Browsing by Subject "Atrial Fibrillation"

Now showing 1 - 10 of 10
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    Atrial Fibrillation and Warfarin
    (2012-07-23) Kreuser, Lucas Jordan
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    Atrial Fibrillation Readmissions: Temporal Trends, Risk Factors and Data Driven Modeling
    (2021-12) Salsabili, Mahsa
    This dissertation provides a background with overview of the clinical perspective, policy perspective and application of data driven modeling for atrial fibrillation (AF) and hospital readmissions. Additionally, three aims focused on temporal trends in AF hospitalization and readmission, predictors of AF readmission, and application of machine learning models in AF readmission are presented. The overall purpose of this dissertation is to develop stronger understanding of the temporal trends in AF hospitalizations and readmission and identify factors that increase the likelihood of readmission among the AF population. The value of application of machine learning algorithms to predict readmissions were assessed and compared to traditional methods. Atrial fibrillation is the most common clinically significant cardiac arrhythmia in the United States. Poorly controlled atrial fibrillation patients are likely to be hospitalized and potentially readmitted to the hospital within 30 days. The Nationwide Readmission Database (NRD) was analyzed using the International Classification of Diseases, Ninth Revision (ICD‐9) and tenth revision (ICD-10) codes to identify adult patients with a primary diagnosis of atrial fibrillation at discharge. Among those admitted with atrial fibrillation on average 57,883 individuals were readmitted per year for all-cause readmission within 30 days from 2010 to 2017. The AF index hospitalization rate increased from 10.4 per 1000 adults in 2010 to 11.1 in 2013 and dropped back to 10.4 in 2014 and increased to 10.9 in 2017. This nationally representative study of primary atrial fibrillation admissions and readmissions found that over the 2010 to 2017 time frame, crude atrial fibrillation index admissions increased, except for 2014 wherethere was a decline. Thirty- day all-cause readmission rates remained relatively stable for atrial fibrillation index patients across the study years. There is limited data regarding 30‐day readmission rates and predictors after discharge for atrial fibrillation. The 2017 NRD was assessed using ICD‐10 codes to identify the AF population. Predictors of readmissions, and performance of the predictive model were analyzed. A hierarchical mixed linear model was used on the best performing model to identify the predictors of readmission based on index admission. Presence of comorbidities such as metastatic cancer, lymphoma and severe renal failure present in index atrial fibrillation during index hospitalization predicted higher likelihood 30‐day readmissions. About 1 in 6 patients had an all-cause 30-day readmission. The patient comorbidities contributed significantly to readmission with oncology comorbidities being the top predictor. There is a lack of studies attempting to predict readmissions among AF population using various machine learning techniques. Using the 2017 NRD, we explored the performance of four common and widely used classification approaches (random forest, decision tree, gradient boosting and Naïve Bayes) in 30-day all-cause readmission for AF patients. To have a less biased and more generalizable model 10-fold cross validation was performed to train and test the data, with five variations of feature presentation. We compared and reported common key performance indicators for binary classification techniques (e.g. Area-Under Curve (AUC), accuracy, sensitivity, specificity, and F1 score) among the various classifiers. Our results reveal that Gradient Boosting has the greatest performance with an AUC of 0.667, which was followed by Naïve Bayes and Random Forest with AUCs of 0.641 and 0.640 respectively. The feature variations with comorbidities present have better performance for these three classifiers. Using Gradient Boosting, Random Forest, and Naïve Bayes we get acceptable performance when assessing AF all cause 30-day readmission. Overall, the results of the dissertation show that the prevalence of AF hospitalizations and readmission is increasing over time. Presence of comorbidities among patients increased the likelihood of readmissions. The performance of linear based model and majority of the machine learning based models improved with the presence of variables representing comorbidities. The overall performance of the best performing machine learning models was similar to the linear model in predicting readmissions among the AF population.
