International Journal of Cardiology 170 (2014) 344–349
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Hyperuricemia and the risk of ischemic stroke in patients with atrial fibrillation — Could it refine clinical risk stratification in AF? Tze-Fan Chao a,b,h,1, Chia-Jen Liu c,d,e,1, Su-Jung Chen f, Kang-Ling Wang a,b,h, Yenn-Jiang Lin a,b,h, Shih-Lin Chang a,b,h, Li-Wei Lo a,b,h, Yu-Feng Hu a,b,h, Ta-Chuan Tuan a,b,h, Tzeng-Ji Chen g, Hsuan-Ming Tsao b,e,h, Shih-Ann Chen a,b,h,⁎ a
Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan c Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan d Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei, Taiwan e Department of Internal Medicine, National Yang-Ming University Hospital, I-Lan, Taiwan f Division of Infectious Diseases, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan g Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan h Cardiovascular Research Center, National Yang-Ming University, Taipei, Taiwan b
a r t i c l e
i n f o
Article history: Received 31 January 2013 Received in revised form 1 August 2013 Accepted 2 November 2013 Available online 13 November 2013 Keywords: Atrial fibrillation Hyperuricemia Stroke CHA2DS2-VASc score
a b s t r a c t Background: Although hyperuricemia has been reported to be a risk factor of stroke, the relationship between hyperuricemia and stroke in patients with atrial fibrillation (AF) remains uncertain. The goal of the present study was to investigate whether hyperuricemia could potentially refine clinical risk stratification in AF. Methods: This study used the “National Health Insurance Research Database” in Taiwan. A total of 7601 AF patients who did not receive antiplatelet agents or oral anticoagulants were identified as the study population. Hyperuricemia was defined as having at least one episode of gout attack necessitating long-term treatment with uric acid-lowering agents. The association between hyperuricemia and ischemic stroke was analyzed. Results: During the follow up of 3.0 ± 2.7 years, 1116 patients (14.7%) experienced ischemic stroke with an annual rate of around 4.9%. Hyperuricemia significantly predicts stroke, with a hazard ratio (HR) of 1.280 after adjusting for CHA2DS2-VASc score and other comorbidities. Among the 376 patients with a CHA2DS2VASc score of 0, hyperuricemia can further stratify them into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020). The adjusted HR of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a score of 3, and became insignificant for patients with a score ≥4. Conclusions: Hyperuricemia was a significant risk factor of stroke which could potentially refine the clinical risk stratification in AF. It deserves a prospective trial to investigate whether it would change the current strategy for stroke preventions using oral anticoagulants. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, and its incidence is projected to rise continuously over the next few decades [1]. It represents an independent and important risk factor of stroke [2,3], and stroke prevention with oral anticoagulants (OACs) is the cornerstone for AF management. Several risk stratification models of different complexities have been introduced to identify AF patients who may benefit from OACs. Recently, a newly developed
⁎ Corresponding author at: Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih-Pai Road, Taipei, Taiwan. Tel.: +886 2 2875 7156; fax: +886 2 2873 5656. E-mail address: [email protected] (S.-A. Chen). 1 Dr. Tze-Fan Chao and Dr Chia-Jen Liu contributed equally to this study. 0167-5273/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijcard.2013.11.011
scoring system, the CHA2DS2-VASc score, which extends the CHADS2 scheme by considering additional stroke risk factors (vascular diseases and female gender), has been recommended as a guide for antithrombotic therapies in AF patients [4–6]. The usefulness of CHA2DS2-VASc score in predicting AF-related thromboembolic events has been validated in several subsequent studies [7–11]. However, the recognition and validation of novel risk factors that could potentially refine the clinical risk stratification in AF patients is still an important issue. Uric acid is a byproduct of purine catabolism, of which the terminal steps are catalyzed by xanthine oxidase. The disease burden of hyperuricemia and gout, which is a painful inflammatory arthritis caused by hyperuricemia, is substantial and continues to rise [12]. Although hyperuricemia with or without gout has been identified as a risk factor of stroke in previous studies [13–17], it remains unclear if it can predict stroke in AF patients. The goal of the present study was to investigate
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
345
Fig. 1. A flowchart of the enrollment of the study patients. A total of 7601 AF patients who did not take anti-platelet agents or OACs between January 1, 2000 and December 31, 2009 were enrolled in this study. During the mean follow-up of 3.0 ± 2.7 years, there were 1116 patients who experienced ischemic stroke. AF = atrial fibrillation, OAC = oral anticoagulants.
the relationship between hyperuricemia and ischemic stroke in AF. We also sought to determine whether hyperuricemia has a potential role in predicting stroke in addition to the CHA2DS2-VASc score. 2. Methods
and chi-square testing for nominal variables. The stroke-free survival curve was plotted using the Kaplan–Meier method with statistical significance examined by the log-rank test. The risk of ischemic stroke was assessed using the Cox regression analysis. All statistical significances were set at p b 0.05 and all statistical analyses were carried out by SPSS 17.0 (SPSS Inc., USA). This manuscript was written following STROBE guidelines for the reporting of observational studies [18].
