scholarly journals The current profile of the patient with atrial fibrillation

10.3823/2572 ◽  
2018 ◽  
Vol 11 ◽  
Author(s):  
Iuliana Ardeleanu ◽  
Liviu Macovei ◽  
Larisa Anghel ◽  
Ana Tanasa ◽  
Mircea Balasanian ◽  
...  

Abstract: Atrial fibrillation (AF) is the most common supraventricular arrhythmia, characterized by an irregular and extremely rapid atrial electrical activation that causes loss of atrial mechanical function and important hemodynamic consequences. AF classification is important in both the therapeutic approach and the prognosis. Several classifications based on the ECG patch, epicardial or endocavitary records have been performed over time, but no classification can take into account all the characteristics of AF and especially associated diseases, which may be both the cause and consequence of arrhythmia. Aim: The aim of the study is to establish the current profile of the patient with atrial fibrillation in the new era of oral anticoagulant therapy and sinus rhythm restoration. Material and methods: The trial was conducted on patients with atrial fibrillation hospitalized between 01.10.2014-31.03.2015 at Institute of Cardiovascular Diseases ”Prof. Dr. G. Georgescu”, Iasi. Patients included in the study were analyzed according to age and sex, criteria for the clinical and paraclinic definition for atrial fibrillation. Results: Atrial fibrillation is an extremely common cardiovascular pathology and is present in about one-third of patients admitted to our clinic. Cardiovascular diseases such as hypertension, ischemic coronary artery disease, and valvulopathy are common in patients with AF. Patients with AF are usually elderly patients with many associated diseases in whom sinus rhythm restoration treatment and anticoagulant therapy are difficult to establish. AF is one of the most common arrhythmias that complicates the evolution of acute myocardial infarction, association between dual antiplatelet therapy and anticoagulation treatment, increasing the risk of bleeding complications. Conclusions: Atrial fibrillation is an extremely common cardiovascular pathology and is present in about one-third of patients admitted to our hospital. The data obtained revealed that this arrhythmia occurs in a small number of cases as the only pathology of the patient, usually associated with numerous comorbidities. Cardiovascular diseases such as hypertension, ischemic coronary artery disease, valvulopathy are common in our practice. Patient with AF is a patient who requires long-term anticoagulant therapy and in whom sinus rhythm recovery therapy is dependent on the precocity of presentation to the physician, as well as on the therapeutic resources of current medicine.

2020 ◽  
Vol 19 (3) ◽  
pp. 2488
Author(s):  
V. K. Kurashin ◽  
N. Yu. Borovkova ◽  
N. N. Borovkov ◽  
V. A. Kurashina ◽  
T. E. Bakka

Aim. To assess clinical and pathogenetic characteristics of patients with atrial fibrillation (AF) hospitalized in cardiology department of the regional clinical hospital, and to clarify the related management strategy.Material and methods. A total of 1164 patients were hospitalized in cardiology department of N.A. Semashko Nizhny Novgorod Regional Clinical Hospital in 2017, of which 331 (28,4%) had AF. These patients were included in the study. We analyzed history data of all patients, standard diagnostic tests were carried out. The CHA2DS2-VASc score was used to determine the risk of thromboembolic events, and the HASBLED score — to determine the bleeding risk.Results. The average age of patients was 63,2±10,0 years. In all patients, AF was diagnosed before admission to the hospital. All patients were hospitalized according to hospital waiting lists due to underlying diseases. The most common diseases were coronary artery disease, mainly in combination with hypertension, inflammatory and dystrophic myocardial disorders. Twenty-four patients were hospitalized due to heart failure progression. Nonvalvular AF prevailed among patients. Most patients had a permanent AF (58,3%), the second place took pa - roxysmal AF (36,8%). Much less frequently (4,9%), a persistent AF was observed. Stratification of risk factors for stroke, systemic thromboembolism, as well as for bleeding when indicated for anticoagulant therapy was carried out. Based on the results, oral anticoagulants were indicated for 260 (78,8%) of participants, while only 38,8% received them before hospitalization.Conclusion. Among patients hospitalized in the cardiology department, 28,4% had AF. The most common was nonvalvular AF, associated mainly with coronary artery disease, essential hypertension and their combination. Anticoagulant therapy was indicated for 78,8% of patients, while only 38,8% received it before. This requires further optimization of management of AF patients.


2017 ◽  
Vol 58 (3) ◽  
pp. 204-212 ◽  
Author(s):  
Lukas J. Motloch ◽  
Sara Reda ◽  
Robert Larbig ◽  
Ariane Wolff ◽  
Karolina A. Motloch ◽  
...  

Heart Rhythm ◽  
2012 ◽  
Vol 9 (12) ◽  
pp. 1923-1929 ◽  
Author(s):  
Bob Weijs ◽  
Ron Pisters ◽  
Rutger J. Haest ◽  
Johannes A. Kragten ◽  
Ivo A. Joosen ◽  
...  

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.


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