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 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 31  |  Issue : 2  |  Page : 387-394

Incidence of atrial fibrillation in ischemic and nonischemic dilated cardiomyopathy


1 Cardiology Department, Faculty of Medicine, Menofia University, Shebin Elkom, Egypt
2 Cardiology Department, Al Nasr Hospital, Branch of Cairo, Health Insurance Commission, Cairo, Egypt

Date of Submission26-Nov-2016
Date of Acceptance16-Jan-2017
Date of Web Publication27-Aug-2018

Correspondence Address:
Kareem M AlAraby
Cardiology department, Al Nasr Hospital, Branch of Cairo, Health Insurance Commission, Cairo
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_644_16

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  Abstract 


Objective
The aim of this study was to identify the incidence of atrial fibrillation (AF) in ischemic dilated cardiomyopathy (IDCM) and nonischemic dilated cardiomyopathy (NIDCM).
Background
AF is a common arrhythmia and is associated with an increased risk for embolic events, congestive heart failure, and total mortality. It lowers the quality of life and has been shown to be associated with worsening of outcome in patients with congestive heart failure of different etiologies.
Materials and methods
Patients were recruited during scheduled outpatient visits to the outpatient clinic in the Menofia University Hospital and Health Insurance Hospital, over the period from July 2015 to March 2016. All patients underwent full physical examination, and ECG, echocardiogram, and coronary angiography were performed to differentiate between IDCM and NIDCM.
Results
Totally, 50 patients had dilated cardiomyopathy (DCM) with left ventricular dysfunction. They were classified into two groups: the NIDCM group (20 patients) and the IDCM group (30 patients). AF was found to be more frequent in IDCM patients than in NIDCM patients (P = 0.006). Dyslipidemia (P = 0.002), diabetes mellitus (DM) (P = 0.05), and the mean left atrial (LA) diameter (5.127 ± 0.798) (P = 0.03) were statistically significant in IDCM patients. The univariate analysis identified the following as predictors of AF incidence: DM (P = 0.006), dyslipidemia (P = 0.016), left ventricular end diastolic diameter (P = 0.022), LA diameter (P = 0.000), and IDCM (P = 0.006). The multivariate regression analysis identified that DM, dyslipidemia, and LA diameter (>4.8 cm) had a more independent predictor value of AF incidence among DCM patients despite etiological cause.
Conclusion
The incidence of AF is more frequent in IDCM than in NIDCM patients. There is no significant difference between the two groups as regards age, sex, BMI, and hypertension. LA dilatation is more significant in IDCM. DM, dyslipidemia, and dilated LA proved to be independent predictors of AF in DCM patients.

Keywords: atrial fibrillation, diabetes mellitus, dilated cardiomyopathy, ischemic dilated cardiomyopathy, nonischemic dilated cardiomyopathy


How to cite this article:
Kamal AM, Omara AA, Samy NI, AlAraby KM. Incidence of atrial fibrillation in ischemic and nonischemic dilated cardiomyopathy. Menoufia Med J 2018;31:387-94

How to cite this URL:
Kamal AM, Omara AA, Samy NI, AlAraby KM. Incidence of atrial fibrillation in ischemic and nonischemic dilated cardiomyopathy. Menoufia Med J [serial online] 2018 [cited 2018 Nov 16];31:387-94. Available from: http://www.mmj.eg.net/text.asp?2018/31/2/387/239758




  Introduction Top


Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice and its prevalence is expected to double by the year 2050 [1]. This arrhythmia is a major public health problem associated with many comorbid conditions and it places a significant financial burden on the healthcare system [2]. In addition, numerous reports have shown that AF is associated with an increased mortality risk [3]. Although mortality from AF classically has been associated with stroke [4],[5], recent reports have identified other conditions that likely contribute to the excess risk for death, including heart failure (HF) [6] and myocardial infarction (MI) [7]. The underlying link between AF and cardiovascular events has been linked to common risk factors, autonomic imbalances, inflammation [8], and abnormalities in hemostasis [9].

Dilated cardiomyopathy (DCM) is a disease with a high incidence and has a great social impact on patients. DCM is one of the cardiomyopathies, a group of diseases that affect primarily the myocardium (the muscle of the heart). Different cardiomyopathies have different causes and affect the heart in different ways [10].