2.1. Database This study used the “National Health Insurance Research Database (NHIRD)” released by the Taiwan National Health Research Institutes (NHRI). The National Health Insurance (NHI) system is a mandatory universal health insurance program that offers comprehensive medical care coverage to all Taiwanese residents. The NHIRD is a cohort dataset that contains all medical claim data for 1,000,000 beneficiaries, who were randomly sampled from the 25.68 million enrollees under the NHI program. These random samples have been confirmed by the NHRI to be representative of the Taiwanese population. In this cohort dataset, the patients' original identification numbers were encrypted to protect their privacy, but the encrypting procedure was consistent, so that linking claims belonging to the same patient was feasible within the NHI database and could be followed continuously. The database has a large sample size and provides a good opportunity to study the risk of stroke among AF patients with or without hyperuricemia. 2.2. Study population From January 1, 2000 to December 31, 2009, a total of 11,268 patients 18 years of age or older with newly diagnosed AF were identified from the NHIRD. Patients who received antithrombotic therapy with either antiplatelet agents or OACs were excluded, resulting in a total of 7601 patients who were selected as the study population. For each patient, the CHA2DS2-VASc score was calculated based on a point system in which 2 points were assigned for a history of stroke or transient ischemic attack (TIA), or age ≥75 years; and 1 point each was assigned for patients aged 65–74 years or those who had a history of hypertension, diabetes, recent cardiac failure, vascular disease (myocardial infarction, complex aortic plaque, or peripheral artery disease), and were female [4]. Hyperuricemia was defined as having at least one episode of gout attack necessitating long-term treatment of uric acid-lowering agents. The primary endpoint was defined as the occurrence of ischemic stroke confirmed by imaging studies of the brain, including a computed tomography scan or magnetic resonance imaging. There were 1116 patients who experienced ischemic stroke during the follow-up. A flowchart of the enrollment of the study population is shown in Fig. 1. 2.3. Statistical analysis The data are presented as the mean value and standard deviation for normally distributed continuous variables and proportions for categorical variables. The differences between continuous values were assessed using an unpaired 2-tailed t test for normally distributed continuous variables, Mann–Whitney rank-sum test for skewed variables,
Table 1 Baseline characteristics of AF patients with and without strokes. Variables
With strokes (n = 1116)
Without strokes (n = 6485)
p value
Age, years Age ≥ 65 years old Age ≥ 75 years old Gender (male)
73.4 ± 10.7 81.8% 49.7% 54.0%
69.4 ± 15.8 68.9% 45.4% 54.7%
b0.001 b0.001 0.007 0.667
b0.001 0.004 0.053 b0.001 b0.001 b0.001
Medical history (components of CHA2DS2-VASc score) Hypertension Diabetes mellitus Congestive heart failure Previous stroke/TIA Previous vascular disease CHA2DS2-VASc score, median (inter-quartile range) Score 0 Score 1 Score 2 Score 3 Score 4 Score 5 Score 6 Score 7 Score 8 Score 9
79.3% 38.3% 45.7% 49.5% 12.5% 5 (4–6)
69.2% 33.8% 42.6% 25.9% 8.5% 4 (2–6)
0.7% 3.9% 7.6% 10.1% 16.8% 19.3% 16.9% 13.2% 8.1% 3.5%
5.7% 9.2% 11.5% 12.4% 15.5% 15.6% 13.0% 9.3% 5.4% 2.5%
Other comorbidities Dyslipidemia Chronic renal disease Chronic pulmonary disease Autoimmune diseases Hyperuricemia
32.5% 10.6% 46.9% 9.2% 30.6%
32.9% 11.1% 48.2% 9.8% 26.2%
AF = atrial fibrillation; TIA = transient ischemic attack.
0.826 0.602 0.419 0.568 0.002
346
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
Table 2 The risk of ischemic stroke in patients with and without hyperuricemia. Variable
Ischemic stroke Yes No Crude hazard ratio (95% CI) Adjusted hazard ratio (95% CI)b a b
All (n = 7601)
Hyperuricemia
n (%) 1116 (14.7%) 6485 (85.3%)
Yes (n = 2039)
No (n = 5562)
n (%) 342 (16.8%)a 1697 (83.2%) 1.436 (1.264–1.632); p value b 0.001 1.280 (1.121–1.462); p value b 0.001
n (%) 774 (13.9%) 4788 (86.1%)
p value = 0.002 in comparison with patients without hyperuricemia. Adjustment for the CHA2DS2-VASc score and other comorbidities listed in Table 1, including dyslipidemia, chronic renal disease, chronic pulmonary disease and autoimmune diseases.
3. Results 3.1. Patient characteristics The mean age of the study population was 70.0 ± 15.3 years and males accounted for 54.6% of the patients. The median value (interquartile range) of the CHA2DS2-VASc score was 4 (3–6), and 86.6% of patients had a score ≥ 2. The mean follow-up duration was 3.0 ± 2.7 years, and there were 1116 patients (14.7%) who experienced ischemic stroke with an annual stroke rate of around 4.9%. The baseline characteristics of patients with and without stroke are shown in Table 1. Patients who experienced events were older and had a higher CHA2DS2-VASc score than those who did not. In regard to the comorbidities other than the components of the CHA2DS2-VASc scheme, hyperuricemia was more prevalent in patients with ischemic stroke. 3.2. Hyperuricemia and the risk of stroke The rate of ischemic stroke was higher in patients with hyperuricemia than those without it (16.8% versus 13.9%, p value = 0.002) (Table 2). Hyperuricemia remained as a significant risk factor of ischemic events, with an adjusted hazard ratio (HR) of 1.280 (95% confidence interval [CI] = 1.121–1.462; p b 0.001) after adjusting for the CHA2DS2-VASc score and other comorbidities, including dyslipidemia, chronic renal disease, chronic pulmonary disease, and autoimmune diseases which were more prevalent among patients with hyperuricemia (Table 2). The associations between hyperuricemia and ischemic stroke in different regression models adjusted for the CHA2DS2-VASc score and its components were shown in Table 3. Fig. 2 shows the Kaplan–Meier curve of stroke-free survival between patients with and without hyperuricemia demonstrating that AF patients with hyperuricemia were associated with a higher stroke rate during the follow-up period. 3.3. Hyperuricemia and the risk of stroke stratified by CHA2DS2-VASc scores In the subgroup analysis based on CHA2DS2-VASc scores, the rate of ischemic stroke was consistently higher in patients with hyperuricemia among groups with a CHA2DS2-VASc score of 0 (Fig. 3A) and ≥ 1 (Fig. 3B). Among the 376 patients with a CHA2DS2VASc score of 0, hyperuricemia can further stratify them into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020), as shown in Fig. 4. Fig. 5 shows that
