Literature DB >> 28123767

Distinct risk factors of atrial fibrillation in patients with and without coronary artery disease: a cross-sectional analysis of the BOREAS-CAG Registry data.

Naoto Murakami1, Masaya Tanno1, Nobuaki Kokubu1, Junichi Nishida1, Nobutaka Nagano1, Hirofumi Ohnishi2, Hiroshi Akasaka1, Takayuki Miki1, Kazufumi Tsuchihashi3, Tetsuji Miura1.   

Abstract

OBJECTIVE: Although risk factors of atrial fibrillation (AF) in the general population have been characterised, their impacts on patients with specific diseases are unclear. Our aim was to determine whether risk factors of AF are different in patients with and those without coronary artery disease (CAD).
METHODS: We enrolled 1871 consecutive patients who underwent coronary angiography for evaluation of symptoms suggestive of CAD in the BOREAS-CAG Registry between August 2014 and January 2015. After exclusion of patients with valvular heart disease or a history of PCI/cardiac surgery, 1150 patients contributed to multivariate logistic regression analysis to identify risk factors of AF. We also retrieved data for 361 consecutive patients with CAD admitted to Sapporo Medical University Hospital between April 2013 and July 2014 and analysed data for 166 patients using the same inclusion and exclusion criteria as those in the BOREAS-CAG Registry.
RESULTS: Unexpectedly, CAD was independently associated with the absence of AF. The patients were then divided into a non-CAD group (n=576) and a CAD group (n=574) for further analysis. The brain natriuretic peptide level showed a strong association with AF regardless of the presence or absence of CAD. In the non-CAD group, lack of statin use was independently associated with AF, whereas high serum uric acid level was an independent explanatory variable of AF in the CAD group. The association of AF with uric acid was confirmed in a separate group of patients (n=166) enrolled in the CAD cohort in Sapporo Medical University Hospital.
CONCLUSIONS: Major risk factors of AF are different in patients with CAD and those without CAD. Patients with CAD are more likely to develop AF when the serum uric acid level is high, whereas no statin administration predicts development of AF in patients without CAD.

Entities:  

Keywords:  BOREAS-CAG Registry; CORONARY ARTERY DISEASE; uric acid

Year:  2017        PMID: 28123767      PMCID: PMC5255559          DOI: 10.1136/openhrt-2016-000573

Source DB:  PubMed          Journal:  Open Heart        ISSN: 2053-3624


A number of cohort studies have shown clinical risk factors for the development of AF in the general population, including advanced age, hypertension, diabetes and heart failure. Major risk factors of AF in patients with certain clinical conditions may be different from those in the general population. No statin administration is associated with AF in patients without CAD, whereas a high uric acid level is a major risk factor associated with AF in patients with CAD. It needs to be confirmed by longitudinal studies whether uric acid-lowering agents and statins are effective for preventing the development of AF in patients with CAD and patients with cardiovascular risk factors but without CAD, respectively.

Introduction

Atrial fibrillation (AF) affects 1–2% of the general population and represents a rapidly growing threat in ageing societies.1 Individuals with AF are at an approximately fivefold higher risk of stroke,2 sevenfold higher risk of heart failure and 1.9-fold higher risk of mortality3 than those without AF. AF plays a role in the development of heart failure with reduced ejection fraction (HFrEF) as well as heart failure with preserved ejection fraction (HFpEF),4 which has been becoming more and more prevalent in patients presenting with acute decompensated heart failure.5 Clinical risk factors for development of AF in the general population have been characterised by a number of cohort studies.6–8 Furthermore, simple score systems have been devised to calculate the risk of AF development by the use of variables such as age, race, body height, weight, blood pressure (BP), smoking status, antihypertensive medication, diabetes and history of myocardial infarction and heart failure.8–10 However, clinical factors that are not incorporated into the score systems also increase the risk of AF development under certain conditions. For example, it has been reported that renal dysfunction,11 presence of obstructive sleep apnoea12 and right ventricular dysfunction13 were significant risk factors for the development of AF after cardiac surgery. Thus, it is unlikely that AF risk score systems are directly applicable to patients with morbidities, including coronary artery disease (CAD). CAD is a risk factor of AF development as well as a disease for which the outcome is modulated by AF.14–17 In a multicentre clinical study conducted in Denmark,16 the development of AF during index hospitalisation for MI was found to be associated with a significantly increased risk of sudden cardiac death. The presence of CAD in patients with previously diagnosed AF has been reported to be associated with recurrent AF episodes,17 symptomatic heart failure14 and increased mortality.18 However, it is not clear whether the presence of CAD simply adds a risk of AF or changes the impact of other risk factors of AF. To address this issue, we performed cross-sectional analyses to determine risk factors of AF in patients with and those without CAD by the use of data in the BOREAS (Broad-range Co-operative Organization for Renal, Arterial and Cardiac Studies by Sapporo Medical University Affiliates)-CAG Registry. We additionally performed similar analyses by the use of a separate database of patients with CAD to validate the findings in the BOREAS-CAG Registry patients.

