Inherited Structural Heart Diseases With Potential Atrial Fibrillation Occurrence

2015 ◽  
Vol 27 (2) ◽  
pp. 242-252 ◽  
Author(s):  
ROBERTA MANUGUERRA ◽  
SERGIO CALLEGARI ◽  
DOMENICO CORRADI
Keyword(s):  
Atrial Fibrillation ◽  
Heart Diseases ◽  
Structural Heart Diseases

Atrial Appendage Transcriptional Profile in Patients with Atrial Fibrillation with Structural Heart Diseases

2006 ◽  
Vol 1091 (1) ◽  
pp. 205-217 ◽  
Author(s):  
MARIA S. KHARLAP ◽  
ANGELICA V. TIMOFEEVA ◽  
LUDMILA E. GORYUNOVA ◽  
GEORGE L. KHASPEKOV ◽  
SERGEY L. DZEMESHKEVICH ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Diseases ◽  
Transcriptional Profile ◽  
Atrial Appendage ◽  
Structural Heart Diseases

scholarly journals Flecainide in Ventricular Arrhythmias: From Old Myths to New Perspectives

2021 ◽  
Vol 10 (16) ◽  
pp. 3696
Author(s):  
Carlo Lavalle ◽  
Sara Trivigno ◽  
Giampaolo Vetta ◽  
Michele Magnocavallo ◽  
Marco Valerio Mariani ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Disease ◽  
Ventricular Arrhythmias ◽  
Heart Diseases ◽  
Structural Heart Disease ◽  
Rhythm Control ◽  
Current Evidence ◽  
Structural Heart Diseases ◽  
Therapeutic Tools ◽  
Sinus Rhythm Maintenance

Flecainide is an IC antiarrhythmic drug (AAD) that received in 1984 Food and Drug Administration approval for the treatment of sustained ventricular tachycardia (VT) and subsequently for rhythm control of atrial fibrillation (AF). Currently, flecainide is mainly employed for sinus rhythm maintenance in AF and the treatment of idiopathic ventricular arrhythmias (IVA) in absence of ischaemic and structural heart disease on the basis of CAST data. Recent studies enrolling patients with different structural heart diseases demonstrated good effectiveness and safety profile of flecainide. The purpose of this review is to assess current evidence for appropriate and safe use of flecainide, 30 years after CAST data, in the light of new diagnostic and therapeutic tools in the field of ischaemic and non-ischaemic heart disease.

scholarly journals Distribution of First-Detected Atrial Fibrillation Patients Without Structural Heart Diseases in Symptom Classifications

2012 ◽  
Vol 76 (4) ◽  
pp. 1020-1023 ◽  
Author(s):  
Keitaro Senoo ◽  
Shinya Suzuki ◽  
Koichi Sagara ◽  
Takayuki Otsuka ◽  
Shunsuke Matsuno ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Diseases ◽  
Structural Heart Diseases

scholarly journals Identifying patients with atrial fibrillation during sinus rhythm on ECG: confirming the utility of artificial intelligence algorithm in a small-scale cohort without structural heart diseases

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
S Suzuki ◽  
J Motogi ◽  
W Matsuzawa ◽  
T Takayanagi ◽  
T Umemoto ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Atrial Fibrillation ◽  
Sinus Rhythm ◽  
Time Course ◽  
Heart Diseases ◽  
Validation Dataset ◽  
Small Scale ◽  
Internal Validation ◽  
Testing Dataset ◽  
Structural Heart Diseases

Abstract Background Detection of atrial fibrillation (AF) out of electrocardiograph (ECG) on sinus rhythm (SR) using artificial intelligence (AI) algorithm has been widely studied within recent couple of years. Generally, it is believed that a huge number of ECGs are necessary for developing an AI-enabled ECG to be adequate to correspond to a lot of minor variations of ECGs. For example, structural heart diseases have typical ECG characteristics, but they could be a noise for the purpose of detecting the small signs of electrocardiographic signature of AF. We hypothesized that when patients with structural heart diseases are excluded, AI-enabled ECG for identifying patients with AF can be developed with a small number of ECGs. Methods We developed an AI-enabled ECG using a convolutional neural network to detect the electrocardiographic signature of AF present during normal sinus rhythm (NSR) using a digital, standard 10-second, 12-lead ECGs. We included all patients who newly visited the Cardiovascular Institute with at least one NSR ECG between Feb 1, 2010, and March 31, 2018. We classified patients with at least one ECG with a rhythm of AF as positive for AF (AF label) and others as negative for AF (SR label). We allocated ECGs to the training, internal validation, and testing datasets in a 7:1:2 ratio. We calculated the area under the curve (AUC) of the receiver operating characteristic curve for the internal validation dataset to select a probability threshold, which we applied to the testing dataset. We evaluated model performance on the testing dataset by calculating the AUC and the sensitivity, specificity, F1 score, and accuracy with two-sided 95% confidence intervals (CIs). Results We totally included 19170 patients with 12-lead ECG. After excluding patients with structural heart diseases, 12825 patients with NSR ECGs at the initial visit were identified (1262 were clinically diagnosed as AF anytime during the time course and 11563 were never diagnosed as AF). Of 11563 non-AF patients, 1818 patients who were followed over 1095 days were selected for the analysis with the SR label, to secure the robustness for maintaining SR. Of 1262 AF patients, 251 patients were selected for the analysis with the AF label, of whom a NSR ECG within 31 days before or after the index AF ECG (the first AF ECG during the time course) could be obtained. In the patients with AF label, the NSR ECG of which the date was the nearest to the index AF ECG was selected for the analysis. The AI-enabled ECG showed an AUC of 0.88 (0.84–0.92) with sensitivity 81% (72–88), specificity 80% (77–83), F1 score 50% (43–57), and overall accuracy 80% (78–83). Conclusion An AI-enabled ECG acquired during NSR allowed identification of patients with AF in a small population without structural heart diseases. FUNDunding Acknowledgement Type of funding sources: None.