the adjusted HR of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a CHA2DS2-VASc score of 3, and became insignificant for patients with a CHA2DS2-VASc score ≥4. 4. Discussion 4.1. Main findings This study enrolled 7601 AF subjects who did not receive medications for thromboprophylaxis and compared the risk of ischemic stroke in patients with hyperuricemia to that of patients without it. The main findings were as follows: (1) hyperuricemia was a significant risk factor of stroke for AF patients. (2) In patients with a CHA2DS2-VASc score of 0, hyperuricemia may be helpful for identifying patients at risk of stroke. (3) Hyperuricemia did not significantly predict ischemic stroke in patients with a CHA2DS2-VASc score ≥4. 4.2. Hyperuricemia and the risk of stroke in AF patients Hyperuricemia has been reported to be associated with endothelial dysfunction, free radical generation, abnormally high levels of systemic inflammatory markers (such as C-reactive protein and interleukin-6), and insulin resistance, which may predispose patients to the risk of cardiovascular events [19–21]. Heo and Lee previously investigated the relationship between serum levels of uric acid and silent brain infarction detected by brain magnetic resonance imaging in a total of 1577 patients, and found that hyperuricemia was an independent risk factor [22]. In addition, several cohort studies have recognized hyperuricemia as an independent risk factor for stroke (Table 4) [13–16], including studies performed by Lehto et al. (HR = 1.74, 95% CI = 1.16–2.61) [13], Chien et al. (HR = 1.23 for males and 1.36 for females) [14], Bos et al. (HR = 1.77, 95% CI = 1.10–2.83) [15], and Hozawa et al. (HR = 1.49, 95% CI = 1.00–2.23) [16]. Although these previous studies enrolled a large number of patients, ranging from 1017 to 13,413 subjects, the percentages of AF patients in the study populations were not reported and seemed to be low. Since these studies did not focus on AF, it remained unclear whether hyperuricemia is a risk factor of ischemic stroke for AF patients. In this nationwide cohort study, we found that hyperuricemia was a significant predictor of ischemic stroke in AF, even after adjusting for the
Table 3 Association of hyperuricemia and ischemic stroke in Cox regression models. Models
Hazard ratio
95% confidence interval
p value
Model 1: adjusted for age and gender Model 2: adjusted for age, gender and hypertension Model 3: adjusted for age, gender and diabetes mellitus Model 4: adjusted for age, gender and congestive heart failure Model 5: adjusted for age, gender and previous stroke/TIA Model 6: adjusted for age, gender and previous vascular disease Model 7: adjusted for CHA2DS2-VASc score
1.325 1.248 1.272 1.309 1.255 1.332 1.194
1.165–1.506 1.096–1.422 1.117–1.449 1.150–1.490 1.103–1.427 1.171–1.515 1.049–1.358
b0.001 0.001 b0.001 b0.001 0.001 b0.001 0.007
TIA = transient ischemic attack.
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
347
CHA2DS2-VASc score ≥ 4, hyperuricemia no longer remained as an important factor associated with ischemic stroke. These observations suggest that hyperuricemia could be regarded as a “red flag” for stroke in patients without clinically apparent comorbidities and may be associated with a pre-diseased complex, including insulin resistance, prediabetes, obesity, systemic inflammation, arterial stiffness and carotid atherosclerosis [19,20,23,24]. These conditions would increase the risk of stroke, but were not included or represented by the CHA2DS2-VASc scheme. Alternatively, hyperuricemia could be just a bystander and plays a less important role in the development of stroke in patients with multiple cardiovascular risk factors who have a high CHA2DS2-VASc score. 4.3. How could hyperuricemia refine the risk stratification in AF patients?
Fig. 2. The risk of ischemic stroke in patients with and without hyperuricemia. A Kaplan– Meier survival analysis showing that AF patients with hyperuricemia are associated with a higher stroke rate compared to those without hyperuricemia (16.8% versus 13.9%, p = 0.002). AF = atrial fibrillation.
CHA2DS2-VASc score. Interestingly, the HRs of hyperuricemia in predicting stroke were attenuated after censoring for more risk factors represented by a high CHA2DS2-VASc score. In patients with a
Fig. 3. Stroke-free survival curves for patients with and without hyperuricemia in groups with different CHA2DS2-VASc scores. In the subgroup analysis based on the CHA2DS2-VASc score, the rate of ischemic stroke was consistently higher in patients with hyperuricemia among groups with a CHA2DS2-VASc score of 0 (A) and ≥1 (B).
The CHADS2 score is the most commonly used scheme in stroke risk stratification for AF [25], despite the fact that it classifies a large proportion of patients as having an “intermediate risk” [26]. The new scoring system, the CHA2DS2-VASc score, has been proposed to complement the CHADS2 score and is recommended as a guide for the use of OACs in the current European Society of Cardiology (ESC) guidelines [4–6]. The CHA2DS2-VASc score has been validated in multiple patient cohorts, and accumulating evidence indicated that it may be better than the CHADS2 score at identifying “truly low-risk” patients with AF [9,10,27–29]. Although it was found that some patients with a low CHA2DS2-VASc score still experienced ischemic stroke, warfarin was not suggested for patients with a score of 0 after taking the risk/benefit balance into consideration. Recently, several new OACs, including dabigatran, rivaroxaban, and apixaban, were proven to be as effective as warfarin in preventing stroke with less events of intracranial hemorrhage, which is the most serious complication of OAC [30–32]. Therefore, if we could further identify patients at risk of stroke among those with a CHA2DS2-VASc score of 0, prescriptions of new OACs may be beneficial and should be considered for them. In the present study, we found that patients with a CHA2DS2-VASc score of 0 and who were diagnosed with hyperuricemia had an annual stroke rate of approximately 2.37%, which was higher than the rates of life threatening (1.22%/year for dabigatran 110 mg; 1.45%/year for dabigatran 150 mg) and intracranial bleeding (0.23%/year for dabigatran 110 mg; 0.30%/year for dabigatran 150 mg) for dabigatran use [30]. Based on these results, a prospective and randomized trial is necessary to investigate whether these patients will benefit from new OAC therapies.