Methods

This study was conducted in strict accordance with the principles of the Declaration of Helsinki and was approved by the Clinical Investigation Ethics Committee of Sapporo Medical University Hospital. All of the study participants gave written informed consent.

Study participants

We retrieved data for 1871 consecutive patients registered in the BOREAS-CAG Registry from August 2014 to January 2015. The BOREAS-CAG Registry is a registry of consecutive patients who have undergone coronary angiography (CAG) in 12 affiliated hospitals. The indication for coronary angiography was in accordance with guidelines of the Japanese Circulation Society (JCS): guidelines for diagnostic evaluation of patients with chronic ischaemic heart disease, guidelines for management of acute coronary syndrome without persistent ST segment elevation and guidelines for the management of patients with ST-elevation acute myocardial infarction (MI). Patients with moderate or severe mitral valve disease or aortic valve disease and those with a history of percutaneous coronary intervention (PCI) and/or cardiac surgery including coronary artery bypass grafting (CABG), aortic valve replacement, mitral valve replacement (MVR) and mitral valve plasty (MVP) were excluded, and the remaining 1150 patients aged 15–96 years contributed to the present analyses (figure 1). To confirm the findings in the BOREAS-CAG Registry participants, we also retrieved data for 361 consecutive patients with CAD admitted during the period from April 2013 to July 2014 from the database of the Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University Hospital. This database consists of clinical data for patients who were admitted to the department and gave consent for providing their data to the database. The same exclusion criteria as those for the BOREAS-CAG Registry were applied after exclusion of patients with acute myocardial infarction, and the remaining 166 patients were included for the analyses. Demographic and clinical parameters were determined at the time of admission. CAD was defined as the presence of luminal diameter narrowing of >50% in one or more major coronary arteries. The patients were assessed for the presence or absence of AF at a single time point, based on their 12-lead ECG at the time of enrolment or in the past or by Holter monitoring recorded in the past in some patients.
Figure 1

Flow chart summarising the study population. CAD, coronary artery disease.

Flow chart summarising the study population. CAD, coronary artery disease.

Statistical analyses

Numeric variables are expressed as means±SD for normal distributions or medians (IQRs) for skewed variables. The distribution of each parameter was tested for its normality using the Shapiro-Wilk W test, and non-normally distributed parameters were logarithmically transformed for regression analyses. Differences between two groups were tested by Fisher's exact test or the χ2 test for categorical variables and by Student's t-test and the Kruskal-Wallis test for continuous variables with normal and skewed distributions, respectively. To assess the independent diagnostic values of the variables, we used multivariate stepwise logistic regression analyses based on Akaike's Information Criterion (AIC) for AF. A p value of <0.05 was considered significant. Statistical analyses were carried out using JMP (V.11 SAS Institute, Cary, North Carolina, USA).

Results

Baseline characteristics of patients in the BOREAS-CAG Registry

Clinical characteristics of the patients in the registry are shown in table 1.
Table 1

Baseline characteristics of patients in the BOREAS-CAG Registry

Overall (n=1150)AF (n=111)Non-AF (n=1039)p Value
Age (years)68.8±12.071.2±8.568.5±12.30.026
Sex (male)772 (67.1)72 (64.9)700 (67.6)0.555
BMI (kg/m2)24.4±4.024.5±4.324.4±4.00.795
CAD574 (49.9)35 (31.5)539 (51.9)<0.001
Smoking648 (60.1)67 (61.5)581 (60.0)0.760
Systolic BP (mm Hg)142.6±29.0131.7±26.1143.8±29.0<0.001
HT751 (69.0)76 (68.5)675 (69.1)0.893
DM408 (37.6)35 (31.5)373 (38.3)0.161
DL582 (53.9)45 (40.5)537 (55.4)0.003
UA (mg/dL)5.9±1.86.4±2.05.9±1.70.002
eGFR (mL/min/1.73m2)65.5±30.055.7±21.766.6±30.6<0.001
BNP (pg/mL)48.0 (18.6-131.5)148.0 (69.3-496.0)42.4 (17.0-105.0)<0.001*
LDL (mg/dL)107.5±32.8100.1±29.9108.3±33.00.021
HbA1c (%)6.3±1.36.3±1.16.3±1.30.872
β blocker273 (25.8)50 (45.5)223 (23.6)<0.001
ACEI/ARB471 (44.4)54 (49.1)417 (43.9)0.295
Statin472 (44.6)29 (26.6)443 (46.7)<0.001
Nicorandil246 (23.3)16 (14.8)230 (24.3)0.028

Data are given as the mean±SD or medians (IQRs), or number of patients with percentage in brackets.

