Coronary artery diseases in Japanese patients with nonvalvular atrial fibrillation

Coronary artery diseases in Japanese patients with nonvalvular atrial fibrillation

Journal of Cardiology 63 (2014) 123–127 Contents lists available at ScienceDirect Journal of Cardiology journal homepage: www.elsevier.com/locate/jj...

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Journal of Cardiology 63 (2014) 123–127

Contents lists available at ScienceDirect

Journal of Cardiology journal homepage: www.elsevier.com/locate/jjcc

Original article

Coronary artery diseases in Japanese patients with nonvalvular atrial fibrillation夽 Keitaro Senoo (MD) a,∗ , Shinya Suzuki (MD) a , Koichi Sagara (MD) a , Takayuki Otsuka (MD) a , Shunsuke Matsuno (MD) a , Tokuhisa Uejima (MD) a , Yuji Oikawa (MD) a , Junji Yajima (MD) a , Kazuyuki Nagashima (MD) a , Hajime Kirigaya (MD) a , Hitoshi Sawada (MD, FJCC) a , Tadanori Aizawa (MD, FJCC) a , Gregory Y.H. Lip (MD) b , Takeshi Yamashita (MD, FJCC) a a b

The Cardiovascular Institute, Tokyo, Japan University of Birmingham, Centre for Cardiovascular Sciences, City Hospital, Birmingham B18 7QH, United Kingdom

a r t i c l e

i n f o

Article history: Received 3 June 2013 Received in revised form 17 July 2013 Accepted 14 August 2013 Available online 23 September 2013 Keywords: Nonvalvular atrial fibrillation Coronary artery disease Incidence Prognosis

a b s t r a c t Background: Both the prevalence of atrial fibrillation and coronary artery disease (CAD) is increasing in aged societies. However, limited data are available regarding the prevalence of CAD and the incidence of coronary events in Japanese patients with nonvalvular atrial fibrillation (NVAF). Methods and results: The data in this study were derived from Shinken Database 2004–2010, which includes 15,227 new patient visitors to the Cardiovascular Institute between June 2004 and March 2011. In the database, 1835 patients were diagnosed with NVAF (mean age 63 years, mean CHADS2 score 1.1 ± 1.1, and 75% were men). The prevalence of CAD at the initial visit was 118 patients (6.4%). They were older age and had a greater prevalence of men, more history of congestive heart failure and more history of cardiovascular risk factors rather than those without. During the follow-up period of 532 ± 599 days, coronary events (myocardial infarction, unstable angina, and stable angina) occurred in 51 patients (1.9%/year). Multivariate analysis showed that a history of CAD (p < 0.001) and older age (p = 0.024) were independent predictors of the incidence of future coronary events. Conclusions: In Japanese patients with NVAF, both the presence of CAD and the occurrence of coronary events are not uncommon. History of CAD and older age are strongly associated with the incidence of coronary events. © 2013 Published by Elsevier Ltd on behalf of Japanese College of Cardiology.

Introduction Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice. AF is associated with multiple symptoms, with significant morbidity and mortality and with decreased quality of life. The prevalence of AF in the US population is expected to increase from 2.3 million in 2001 to 5.6 million in 2050 [1]. Since the current prevalence of AF is somewhat lower or comparable to that observed

DOI of commentary article: http://dx.doi.org/10.1016/j.jjcc.2013.09.010. 夽 This article is a revised and expanded version of a presentation entitled “Prevalence and incidence of coronary artery disease in patients with nonvalvular atrial fibrillation: The Shinken database” presented at ACC.13 in San Francisco from March 9–11, 2013. ∗ Corresponding author at: Department of Cardiology, The Cardiovascular Institute, 3-2-19 Nishiazabu, Minato-Ku, Tokyo 106-0031, Japan. Tel.: +81 3 3408 2151; fax: +81 3 3408 2159. E-mail address: [email protected] (K. Senoo).