Fig. 4. A flowchart demonstrating the stroke rates according to the CHA2DS2-VASc scores and hyperuricemia. Hyperuricemia can further stratify patients with a CHA2DS2-VASc score of 0 into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020).
348
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
Fig. 5. Hyperuricemia and the risk of stroke in patients with different CHA2DS2-VASc scores. The hazard ratio of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a CHA2DS2-VASc score of 3, and became insignificant for patients with a CHA2DS2-VASc score ≥4. CI = confidence interval, HR = hazard ratio. *Adjustment for other comorbidities listed in Table 1, including dyslipidemia, chronic renal disease, chronic pulmonary disease and autoimmune diseases.
4.4. Study limitations There were several limitations in the present study. First, the absolute values of uric acid were not available in the nationwide dataset. However, the levels of uric acid fluctuate significantly and are not constant, which make it difficult to determine the levels appropriately. In the present study, patients were regarded as having hyperuricemia only when they suffered at least one episode of gout attack that necessitated long-term treatment of uric acid-lowering agents. Therefore, we focused on symptomatic hyperuricemia, and the results based on this definition may be more clinically relevant. Second, information about the types of AF (paroxysmal or non-paroxysmal) was lacking. Nevertheless, since the risk of stroke did not differ between patients with paroxysmal or non-paroxysmal AF [33,34], the type of AF may not confound the findings of this study. Third, the number of events in patients with a CHA2DS2-VASc score of 0 was small, and the usefulness of hyperuricemia for further risk stratifications among these low-risk patients may not be conclusive based on the results presented here. Lastly, we were not able to clearly confirm the cause of ischemic stroke since it can be due to thrombosis of the cerebral artery or AF-related thromboembolism. However, it was also a common limitation in previous randomized trials [30–32].
Hyperuricemia could potentially refine the clinical risk stratification for AF patients, and thus deserves a further prospective and largescale clinical trial to investigate whether it would change the current strategy for the use of OACs in stroke prevention. Acknowledgments This work was supported in part by grants from the National Science Council (NSC98-2410-H-010-003-MY2), and the Taipei Veterans General Hospital (V99C1-140, V99A-153, V100D-002-3, and V101D-001-2). References
5. Conclusion In this AF cohort study, hyperuricemia was a significant risk factor of ischemic stroke after adjusting for the CHA2DS2-VASc score.
[1] Potpara TS, Lip GY. Lone atrial fibrillation: what is known and what is to come. Int J Clin Pract 2011;65:446–57. [2] Chugh SS, Blackshear JL, Shen WK, Hammill SC, Gersh BJ. Epidemiology and natural history of atrial fibrillation: clinical implications. J Am Coll Cardiol 2001;37:371–8. [3] Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke 1991;22:983–8. [4] Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest 2010;137:263–72. [5] Camm AJ, Kirchhof P, Lip GY, 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. [6] Camm AJ, Lip GY, De Caterina R, et al. 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC guidelines for the management of atrial fibrillation developed with the special contribution of the European Heart Rhythm Association. Eur Heart J 2012;33:2719–47.
Table 4 Summary of the cohort studies showing hyperuricemia as a risk factor of stroke. Author (year) Lehto et al. (1998)13 Chien et al. (2005)14 Bos et al. (2006)15 Hozawa et al. (2006)16
Patient number
Age
Outcome
Risk of outcome HR (95% CI)
p value
% AF in the study group
1017 3602
45–64 N35
Any stroke except SAH Any type of stroke
63–76 45–64
Ischemic stroke Ischemic stroke
0.008 0.054 0.021 N.R. 0.02
N.R. N.R.
4385 13,413
1.74 (1.16–2.61)a Male: 1.23 (1.00–1.53)b Female: 1.36 (1.05–1.75)b 1.77 (1.10–2.83)c 1.49 (1.00–2.23)d
N.R. N.R.
AF = atrial fibrillation; CI = confidence interval; HR = hazard ratio; N.R. = not reported; SAH = subarachnoid hemorrhage. a Adjusted for age, gender, smoking, cholesterol and hypertension. b Adjusted for age. Uric acid was regarded as a continuous variable. c Age- and sex-adjusted HR for the highest versus the lowest quintile of uric acid for ischemic stroke. d Adjusted HR for the highest versus the lowest quartile of uric acid for ischemic stroke. The regression model included age, sex, race, education, systolic blood pressure, diabetes mellitus, anti-hypertensive medication, cigarette smoking status, ethanol intake, serum albumin, von Willebrand factor, body mass index, waist-to-hip ratio, and low HDL cholesterol.