*Kruskal-Wallis test.

ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin II type 1 receptor blockers; AF, atrial fibrillation; BNP, B-type natriuretic peptide; BMI, body mass index; CAD, coronary artery disease; DL, dyslipidemia; DM, diabetes mellitus; eGFR, estimated glomerular filtration ratio; HT, hypertension; LDL, low-density lipoprotein cholesterol; UA, uric acid.

Baseline characteristics of patients in the BOREAS-CAG Registry Data are given as the mean±SD or medians (IQRs), or number of patients with percentage in brackets. *Kruskal-Wallis test. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin II type 1 receptor blockers; AF, atrial fibrillation; BNP, B-type natriuretic peptide; BMI, body mass index; CAD, coronary artery disease; DL, dyslipidemia; DM, diabetes mellitus; eGFR, estimated glomerular filtration ratio; HT, hypertension; LDL, low-density lipoprotein cholesterol; UA, uric acid. Patients with AF were significantly older and less likely to have dyslipidemia than those without AF. The level of uric acid (UA) was higher, estimated glomerular filtration rate (eGFR) was lower, brain natriuretic peptide (BNP) level was higher and low-density lipoprotein (LDL) cholesterol level was lower in patients with AF than in those without AF. Statin and nicorandil were administered less often in patients with AF than in without AF, whereas more patients with AF than patients without AF were treated with β blockers, most likely to achieve optimal control of heart rate. Systolic BP was significantly lower in patients with AF than in patients without AF (131.7±26.1 mm Hg vs 143.8±29.0 mm Hg, p<0.001), probably as a result of taking heart rate-lowering medications with negative inotropic actions, including β blockers, diltiazem and/or verapamil. Thirty-five (6.1%) of the 574 patients with CAD and 76 (13.2%) of the 576 patients without CAD had AF (tables 1 and 3). Unexpectedly, the prevalence of CAD was significantly lower in patients with AF than in those without AF (table 1).
Table 3

Clinical characteristics of non-CAD and CAD groups with and without AF

Non-CAD group
CAD group
AF (n=76)Non-AF (n=500)p ValueAF (n=35)Non-AF (n=539)p Value
Age (years)70.7±8.567.6±13.10.04672.3±8.569.4±11.50.126
Sex (male)46 (60.5)297 (59.5)0.86826 (74.3)403 (75.2)0.090
BMI (kg/m2)25.1±4.224.6±4.30.34923.3±4.524.3±3.70.154
Smoking42 (56.8)258 (55.5)0.83825 (71.4)323 (64.1)0.380
HT51 (67.1)306 (65.7)0.80625 (71.4)369 (72.2)0.920
DM23 (30.3)157 (33.8)0.54012 (34.3)216 (42.4)0.345
DL27 (35.5)229 (49.6)0.02318 (51.4)308 (60.8)0.276
UA (mg/dL)6.3±1.65.9±1.80.0546.7±2.75.9±1.70.007
eGFR(mL/min/1.73m2)56.5±20.168.7±23.8<0.00154.0±24.964.7±35.60.041
BNP (pg/mL)144.3 (74.4-437.3)33.8 (14.5-92.1)<0.001*168.4 (52.8-687.9)49.0 (19.3-123.1)<0.001*
LDL (mg/dL)98.3±30.9106.1±32.10.072103.9±27.6110.4±33.70.315
HbA1c (%)6.3±1.16.2±1.20.3566.3±1.16.4±1.40.746
β blocker36 (48.0)102 (22.7)<0.00114 (40.0)121 (24.3)0.039
ACEI/ARB36 (48.0)193 (42.6)0.38318 (51.4)224 (45.0)0.459
Statin15 (20.3)187 (41.5)<0.00114 (40.0)256 (51.4)0.192
Nicorandil7 (9.6)69 (15.3)0.19879 (25.7)161(32.4)0.413

Data are given as the mean±SD or medians (IQRs), or number of patients with percentage in brackets.