in Western countries, the AF population is expected to increase also in Japan. The mortality rate of AF patients is almost twice that of patients with normal sinus rhythm. Notably, this observation has been attributed to an increased cardiac death due to underlying heart disease [2–5] rather than to thromboembolism [6]. In Western countries, coronary artery disease (CAD) is highly prevalent among patients with AF and may be one of its underlying causes [7]. Furthermore, AF may be the sole manifestation of CAD [8]. Interestingly, epidemiological data have indicated that ischemic heart disease is one of the most common underlying causes of death among patients with AF [9]. These observations have therefore led to an increased interest in the evaluation of underlying CAD in patients with nonvalvular atrial fibrillation (NVAF). The present study aimed to investigate the prevalence of CAD and the incidence of coronary events in Japanese patients with NVAF in a single-hospital-based cohort study.

0914-5087/$ – see front matter © 2013 Published by Elsevier Ltd on behalf of Japanese College of Cardiology. http://dx.doi.org/10.1016/j.jjcc.2013.08.007

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Methods Study patients The Shinken database comprises all new patients visiting the Cardiovascular Institute in Tokyo, Japan (“Shinken” is an abbreviated name in Japanese for the name of the hospital), and excludes patients with active cancer and any foreign travellers. The principal aim of this hospital-based database is surveillance of the prevalence and prognosis of cardiovascular diseases in the urban areas of Japan [10–12]. The registry started in June 2004, and patients have been continually registered to the database annually thereafter. Information about patients’ health status and the incidence of cardiovascular events and mortality are maintained in the database by its link to the hospital’s medical records and by a mail enquiry sent to patients approximately once or twice per year. The data in the present study were derived from this database between June 2004 and March 2010 (Shinken Database 2004–2010), which included 15,227 new visiting patients. The database contained 1835 patients with the diagnosis of NVAF.

variables was calculated by the person-year methods. Univariate and multivariate Cox regression analyses were performed to identify the predictors for the incidence of coronary events. In multivariate model, co-factors significantly associated with incidence of coronary events in the univariate models were considered in the stepwise method. All statistical analyses were performed using SPSS (SPSS Inc., Chicago, IL, USA) for Windows (Microsoft Corp., Redmond, WA, USA), version 19.0 software. Statistical significance was set at p < 0.05.

Ethical issues The ethical committee at the Cardiovascular Institute granted ethical permission for this study, and all the patients provided written informed consent.

Results Characteristics of the total study patients

Data collection For each patient, an electrocardiogram and a chest radiograph were obtained, and the cardiovascular status was then evaluated using echocardiography, exercise test, and 24-h Holter monitor records from the initial visit according to the attending physicians. The following information was collected from the database: (1) patient data (age, sex, and type of AF), (2) cardiovascular diseases, (3) cardiovascular risk factors, and (4) use of medications. The body mass index was calculated as weight in kilograms divided by height in meters squared. The CHADS2 score is calculated by adding 1 point each for congestive heart failure, hypertension, age ≥75 years, and diabetes mellitus, and by adding 2 points for a previous stroke or transient ischemic attack [13]. In the present study, patients were divided into 3 CHADS2 score categories (0, 1, and ≥2). Definitions of AF, CAD, and coronary events In the present study, AF was diagnosed based on electrocardiography at the initial visit, which included 12-lead surface electrocardiograms or 24-h Holter monitor records. AF was also diagnosed based on any medical history of AF from referring physicians. The definition of CAD included: (1) history of percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) and (2) ≥50% coronary stenosis as documented by coronary angiography (CAG) results and the detection of ischemia on stress testing including the treadmill stress test, radioisotope single-photon emission computed tomography, and/or fractional flow reserve (FFR) during CAG. FFR, an index of coronary stenosis severity, can be calculated from the ratio of hyperemic distal to proximal coronary pressure. Coronary events were defined as hospitalization for myocardial infarction, unstable angina, or stable angina. The incidence of coronary events was presented using the person-year method. Statistical analysis In baseline characteristics, continuous variables and categorical variables are expressed as mean ± SD and absolute numbers (percentage), respectively. A chi-square test and an unpaired Student’s t-test were used for the comparison of categories and continuous variables between 2 groups, respectively. The cumulative incidence of coronary events was estimated by the Kaplan–Meier method. The incidence of coronary events according to the significant univariate