The main cause for the development of DCM is an ischemic heart disease (IHD), which is thought to be responsible for ventricular dilatation in more than 60% of cases of DCM [11]. However, in nonischemic dilated cardiomyopathy (NIDCM) the myocardium is dilated, often without any obvious cause. Either left or right ventricular systolic pump function of the heart is impaired, leading to progressive cardiac enlargement, a process called remodeling [12]. This type includes left ventricular (LV) noncompaction, familial DCM, Takotsubo cardiomyopathy, postmyocarditis DCM, peripartum cardiomyopathy, and idiopathic [13],[14],[15],[16]. Ultrastructural changes in atrial myocytes lead to atrial remodeling and result in the development of multiple reentry circuits that culminate in AF. It is therefore thought that AF is an important clinical manifestation in the setting of left ventricular dysfunction (LVD) where it serves as a precipitant and harbinger of increased morbidity and mortality [17],[18],[19]. With the advent of new therapies for cardiovascular disease, the epidemiology of cardiovascular complications has changed. The global population is living longer, resulting in myocardial dysfunction and arrhythmia becoming growing pandemics. Impairment of LV function with or without an ischemic etiology is significantly associated with the development of AF. This is exemplified by the increasing prevalence of AF with incremental progression of New York Heart Association class of HF [17],[18].

The epidemiology of AF and congestive heart failure (CHF) is becoming increasingly common, with an estimated prevalence of 20 million people worldwide; similarly, AF has the highest prevalence of all sustained arrhythmias, affecting 1.5% of the population of the USA [1]. The prevalence of AF in LVD ranges from 5 to 65% and appears to depend on both the severity of HF and patient age [20],[21]. The incidence of AF complicating MI is estimated to be between 2.3 and 21% [22]. The close association between AF and MI may be attributed to the common risk factors such as age, hypertension (HTN), diabetes mellitus (DM), coronary artery disease (CAD), and HF [23]. The literature gives special attention to ventricular arrhythmias, which can lead to one of the two death mechanisms in DCM, sudden death. Fewer studies give attention to supraventricular arrhythmias. Among supraventricular arrhythmias, AF is the most common in DCM. Therefore, this study aimed to detect the incidence of AF in ischemic dilated cardiomyopathy (IDCM) and NIDCM.


  Materials and Methods Top


Our cohort study was conducted on patients who were recruited during scheduled outpatient visits to the cardiology outpatient clinic in the Menofia University Hospital, and Health Insurance Hospital (Alnasr Hospital in Helwan city), over the period from July 2015 to March 2016. Totally, 50 patients with established diagnoses of stable CHF with LVD [24] met eligibility criteria and provided written informed consent to participate.

They were classified into two groups according to the etiology of DCM.

Group 1: it included 20 patients with NIDCM who had normal coronaries.

Group 2: it included 30 patients with IDCM. The ischemic etiology was accepted based on history of MI or on objective evidence of CAD at coronary angiography in patients with LV systolic dysfunction [25],[26].

Inclusion criteria

  • IDCM and NIDCM with LVD criteria [24]
  • Left ventricular ejection fractions (LVEFs) 45% or less and clinical stability, without the need for hospital admission or intravenous vasoactive agents
  • Left ventricular end diastolic diameter (LVEDd) greater than 27 mm/m 2 body surface area.


Exclusion criteria

  • Valvular disease and prosthetic valve
  • Congenital heart disease
  • Undergone any cardiac revascularization procedure less than 30 days before enrollment
  • Hospitalization for MI and unstable angina, within the past 3 months.


Methodology

The protocol was approved by the Local Research Ethics Committee, and each patient provided informed consent.

At first, ethical issue was cleared for the patients and clear consent was obtained.

All patients were subjected to the following.

Clinical assessment

All patients underwent full physical and medical examination. Full history was taken from each patient, including name, age, sex, and smoking. Body weight and height were measured during the visit to calculate BMI [27] and data on history of IHD and family history of IHD were collected.

Risk factors

Risk factors were defined as follows:

HTN: patients who were treated with antihypertensive drugs or those with daily blood pressure readings greater than 140/90 mmHg during hospitalization were considered to have HTN [28]; blood pressure was measured using a random zero sphygmomanometer.

DM was diagnosed when fasting plasma glucose level was at or above 126 mg/dl [28], a 2 h value in an oral glucose tolerance test at or above 200 mg/dl, or a random plasma glucose concentration of 200 mg/dl in the presence of symptoms.