*Kruskal-Wallis test.

ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin II type 1 receptor blockers; AF, atrial fibrillation; BMI, body mass index; BNP, B-type natriuretic peptide; CAD, coronary artery disease; DL, dyslipidemia; DM, diabetes mellitus; eGFR, estimated glomerular filtration ratio; HT, hypertension; LDL, low-density lipoprotein cholesterol; UA, uric acid.

Multivariate logistic regression analysis for AF in all enrolled participants

Multivariate logistic regression analysis revealed that the presence of AF was independently associated with high BNP level, low systolic BP level and no statin administration in addition to the absence of CAD (table 2).
Table 2

Multivariate logistic regression analysis for AF

OR95% CIp Value
log BNP1.591.30 to 1.99<0.001
CAD0.350.20 to 0.62<0.001
Systolic BP (mm Hg)0.980.98 to 0.990.001
Statin0.510.28 to 0.900.019
β blocker1.690.97 to 2.900.064
Age (years)1.021.00 to 1.050.098
DM0.680.38 to 1.180.171
eGFR (mL/min/1.73m2)0.990.98 to 1.000.247
Sex (male)0.910.53 to 1.590.747

AF, atrial fibrillation; CAD, coronary artery disease; eGFR, estimated glomerular filtration ratio.

Multivariate logistic regression analysis for AF AF, atrial fibrillation; CAD, coronary artery disease; eGFR, estimated glomerular filtration ratio. The association between AF and absence of CAD was unexpected since CAD is an established risk factor of AF.7–10 However, the participants enrolled in this study were patients with an indication for coronary angiography, and the difference in entry criteria is likely to be an explanation for the discrepancy from the results of earlier studies in general populations. The independent association of low systolic BP level with AF was most likely due to the effect of drug therapy for AF.

Baseline characteristics: non-CAD group versus CAD group

We next examined differences in clinical characteristics and AF risk factors according to the presence (n=574) and absence (n=576) of CAD (figure 1 and online supplementary table S1). As shown in online supplementary table S1, the patients in the CAD group had well-known coronary risk factors than did those in the non-CAD group; age, percentage of males and prevalences of current or past smoking, hypertension (HT), diabetes (DM) and dyslipidemia (DL) were all significantly higher in the CAD group than in the non-CAD group. Despite significantly more frequent administration of statins in the CAD group, the level of LDL cholesterol was still significantly higher in the CAD group. The CAD group showed significantly higher levels of HbA1c than those in the non-CAD group. eGFR was lower and BNP was higher in the CAD group than in the non-CAD group, but the differences did not reach statistical significance. There were no inter-group differences in the use of β blockers and angiotensin-converting enzyme inhibitors (ACEI)/angiotensin type 1 receptor blockers (ARB). The prevalence of AF in patients in the BOREAS-CAG Registry (9.7%) was much higher than that in the general population,1 in agreement with the high prevalences of risk factors including HT, DM and heart failure (table 1). When analysed separately (see online supplementary figure S1), the non-CAD group showed a significantly higher prevalence of either paroxysmal AF (PAF) or chronic AF (CAF), as well as overall AF, than did the CAD group (5.6% vs 3.1% for PAF, 7.6% vs 3.0% for CAF and 13.2% vs 6.1% for overall AF, all p<0.001). The percentages of patients who were administered a statin (50.7% vs 38.5%, p<0.001) and nicorandil (32.0% vs 14.5%, p<0.001) were significantly higher in the CAD group than in the non-CAD group (see online supplementary table S1).

Clinical characteristics of patients with AF and those without AF in the non-CAD group

In the non-CAD group, patients with AF were significantly older and had significantly lower prevalence of DL, lower eGFR and higher BNP than patients without AF (table 3). Clinical characteristics of non-CAD and CAD groups with and without AF Data are given as the mean±SD or medians (IQRs), or number of patients with percentage in brackets. *Kruskal-Wallis test. ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin II type 1 receptor blockers; AF, atrial fibrillation; BMI, body mass index; BNP, B-type natriuretic peptide; CAD, coronary artery disease; DL, dyslipidemia; DM, diabetes mellitus; eGFR, estimated glomerular filtration ratio; HT, hypertension; LDL, low-density lipoprotein cholesterol; UA, uric acid. The percentage of patients who were administered a statin was much lower for patients with AF than for those without AF (20.3% vs 41.5%, p<0.001, table 3). More patients with AF were taking β blockers than were patients without AF, as was the case with the overall data in this registry.