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    Extending Function and Applications of Isolated Cardiopulmonary Systems
    (2016-11) Howard, Brian
    The use of isolated mammalian hearts has a history that is responsible for a staggering amount of the basic physiological knowledge we have about the cardiovascular system and is a primary gateway between ideas and clinical treatment. Advances in cardiac physiology, surgery, transplantation, pacing, defibrillation, ablation, and pharmacology are derived from this area of research. The work outlined here takes identified issues with experimental preparations, as well as clinical applications, to investigate solutions and directions for their systematic address. Extending the utility and window of viability of the isolated heart and lungs has resulted in clinically applicable advances in drug treatments and assessment tools. Most importantly though, it has the potential to expand the population of acceptable donor organs where there is immediate need and continuous shortfall in supply. My thesis consists of chapters which progress in translational application, making use of novel and comprehensive ways of controlling and investigating isolated cardiovascular systems. In the first chapter, the Visible Heart® preparation is used to replicate and extend a classic temperature experiment in the large isolated porcine heart. This chapter also addresses the clinical applications of optimizing heart function with emerging isolated heart transportation devices; making the best use of efforts to assess and maintain the heart for transplantation. This is followed in chapters 2 using the Visible Heart® system to assess therapeutic drug delivery for treating atrial fibrillation and again preserving a heart’s function for transplantation. The advancement of the isolated heart preparation is further driven by procedural concerns with cryo-ablation technologies to include functional lungs. This comprehensive system is used on actual human heart lung-bloc combinations for investigative purposes and required its own set of unique engineering solutions to produce a viable test platform. It is also this evolution of the isolated heart preparation that was a significant factor in bringing the Lung Organ Care System (OCS™) to the Visible Heart Laboratory as a unique research tool. As a commercial device, the OCS™ device seeks to replace the storage-on-ice standard of care with warm and ventilated perfusion of the lungs independent of the heart. As a laboratory instrument it has allowed new opportunities for investigating both basic lung physiology as well as providing lessons that are clinically applicable. The completely novel thermal monitoring of the lungs in this isolated state are discussed in Chapter 5 which investigates thermal tools and profiling of lung damage for the first time. This provides a whole new paradigm for emerging lung and general organ assessment directly relating identified injury states, overall lung function, and recovery/damage profiles that may help physicians make better use of precious donor lungs. In extending the use of the isolated lungs to an underutilized population of donors, the final chapter, Chapter 6, demonstrates for the first time a controlled study and injury model for donation after cardiac death (DCD). With modification to the current clinical use protocol for the OCS™ device, the viability window for injured lungs is shown to be nearly tripled. The impact of demonstrating viable DCD lungs on this system is the potential to greatly expand the number of lungs for transplantation, which would be invaluable to many currently on a long wait list. My thesis work has produced stable isolated cardio-vasculature systems with direct impact on the design of devices, investigation, therapy and monitoring in the pursuit of bettering the standard of care and expanding the availability of the organs for transplantation. It provides new and unique combinations of heart and lungs tailored to the investigative necessity in human anatomy and a more comprehensively described large mammalian model for anatomy, physiology and acute injury.
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    Novel approaches for quantitative electrogram analysis for rotor identification: Implications for ablation in patients with atrial fibrillation
    (2017-05) Poigai Arunachalam, Shivaram
    Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that causes stroke affecting more than 2.3 million people in the US. Catheter ablation with pulmonary vein isolation (PVI) to terminate AF is successful for paroxysmal AF but suffers limitations with persistent AF patients as current mapping methods cannot identify AF active substrates outside of PVI region. Recent evidences in the mechanistic understating of AF pathophysiology suggest that ectopic activity, localized re-entrant circuit with fibrillatory propagation and multiple circuit re-entries may all be involved in human AF. Accordingly, the hypothesis that rotor is an underlying AF mechanism is compatible with both the presence of focal discharges and multiple wavelets. Rotors are stable electrical sources which have characteristic spiral waves like appearance with a pivot point surrounded by peripheral region. Targeted ablation at the rotor pivot points in several animal studies have demonstrated efficacy in terminating AF. The objective of this dissertation was to develop robust spatiotemporal mapping techniques that can fully capture the intrinsic dynamics of the non-stationary time series intracardiac electrogram signal to accurately identify the rotor pivot zones that may cause and maintain AF. In this thesis, four time domain approaches namely multiscale entropy (MSE) recurrence period density entropy (RPDE), kurtosis and intrinsic mode function (IMF) complexity index and one frequency domain approach namely multiscale frequency (MSF) was proposed and developed for accurate identification of rotor pivot points. The novel approaches were validated using optical mapping data with induced ventricular arrhythmia in ex-vivo isolated rabbit heart with single, double and meandering rotors (including numerically simulated data). The results demonstrated the efficacy of the novel approaches in accurate identification of rotor pivot point. The chaotic nature of rotor pivot point resulted in higher complexity measured by MSE, RPDE, kurtosis, IMF and MSF compared to the stable rotor periphery that enabled its accurate identification. Additionally, the feasibility of using conventional catheter mapping system to generate patient specific 3D maps for intraprocedural guidance for catheter ablation using these novel approaches was demonstrated with 1055 intracardiac electrograms obtained from both atria’s in a persistent AF patient. Notably, the 3D maps did not provide any clinically significant information on rotor pivot point identification or the presence of rotors themselves. Validation of these novel approaches is required in large datasets with paroxysmal and persistent AF patients to evaluate their clinical utility in rotor identification as potential targets for AF ablation.
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    Oral Anticoagulation: for Stroke Prevention in Patients with Atrial Fibrillation
    (2010-11-02) McKenzie, Kyle
    Oral anticoagulants are effective at preventing strokes in patients who have atrial fibrillation without significantly increasing hemorrhage. The more risk factors for stroke that a patient has along with atrial fibrillation the more benefit from oral anticoagulants. The benefit of stroke prevention needs to be weighed against risk of hemorrhage, life style change, medical monitoring, and cost.