Hyperlipidemia was diagnosed when the total cholesterol level was above 240 mg/dl or triglyceride level was greater than 199 mg/dl and low-density lipoprotein cholesterol was greater than 160 mg/dl [28].

ECG

All patients underwent a standard 12-lead ECG. ECGs were recorded at a speed of 25 mm/s and a scale of 10 mm/mV. The diagnosis of AF was documented using ECGs obtained during the attack; they fulfilled the following criteria: AF absence of P waves, coarse or fine fibrillatory waves, and completely irregular RR-intervals [29]. In particular, it was performed to distinguish AF from atrial flutter, which is defined as the presence of flutter waves with a rate between 250 and 350/min and regular or irregular RR-intervals. We asked whether the patients had AF at the baseline ECG.

Echocardiography

Patients were imaged by means of echocardiographic examination in the left lateral decubitus position in the parasternal and apical views using a commercially available system (Vingmed Seven; General Electric, Milwaukee, Wisconsin, USA). LVEF was calculated from the conventional apical two-chamber and four-chamber images, using the biplane Simpson's technique. Echocardiographic data were LVEF, LV and left atrial (LA) dimensions, presence of mitral and/or aortic regurgitation, and the presence and degree of the LV diastolic dysfunction [30].

Coronary angiography

All patients underwent coronary imaging test (assessment of CAD).

The diagnostic procedure was performed by an experienced interventional cardiologist by using a Siemens high core system (Seldinger's technique) through the right femoral artery after inducing local anesthesia with xylocaine. For better displaying the lesions, to make the grading assessment possible, angiographies were performed in several views. Intra-arterial systolic and diastolic pressures of the ascending aorta were measured during cardiac catheterization. In patients with creatinine level 1.5 mg/dl or less and significant CAD, abdominal aortography was performed using a pigtail catheter with a pump injector for evaluating and/ruling out renal artery stenosis [31],[32].

Statistical analysis

All continuous variables were presented as mean ± SD if they were normally distributed, whereas categorical variables were described as absolute and relative (percentage) frequencies. Comparisons of continuous variables between the individual study groups were made using the unpaired t-test. Categorical data analysis was performed using Pearson's χ2-test or Fisher's exact test (two-tailed) if the expected count in any cell was less than 5. Analyses were performed with statistical package for the social sciences version 12.0 statistical package (SPSS; SPSS Inc., Chicago, Illinois, USA).


  Results Top


Patients were classified into two groups according to the etiology of DCM [Figure 1].
Figure 1: Percentage of nonischemic dilated cardiomyopathy and ischemic dilated cardiomyopathy patients in the whole study population.

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The NIDCM group included 20 patients who constituted 40% of the whole study population.

The IDCM group included 30 patients who constituted 60% of the whole study population.

As regards baseline clinical characteristics of the whole study population, the mean age of the whole cohort was 61.04 ± 13.7 years; there were 48 (96%) male patients and two (4%) female patients. The mean BMI was 27.46 ± 3.30 kg/m 2. There were 33 (66%) diabetic patients, 26 (52%) hypertensive patients, 26 (52%) dyslipidemic patients, 35 (43.3%) smokers, and 19 (38%) had AF.

Dyslipidemia (P = 0.002) and DM (P = 0.05) were significantly more frequent in the IDCM group of patients. There was no significant difference between the two study groups as regards the other clinical characteristics (age, sex, BMI, smoking, and HTN) (P > 0.05 for all) [Table 1].
Table 1: Effect of baseline clinical characteristics on study groups

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As regards the frequency of AF, patients of the IDCM group had significantly more frequent incidence of AF, compared with patients of the NIDCM group (P = 0.006) [Table 2] and [Figure 2].
Table 2: Echocardiographic findings of the two study groups

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Figure 2: Incidence of atrial fibrillation in two individual study groups.