Multivariate logistic regression analysis for AF in the non-CAD group

Multivariate logistic regression analysis demonstrated that BNP was independently associated with the presence of AF (p<0.001) and that statin administration was highly predictive of the absence of AF (p=0.006, table 4) in the non-CAD group (table 4). The association of statin administration with the absence of AF suggests that a statin may suppress development of AF by reducing the LDL level. However, the level of LDL paradoxically tended to be higher in patients without AF than in those with AF (106.1±32.1 mg/dL vs 98.3±30.9 mg/dL, p=0.072, table 3) in the non-CAD group. Indeed, no treatment with a statin was associated with a significantly higher prevalence of AF regardless of the level of LDL cholesterol in the non-CAD group (see online supplementary figure S2).
Table 4

Multivariate logistic regression analysis for AF

OR95% CIp Value
Non-CAD group
 log BNP1.841.41 to 2.43<0.001
 Statin0.360.16 to 0.760.006
 β blocker1.870.94 to 3.700.075
 eGFR (mL/min/1.73 m2)0.990.97 to 1.010.146
 Age (years)1.010.99 to 1.040.328
 DM0.710.34 to 1.430.348
 Sex (male)1.120.58 to 2.150.744
CAD group
 log BNP1.561.18 to 2.07<0.001
 UA (mg/dL)1.211.00 to 1.500.047
 DM0.520.20 to 1.260.151
 Age (years)1.020.98 to 1.070.428
 Sex (male)0.80.31 to 2.260.657

AF, atrial fibrillation; CAD, coronary artery disease; eGFR, estimated glomerular filtration ratio; UA, uric acid.

Multivariate logistic regression analysis for AF AF, atrial fibrillation; CAD, coronary artery disease; eGFR, estimated glomerular filtration ratio; UA, uric acid.

Clinical characteristics of patients with AF and those without AF in the CAD group

When the clinical characteristics of patients with AF and those without AF in the CAD group were compared, significantly higher UA, lower eGFR and higher BNP were found in patients with AF (table 3). Patients in the CAD group were administered similar medications regardless of the presence or absence of AF, though the percentage of patients prescribed a β blocker was significantly higher for patients with AF than for those without AF, as was the case in the non-CAD group.

Multivariate logistic regression analysis for AF in the CAD group

Multivariate logistic regression analysis showed that BNP and UA levels were independently associated with AF in patients with CAD (ORs: 1.56 per log BNP and 1.21 per mg/dL for UA, table 4).

Clinical characteristics in the CAD cohort in Sapporo Medical University Hospital

There are some differences between the characteristics of patients with CAD enrolled in Sapporo Medical University Hospital (see online supplementary table S2) and those in the BOREAS-CAG Registry. The patients in the Sapporo Medical University Hospital cohort showed lower eGFR (53.1±24.1 vs 64.0±35.0 mL/min/1.73 m2) and a lower LDL cholesterol level (91.2±33.3 vs 110±33.4 mg/dL, online supplementary table S1 and S2). However, as was found for patients in the BOREAS-CAG Registry, levels of BNP and UA and the proportion of patients on a β blocker were significantly higher in patients with AF than in those without AF (see online supplementary table S2). BNP and UA were also shown to be independently associated with the presence of AF by multivariate logistic regression analysis (see online supplementary table S3), reinforcing the results of the BOREAS-CAG Registry analysis.