HEART COMPLICATIONS IN HYPERTHYROIDISM

2011 ◽  
pp. 7-17
Author(s):  
Hai Thuy Nguyen ◽  
Anh Vu Nguyen
Keyword(s):  
Atrial Fibrillation ◽  
Blood Pressure ◽  
Heart Rate ◽  
Heart Diseases ◽  
Systolic Dysfunction ◽  
Oxygen Demand ◽  
Left Ventricular ◽  
Cardiac Contraction ◽  
Cardiac Complications ◽  
Cardiac Symptoms

Thyroid hormone increases the force of the contraction and the amount of the heart muscle oxygen demand. It also increases the heart rate. Due to these reasons, the work of the heart is greatly increased in hyperthyroidism. Hyperthyroidism increases the amount of nitric oxide in the intima, lead them to be dilated and become less stiff. Cardiac symptoms can be seen in anybody with hyperthyroidism, but can be particularly dangerous in whom have underlying heart diseases. Common symptoms include: tachycardia and palpitations. Occult hyperthyroidism is a common cause of an increased heart rate at rest and with mild exertion. Hyperthyroidism can also produce a host of other arrhythmias such as PVCs, ventricular tachycardia and especially atrial fibrillation. Left ventricular diastolic dysfunction and systolic dysfunction, Mitral regurgitation and mitral valve prolapsed are heart complications of hyperthyroism could be detected by echocardiography. The forceful cardiac contraction increases the systolic blood pressure despite the increased relaxation in the blood vessels reduces the diastolic blood pressure. Atrial fibrillation, atrial enlargement and congestive heart failure are important cardiac complications of hyperthyroidism. An increased risks of stroke is common in patients with atrial fibrillation. Graves disease is linked to autoimmune complications, such as cardiac valve involvement, pulmonary arterial hypertension and specific cardiomyopathy. Worsening angina: Patients with coronary artery disease often experience a marked worsening in symptoms with hyperthyroidism. These can include an increase in chest pain (angina) or even a heart attack.

scholarly journals Identification and prognostication of the substrate of ventricular arrhythmia with cardiac magnetic resonance (CMR) imaging in patients with normal echocardiography

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
S Younus ◽  
H Maqsood ◽  
A Gulraiz ◽  
MD Khan ◽  
R Awais
Keyword(s):  
Heart Disease ◽  
Ventricular Tachycardia ◽  
Cardiac Magnetic Resonance ◽  
Chest Pain ◽  
Magnetic Resonance ◽  
Ventricular Arrhythmia ◽  
Heart Diseases ◽  
Sustained Ventricular Tachycardia ◽  
Structural Heart Diseases ◽  
Cmr Imaging

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Self Introduction Malignant ventricular arrhythmia contributes to approximately half of the sudden cardiac deaths. In common practice, echocardiography is used to identify structural heart diseases that are the most frequent substrate of VA. Identification and prognostication of structural heart diseases are very important as they are the main determinant of poor prognosis of ventricular arrhythmia. Purpose : The objective of this study is to determine whether cardiac magnetic resonance (CMR) may identify structural heart disease (SHD) in patients with ventricular arrhythmia who had no pathology observed on echocardiography. Methods : A total of 864 consecutive patients were enrolled in this single-center prospective study with significant ventricular arrhythmia. VA was characterized as >1000 ventricular ectopic beats per 24 hours, non-sustained ventricular arrhythmia, sustained ventricular arrhythmia, and no pathological lesion on echocardiography. The primary endpoint was the detection of SHD with CMR. Secondary endpoints were a composite of CMR detection of SHD and abnormal findings not specific for a definite SHD diagnosis. Results : CMR studies were used to diagnose SHD in 212 patients (24.5%) and abnormal findings not specific for a definite SHD diagnosis in 153 patients (17.7%). Myocarditis (n = 84) was the more frequent disease, followed by arrhythmogenic cardiomyopathy (n = 51), ischemic heart disease (n = 32), dilated cardiomyopathy (n = 17), hypertrophic cardiomyopathy (n = 12), congenital cardiac disease (n = 08), left ventricle noncompaction (n = 5), and pericarditis (n = 3). The strongest univariate and multivariate predictors of SHD on CMR images were chest pain (odds ratios [OR]: 2.5 and 2.33, respectively) and sustained ventricular tachycardia (ORs: 2.62 and 2.21, respectively). Conclusion : Our study concludes that SHD was able to be identified on CMR imaging in a significant number of patients with malignant VA and completely normal echocardiography. Chest pain and sustained ventricular tachycardia were the two strongest predictors of positive CMR imaging results. Abstract Figure. Distribution of different SHD

