scholarly journals Guideline-Concordant Antiarrhythmic Drug Use in the Get With The Guidelines: Atrial Fibrillation Registry

2021 ◽  
Author(s):  
Michael E. Field ◽  
DaJuanicia N. Holmes ◽  
Richard L. Page ◽  
Gregg C. Fonarow ◽  
Roland A. Matsouaka ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Antiarrhythmic Drug ◽  
Temporal Trends ◽  
Structural Heart Disease ◽  
Primary Diagnosis ◽  
Geographic Region ◽  
Patient Specific ◽  
Specific Patient ◽  
Get With The Guidelines

Background - Antiarrhythmic drug (AAD) therapy for atrial fibrillation (AF) can be associated with both proarrhythmic and noncardiovascular toxicities. Practice guidelines recommend tailored AAD therapy for AF based on patient-specific characteristics, such as coronary artery disease and heart failure, to minimize adverse events. However, current prescription patterns for specific AADs and the degree to which these guidelines are followed in practice are unknown. Methods - Patients enrolled in the Get With The Guidelines-AFIB registry with a primary diagnosis of AF discharged on an AAD between 1/2014 and 11/2018 were included. We analyzed rates of prescription of each AAD in several subgroups including those without structural heart disease. We classified AAD use as guideline-concordant or non-guideline concordant based on six criteria derived from the AHA/ACC/HRS AF Guidelines. Guideline concordance for amiodarone was not considered applicable, since its use is not specifically contraindicated in the guidelines for reasons such as structural heart disease or renal function. We analyzed guideline-concordant AAD use by specific patient and hospital characteristics, and regional and temporal trends. Results - Among 21,921 patients from 123 sites, the median age was 69 years, 46% female, and 51% had paroxysmal AF. The most commonly prescribed AAD was amiodarone (38%). Sotalol (23.2%) and dofetilide (19.2%) were each more commonly prescribed than either flecainide (9.8%) or propafenone (4.8%). Overall guideline-concordant AAD prescription at discharge was 84%. Guideline-concordant AAD use by drug was as follows: dofetilide 93%, sotalol 66%, flecainide 68%, propafenone 48%, and dronedarone 80%. There was variability in rate of guideline-concordant AAD use by hospital and geographic region. Conclusions - Amiodarone remains the most commonly prescribed AAD for AF followed by sotalol and dofetilide. Rates of guideline-concordant AAD use were high and there was significant variability by specific drugs, hospitals, and regions, highlighting opportunities for additional quality improvement.

scholarly journals Antiarrhythmic Drug Use in Patients <65 Years With Atrial Fibrillation and Without Structural Heart Disease

2015 ◽  
Vol 115 (3) ◽  
pp. 316-322 ◽  
Author(s):  
Nancy M. Allen LaPointe ◽  
Dadi Dai ◽  
Laine Thomas ◽  
Jonathan P. Piccini ◽  
Eric D. Peterson ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Drug Use ◽  
Antiarrhythmic Drug ◽  
Structural Heart Disease

Advanced interatrial block precedes atrial fibrillation and stroke. The prospective interatrial Block And Yearly EventS (BAYES) registry

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Martinez-Selles ◽  
R Elosua ◽  
M Ibarrola ◽  
M De Andres ◽  
P Diez-Villanueva ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Sinus Rhythm ◽  
Structural Heart Disease ◽  
P Wave ◽  
Wave Duration ◽  
P Wave Duration ◽  
Previous Diagnosis ◽  
Surface Ecg ◽  
Interatrial Block

Abstract Background Advanced interatrial block (IAB), prolonged and bimodal P waves in surface ECG inferior leads, is an unrecognized surrogate of atrial dysfunction and a trigger of atrial dysrhythmias, mainly atrial fibrillation (AF). Our aim was to prospectively assess whether advanced IAB in sinus rhythm precedes AF and stroke in elderly outpatients with structural heart disease, a group not previously studied. Methods Prospective observational registry that included outpatients aged ≥70 years with structural heart disease and no previous diagnosis of AF. Patients were divided into three groups according to P-wave characteristics. Results Among 556 individuals, 223 had normal P-wave (40.1%), 196 partial IAB (35.3%), and 137 advanced IAB (24.6%). After a median follow-up of 694 days; 93 patients (16.7%) developed AF, 30 stroke (5.4%), and 34 died (6.1%). Advanced IAB was independently associated with AF (hazard ratio [HR] 2.9, 95% confidence interval [CI] 1.7–5.1, p&lt;0.001), stroke (HR 3.8, 95% CI 1.4–10.7, p=0.010), and AF/stroke (HR 2.6, 95% CI 1.5–4.4, p=0.001). P-wave duration (ms) was independently associated with AF (HR 1.05, 95% CI 1.03–1.07, p&lt;0.001), AF/stroke (HR 1.04, 95% CI 1.02–1.06, p&lt;0.001), and mortality (HR 1.04, 95% CI 1.00–1.08, p=0.021). Conclusions The presence of advanced IAB in sinus rhythm is a risk factor for AF and stroke in an elderly population with structural heart disease and no previous diagnosis of AF. P-wave duration was also associated with all-cause mortality. Figure. Age- and sex-adjusted linear and non-linear association between P-wave duration (msec) and atrial fibrillation (A), stroke (B), and atrial fibrillation or stroke (C) risk. Results of a generalized additive model with spline smoothing functions and 4 degrees of freedom. Figure 1. Kaplan-Meyer curves of survival free of atrial fibrillation (A), stroke (B) and atrial fibrillation or stroke (C) in patients with normal P-wave, partial interatrial block (IAB) and advanced IAB. Funding Acknowledgement Type of funding source: None

scholarly journals Electropathological Substrate of Long-Standing Persistent Atrial Fibrillation in Patients With Structural Heart Disease