Discussion

The results of cross-sectional analyses of patients in the BOREAS-CAG Registry suggest that the major risk factors of AF are different in patients with CAD and those without CAD: high UA level in patients with CAD versus no statin use in patients without CAD, though high BNP level was a common risk factor of AF regardless of the presence or absence of CAD. The association between UA and AF in the patients with CAD was confirmed by analysis of a separate group of patients enrolled in our institute. The findings in the analyses of the BOREAS-CAG Registry seem to be different to those in the classical AF literature. Clinically apparent, symptomatic CAD was shown to be an established risk factor for AF in previous studies,19 20 whereas multivariate analysis in the present study showed that the prevalence of AF was lower in patients with CAD than in patients without CAD and that the absence of CAD was independently associated with AF (table 2). This discrepancy was unexpected, but there are two non-mutually exclusive explanations. First, criteria for enrolment of study participants in this study were different from those in previous observational studies in which general populations were enrolled.8 In the BOREAS-CAG Registry, patients who underwent coronary angiography for evaluation of chest pain, discomfort or other signs suggestive of CAD were consecutively enrolled. Thus, it is possible that AF was a major cause of non-CAD chest symptoms, resulting in a high prevalence of AF (13.2%) in patients without CAD. In fact, alteration in the CAD-AF association by selection of a specific group of patients was observed in the COMET study in which 3029 patients with heart failure (NYHA II-IV) were enrolled.21 In the COMET study, prevalence of angiographically confirmed CAD was significantly lower in patients with AF than in patients without AF (52.8% vs 60.1%, p=0.016), apparently arguing against an association between AF and CAD in a general population. Second, difference in medication may be involved in the difference in AF prevalence between the patients with CAD and the patients without CAD. In the BOREAS-CAG Registry, a significantly smaller proportion of patients without CAD were administered a statin than the patients with CAD (see online supplementary table S1), and statin administration was independently associated with the absence of AF in the overall registry data (table 2). Thus, more frequent use of a statin in patients with CAD might outweigh the enhanced susceptibility to AF by the presence of CAD. Meta-analysis of randomised controlled trials demonstrated that statin therapy was associated with a decreased risk of AF or recurrence of AF in patients in sinus rhythm with a history of previous AF, undergoing cardiac surgery or after acute coronary syndrome.22 The COMET study also showed that prevalence of statin administration was significantly higher in patients without AF than in those with AF (23.7% vs 10.5%, p<0.0001).21 The beneficial effect of a statin seemed to be more pronounced in the prevention of AF recurrence than in primary prevention of AF.22 23 In this study, association of no statin use with AF was significant in the non-CAD group but not in the CAD group. Why statin use was not selected as a significant explanatory variable for AF in patients with CAD is unclear. When patients who were administered statin were analysed, LDL cholesterol level was significantly higher in the CAD group than in the non-CAD group (108.5±35 vs 98.1±35.0, p=0.003). This finding suggests that insufficient cholesterol-lowering effects of statins in patients with CAD may underlie the lack of statin-associated reduction in AF prevalence. However, this possibility is unlikely because of the following reasons. First, the level of LDL cholesterol tended to be lower in patients with AF than in those without AF in the non-CAD and CAD groups (table 3). Second, treatment with a statin was not associated with significant reduction of AF when the LDL cholesterol level was <140 mg/dL, <120 mg/dL or even <100 mg/dL in the CAD group (see online supplementary figure S3), whereas prevalence of AF was consistently lower in statin-treated patients regardless of the LDL cholesterol level in the non-CAD group (see online supplementary figure S2). Hyperuricemia has been shown to be associated with AF in patients with HT,24 heart failure25 or type 2 diabetes mellitus.26 It has also been reported that serum UA level was significantly correlated with the development of AF in a concentration-dependent manner,27 and a meta-analysis of 6 cross-sectional and 3 cohort studies confirmed the association of hyperuricemia with AF.28 However, to the best of our knowledge, the relationship between CAD and UA-associated AF risk has not been examined in detail. In this study, UA levels were similar in the CAD and non-CAD groups (see online supplementary table S1), but UA was selected as a significant explanatory variable of AF only in the CAD group (table 4). Why UA was not associated with AF in the non-CAD patients is unclear. The serum level of UA in the non-CAD patients (5.9±1.7 mg/dL) was slightly lower than levels in earlier studies showing UA-associated increased risk of AF (6.2±0.2 vs 5.3±1.6 mg/dL, 6.4±2.1 vs 5.7±1.9 mg/dL and 6.3±1.6 vs 5.0±1.3 mg/dL for patients with AF and those without AF, respectively24–26). Besides, since the present analysis is cross-sectional, we cannot exclude the possibility that the duration of elevated UA level was shorter in participants of this study than in participants of earlier studies, in which patients free from AF at baseline were followed for 10 years.26 Another possible explanation is alteration in myocardial sensitivity to UA in the presence of CAD. However, there is no clinical evidence supporting this speculation. A significant association of high UA level with AF development and an association of statin use with reduced AF incidence shown in this study and earlier studies suggest possible benefits of UA-lowering agents and statins for prevention of AF. Emerging evidence suggests that oxidative stress and inflammation promote structural and electrical cardiac remodelling of the atrium, predisposing the heart to atrial fibrosis and AF.29 30 Statins and allopurinol, a xanthine oxidase inhibitor to reduce production of UA, have been shown to have anti-inflammatory/antioxidative actions31–34 and possibly intervene in the process of atrial remodelling by risk factors of AF. However, the clinical benefit of statins or allopurinol in prevention of AF has not been unequivocally demonstrated. A recent meta-analysis demonstrated that perioperative statin therapy in statin-naive patients with sinus rhythm undergoing cardiac surgery was associated with a decrease in the development of postoperative AF.35 In contrast, a recent randomised clinical trial with 1922 patients failed to show significant prevention of AF after cardiac surgery by rosuvastatin (20 mg/day).36 Clinical benefit of allopurinol or other UA-lowering agents has not been critically tested by large randomised clinical trials, though allopurinol use was shown to be independently associated with a lower risk of new onset of AF in a cohort of elderly patients (78.2±7.2 years).37 Interestingly, longer duration of allopurinol administration achieved greater risk reduction, supporting the notion that suppression of atrial remodelling over a long period by the antioxidative property of the agent was involved in the clinical effects.37 Causal relationships between elevation of serum UA level, AF development and CAD remain to be examined in future studies. Finally, since all patients in the BOREAS-CAG Registry were Japanese, the results are not directly translatable to other ethnicities. On the other hand, the Japanese are often significantly under-represented in clinical trials, and thus the results of the present analysis may be important in identifying trends in aetiology in such populations.