Table 1 shows the baseline characteristics of the study patients. In this study, 1835 patients (age, 63.2 ± 12.6 years; 1388 men) were enrolled. Among them, 45.4% had tobacco use (current and past), 44.9% hypertension, 25.2% dyslipidemia, and 16.3% diabetes mellitus. The mean CHADS2 score of the study patients was 1.1 ± 1.1 (CHADS2 = 0, n = 685; CHADS2 = 1, n = 589; CHADS2 ≥ 2, n = 561). Forty-seven percent of patients were treated with warfarin, and 39% with aspirin.

Prevalence of CAD In the total study patients, patients with a history of CAD were 118 (6.4%) at the initial visit. They were older age and had a higher prevalence of men, more history of congestive heart failure and more history of cardiovascular risk factors than those without. Additionally, they had higher CHADS2 score than those without (2.3 ± 1.2 vs. 1.0 ± 1.1, p < 0.001).

Incidence of coronary events During the follow-up of 532 ± 599 days, 51 patients (1.9%/year) experienced coronary events. The Kaplan–Meier curves for the incidence rate of coronary events are shown in Fig. 1. Oral anticoagulants prescription was not associated with the incidence of coronary events in this study. Univariate Cox regression analysis showed that older age (p = 0.002), men (p = 0.048), hypertension (p = 0.004), diabetes mellitus (p = 0.004), history of heart failure (p = 0.004), history of CAD (p < 0.001), and CHADS2 score ≥ 2 (p < 0.001) were associated with the incidence of coronary events (Table 2). Multivariate Cox regression analysis including univariate factors showed that older age (p = 0.024) and history of CAD (p < 0.001) were the independent determinants of incidence of coronary events (Table 3). We demonstrated the incidence of coronary events according to the significant univariate values (Fig. 2). Among them, coronary events occurred more frequently in patients with conventional coronary risk factors (i.e. older age, men, hypertension, diabetes mellitus, history of congestive heart failure) and a history of CAD. In addition, coronary events occurred in 11 patients (1.1%/year) in the CHADS2 = 0, 12 (1.4%/year) in CHADS2 = 1, and 28 (3.6%/year) in CHADS2 ≥ 2, respectively. Hence, there was a significant linear trend between CHADS2 scores and annual coronary events rate.

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Table 1 Patient characteristics. Patient characteristics

Age ± SD (years) Male (%) BMI Type of AF First-detected Paroxysmal Persistent Permanent CHADS2 score 0 1 ≥2 Cardiovascular diseases History of congestive heart failure History of TIA/stroke Cardiovascular risk factors Smoking Dyslipidemia Hypertension Chronic kidney disease Diabetes mellitus Medication at discharge Aspirin Thienopyridine Warfarin Beta-blockers Calcium channel blocker Digitalis glycosides Diuretics RAS inhibitors Statin

History of CAD

Overall (n = 1835)

p-Value

Yes (n = 118)

No (n = 1717)

70.0 ± 9.4 103 (87.3) 24.2 ± 3.2

62.8 ± 12.6 1285 (74.8) 23.8 ± 3.5

63.2 ± 12.6 1388 (75.6) 23.9 ± 3.5

<0.001 0.001 0.355

40 (33.9) 32 (27.1) 11 (9.3) 35 (29.7)

428 (24.9) 748 (43.6) 184 (10.7) 357 (20.8)

468 (25.5) 780 (42.5) 195 (10.6) 392 (21.4)

0.022 <0.001 0.387 0.018

7 (5.9) 23 (19.5) 88 (74.6)

678 (39.5) 566 (33.0) 473 (27.5)

685 (37.3) 589 (32.1) 561 (30.6)

<0.001 0.001 <0.001

80 (67.8) 12 (10.2)

