, in patients with AF compared to SR; 4) to evaluate the accuracy of conventional BP measurement in relation to peripheral and central intra-arterial BP, in patients with AF and compared to SR. Methods and results: In the prospective study I, patients scheduled for a coronary angiography were recruited. Participants included 21 patients in AF and 12 patients with SR. Intra-arterial BP was recorded from the radial and brachial artery and from the ascending aorta. The primary outcome measure was beat-to-beat BP variability, defined as average systolic and diastolic BP difference between consecutive beats, at each site of measurement. A significant difference (p<0.001) in BP variability, in AF compared to SR, was observed for all locations of measurement. Systolic BP variability was roughly doubled in patients with AF (4.9 vs 2.4 mmHg), whereas diastolic BP variability was approximately six times as high (7.5 vs 1.2 mmHg) in patients with AF compared to SR. Study II was a retrospective registry analysis based on data from electronic medical records. 487 patients, treated with electrical cardioversion (ECV) for persistent AF, were included in the study. Information regarding auscultatory sphygmomanometric BP and rhythm, on the day before and 7 days after ECV, was obtained. The primary outcome measure was BP change in patients with restored SR after ECV. In this group with restored SR, systolic BP increased by 9 mmHg (p<0.01), whereas diastolic BP decreased by 3 mmHg (p<0.01). Furthermore, the proportion of patients with a hypertensive BP-level (≥140/90) increased by 40% in this group. In study III, 98 patients with persistent AF undergoing ECV were prospectively recruited. BP was evaluated with 24-h ambulatory BP monitoring before and approximately one week after ECV. The primary outcome measure was BP change in patients with restored SR after ECV. Among 60 patients maintaining SR, mean systolic 24-h ambulatory BP increased by 5.6 mmHg (p<0.001) and mean diastolic 24-h ambulatory BP decreased by 4.7 mmHg (p<0.001). Accordingly, a 10.4 mmHg (25%) increase in pulse pressure was observed among patients with restored SR. Study IV comprised the same individuals as study I. Conventional BP (auscultatory sphygmomanometric and automated oscillometric) and intra-arterial BP was measured simultaneously. The first aim was to investigate how intra-arterial BP changes throughout the arterial tree in patients with AF in comparison to patients in SR. The second aim was to evaluate the accuracy of conventional BP measurement in patients with AF in comparison to central and peripheral intra-arterial BP, and in comparison to patients in SR. BP changes throughout the arterial tree was similar in patients with AF compared to SR. Conventional BP was in general very accurate in comparison to diastolic intra-arterial BP, both in AF and SR. In patients with AF, oscillometric blood pressure overestimated systolic intra-arterial brachial (4.1 mmHg, p=0.07) and central (5.0 mmHg, p=0.04) BP. With measurement bias in SR taken into account, oscillometric BP over-estimated systolic intra-arterial brachial BP by 14.1 mmHg (p<0.01) and central BP by 9.0 mmHg (p=0.01) in patients with AF. Conclusions: Beat-to-beat BP variability is increased in patients with AF compared to SR. According to the results from studies in this thesis, systolic BP is lower and diastolic BP is higher in AF compared to SR, as measured by auscultatory sphyghmomanometry or by oscillometric 24-h ambulatory BP monitoring. As a consequence, pulse pressure is markedly lower in AF compared to SR. Intra-arterial BP change throughout the arterial tree is similar in patients with AF and SR. Conventional BP measurement was accurate in relation to diastolic intra- arterial BP, but oscillometric BP measurement overestimated intra-arterial brachial and central systolic BP in patients with AF, in particular when compared to patients in SR. The presence of AF affects BP. This may have implications for the accuracy of conventional BP measurement and may possibly also have pathophysiological consequences. Suboptimal understanding, measurement and treatment of BP may negatively influence prognosis in patients with AF

Early Detection and Continuous Monitoring of Atrial Fibrillation from ECG Signals with a Novel Beat-Wise Severity Ranking Approach

Irregularities in heartbeats and cardiac functioning outside of clinical settings are often not available to the clinicians, and thus ignored. But monitoring these with high-risk population might assist in early detection and continuous monitoring of Atrial Fibrillation(AF). Wearable devices like smart watches and wristbands, which can collect Electrocardigraph(ECG) signals, can monitor and warn users of unusual signs in a timely manner. Thus, there is a need to develop a real-time monitoring system for AF from ECG. We propose an algorithm for a simple beat-by-beat ECG signal multilevel classifier for AF detection and a quantitative severity scale (between 0 to 1) for user feedback. For this study, we used ECG recordings from MIT BIH Atrial Fibrillation, MIT BIH Long-term Atrial Fibrillation Database. All ECG signals are preprocessed for reducing noise using filter. Preprocessed signal is analyzed for extracting 39 features including 20 of amplitude type and 19 of interval type. The feature space for all ECG recordings is considered for Classification. Training and testing data include all classes of data i.e., beats to identify various episodes for severity. Feature space from the test data is fed to the classifier which determines the class label based on trained model. A class label is determined based on number of occurences of AF and other arrhythmia episodes such as AB(Atrial Bigeminy), SBR(Sinus Bradycardia), SVTA(Supra Ventricular Tacchyarrhythmia). Accuracy of 96.7764% is attained with Random Forest algorithm, Furthermore, precision and recall are determined based on correct and incorrect classifications for each class. Precision and recall on average of Random Forest Classifier are obtained as 0.968 and 0.968 respectievely. This work provides a novel approach to enhance existing method of AF detection by identifying heartbeat class and calculates a quantitative severity metric that might help in early detection and continuous monitoring of AF