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    Patient Information on Atrial Fibrillation
    (2011-08-03) Knight-Brown, Miranda
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    Signal processing approaches for the spatiotemporal analysis of cardiac arrhythmias using intracardiac electrograms
    (2022-02) Ravikumar, Vasanth
    Each heartbeat is controlled by an electrical wave of excitation that propagates throughthe heart and initiates cardiac contraction. The normal heartbeat is initiated by pacemaker cells in the sinus node located in the right atrium, propagate throughout the atria, and then enters the ventricles via the atrioventricular junction and finally ends in the Purkinje fibers. The rate and regularity of these cardiac rhythms are determined by the intrinsic firing rate (automaticity) of the pacemaker cells and the influence of extrinsic factors, including various ionic mechanisms and drugs. Abnormal regimes of wave initiation and propagation result in cardiac arrhythmias. Various mechanisms, including local ectopic activity, focal triggers, wave breaks, and functional reentry, drive the arrhythmic activity in the heart. The spatiotemporal complexity of each of these underlying mechanisms is different, with more complexity seen in tachyarrhythmias and less complexity for bradyarrhythmias. Understanding the spatiotemporal complexity of the different arrhythmias is of great interest to electrophysiologists. In recent years, catheter ablation therapy (non-pharmacological approach) has had anincreasingly important role in curing many arrhythmias. The underlying spatiotemporal complexity of each arrhythmia plays an important role in deciding the target sites for ablation in this therapy. Currently, existing signal analysis techniques are not robust for all types of arrhythmias. Therefore it is essential to develop new approaches that can fully capture the intrinsic dynamics and the spatiotemporal complexity of both atrial and ventricular arrhythmias using intracardiac electrogram signals. Some novel approaches, namely multiscale frequency, multiscale entropy, kurtosis, and Shannon entropy was developed using the ex-vivo optical mapping of rabbit hearts. But, the nature of signals obtained during optical mapping is very different from the intracardiac electrograms obtained during the catheter ablation procedure. Also, the clinical recordings suffer from limitations such as sparse spatial data availability and sequential mapping. Therefore it is essential to enhance the above techniques to work on the intracardiac electrograms and also identify the spatial sites in the heart that maintain these arrhythmic activities. For my study, the intracardiac analysis was performed under two different types ofcardiac arrhythmic rhythms, namely Atrial Fibrillation (AF) and Ventricular Fibrillation (VF). Atrial Fibrillation (AF) is an arrhythmia in the upper two chambers (atria) of the heart. AF is responsible for significant impairment in quality of life and contributes to substantial morbidity and health care expenditure. AF is the most common arrhythmia in humans and, as such, is heterogeneous in its mechanism, presentation, and clinical course and therefore requires individualized treatment. Ventricular fibrillation (VF) is a type of lethal heart rhythm. During ventricular fibrillation, disorganized heart signals cause the lower heart chambers (ventricles) to quiver, and the heart does not pump blood to the rest of the body. Ventricular fibrillation is an emergency that requires immediate medical attention. It's the most frequent cause of sudden cardiac death. Although both these rhythms originate at different locations of the heart and havedifferent types of rhythms and morphology, the underlying spatiotemporal organizations and intracardiac electrogram analysis approaches are similar. Therefore, my thesis consists of the following three objectives: 1. Clinical implementation and validation of novel approaches using intracardiac electrograms to characterize the spatiotemporal dynamics of the AF arrhythmic activities. 2. Development of a similarity score using a combination of various iEGMs analysis techniques to more accurately identify the spatial location of active sites in AF patients. 3. Development of an analytical approach to characterize the organization (organized or disorganized) of VF electrical activities using clinical intracardiac electrograms.
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    So I have atrial fibrillation…
    (2011-08-03) Edin, Colt
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    Studies of cryothermal ablation for the treatment of atrial fibrillation
    (2014-04) Goff, Ryan Patrick
    Atrial fibrillation (AF) remains as the most prevalent tachyarrhythmia, with a prevalence in the U.S., of 1% in the general population. The current therapeutic/treatment paradigm for the patient with atrial fibrillation, is to first attempt to restore normal rhythm via anti-arrhythmic pharmaceuticals. If this does not ameliorate the problem, or the patient does not well tolerate the drug side-effects, a transcatheter ablation is usually performed. The relatively recent introduction of cryoballoon based ablation has provided the electrophysiologist with an easier method of treating AF via pulmonary vein isolation. However, despite current clinical use research questions regarding anatomy, dosing, and device-tissue interactions have remained unanswered.Anatomical studies of the phrenic nerve, coronary sinus, left atria, and pulmonary vein anatomy were performed using high-resolution MRI and direct measurements on heart specimens. These novel anatomical studies may guide future device iterations and the computer based models used for numerical simulation. The amount of cooling required to injure and/or kill cardiac tissue, lung tissue, and the phrenic nerve was quantified using novel in-vitro models. These data may be used for procedural modeling and dosing optimization. Device-tissue interactions were studied using a functional, isolated heart-lung bloc model and a patent has been filed for this methodology. Using this model infrared imaging was performed to quantify the level of cooling being achieved by cryoballoon catheters. A separate study was performed using MRI to quantify ice dynamics and to our knowledge is the first cardiac cryoablation performed in an MR environment. This collection of work will aid the clinical, scientific, and engineering communities in further optimization of cardiac cryoablation.