231 (13.5) 103 (6.0)

311 (16.9) 115 (6.3)

<0.001 0.06

63 (53.4) 69 (58.5) 81 (68.6) 46 (39.0) 48 (40.7)

771 (44.9) 393 (22.9) 743 (43.3) 449 (26.2) 251 (14.6)

834 (45.4) 462 (25.2) 824 (44.9) 495 (27.0) 299 (16.3)

0.045 <0.001 <0.001 0.002 <0.001

95 (80.5) 69 (58.5) 71 (60.2) 72 (61.0) 33 (28.0) 27 (22.9) 55 (46.6) 72 (61.0) 58 (49.2)

626 (36.5) 43 (2.5) 796 (46.4) 543 (31.6) 256 (14.9) 263 (15.3) 324 (18.9) 494 (28.8) 176 (10.3)

721 (39.3) 112 (6.1) 867 (47.2) 615 (33.5) 289 (15.7) 290 (15.8) 379 (20.7) 566 (30.8) 234 (12.8)

<0.001 <0.001 0.002 <0.001 <0.001 0.024 <0.001 <0.001 <0.001

AF, atrial fibrillation; CAD, coronary artery disease; BMI, body mass index; CHADS2 score, congestive heart failure, hypertension, age > 75, diabetes mellitus, stroke or TIA; TIA, transient ischemic attack; RAS, renin-angiotensin system.

Fig. 1. The Kaplan–Meier curve for the incidence of coronary events. Coronary events represent myocardial infarction, unstable angina, and stable angina.

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Table 2 Univariate analysis for the incidence of coronary events.

Univariate analysis Age Sex, men Body mass index Smoking Hypertension Dyslipidemia Diabetes mellitus Chronic kidney disease History of stroke or TIA History of heart failure History of CAD CHADS2 score = 0 CHADS2 score = 1 CHADS2 score ≥ 2

Hazard ratio

95% CI

p-Value

1.040 2.237 1.023 1.160 2.304 1.599 2.414 1.531 1.056 2.337 9.234

1.015–1.066 1.007–4.968 0.932–1.123 0.662–2.032 1.306–4.067 0.893–2.862 1.336–4.362 0.862–2.719 0.329–3.391 1.305–4.183 5.188–16.432 Reference 0.572–2.936 1.626–6.562

0.002 0.048 0.631 0.603 0.004 0.155 0.004 0.147 0.928 0.004 <0.001

1.295 3.266

0.535 0.001

TIA, transient ischemic attack; CAD, coronary artery disease; CHADS2 score, congestive heart failure, hypertension, age > 75, diabetes mellitus, stroke or TIA.

Table 3 Multivariate analysis for the incidence of coronary events. Hazard ratio Multivariate analysis History of CAD Age

9.234 1.031

95% CI 5.188–16.432 1.005–1.058

p-Value <0.001 0.021

CAD, coronary artery disease.

Fig. 2. The incidence of coronary events according to the significant univariate valuables. CHF, congestive heart failure; CAD, coronary artery disease.

Discussion In the present study, we have shown that both the prevalence of CAD and the incidence of coronary events are not uncommon in our Japanese NVAF patients. This is the first study to examine the prevalence of CAD and the incidence of coronary events in Japanese NVAF patients. Prevalence of CAD and incidence of coronary events in NVAF patients