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Among echocardiographic findings, the mean LA diameter was significantly higher in the IDCM group compared with the NIDCM group (5.127 ± 0.798 vs. 4.680 ± 0.626) (P = 0.03). There was no significant difference between the two groups as regards the mean of other findings (LVEDd, left ventricular end systolic diameter, and EF) (P > 0.05 for both) [Table 3].
Table 3: Effect of baseline clinical characteristics on the incidence of atrial fibrillation

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Univariate analysis was used to identify the predictors of AF in whole study groups. It showed that DM (P = 0.006) and dyslipidemia (P = 0.016) were significantly more frequent in AF patients [Table 5]. There was no difference between AF patients and sinus rhythm (SR) patients as regards the other clinical characteristics (age, sex, BMI, smoking, and HTN) (P > 0.05 for all).
Table 5: Effect of echocardiography findings on incidence of atrial fibrillation

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Univariate analysis showed that the incidence of AF patients who had IDCM was significantly higher than that for AF patients who had NIDCM (P = 0.006) [Table 4].
Table 4: Effect of study groups on the incidence of atrial fibrillation

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As regards echocardiographic findings, univariate analysis showed that the mean LA diameter and LVEDd were significantly higher in AF patients compared with SR patients (5.589 ± 0.544 vs. 4.555 ± 0.589 and 7.163 ± 0.577 vs. 6.739 ± 0.793, respectively) (P < 0.05 for both) [Table 5].

The univariate analysis identified the following as predictors of AF incidence: DM (P = 0.006), dyslipidemia (P = 0.016), LVEDd (P = 0.022), LA diameter (P = 0.000), and IDCM (P = 0.006).

We performed multivariate regression analysis utilizing all variables (DM, dyslipidemia, LVEDd, LA diameter, and IDCM) as independent predictors against AF incidence as a dependent variable. It identified that DM, dyslipidemia, and an increase in LA diameter had a more independent predictor function of AF among DCM patients despite etiological cause of DCM [Table 6].
Table 6: Multivariate regression analysis to identify independent predictors of atrial fibrillation incidence

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To test the discrimination power of the independent predictors of AF incidence among DCM patients (DM, dyslipidemia, and LA diameter), a receiver operating characteristic (ROC) curve was constructed [Table 7] and [Figure 3], [Figure 4], [Figure 5]. DM predicts AF incidence with a sensitivity of 90.4%, specificity of 84.4%, and area under curve (AUC) of 0.67; dyslipidemia predicts AF incidence with a sensitivity of 74.6%, specificity of 61.3%, and AUC of 0.68; and LA diameter predicts AF incidence with a sensitivity of 95.6%, specificity of 71%, and AUC of 0.91, and the cutoff value of LA diameter that best predicts AF incidence was greater than 4.8 cm.
Table 7: Receiver operating characteristic curve analysis to discriminate power of the independent predictors of atrial fibrillation incidence in dilated cardiomyopathy patients

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Figure 3: Receiver operating characteristic curves analysis for diabetes mellitus that predicts atrial fibrillation incidence in dilated cardiomyopathy patients.

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Figure 4: Receiver operating characteristic curves analysis for dyslipidemia that predicts atrial fibrillation incidence in dilated cardiomyopathy patients.

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Figure 5: Receiver operating characteristic curves analysis for left atrial diameter that predicts atrial fibrillation incidence in dilated cardiomyopathy patients.

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  Discussion Top


AF is the most common arrhythmia and is associated with an increased risk for embolic events, CHF, and total mortality. AF is common in DCM, and it limits cardiovascular capacity, lowers the quality of life and has been shown to associate with worsening outcome in patients with CHF of different etiologies: ischemic and nonischemic. The risk of developing AF is increased six-fold. Impairment of LV function with or without an ischemic etiology is significantly associated with the development of AF [17],[19]. Hence, in this study, we aimed to identify the incidence of AF and the risk factors affecting its prevalence among IDCM and NIDCM patients.

The current study showed that the mean age of the whole cohort was 61.04 ± 13.7 years; there were 48 (96%) male patients. The mean BMI was 27.46 ± 3.30 kg/m 2. There were 33 (66%) diabetic patients, 26 (52%) hypertensive patients, 26 (52%) dyslipidemic patients, 35 (43.3%) smokers, and 19 (38%) patients with AF.

Dyslipidemia and DM were significantly more frequent in the IDCM group of patients (P < 0.05). There was no significant difference between the two study groups as regards age, sex, BMI, smoking, and HTN (P > 0.05 for all).

Fazio et al. [33] aimed to differentiate between IDCM and NIDCM. The study enrolled 134 patients with DCM: 74 with the ischemic form and 60 with the nonischemic one. It did not find statistically significant differences between the two groups as regards age, BMI, smoking, DM, and HTN (P > 0.05 for all). This matched with our results, except for DM and dyslipidemia, which were found to be more frequent in the IDCM group.

In the current study, the incidence of AF was higher in patients of the IDCM group compared with patients of the NIDCM group (P = 0.006).

