Modelling and robust estimation of AV node function during AF

Objective: The purpose of the present thesis is to enrich the robustness of a statistical atrioventricular (AV) node model during atrial Fibrillation (AF). The model takes into account electrophysiological properties as the two pathways, their refractory periods and concealed conduction; these pathways are located between sinoatrial (SA) and AV node. It is highly desirable understanding of the AV node function, in order to achieve optimal arrhythmia management for those patients affected by AF, which is the most common arrhythmia. Methods: The simulation has been improved by introducing a new parameter that represents the probability of an impulse choosing either one of the two pathways. Exploration data has been conducted keeping fixed a set of parameters while varying one of them. Results: The model concerns a relationship between the probability of an atrial impulse passing through (output parameter, a) and choosing (input parameter, g) either one of two pathway. To test its accuracy and precision mean absolute error (MAE) and root mean square error (RMSE) have been calculated for different g, obtaining, MAE = 3:8_8:2023_1

Model-based Analysis of Temporal Patterns in Atrioventricular Node Conduction During Atrial Fibrillation

The lifetime risk of developing atrial fibrillation (AF) is estimated to be between 1in 3 to 1 in 4 individuals, making it the most common arrhythmia in the world.For persistent AF, rate control drugs with the purpose to affect the conduction properties of the atrioventricular (AV) node are the most common treatment. The drug of choice varies between β-blockers and calcium channel blockers, often chosen empirically. This can lead to long periods of time before sufficient treatment is found. However, due to the physiological differences between the drug types, it could be possible to predict the effect of the drugs and thus assist in treatment selection. The main focus of this thesis is therefore to assess drug-dependent differences in the AV node, using non-invasive measurements. This thesis comprises an introduction to the subject as well as two papers. The first paper proposes a framework for assessing the conduction properties of the AV node non-invasively using a mathematical model of the AV node in combination with a genetic algorithm.The second paper is a continuation of the work in paper I, where the proposed workflow was adapted to assess the drug-dependent effect on the AV node of four different rate control drugs during a period of 24 hours.The methods presented in this thesis have made it possible to assess both the refractory period and the conduction delay in the AV node in a robust way using ECG, and by doing so found population-related differences in AV node conduction properties between drug types

Novel Approaches to ECG-Based Modeling and Characterization of Atrial Fibrillation

This thesis deals with signal processing algorithms for analysis of the electrocardiogram (ECG) during atrial fibrillation (AF). Such analysis can be used for diagnosing patients, and for monitoring and predicting their response to various treatment. The thesis comprises an introduction and five papers describing methods for ECG-based modeling and characterization of AF. Paper I--IV deal with methods for characterization of the atrial activity, whereas Paper V deals with modeling of the ventricular response, both problems with the assumption that AF is present. In Paper I, a number of measures characterizing the atrial activity in the ECG, obtained using time-frequency analysis as well as nonlinear methods, are evaluated for their ability to predict spontaneous termination of AF. The AF frequency, i.e, the repetition rate of the atrial fibrillatory waves of the ECG, proved to be a significant factor for discrimination between terminating and non-terminating AF. Noise is a common problem in ECG signals, particularly in long-term ambulatory recordings. Hence, robust algorithms for analysis and characterization are required. In Paper II, a robust method for tracking the AF frequency in noisy signals is presented. The method is based on a hidden Markov model (HMM), which takes the harmonic pattern of the atrial activity into account. Using the HMM-based method, the average RMS error of the frequency estimates at high noise levels was significantly lower compared to existing methods. In Paper III, the HMM-based method is employed for analysis of 24-h ambulatory ECG signals in order to explore circadian variation in AF frequency. Circadian variations reflect autonomic modulation; attenuation or absence of such variations may help to diagnose patients. Methods based on curve fitting, autocorrelation, and joint variation, respectively, are employed to quantify circadian variations, showing that it is present in most patients with long-standing persistent AF, although the short-term variation is considerable. In Paper IV, 24-h ambulatory ECG recordings with paroxysmal and persistent AF are analyzed using an entropy-based method for characterization of the atrial activity. Short segments are classified based on these measures, showing that it is feasible to distinguish between patient with paroxysmal and persistent AF from 10-s ECGs; the average classification rate was above 95%. The ventricular response during AF is mainly determined by the AV nodal blocking of atrial impulses. In Paper V, a new model-based approach for analysis of the ventricular response during AF is proposed. The model integrates physiological properties of the AV node and the atrial fibrillatory rate; the model parameters can be estimated from ECG signals. Results show that ventricular response is sufficiently represented by the estimated model in a majority of the recordings; in 85.7% of the analyzed 30-min segments the model fit was considered accurate, and that changes of AV nodal properties caused by autonomic modulation could be tracked through the estimated model parameters. In summary, the work within this thesis contributes with new methods for non-invasive analysis of AF, which can be used to tailor and evaluate different strategies for AF treatment