Study limitations

There are several limitations in this study. First, as this was a cross-sectional study, the temporal order of variables cannot be determined, and thus the direction of causality is unclear. Second, AF was diagnosed if recorded clinically at the time of enrolment, as mentioned in the ‘Methods’ section and was not sought actively thereafter. Thus, PAF may have been missed in some patients. Third, information regarding types of statin was not obtained from the BOREAS-CAG Registry. Since the clinical benefit for AF may depend on the type of statin,23 we cannot exclude the possibility that types of statins were not well balanced in the patients with CAD and patients without CAD, leading to the difference in the association between AF and statin use in the two groups. Finally, the present results are not directly applicable to the general population because all of the participants in this study had indications for coronary angiography. In fact, the prevalence of AF in the patients in the BOREAS-CAG Registry (9.7% in overall patients, 6.1% in patients with CAD and 13.2% in patients without CAD) was much higher than that in the general population (ie, 1–2%). The high prevalences of HT (69.0%), DM (37.6%) and latent heart failure as indicated by elevated BNP may have predisposed patients in the BOREAS-CAG Registry to development of AF.

Conclusions

Cross-sectional analysis of the BOREAS-CAG Registry data indicated that risk factors of AF are distinct in patients with CAD and those without CAD. No statin administration was associated with AF in patients without CAD, whereas high UA was the risk factor associated with AF in patients with CAD. The present findings need to be confirmed by longitudinal studies.
  37 in total

1.  Prognostic relevance of atrial fibrillation in patients with chronic heart failure on long-term treatment with beta-blockers: results from COMET.

Authors:  Karl Swedberg; Lars G Olsson; Andrew Charlesworth; John Cleland; Peter Hanrath; Michel Komajda; Marco Metra; Christian Torp-Pedersen; Philip Poole-Wilson
Journal:  Eur Heart J       Date:  2005-03-14       Impact factor: 29.983

2.  Association of serum uric acid with incident atrial fibrillation (from the Atherosclerosis Risk in Communities [ARIC] study).

Authors:  Leonardo Tamariz; Sunil Agarwal; Elsayed Z Soliman; Alanna M Chamberlain; Ronald Prineas; Aaron R Folsom; Marietta Ambrose; Alvaro Alonso
Journal:  Am J Cardiol       Date:  2011-08-17       Impact factor: 2.778

3.  Outcome of heart failure with preserved ejection fraction in a population-based study.

Authors:  R Sacha Bhatia; Jack V Tu; Douglas S Lee; Peter C Austin; Jiming Fang; Annick Haouzi; Yanyan Gong; Peter P Liu
Journal:  N Engl J Med       Date:  2006-07-20       Impact factor: 91.245

Review 4.  Comprehensive risk reduction in patients with atrial fibrillation: emerging diagnostic and therapeutic options--a report from the 3rd Atrial Fibrillation Competence NETwork/European Heart Rhythm Association consensus conference.