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349 [7] Olesen JB, Lip GY, Hansen ML, et al. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study. BMJ 2011;342:d124. [8] Chao TF, Lin YJ, Tsao HM, et al. CHADS(2) and CHA(2)DS(2)-VASc scores in the prediction of clinical outcomes in patients with atrial fibrillation after catheter ablation. J Am Coll Cardiol 2011;58:2380–5. [9] Potpara TS, Polovina MM, Licina MM, Marinkovic JM, Prostran MS, Lip GY. Reliable identification of “truly low” thromboembolic risk in patients initially diagnosed with “lone” atrial fibrillation: the Belgrade Atrial Fibrillation Study. Circ Arrhythm Electrophysiol 2012;5:319–26. [10] Olesen JB, Torp-Pedersen C, Hansen ML, Lip GY. The value of the CHA 2DS2-VASc score for refining stroke risk stratification in patients with atrial fibrillation with a CHADS 2 score 0–1: a nationwide cohort study. Thromb Haemost 2012;107:1172–9. [11] Chao TF, Liu CJ, Chen SJ, et al. Atrial fibrillation and the risk of ischemic stroke: does it still matter in patients with a CHA2DS2-VASc score of 0 or 1? Stroke 2012;43:2551–5. [12] Zhu Y, Pandya BJ, Choi HK. Prevalence of gout and hyperuricemia in the US general population: the National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 2011;63:3136–41. [13] Lehto S, Niskanen L, Ronnemaa T, Laakso M. Serum uric acid is a strong predictor of stroke in patients with non-insulin-dependent diabetes mellitus. Stroke 1998;29:635–9. [14] Chien KL, Hsu HC, Sung FC, Su TC, Chen MF, Lee YT. Hyperuricemia as a risk factor on cardiovascular events in Taiwan: the Chin-Shan Community Cardiovascular Cohort Study. Atherosclerosis 2005;183:147–55. [15] Bos MJ, Koudstaal PJ, Hofman A, Witteman JC, Breteler MM. Uric acid is a risk factor for myocardial infarction and stroke: the Rotterdam Study. Stroke 2006;37:1503–7. [16] Hozawa A, Folsom AR, Ibrahim H, Javier Nieto F, Rosamond WD, Shahar E. Serum uric acid and risk of ischemic stroke: the ARIC Study. Atherosclerosis 2006;187:401–7. [17] Kim SY, Guevara JP, Kim KM, Choi HK, Heitjan DF, Albert DA. Hyperuricemia and risk of stroke: a systematic review and meta-analysis. Arthritis Rheum 2009;61:885–92. [18] von Elm E, Altman DG, Egger M, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007;335:806–8. [19] Ruggiero C, Cherubini A, Ble A, et al. Uric acid and inflammatory markers. Eur Heart J 2006;27:1174–81.
349
[20] Krishnan E, Pandya BJ, Chung L, Hariri A, Dabbous O. Hyperuricemia in young adults and risk of insulin resistance, prediabetes, and diabetes: a 15-year follow-up study. Am J Epidemiol 2012;176:108–16. [21] Papezikova I, Pekarova M, Kolarova H, et al. Uric acid modulates vascular endothelial function through the down regulation of nitric oxide production. Free Radic Res 2013;47:82–8. [22] Heo SH, Lee SH. High levels of serum uric acid are associated with silent brain infarction. J Neurol Sci 2010;297:6–10. [23] Ishizaka N, Ishizaka Y, Toda E, Nagai R, Yamakado M. Association between serum uric acid, metabolic syndrome, and carotid atherosclerosis in Japanese individuals. Arterioscler Thromb Vasc Biol 2005;25:1038–44. [24] Ishizaka N, Ishizaka Y, Toda E, Hashimoto H, Nagai R, Yamakado M. Higher serum uric acid is associated with increased arterial stiffness in Japanese individuals. Atherosclerosis 2007;192:131–7. [25] 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. [26] Lip GY, Halperin JL. Improving stroke risk stratification in atrial fibrillation. Am J Med 2010;123:484–8. [27] Lip GY. Stroke in atrial fibrillation: epidemiology and thromboprophylaxis. J Thromb Haemost 2011;9(Suppl. 1):344–51. [28] Van Staa TP, Setakis E, Di Tanna GL, Lane DA, Lip GY. A comparison of risk stratification schemes for stroke in 79,884 atrial fibrillation patients in general practice. J Thromb Haemost 2011;9:39–48. [29] Abu-Assi E, Otero-Ravina F, Allut Vidal G, et al. Comparison of the reliability and validity of four contemporary risk stratification schemes to predict thromboembolism in non-anticoagulated patients with atrial fibrillation. Int J Cardiol 2013;166:205–9. [30] Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med 2009;361:1139–51. [31] Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med 2011;365:883–91. [32] Granger CB, Alexander JH, McMurray JJ, et al. Apixaban versus warfarin in patients with atrial fibrillation. N Engl J Med 2011;365:981–92. [33] Hart RG, Pearce LA, Rothbart RM, McAnulty JH, Asinger RW, Halperin JL. Stroke with intermittent atrial fibrillation: incidence and predictors during aspirin therapy. Prevention in Atrial Fibrillation Investigators. Stroke J Am Coll Cardiol 2000;35:183–7. [34] Hohnloser SH, Pajitnev D, Pogue J, et al. Incidence of stroke in paroxysmal versus sustained atrial fibrillation in patients taking oral anticoagulation or combined antiplatelet therapy: an ACTIVE W Substudy. J Am Coll Cardiol 2007;50:2156–61.