Impact of atrial fibrillation on the cardiovascular system through a lumped-parameter approach

Atrial fibrillation (AF) is the most common arrhythmia affecting millions of people in the Western countries and, due to the widespread impact on the population and its medical relevance, is largely investigated in both clinical and bioengineering sciences. However, some important feedback mechanisms are still not clearly established. The present study aims at understanding the global response of the cardiovascular system during paroxysmal AF through a lumped-parameter approach, which is here performed paying particular attention to the stochastic modeling of the irregular heartbeats and the reduced contractility of the heart. AF can be here analyzed by means of a wide number of hemodynamic parameters and avoiding the presence of other pathologies, which usually accompany AF. Reduced cardiac output with correlated drop of ejection fraction and decreased amount of energy converted to work by the heart during blood pumping, as well as higher left atrial volumes and pressures are some of the most representative results aligned with the existing clinical literature and here emerging during acute AF. The present modeling, providing new insights on cardiovascular variables which are difficult to measure and rarely reported in literature, turns out to be an efficient and powerful tool for a deeper comprehension and prediction of the arrythmia impact on the whole cardiovascular system.Comment: 16 pages, 8 figures, 2 tables, Medical & Biological Engineering & Computing, 2014, Print ISSN: 0140-0118, Online ISSN: 1741-044

Incidence, predictors, and evolution of conduction disorders and atrial arrhythmias after contemporary mitral valve repair

Background: Conduction disorders (CD) and atrial arrhythmias (AA) in the postoperative period of cardiac surgery impede prompt clinical recovery and prolong hospitalization. Mitral valve repair (MVR) has become the treatment of choice for patients with significant valvular regurgitation, but information on CD and AA in this population is scarce.Methods: Records of consecutive patients undergoing MVR at a single center were reviewed. Patients with a preoperative pacemaker, CD, prior cardiac surgery or concomitant MVR were excluded. A total of 290 patients were included in the final analysis. Electrocardiograms pre andpost-operatively were analyzed for CD and AA.Results: CD occurred in 69 (23.7%) patients: 47 (16.2%) had first degree atrio-ventricular block (AVB), 10 (3.4%) had Mobitz I, 3 (1.03%) had Mobitz II, and 9 (3.1%) complete AVB. Only 6 (2.0%) patients required pacemakers. Univariate predictors of AVB were age, preexisting right bundle branch block (RBBB), mitral valve ring size, and bypass time. The only multivariate predictors of AVB were bypass time and preexisting RBBB (OR 3.23 and 1.98, respectively). The most common AA was atrial fibrillation 13.1% (38 patients) followed by atrial flutter 2.7% (8 patients). Multivariate predictors of AA were age and left atrial size (OR 1.85 and 4.2, respectively). Length of stay in patients with CD or AA was prolonged 2.2 ± 2 days compared to controls (p < 0.05).Conclusions: In this large sample of patients undergoing MVR, we found that bypass time and preexisting RBBB were independent predictors of CD; age and left atrial size were independent predictors of AA.

The effects of nicotine and cigarette smoking on cardiac electrophysiology.