Our results go hand in hand with the data published by Pedersen et al. [34]. There were 3587 patients admitted in hospital because of HF who were included in this study. All patients were examined using echocardiography and the presence of AF was recorded. It was found that there was a significant relation between incidence, importance of AF, and HF with ischemic etiology (P = 0.034). In patients with AF at the time of discharge and HF with ischemic etiology, HR was 1.25 (95% confidence interval: 1.09–1.42) (P < 0.001). In patients with AF at discharge and HF without IHD, HR was 1.01 (95% confidence interval: 0.88–1.16) (P = 0.88).

In between the echocardiographic findings, the mean LA diameter was significantly higher in the IDCM group compared with the NIDCM group (5.127 ± 0.798 vs. 4.680 ± 0.626) (P = 0.03).

As regards AF and risk factors affecting its frequency of incidence in study groups, the univariate analysis identified the following as predictors of AF incidence: DM, dyslipidemia, LVEDd, LA diameter, and IDCM (P < 0.05 of all).

The multivariate regression analysis identified that DM, dyslipidemia, and an increase in LA diameter had a more independent predictor function of AF among DCM patients despite the etiological cause of DCM. ROC curve has shown that DM predicted the incidence of AF with a sensitivity of 90.4% and specificity 84.4% and dyslipidemia predicted the incidence of AF with a sensitivity of 74.6% and a specificity of 61.3%. Moreover, LA diameter predicts AF incidence with a sensitivity of 95.6% and specificity 71%, and the cutoff value of LA diameter that best predicts the AF incidence was greater than 4.8 cm.

The study by Matei et al. [35] included 348 patients diagnosed with DCM, in SR, who were divided according to etiology as follows: subgroup A, nonischemic etiology, and subgroup B, ischemic etiology. The prevalence of permanent AF was found to be 12% in patients with NIDCM and 9% in patients with ischemic etiology. It was found that univariate and multivariate analysis (Cox) showed a good prediction of paroxysmal AF. In univariate analysis LVEDd (HR = 2.7, P < 0.05) was a good predictor, and the best predictor of permanent AF was LA diameter (HR = 7.96, P < 0.005). LA diameter greater than 41 mm had high sensitivity (over 70%, of permanent AF). This matched with the results of our study, whereas the mean of LA diameter (5.589 ± 0.544, P < 0.001) and the mean of LVEDd (6.739 ± 0.793, P < 0.022) in univariate analysis. Using ROC curve, it was found that LA diameter was one of the independent predictors of AF incidence and has a sensitivity of 95.6% and a specificity of 71%, and the cutoff value of LA diameter that best predicts AF incidence was greater than 4.8 cm.

Takarada et al. [36] evaluated the relation of atrial rhythm with a clinical course of treatment in 147 patients diagnosed with DCM. Totally, 36 (24%) patients had either transient (nine patients) or persistent (27 patients) AF. Compared with DCM patients with SR, the AF patients did not differ in age, LV dimensions, or hemodynamic parameters, but the AF patients had slightly larger LA diameter. This is in agreement with our results; 38% AF patients with DCM had a larger LA diameter (5.589 ± 0.544, P < 0.001), and the cutoff value of LA diameter that best predicts AF incidence was greater than 4.8 cm, with no difference in age, sex, BMI, smoking, and HTN.


  Conclusion Top


The current study identified that the incidence of AF is higher in IDCM patients than in NIDCM patients, and there is no difference between two groups as regards age, sex, BMI, and HTN. Moreover, there was no difference in echocardiographic parameters except dilated LA more in IDCM. DM, dyslipidemia, and LA diameter greater than 4.8 cm have been proved to be independent predictors of AF incidence among DCM patients regardless of its etiology.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, et al. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: The AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA 2001; 285:2370–2375.  Back to cited text no. 1
    
2.
Kim MH, Johnston SS, Chu BC, Dalal MR, Schulman KL. Estimation of total incremental health care costs in patients with atrial fibrillation in the United States. Circ Cardiovasc Qual Outcomes 2011; 4:313–320.  Back to cited text no. 2
    
3.
Krahn AD, Manfreda J, Tate RB, Mathewson FA, Cuddy TE. The natural history of atrial fibrillation: incidence, risk factors, and prognosis in the Manitoba follow-up study. Am J Med 1995; 98:476–484.  Back to cited text no. 3
    