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Hyperuricemia and the risk of ischemic stroke in patients with atrial fibrillation — Could it refine clinical risk stratification in AF? Tze-Fan Chao a,b,h,1, Chia-Jen Liu c,d,e,1, Su-Jung Chen f, Kang-Ling Wang a,b,h, Yenn-Jiang Lin a,b,h, Shih-Lin Chang a,b,h, Li-Wei Lo a,b,h, Yu-Feng Hu a,b,h, Ta-Chuan Tuan a,b,h, Tzeng-Ji Chen g, Hsuan-Ming Tsao b,e,h, Shih-Ann Chen a,b,h,⁎ a
Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan c Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan d Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei, Taiwan e Department of Internal Medicine, National Yang-Ming University Hospital, I-Lan, Taiwan f Division of Infectious Diseases, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan g Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan h Cardiovascular Research Center, National Yang-Ming University, Taipei, Taiwan b
a r t i c l e
i n f o
Article history: Received 31 January 2013 Received in revised form 1 August 2013 Accepted 2 November 2013 Available online 13 November 2013 Keywords: Atrial fibrillation Hyperuricemia Stroke CHA2DS2-VASc score
a b s t r a c t Background: Although hyperuricemia has been reported to be a risk factor of stroke, the relationship between hyperuricemia and stroke in patients with atrial fibrillation (AF) remains uncertain. The goal of the present study was to investigate whether hyperuricemia could potentially refine clinical risk stratification in AF. Methods: This study used the “National Health Insurance Research Database” in Taiwan. A total of 7601 AF patients who did not receive antiplatelet agents or oral anticoagulants were identified as the study population. Hyperuricemia was defined as having at least one episode of gout attack necessitating long-term treatment with uric acid-lowering agents. The association between hyperuricemia and ischemic stroke was analyzed. Results: During the follow up of 3.0 ± 2.7 years, 1116 patients (14.7%) experienced ischemic stroke with an annual rate of around 4.9%. Hyperuricemia significantly predicts stroke, with a hazard ratio (HR) of 1.280 after adjusting for CHA2DS2-VASc score and other comorbidities. Among the 376 patients with a CHA2DS2VASc score of 0, hyperuricemia can further stratify them into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020). The adjusted HR of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a score of 3, and became insignificant for patients with a score ≥4. Conclusions: Hyperuricemia was a significant risk factor of stroke which could potentially refine the clinical risk stratification in AF. It deserves a prospective trial to investigate whether it would change the current strategy for stroke preventions using oral anticoagulants. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, and its incidence is projected to rise continuously over the next few decades [1]. It represents an independent and important risk factor of stroke [2,3], and stroke prevention with oral anticoagulants (OACs) is the cornerstone for AF management. Several risk stratification models of different complexities have been introduced to identify AF patients who may benefit from OACs. Recently, a newly developed
⁎ Corresponding author at: Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih-Pai Road, Taipei, Taiwan. Tel.: +886 2 2875 7156; fax: +886 2 2873 5656. E-mail address: [email protected] (S.-A. Chen). 1 Dr. Tze-Fan Chao and Dr Chia-Jen Liu contributed equally to this study. 0167-5273/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijcard.2013.11.011
scoring system, the CHA2DS2-VASc score, which extends the CHADS2 scheme by considering additional stroke risk factors (vascular diseases and female gender), has been recommended as a guide for antithrombotic therapies in AF patients [4–6]. The usefulness of CHA2DS2-VASc score in predicting AF-related thromboembolic events has been validated in several subsequent studies [7–11]. However, the recognition and validation of novel risk factors that could potentially refine the clinical risk stratification in AF patients is still an important issue. Uric acid is a byproduct of purine catabolism, of which the terminal steps are catalyzed by xanthine oxidase. The disease burden of hyperuricemia and gout, which is a painful inflammatory arthritis caused by hyperuricemia, is substantial and continues to rise [12]. Although hyperuricemia with or without gout has been identified as a risk factor of stroke in previous studies [13–17], it remains unclear if it can predict stroke in AF patients. The goal of the present study was to investigate
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
345
Fig. 1. A flowchart of the enrollment of the study patients. A total of 7601 AF patients who did not take anti-platelet agents or OACs between January 1, 2000 and December 31, 2009 were enrolled in this study. During the mean follow-up of 3.0 ± 2.7 years, there were 1116 patients who experienced ischemic stroke. AF = atrial fibrillation, OAC = oral anticoagulants.
the relationship between hyperuricemia and ischemic stroke in AF. We also sought to determine whether hyperuricemia has a potential role in predicting stroke in addition to the CHA2DS2-VASc score. 2. Methods
and chi-square testing for nominal variables. The stroke-free survival curve was plotted using the Kaplan–Meier method with statistical significance examined by the log-rank test. The risk of ischemic stroke was assessed using the Cox regression analysis. All statistical significances were set at p b 0.05 and all statistical analyses were carried out by SPSS 17.0 (SPSS Inc., USA). This manuscript was written following STROBE guidelines for the reporting of observational studies [18].
2.1. Database This study used the “National Health Insurance Research Database (NHIRD)” released by the Taiwan National Health Research Institutes (NHRI). The National Health Insurance (NHI) system is a mandatory universal health insurance program that offers comprehensive medical care coverage to all Taiwanese residents. The NHIRD is a cohort dataset that contains all medical claim data for 1,000,000 beneficiaries, who were randomly sampled from the 25.68 million enrollees under the NHI program. These random samples have been confirmed by the NHRI to be representative of the Taiwanese population. In this cohort dataset, the patients' original identification numbers were encrypted to protect their privacy, but the encrypting procedure was consistent, so that linking claims belonging to the same patient was feasible within the NHI database and could be followed continuously. The database has a large sample size and provides a good opportunity to study the risk of stroke among AF patients with or without hyperuricemia. 2.2. Study population From January 1, 2000 to December 31, 2009, a total of 11,268 patients 18 years of age or older with newly diagnosed AF were identified from the NHIRD. Patients who received antithrombotic therapy with either antiplatelet agents or OACs were excluded, resulting in a total of 7601 patients who were selected as the study population. For each patient, the CHA2DS2-VASc score was calculated based on a point system in which 2 points were assigned for a history of stroke or transient ischemic attack (TIA), or age ≥75 years; and 1 point each was assigned for patients aged 65–74 years or those who had a history of hypertension, diabetes, recent cardiac failure, vascular disease (myocardial infarction, complex aortic plaque, or peripheral artery disease), and were female [4]. Hyperuricemia was defined as having at least one episode of gout attack necessitating long-term treatment of uric acid-lowering agents. The primary endpoint was defined as the occurrence of ischemic stroke confirmed by imaging studies of the brain, including a computed tomography scan or magnetic resonance imaging. There were 1116 patients who experienced ischemic stroke during the follow-up. A flowchart of the enrollment of the study population is shown in Fig. 1. 2.3. Statistical analysis The data are presented as the mean value and standard deviation for normally distributed continuous variables and proportions for categorical variables. The differences between continuous values were assessed using an unpaired 2-tailed t test for normally distributed continuous variables, Mann–Whitney rank-sum test for skewed variables,
Table 1 Baseline characteristics of AF patients with and without strokes. Variables
With strokes (n = 1116)
Without strokes (n = 6485)
p value
Age, years Age ≥ 65 years old Age ≥ 75 years old Gender (male)
73.4 ± 10.7 81.8% 49.7% 54.0%
69.4 ± 15.8 68.9% 45.4% 54.7%
b0.001 b0.001 0.007 0.667
b0.001 0.004 0.053 b0.001 b0.001 b0.001
Medical history (components of CHA2DS2-VASc score) Hypertension Diabetes mellitus Congestive heart failure Previous stroke/TIA Previous vascular disease CHA2DS2-VASc score, median (inter-quartile range) Score 0 Score 1 Score 2 Score 3 Score 4 Score 5 Score 6 Score 7 Score 8 Score 9
79.3% 38.3% 45.7% 49.5% 12.5% 5 (4–6)
69.2% 33.8% 42.6% 25.9% 8.5% 4 (2–6)
0.7% 3.9% 7.6% 10.1% 16.8% 19.3% 16.9% 13.2% 8.1% 3.5%
5.7% 9.2% 11.5% 12.4% 15.5% 15.6% 13.0% 9.3% 5.4% 2.5%
Other comorbidities Dyslipidemia Chronic renal disease Chronic pulmonary disease Autoimmune diseases Hyperuricemia
32.5% 10.6% 46.9% 9.2% 30.6%
32.9% 11.1% 48.2% 9.8% 26.2%
AF = atrial fibrillation; TIA = transient ischemic attack.