Cigarette smoking is a leading cause of preventable disease and premature death worldwide. The adverse effects of cigarette smoking, including proarrhythmia, are related to the mixture of chemicals, including nicotine (which sustains tobacco addiction). However, it remains unclear which individual tobacco smoke constituents and biological pathways mediate this increased risk. The purpose of this research was to explore the chronic effects of cigarette smoking, as well as compare the acute effects of nicotine and cigarette smoking, and the possible role of β-adrenoreceptors, on human cardiac electrophysiology. Chapter 1 is a comprehensive literature review of (a) the ex vivo and in vivo effects of nicotine and non-nicotine constituents of cigarette smoking on cardiac ion channels, (b) the direct and indirect effects of the autonomic nervous system on cardiac electrophysiology, and (c) studies of acute and chronic effects of cigarette smoking in humans. Chapter 2 consists of two studies in which we used cotinine levels to investigate the differences in baseline cardiac electrocardiogram between chronic smokers and non-smokers, and to define smoking status and its burden. We also explored the relationship between urinary catecholamines, cotinine, and electrocardiographic changes. Chapter 3 features the 2 x 2 factorial experimental study designed to compare the acute effects of cigarette smoking and nicotine, with and without a β-blocker (propranolol). We found that chronic cigarette smoking was associated with a shortened PR segment at baseline, and that dopamine possibly mediates this effect. There was also (corrected) QT interval shortening with increased cotinine levels. This experimental study revealed that the non-nicotine constituents in cigarette smoking were mainly responsible for PR segment shortening, through β-adrenoreceptors. Other evidence revealed that, although nicotine in cigarette smoke is primarily responsible for sympathetic activation and (corrected) QT interval shortening, it is the non-nicotine constituents that depress the ST segment. Collectively, acute and chronic exposure studies indicate that smoking may promote cardiac arrhythmia, primarily via β-adrenoreceptors, causing acceleration of dromotropy and ischemia (non-nicotine mediated), and ventricular repolarization (nicotine-mediated). This research elucidated a major physiological mechanism driving the effect of cigarette smoking and nicotine on cardiac electrophysiology. Consequently, these findings will inform U.S. Food and Drug Administration of tobacco and nicotine-containing products’ impact on the human cardiac electrical system, and potentially help regulate alternative forms of nicotine delivery and protect public health

Electrocardiographic changes in patients undergoing targeted temperature management

ObjectivesTargeted temperature management is the recommended therapy for comatose patients after an out‐of‐hospital cardiac arrest resuscitation due to the reduction in neurological damage and improved outcomes. However, there may result in electrocardiographic instability depending on the degree of targeted temperature management, including minor or life‐threatening dysrhythmias or conduction delays. This project aims to describe the frequency of ECG interval changes and clinically relevant dysrhythmias in targeted temperature management patients.MethodsThis is a retrospective observational study from January 2009 to December 2015. Patients who qualified for the study had a non‐traumatic cardiac arrest with a return of spontaneous circulation, received targeted temperature management at 33.5°C for 24 hours followed by 16 hours of rewarming. ECG interval changes and dysrhythmias were recorded immediately after return of spontaneous circulation, and at 24 and 48 hours post return of spontaneous circulation.ResultsA total of 322 patients (age 61.0 ± 16.9 years) had targeted temperature management initiated during the study period, of which 169 had complete data and 13 died prior to completing 24 hours of hypothermia. There were statistically significant changes during targeted temperature management in heart rate (96.7 ± 26.0/min before targeted temperature management; 69.5 ± 19.1/min during, P < 0.001), QRS duration (115.1 ± 32.6 ms before targeted temperature management; 107.8 ± 27.9 ms during targeted temperature management, P < 0.001), and QTc (486.3 ± 52.8 ms before targeted temperature management; 526.9 ± 61.7 ms during targeted temperature management, P < 0.001). There were cardiac dysrhythmias that received treatment during cooling and rewarming.ConclusionDuring the period of targeted temperature management and rewarming, we observed few self‐limiting ECG interval changes and no clinically significant dysrhythmias in this population during the period of targeted temperature management.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156464/2/emp212104_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156464/1/emp212104.pd