in Japanese patients has long been unknown. The present study revealed that it was 1.9%/year in NVAF patients, which was also relatively low compared with previous Western reports (3.1%/year) [20]. The differences in the prevalence of CAD and incidence of coronary events in NVAF patients between Japan and Western countries are not clear, but might be linked to differences in patients’ backgrounds. Actually, the distribution of CHADS2 scores was different. In the present study, low-risk patients (0 or 1 points) accounted for approximately 70% of the total, while low-risk patients with CHADS2 scores of 0 or 1 accounted for approximately 17–53% of the subjects in the previous Western reports [21–23]. The independent predictors of the incidence of coronary events were a history of CAD and older age, in this study. Although a causal relationship between CAD and AF was not yet investigated, patients with a history of CAD were strongly associated with future coronary events, suggesting greater CAD burden conferred a significantly higher risk for clinical plaque progression. Second, age steadily increases the absolute baseline risk of coronary events independent of the conventional risk factors. Therefore, patients without risk factors will tend to present at a much later age once their baseline absolute risk increases sufficiently to cause a significant prevalence of disease. AF and CAD CAD is highly prevalent among patients with AF and may be one of its etiologic factors in Western countries [7]. Once AF is diagnosed, the presence of CAD is shown to be related to recurrent AF episodes [24], to the presence of symptoms (including arrhythmic, heart failure, and angina symptoms) [25], and to increased risk of death [26,27]. Therefore, CAD plays an important role in the mortality and quality of life of patients with NVAF. Additionally, there are mechanistic reasons for the link between AF and CAD. AF has been shown to independently increase systemic inflammation as measured by C-reactive protein (CRP) level, which increases with increasing CHADS2 score [28]. In addition, higher CRP levels were found to be associated with a significantly increased risk for coronary events, including death, myocardial infarction, or unstable angina pectoris [29]. These results may suggest that the CHADS2 score reflects blood stasis and the presence of systemic inflammation, which causes left atrial endothelial damage, dysfunction, and, finally, cardiovascular events. In the present study, we additionally found that the prevalence of CAD increased with an increase in CHADS2 score, and that the incidence of coronary events was also higher with increasing CHADS2 score. Among components of the CHADS2 score, older age, hypertension, and diabetes are also well-recognized risk factors for CAD. In fact, the REACH study [22] also found that the CHADS2 score classification was useful in predicting not only stroke but also cardiovascular death in stable outpatients with established or at high risk of atherothrombosis. Therefore, the prevention of both stroke and coronary events, and more intensive antithrombotic therapy, would be needed for NVAF patients with high CHADS2 scores. However, the risk of hemorrhage increases in case of combined use of an anticoagulant and antiplatelet drugs [30,31]. In such cases, special attention for the safe management of antithrombotic therapy would be necessary, which has been already proposed in a recent bleeding risk assessment guideline from the European Society of Cardiology in 2010 [32]. Limitations

In several reports from Western countries [14–17], the prevalence of CAD in AF patients has been reported to be 18–34%. In contrast, the prevalence of CAD in the present study was relatively low (6.4%), in accordance with previous Japanese studies (7–8%) [10,18,19]. The overall incidence rate of coronary events

The present study is limited by its retrospective nature; the results should be confirmed by prospective cohort studies. Second, the population was limited to patients visiting a single cardiovascular hospital in an urban city in Japan and therefore, cannot simply