4.
O'Neal WT, MPH, Efird JT, Judd SE, McClure LA, Howard VJ, et al. Impact of awareness and patterns of non hospitalized atrial fibrillation on the risk of mortality: the Reasons for Geographic And Racial Differences in Stroke (REGARDS) Study. Clin Cardiol 2016; 39:103–110.  Back to cited text no. 4
    
5.
Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham study. Stroke 1991; 22:983–988.  Back to cited text no. 5
    
6.
O'Neal WT, Qureshi W, Zhang ZM, et al. Bidirectional association between atrial fibrillation and congestive heart failure in the elderly. J Cardiovasc Med (Hagerstown) 2016; 17:181–186.  Back to cited text no. 6
    
7.
Soliman EZ, Lopez F, O'Neal WT, Chen LY, Bengtson L, Zhang ZM, et al. Atrial fibrillation and risk of ST-segment elevation versus non-ST-segment-elevation myocardial infarction: the Atherosclerosis Risk in Communities (ARIC) study. Circulation 2015; 131:1843–1850.  Back to cited text no. 7
    
8.
O'Neal WT, Efird JT, Yeboah J, Nazarian S, Alonso A, Heckbert SR, et al. Brachial flow-mediated dilation and incident atrial fibrillation: the multi-ethnic study of atherosclerosis. Arterioscler Thromb Vasc Biol 2014; 34:2717–2720.  Back to cited text no. 8
    
9.
Howard VJ, Safford MM, Cushman M, Zakai NA. Inflammation and hemostasis in atrial fibrillation and coronary heart disease: the reasons for geographic and racial differences in stroke study. Atherosclerosis 2015; 243:192–197.  Back to cited text no. 9
    
10.
Maron BJ, Towbin JA, Thiene G, Antzelevitch C, Corrado D, Arnett D, et al. Contemporary definitions and classification of the cardiomyopathies: an American Heart Association Scientific Statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention. Circulation 2006; 113:1807–1816.  Back to cited text no. 10
    
11.
Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD. Third universal definition of myocardial infarction. Circulation 2012; 126:2020–2035.  Back to cited text no. 11
    
12.
Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD, et al.Harrison's principles of internal medicine (ISBN 0-07140235-7). 16th ed. New York: McGraw-Hill Medical Publishing Division; 2005.  Back to cited text no. 12
    
13.
Fatkin D, Members of the CSANZ Cardiac Genetic Diseases Council Writing Group. Guidelines for the diagnosis and management of familial dilated cardiomyopathy. Heart Lung Circ 2011; 20:691–693.  Back to cited text no. 13
    
14.
Merchant EE, Johnson SW, Nguyen, Kang C, Mallon WK. Takotsubo cardiomyopathy: a consensus document. G Ital Cardiol (Rome) 2008; 9:785–797.  Back to cited text no. 14
    
15.
Sliwa K, Hilfiker-Kleiner D, Petrie MC, Mebazaa A, Pieske B, Buchmann E, et al. Current state of knowledge on aetiology, diagnosis, management, and therapy of peripartum cardiomyopathy: a position statement from the Heart Failure Association of the European Society of Cardiology Working Group on peripartum cardiomyopathy. Eur J Heart Fail 2010; 12:767.  Back to cited text no. 15
    
16.
Manolio TA, Baughman KL, Rodeheffer R, Pearson TA, Bristow JD, Michels VV, et al. Prevalence and etiology of idiopathic dilated cardiomyopathy (summary of a National Heart, Lung and Blood Institute Workshop). Am J Cardiol 1992; 69:1459–1466.  Back to cited text no. 16
    
17.
Wang TJ, Larson MG, Levy D, Vasan RS, Leip EP, Wolf PA, et al. Temporal relations of atrial fibrillation and congestive heart failure and their joint influence on mortality: the Framingham Heart Study. Circulation. 2003; 107:2920–2925.  Back to cited text no. 17
    
18.
Pedersen OD, Bagger H, Keller N, Marchant B, Køber L, Torp-Pedersen C. Efficacy of dofetilide in the treatment of atrial fibrillation-flutter in patients with reduced left ventricular function: a Danish investigations of arrhythmia and mortality on dofetilide (diamond) substudy. Circulation 2001; 104:292–296.  Back to cited text no. 18
    