The impact of physical exercise on the occurence of arrhythmias in athletes – recommendations

2018 ◽  
Vol 1 (46) ◽  
pp. 11-15
Author(s):  
Jakub Szwed ◽  
Michał Kowara ◽  
Marcin Grabowski
Keyword(s):  
Physical Exercise ◽  
Heart Diseases ◽  
Sudden Cardiac Arrest ◽  
Endurance Sports ◽  
Endurance Sport ◽  
Sport Training ◽  
Negative Results ◽  
Structural Heart Diseases ◽  
Long Time ◽  
The Impact

The aim of this article is to demonstrate the impact of physical exercise on the development of arrhytmias in athletes. The studies show that this relation exist and concerns endurance sports practiced for a long time. In addition, this article contains review of the most common arrhythmias in athletes and appropriate recommendations. The time of arrhythmias onset depends on the presence of structural heart diseases. If the cardiac disorder is absent the arrhythmias appear at the age 40-50. If the structural heart diseases exist, the arrhythmias occur in young athletes and are more dangerous (can lead to sudden cardiac arrest). The most common arrhythmia in endurance athletes is atrial fibrillation. In order to avoid negative results of endurance sports, such as cardiac arrhythmias, the reliable examinations are necessary, especially to exclude structural cardiac diseases. These examinations should be undertaken before initiation of endurance sport training and routinely later, in course of follow-up.

Diagnostic value of assessment of coronary calcification in dysplastic heart

2021 ◽  
Vol 19 (1) ◽  
pp. 75-77
Author(s):  
L. T. Pimenov ◽  
◽  
V. V. Remnyakov ◽  
M. Yu. Smetanin ◽  
E. N. Avdeev ◽  
...  
Keyword(s):  
Connective Tissue ◽  
System Development ◽  
Heart Diseases ◽  
Coronary Calcification ◽  
Diagnostic Value ◽  
Conduction Disorders ◽  
Increased Risk ◽  
Structural Heart Diseases ◽  
Connective Tissue Dysplasia ◽  
Functional Features

The problem of heart connective tissue dysplasia syndrome is extremely relevant due to the increased risk of rhythm and conduction disorders, infectious endocarditis, thromboembolism and sudden cardiac death (SCD). Structural heart diseases (SHD) are manifestations of minor anomalies of the cardiovascular system development. Dysplastic heart refers to the combination of constitutional, topographical, anatomical, and functional features of the heart in a patient with connective tissue dysplasia (CTD). The standard for the diagnosis of coronary calcification (CC), one of the known predictors of coronary heart disease (CHD) and complications of cardiovascular diseases (CVD), is multispiral computed tomography (MSCT).

scholarly journals The Changing Paradigm in the Treatment of Structural Heart Disease and the Need for the Interventional Imaging Specialist

2016 ◽  
Vol 11 (2) ◽  
pp. 135
Author(s):  
Nina C Wunderlich ◽  
Harald Küx ◽  
Felix Kreidel ◽  
Ralf Birkemeyer ◽  
Robert J Siegel ◽  
...  
Keyword(s):  
Heart Disease ◽  
Heart Diseases ◽  
Three Dimensional ◽  
Structural Heart Disease ◽  
Percutaneous Treatment ◽  
Interventional Imaging ◽  
Key Factor ◽  
Structural Heart Diseases ◽  
Specialist Standard ◽  
Contrast Ventriculography

Percutaneous interventions in structural heart diseases are emerging rapidly. The variety of novel percutaneous treatment approaches and the increasing complexity of interventional procedures are associated with new challenges and demands on the imaging specialist. Standard catheterisation laboratory imaging modalities such as fluoroscopy and contrast ventriculography provide inadequate visualisation of the soft tissue or three-dimensional delineation of the heart. Consequently, additional advanced imaging technology is needed to diagnose and precisely identify structural heart diseases, to properly select patients for specific interventions and to support fluoroscopy in guiding procedures. As imaging expertise constitutes a key factor in the decision-making process and in the management of patients with structural heart disease, the sub-speciality of interventional imaging will likely develop out of an increased need for high-quality imaging.

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