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be extrapolated to the general population. Therefore, these results should be re-examined in population-based studies. Third, we analyzed only patients with AF, therefore it was unclear that AF itself related to the incidence of coronary events. Finally, in the present study, AF was diagnosed by medical history and clinical examinations, including electrocardiograms and Holter recordings. This method is well known to underestimate AF prevalence, because asymptomatic AF is neglected [24]. Conclusion In our Japanese population, both the prevalence of CAD and the incidence of coronary events are not uncommon in patients with NVAF. History of CAD and older age are strongly associated with the incidence of coronary events. Acknowledgments We thank Shiro Ueda and Nobuko Ueda at Medical Edge Co., Ltd. for assembling the database by Clinical Study Supporting System (CliSSS) and Ineko Hayakawa, Hiroaki Arai, and Hirokazu Aoki for data management and system administration. References [1] Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, Singer DE. 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;285:2370–5. [2] Flegel KM, Shipley MJ, Rose G. Risk of stroke in non-rheumatic atrial fibrillation. Lancet 1987;1:526–9. [3] Kannel WB, Abbott RD, Savage DD, McNamara PM. Coronary heart disease and atrial fibrillation: the Framingham Study. Am Heart J 1983;106: 389–96. [4] Krahn AD, Manfreda J, Tate RB, Mathewson FA, Cuddy TE. The natural history of atrial fibrillation: incidence, risk factors, and prognosis in the Manitoba FollowUp Study. Am J Med 1995;98:476–84. [5] Psaty BM, Manolio TA, Kuller LH, Kronmal RA, Cushman M, Fried LP, White R, Furberg CD, Rautaharju PM. Incidence of and risk factors for atrial fibrillation in older adults. Circulation 1997;96:2455–61. [6] 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. [7] Lip GY, Beevers DG. ABC of atrial fibrillation. History, epidemiology, and importance of atrial fibrillation. BMJ 1995;311:1361–3. [8] Schoonderwoerd BA, Van Gelder I, Crijns HJ. Left ventricular ischemia due to coronary stenosis as an unexpected treatable cause of paroxysmal atrial fibrillation. J Cardiovasc Electrophysiol 1999;10:224–8. [9] Wattigney WA, Mensah GA, Croft JB. Increased atrial fibrillation mortality: United States, 1980–1998. Am J Epidemiol 2002;155:819–26. [10] Suzuki S, Yamashita T, Otsuka T, Sagara K, Uejima T, Oikawa Y, Yajima J, Koike A, Nagashima K, Kirigaya H, Ogasawara K, Sawada H, Aizawa T. Prevalence and prognosis of patients with atrial fibrillation in Japan: a prospective cohort of Shinken Database 2004. Circ J 2008;72:914–20. [11] Suzuki S, Yamashita T, Otsuka T, Sagara K, Uejima T, Oikawa Y, Yajima J, Koike A, Nagashima K, Kirigaya H, Ogasawara K, Sawada H, Aizawa T. Recent mortality of Japanese patients with atrial fibrillation in an urban city of Tokyo. J Cardiol 2011;58:116–23. [12] Suzuki S, Yamashita T, Ohtsuka T, Sagara K, Uejima T, Oikawa Y, Yajima J, Koike A, Nagashima K, Kirigaya H, Ogasawara K, Sawada H, Yamazaki T, Aizawa T. Body size and atrial fibrillation in Japanese outpatients. Circ J 2010;74: 66–70.