0.826 0.602 0.419 0.568 0.002
346
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
Table 2 The risk of ischemic stroke in patients with and without hyperuricemia. Variable
Ischemic stroke Yes No Crude hazard ratio (95% CI) Adjusted hazard ratio (95% CI)b a b
All (n = 7601)
Hyperuricemia
n (%) 1116 (14.7%) 6485 (85.3%)
Yes (n = 2039)
No (n = 5562)
n (%) 342 (16.8%)a 1697 (83.2%) 1.436 (1.264–1.632); p value b 0.001 1.280 (1.121–1.462); p value b 0.001
n (%) 774 (13.9%) 4788 (86.1%)
p value = 0.002 in comparison with patients without hyperuricemia. Adjustment for the CHA2DS2-VASc score and other comorbidities listed in Table 1, including dyslipidemia, chronic renal disease, chronic pulmonary disease and autoimmune diseases.
3. Results 3.1. Patient characteristics The mean age of the study population was 70.0 ± 15.3 years and males accounted for 54.6% of the patients. The median value (interquartile range) of the CHA2DS2-VASc score was 4 (3–6), and 86.6% of patients had a score ≥ 2. The mean follow-up duration was 3.0 ± 2.7 years, and there were 1116 patients (14.7%) who experienced ischemic stroke with an annual stroke rate of around 4.9%. The baseline characteristics of patients with and without stroke are shown in Table 1. Patients who experienced events were older and had a higher CHA2DS2-VASc score than those who did not. In regard to the comorbidities other than the components of the CHA2DS2-VASc scheme, hyperuricemia was more prevalent in patients with ischemic stroke. 3.2. Hyperuricemia and the risk of stroke The rate of ischemic stroke was higher in patients with hyperuricemia than those without it (16.8% versus 13.9%, p value = 0.002) (Table 2). Hyperuricemia remained as a significant risk factor of ischemic events, with an adjusted hazard ratio (HR) of 1.280 (95% confidence interval [CI] = 1.121–1.462; p b 0.001) after adjusting for the CHA2DS2-VASc score and other comorbidities, including dyslipidemia, chronic renal disease, chronic pulmonary disease, and autoimmune diseases which were more prevalent among patients with hyperuricemia (Table 2). The associations between hyperuricemia and ischemic stroke in different regression models adjusted for the CHA2DS2-VASc score and its components were shown in Table 3. Fig. 2 shows the Kaplan–Meier curve of stroke-free survival between patients with and without hyperuricemia demonstrating that AF patients with hyperuricemia were associated with a higher stroke rate during the follow-up period. 3.3. Hyperuricemia and the risk of stroke stratified by CHA2DS2-VASc scores In the subgroup analysis based on CHA2DS2-VASc scores, the rate of ischemic stroke was consistently higher in patients with hyperuricemia among groups with a CHA2DS2-VASc score of 0 (Fig. 3A) and ≥ 1 (Fig. 3B). Among the 376 patients with a CHA2DS2VASc score of 0, hyperuricemia can further stratify them into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020), as shown in Fig. 4. Fig. 5 shows that
the adjusted HR of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a CHA2DS2-VASc score of 3, and became insignificant for patients with a CHA2DS2-VASc score ≥4. 4. Discussion 4.1. Main findings This study enrolled 7601 AF subjects who did not receive medications for thromboprophylaxis and compared the risk of ischemic stroke in patients with hyperuricemia to that of patients without it. The main findings were as follows: (1) hyperuricemia was a significant risk factor of stroke for AF patients. (2) In patients with a CHA2DS2-VASc score of 0, hyperuricemia may be helpful for identifying patients at risk of stroke. (3) Hyperuricemia did not significantly predict ischemic stroke in patients with a CHA2DS2-VASc score ≥4. 4.2. Hyperuricemia and the risk of stroke in AF patients Hyperuricemia has been reported to be associated with endothelial dysfunction, free radical generation, abnormally high levels of systemic inflammatory markers (such as C-reactive protein and interleukin-6), and insulin resistance, which may predispose patients to the risk of cardiovascular events [19–21]. Heo and Lee previously investigated the relationship between serum levels of uric acid and silent brain infarction detected by brain magnetic resonance imaging in a total of 1577 patients, and found that hyperuricemia was an independent risk factor [22]. In addition, several cohort studies have recognized hyperuricemia as an independent risk factor for stroke (Table 4) [13–16], including studies performed by Lehto et al. (HR = 1.74, 95% CI = 1.16–2.61) [13], Chien et al. (HR = 1.23 for males and 1.36 for females) [14], Bos et al. (HR = 1.77, 95% CI = 1.10–2.83) [15], and Hozawa et al. (HR = 1.49, 95% CI = 1.00–2.23) [16]. Although these previous studies enrolled a large number of patients, ranging from 1017 to 13,413 subjects, the percentages of AF patients in the study populations were not reported and seemed to be low. Since these studies did not focus on AF, it remained unclear whether hyperuricemia is a risk factor of ischemic stroke for AF patients. In this nationwide cohort study, we found that hyperuricemia was a significant predictor of ischemic stroke in AF, even after adjusting for the
Table 3 Association of hyperuricemia and ischemic stroke in Cox regression models. Models
Hazard ratio
95% confidence interval
p value
Model 1: adjusted for age and gender Model 2: adjusted for age, gender and hypertension Model 3: adjusted for age, gender and diabetes mellitus Model 4: adjusted for age, gender and congestive heart failure Model 5: adjusted for age, gender and previous stroke/TIA Model 6: adjusted for age, gender and previous vascular disease Model 7: adjusted for CHA2DS2-VASc score
1.325 1.248 1.272 1.309 1.255 1.332 1.194
1.165–1.506 1.096–1.422 1.117–1.449 1.150–1.490 1.103–1.427 1.171–1.515 1.049–1.358
b0.001 0.001 b0.001 b0.001 0.001 b0.001 0.007
TIA = transient ischemic attack.