19.
Dries DL. Exner DV, Gersh BJ, Domanski MJ, Waclawiw MA, Stevenson LW. Atrial fibrillation is associated with an increased risk for mortality and heart failure progression in patients with asymptomatic and symptomatic left ventricular systolic dysfunction: a retrospective analysis of the SOLVD trials. Studies of left ventricular dysfunction. J Am Coll Cardiol 1998; 32:695–703.  Back to cited text no. 19
    
20.
Maisel WH, Stevenson LW. Atrial fibrillation in heart failure: epidemiology, pathophysiology, and rationale for therapy. Am J Cardiol 2003; 91:2D–8D.  Back to cited text no. 20
    
21.
Benjamin EJ, Levy D, Vaziri SM, D'Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham heart study. JAMA 1994; 271:840–844.  Back to cited text no. 21
    
22.
Schmitt J, Duray G, Gersh BJ, Hohnloser SH. Atrial fibrillation in acute myocardial infarction: a systematic review of the incidence, clinical features and prognostic implications. Eur Heart J 2009; 30:1038–1045.  Back to cited text no. 22
    
23.
Jons C. Jacobsen UG, Joergensen RM, Olsen NT, Dixen U, Johannessen A. The incidence and prognostic significance of new-onset atrial fibrillation in patients with acute myocardial infarction and left ventricular systolic dysfunction: a CARISMA substudy. Heart Rhythm 2011; 8:342–348.  Back to cited text no. 23
    
24.
Dickstein K, Cohen-Solal A, Filippatos G, McMurray JJ, Ponikowski P, Poole-Wilson PA. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: the Task Force for the Diagnosis and Treatment of Acute and Chronic Heart Failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur J Heart Fail 2008; 10:933–989.  Back to cited text no. 24
    
25.
Gheorghiade M, Bonow RO. Chronic heart failure in the United States: a manifestation of coronary artery disease. Circulation 1998; 97:282–289.  Back to cited text no. 25
    
26.
Felker GM, Shaw LK, O'Connor CM. A standardized definition of ischemic cardiomyopathy for use in clinical research. J Am Coll Cardiol 2002; 39:210–218.  Back to cited text no. 26
    
27.
Dennis L, Braunwald E, Fauci AS, et al.Harrison's principles of internal medicine. Vol. 64. 16th ed. 2004. p. 422.  Back to cited text no. 27
    
28.
Boon NA, Colledge NR, Walker BR, et al.Davidson's principles and practice of medicine. 20 ed. Elsevier: Churchill Livingstone; 2006; pp. 581–609.  Back to cited text no. 28
    
29.
Antman EM, Eugene B. Text book of cardiovascular medicine. Philadelphia: W.B. Saunders Company; 1997. p. 1208.  Back to cited text no. 29
    
30.
Carasso S, Sandach A, Beinart R, et al. For the Echocardiography Working Group of the Israel Heart Society. Usefulness of four echocardiographic risk assessments in predicting 30-day outcome in acute myocardial infarction. Am J Cardiol 2005; 96:25–30.  Back to cited text no. 30
    
31.
Ramirez G, Bugni W, Farber SM, Curry AJ. Incidence of renal artery stenosis in a population having cardiac catheterization. South Med J 1987; 806:734–737.  Back to cited text no. 31
    
32.
Jean WJ, Al-Bitar I, Zwicke DL, Port SC, Schmidt DH, Bajwa TK. High incidence of renal artery stenosis in patients with coronary artery disease. Catheter Cardiovasc Diagn 1994; 32:8–10.  Back to cited text no. 32
    
33.
Fazio G, Vernuccio F, Grassedonio E, et al. Ischemic and non-ischemic dilated cardiomyopathy. Cent Eur J Med 2014; 9:15–20.  Back to cited text no. 33
    
34.
Pedersen OD, Sndergaard P, Nielsen T, et al. DIAMOND study group investigators. Atrial fibrillation, ischaemic heart disease, and the risk of death in patients with heart failure. Eur Heart J 2006; 27:2866–2870.  Back to cited text no. 34
    
35.
Matei C, Ioana Pop I, Badea M, et al. Predictive factors for atrial fibrillation appearance in dilated cardiomyopathy. Rom J Cardiol 2012;22:22–22.  Back to cited text no. 35
    
36.
Takarada A, Kurogane H, Hayashi T, et al. Prognostic significance of atrial fibrillation in dilated cardiomyopathy. Jpn Heart J 1993; 34:749–758.  Back to cited text no. 36
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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Abstract
Introduction
Materials and Me...
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