127

[13] Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA 2001;285:2864–70. [14] Van Gelder IC, Groenveld HF, Crijns HJ, Tuininga YS, Tijssen JGP, Alings AM, Hillege HL, Bergsma-Kadijk JA, Cornel JH, Kamp O, Tukkie R, Bosker HA, Van Veldhuisen DJ, Van den Berg MP, RACE II Investigators. Lenient versus strict rate control in patients with atrial fibrillation. N Engl J Med 2010;362:1363–73. [15] Kralev S, Schneider K, Lang S, Süselbeck T, Borggrefe M. Incidence and severity of coronary artery disease in patients with atrial fibrillation undergoing first-time coronary angiography. PLoS ONE 2011;6:e24964. [16] Hohnloser SH, Crijns HJ, van Eickels M, Gaudin C, Page RL, Torp-Pedersen C, Connolly SJ. N Engl J Med 2009;360:668–78. [17] Wyse DG, Waldo AL, DiMaroco JP, The Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) Investigators. A comparison of rate control and rhythm control in patients with atrial fibrillation. N Engl J Med 2002;347:1834–40. [18] Ogawa S, Yamashita T, Yamazaki T, Aizawa Y, Atarashi H, Inoue H, Ohe T, Ohtsu H, Okumura K, Katoh T, Kamakura S, Kumagai K, Kurachi Y, Kodama I, Koretsune Y, et al. Circ J 2009;73:242–8. [19] Akao M, Chun YH, Wada H, Esato M, Hashimoto T, Abe M, Hasegawa K, Tsuji H, Furuke K, Fushimi AF. J Cardiol 2013;61:260–6. [20] Miyasaka Y, Barnes M, Gersh BJ, Cha SS, Bailey KR, Seward JB, Iwasaka T, Tsang TS. Coronary ischemic events after first atrial fibrillation: risk and survival. Am J Med 2007;120:357–63. [21] Naccarelli GV, Panaccio MP, Cummins G, Tu N. CHADS2 and CHA2DS2-VASc risk factors to predict first cardiovascular hospitalization among atrial fibrillation/atrial flutter patients. Am J Cardiol 2012;109:1526–33. [22] Goto S, Bhatt D, Rother J, Alberts M, Hill MD, Ikeda Y, Uchiyama S, D’Agostino R, Ohman EM, Liau CS, Hirsch AT, Mas JL, Wilson PW, Corbalán R, Aichner F, et al. Prevalence, clinical profile, and cardiovascular outcomes of atrial fibrillation patients with atherothrombosis. Am Heart J 2008;156:855–63. [23] Go AS, Hylek EM, Chang Y, Phillips KA, Henault LE, Capra AM, Jensvold NG, Selby JV, Singer DE. Anticoagulation therapy for stroke prevention in atrial fibrillation: how well do randomized trials translate into clinical practice? JAMA 2003;290:2685–92. [24] Suttorp MJ, Kingma JH, Koomen EM, van’t Hof A, Tijssen JG, Lie KI. Recurrence of paroxysmal atrial fibrillation or flutter after successful cardioversion in patients with normal left ventricular function. Am J Cardiol 1993;71:710–3. [25] Flaker GC, Belew K, Beckman K, Vidaillet H, Kron J, Safford R, Mickel M, Barrell P. Am Heart J 2005;149:657–63. [26] Corley SD, Epstein AE, DiMarco JP, Domanski MJ, Geller N, Greene HL, Josephson RA, Kellen JC, Klein RC, Krahn AD, Mickel M, Mitchell LB, Nelson JD, Rosenberg Y, Schron E, et al. Relationships between sinus rhythm, treatment, and survival in the Atrial Fibrillation Follow-Up Investigation of Rhythm Management (AFFIRM) Study. Circulation 2004;109:1509–13. [27] Curtis AB, Gersh BJ, Corley SD, DiMarco JP, Domanski MJ, Geller N, Greene HL, Kellen JC, Mickel M, Nelson JD, Rosenberg Y, Schron E, Shemanski L, Waldo AL, Wyse DG, et al. Clinical factors that influence response to treatment strategies in atrial fibrillation: the Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) study. Am Heart J 2005;149:645–9. [28] Maehama T, Okura H, Imai K, Yamada R, Obase K, Saito K, Hayashida A, Neishi Y, Kawamoto T, Yoshida K. Usefulness of CHADS2 score to predict C-reactive protein, left atrial blood stasis, and prognosis in patients with nonrheumatic atrial fibrillation. Am J Cardiol 2010;106:535–8. [29] Momiyama Y, Kawaguchi A, Kajiwara I, Ohmori R, Okada K, Saito I, Konishi M, Nakamura M, Sato S, Kokubo Y, Mannami T, Adachi H, Kario K, Iso H, Ohsuzu F, et al. Prognostic value of plasma high-sensitivity C-reactive protein levels in Japanese patients with stable coronary artery disease: the Japan NCVC-Collaborative Inflammation Cohort (JNIC) Study. Atherosclerosis 2009;207:272–6. [30] Singer DE, Albers GW, Dalen JE, Go AS, Halperin JL, Manning WJ. Antithrombotic therapy in atrial fibrillation: the Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy. Chest 2004;126(3 Suppl.):429S–56S. [31] Inoue H. Thromboembolism in patients with nonvalvular atrial fibrillation: comparison between Asian and Western countries. J Cardiol 2013;61:1–7. [32] European Heart Rhythm AssociationEuropean Association for Cardio-Thoracic Surgery, Camm AJ, Kirchhof P, Lip GY, Schotten U, Savelieva I, Ernst S, Van Gelder IC, Al-Attar N, Hindricks G, Prendergast B, Heidbuchel H, Alfieri O, Angelini A, et al. Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J 2010;31:2369–429.