Authors:  Paulus Kirchhof; Gregory Y H Lip; Isabelle C Van Gelder; Jeroen Bax; Elaine Hylek; Stefan Kaab; Ulrich Schotten; Karl Wegscheider; Giuseppe Boriani; Axel Brandes; Michael Ezekowitz; Hans Diener; Laurent Haegeli; Hein Heidbuchel; Deirdre Lane; Luis Mont; Stephan Willems; Paul Dorian; Maria Aunes-Jansson; Carina Blomstrom-Lundqvist; Maria Borentain; Stefanie Breitenstein; Martina Brueckmann; Nilo Cater; Andreas Clemens; Dobromir Dobrev; Sergio Dubner; Nils G Edvardsson; Leif Friberg; Andreas Goette; Michele Gulizia; Robert Hatala; Jenny Horwood; Lukas Szumowski; Lukas Kappenberger; Josef Kautzner; Angelika Leute; Trudie Lobban; Ralf Meyer; Jay Millerhagen; John Morgan; Felix Muenzel; Michael Nabauer; Christoph Baertels; Michael Oeff; Dieter Paar; Juergen Polifka; Ursula Ravens; Ludger Rosin; W Stegink; Gerhard Steinbeck; Panos Vardas; Alphons Vincent; Maureen Walter; Günter Breithardt; A John Camm
Journal:  Europace       Date:  2011-07-26       Impact factor: 5.214

5.  A clinical risk score for atrial fibrillation in a biracial prospective cohort (from the Atherosclerosis Risk in Communities [ARIC] study).

Authors:  Alanna M Chamberlain; Sunil K Agarwal; Aaron R Folsom; Elsayed Z Soliman; Lloyd E Chambless; Richard Crow; Marietta Ambrose; Alvaro Alonso
Journal:  Am J Cardiol       Date:  2011-01       Impact factor: 2.778

6.  Statins downregulate myeloperoxidase gene expression in macrophages.

Authors:  Alan P Kumar; Wanda F Reynolds
Journal:  Biochem Biophys Res Commun       Date:  2005-06-03       Impact factor: 3.575

7.  Effect of preoperative obstructive sleep apnea on the frequency of atrial fibrillation after coronary artery bypass grafting.

Authors:  Erik M van Oosten; Andrew Hamilton; Dimitri Petsikas; Darrin Payne; Damian P Redfearn; Shetuan Zhang; Wilma M Hopman; Adrian Baranchuk
Journal:  Am J Cardiol       Date:  2013-12-25       Impact factor: 2.778

8.  The natural history of atrial fibrillation: incidence, risk factors, and prognosis in the Manitoba Follow-Up Study.

Authors:  A D Krahn; J Manfreda; R B Tate; F A Mathewson; T E Cuddy
Journal:  Am J Med       Date:  1995-05       Impact factor: 4.965

9.  Atrial sources of reactive oxygen species vary with the duration and substrate of atrial fibrillation: implications for the antiarrhythmic effect of statins.

Authors:  Svetlana N Reilly; Raja Jayaram; Keshav Nahar; Charalambos Antoniades; Sander Verheule; Keith M Channon; Nicholas J Alp; Ulrich Schotten; Barbara Casadei
Journal:  Circulation       Date:  2011-08-15       Impact factor: 29.690

10.  Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium.

Authors:  Alvaro Alonso; Bouwe P Krijthe; Thor Aspelund; Katherine A Stepas; Michael J Pencina; Carlee B Moser; Moritz F Sinner; Nona Sotoodehnia; João D Fontes; A Cecile J W Janssens; Richard A Kronmal; Jared W Magnani; Jacqueline C Witteman; Alanna M Chamberlain; Steven A Lubitz; Renate B Schnabel; Sunil K Agarwal; David D McManus; Patrick T Ellinor; Martin G Larson; Gregory L Burke; Lenore J Launer; Albert Hofman; Daniel Levy; John S Gottdiener; Stefan Kääb; David Couper; Tamara B Harris; Elsayed Z Soliman; Bruno H C Stricker; Vilmundur Gudnason; Susan R Heckbert; Emelia J Benjamin
Journal:  J Am Heart Assoc       Date:  2013-03-18       Impact factor: 5.501

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  3 in total

1.  Predictive value of CHADS2 and CHA2DS2-VASc scores for acute myocardial infarction in patients with atrial fibrillation.

Authors:  Hui Pang; Bing Han; Qiang Fu; Zhenkun Zong
Journal:  Sci Rep       Date:  2017-07-05       Impact factor: 4.379

Review 2.  The Key Role of Uric Acid in Oxidative Stress, Inflammation, Fibrosis, Apoptosis, and Immunity in the Pathogenesis of Atrial Fibrillation.

Authors:  Yawen Deng; Fei Liu; Xiaolei Yang; Yunlong Xia
Journal:  Front Cardiovasc Med       Date:  2021-02-26

3.  Atrial fibrillation risk factors in patients with ischemic stroke.

Authors:  Paweł Wańkowicz; Przemysław Nowacki; Monika Gołąb-Janowska
Journal:  Arch Med Sci       Date:  2019-04-05       Impact factor: 3.318

  3 in total

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