2010 ◽  
Vol 3 (6) ◽  
pp. 606-615 ◽  
Author(s):  
Maurits A. Allessie ◽  
Natasja M.S. de Groot ◽  
Richard P.M. Houben ◽  
Ulrich Schotten ◽  
Eric Boersma ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Structural Heart Disease ◽  
Persistent Atrial Fibrillation

On-device Prior Knowledge Incorporated Learning for Personalized Atrial Fibrillation Detection

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-25
Author(s):  
Zhenge Jia ◽  
Yiyu Shi ◽  
Samir Saba ◽  
Jingtong Hu
Keyword(s):  
Atrial Fibrillation ◽  
Prior Knowledge ◽  
Domain Knowledge ◽  
Fine Tuning ◽  
Cardiac Monitoring ◽  
Patient Specific ◽  
Detection Accuracy ◽  
Specific Patient ◽  
Deep Model ◽  
Tuning Strategy

Atrial Fibrillation (AF), one of the most prevalent arrhythmias, is an irregular heart-rate rhythm causing serious health problems such as stroke and heart failure. Deep learning based methods have been exploited to provide an end-to-end AF detection by automatically extracting features from Electrocardiogram (ECG) signal and achieve state-of-the-art results. However, the pre-trained models cannot adapt to each patient’s rhythm due to the high variability of rhythm characteristics among different patients. Furthermore, the deep models are prone to overfitting when fine-tuned on the limited ECG of the specific patient for personalization. In this work, we propose a prior knowledge incorporated learning method to effectively personalize the model for patient-specific AF detection and alleviate the overfitting problems. To be more specific, a prior-incorporated portion importance mechanism is proposed to enforce the network to learn to focus on the targeted portion of the ECG, following the cardiologists’ domain knowledge in recognizing AF. A prior-incorporated regularization mechanism is further devised to alleviate model overfitting during personalization by regularizing the fine-tuning process with feature priors on typical AF rhythms of the general population. The proposed personalization method embeds the well-defined prior knowledge in diagnosing AF rhythm into the personalization procedure, which improves the personalized deep model and eliminates the workload of manually adjusting parameters in conventional AF detection method. The prior knowledge incorporated personalization is feasibly and semi-automatically conducted on the edge, device of the cardiac monitoring system. We report an average AF detection accuracy of 95.3% of three deep models over patients, surpassing the pre-trained model by a large margin of 11.5% and the fine-tuning strategy by 8.6%.

Atrial flutter: clinical presentation

ESC CardioMed ◽  
2018 ◽  
pp. 2208-2211
Author(s):  
Bhupesh Pathik ◽  
Jonathan M. Kalman
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Atrial Flutter ◽  
Clinical Presentation ◽  
Three Dimensional ◽  
Structural Heart Disease ◽  
Underlying Mechanism ◽  
Clinical Presentations ◽  
Ventricular Response ◽  
Focal Atrial Tachycardia

Atrial flutter refers to an electrocardiographic (ECG) appearance of continuously undulating flutter waves without an isoelectric baseline. It represents a heterogeneous group of atrial arrhythmias characterized by a macroreentrant mechanism. However, focal atrial tachycardia, especially if rapid and in the context of underlying structural heart disease or prior atrial surgery, may also cause a similar ECG appearance. A definition based on the underlying macroreentrant mechanism is therefore preferred particularly in the current era of three-dimensional electroanatomical mapping which allows detailed anatomical delineation of the circuit location. The clinical presentations of atrial macroreentry are variable and are influenced by ventricular response rate, presence of underlying structural heart disease, prior atrial surgery, or medications. The purpose of this chapter is to describe the different clinical presentations of this arrhythmia as well as its classification according to underlying mechanism. In addition, the clinical presentation of atrial macroreentry in special clinical situations is discussed. These include (1) the relationship between atrial fibrillation and cavotricuspid isthmus-dependent atrial macroreentry, (2) the organization of atrial fibrillation into atrial macroreentry with flecainide treatment, and (3) the association between atrial macroreentry and tachycardia-induced cardiomyopathy.

Computed tomography for cardiac morphology, function, and valve disease

ESC CardioMed ◽  
2018 ◽  
pp. 560-565
Author(s):  
Victoria Delgado
Keyword(s):  
Computed Tomography ◽  
Heart Disease ◽  
Valvular Heart Disease ◽  
Imaging Technique ◽  
Three Dimensional ◽  
Structural Heart Disease ◽  
Patient Specific ◽  
Cardiac Morphology ◽  
Imaging Tool ◽  
Transcatheter Interventions

Computed tomography (CT) has become an important imaging tool to evaluate cardiac anatomy. This three-dimensional, isotropic imaging technique provides volumetric datasets with submillimetre tissue resolution that can be post-processed to define the cardiac structures. CT has become the mainstay imaging technique for selection of patients for, and planning of, transcatheter interventions for structural heart disease. Electrocardiographic-gated CT permits acquisition of cardiac datasets along the cardiac cycle enabling assessment of left and right ventricular function and valvular heart disease. In addition, the advent of three-dimensional printing technologies, which use three-dimensional patient-specific models frequently obtained from CT datasets, has opened a myriad of possibilities in terms of development of anatomical teaching tools, functional models to assess vessel and valve function, planning surgical or transcatheter interventions, and designing of transcatheter cardiac devices. This chapter reviews the role of CT in assessing cardiac morphology and function and valvular heart disease.

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