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
347
CHA2DS2-VASc score ≥ 4, hyperuricemia no longer remained as an important factor associated with ischemic stroke. These observations suggest that hyperuricemia could be regarded as a “red flag” for stroke in patients without clinically apparent comorbidities and may be associated with a pre-diseased complex, including insulin resistance, prediabetes, obesity, systemic inflammation, arterial stiffness and carotid atherosclerosis [19,20,23,24]. These conditions would increase the risk of stroke, but were not included or represented by the CHA2DS2-VASc scheme. Alternatively, hyperuricemia could be just a bystander and plays a less important role in the development of stroke in patients with multiple cardiovascular risk factors who have a high CHA2DS2-VASc score. 4.3. How could hyperuricemia refine the risk stratification in AF patients?
Fig. 2. The risk of ischemic stroke in patients with and without hyperuricemia. A Kaplan– Meier survival analysis showing that AF patients with hyperuricemia are associated with a higher stroke rate compared to those without hyperuricemia (16.8% versus 13.9%, p = 0.002). AF = atrial fibrillation.
CHA2DS2-VASc score. Interestingly, the HRs of hyperuricemia in predicting stroke were attenuated after censoring for more risk factors represented by a high CHA2DS2-VASc score. In patients with a
Fig. 3. Stroke-free survival curves for patients with and without hyperuricemia in groups with different CHA2DS2-VASc scores. In the subgroup analysis based on the CHA2DS2-VASc score, the rate of ischemic stroke was consistently higher in patients with hyperuricemia among groups with a CHA2DS2-VASc score of 0 (A) and ≥1 (B).
The CHADS2 score is the most commonly used scheme in stroke risk stratification for AF [25], despite the fact that it classifies a large proportion of patients as having an “intermediate risk” [26]. The new scoring system, the CHA2DS2-VASc score, has been proposed to complement the CHADS2 score and is recommended as a guide for the use of OACs in the current European Society of Cardiology (ESC) guidelines [4–6]. The CHA2DS2-VASc score has been validated in multiple patient cohorts, and accumulating evidence indicated that it may be better than the CHADS2 score at identifying “truly low-risk” patients with AF [9,10,27–29]. Although it was found that some patients with a low CHA2DS2-VASc score still experienced ischemic stroke, warfarin was not suggested for patients with a score of 0 after taking the risk/benefit balance into consideration. Recently, several new OACs, including dabigatran, rivaroxaban, and apixaban, were proven to be as effective as warfarin in preventing stroke with less events of intracranial hemorrhage, which is the most serious complication of OAC [30–32]. Therefore, if we could further identify patients at risk of stroke among those with a CHA2DS2-VASc score of 0, prescriptions of new OACs may be beneficial and should be considered for them. In the present study, we found that patients with a CHA2DS2-VASc score of 0 and who were diagnosed with hyperuricemia had an annual stroke rate of approximately 2.37%, which was higher than the rates of life threatening (1.22%/year for dabigatran 110 mg; 1.45%/year for dabigatran 150 mg) and intracranial bleeding (0.23%/year for dabigatran 110 mg; 0.30%/year for dabigatran 150 mg) for dabigatran use [30]. Based on these results, a prospective and randomized trial is necessary to investigate whether these patients will benefit from new OAC therapies.
Fig. 4. A flowchart demonstrating the stroke rates according to the CHA2DS2-VASc scores and hyperuricemia. Hyperuricemia can further stratify patients with a CHA2DS2-VASc score of 0 into 2 groups with different stroke rates (7.1% versus 1.3%, p = 0.020).
348
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349
Fig. 5. Hyperuricemia and the risk of stroke in patients with different CHA2DS2-VASc scores. The hazard ratio of hyperuricemia in predicting ischemic stroke diminished from 7.491 for patients with a CHA2DS2-VASc score of 0 to 1.659 for those with a CHA2DS2-VASc score of 3, and became insignificant for patients with a CHA2DS2-VASc score ≥4. CI = confidence interval, HR = hazard ratio. *Adjustment for other comorbidities listed in Table 1, including dyslipidemia, chronic renal disease, chronic pulmonary disease and autoimmune diseases.
4.4. Study limitations There were several limitations in the present study. First, the absolute values of uric acid were not available in the nationwide dataset. However, the levels of uric acid fluctuate significantly and are not constant, which make it difficult to determine the levels appropriately. In the present study, patients were regarded as having hyperuricemia only when they suffered at least one episode of gout attack that necessitated long-term treatment of uric acid-lowering agents. Therefore, we focused on symptomatic hyperuricemia, and the results based on this definition may be more clinically relevant. Second, information about the types of AF (paroxysmal or non-paroxysmal) was lacking. Nevertheless, since the risk of stroke did not differ between patients with paroxysmal or non-paroxysmal AF [33,34], the type of AF may not confound the findings of this study. Third, the number of events in patients with a CHA2DS2-VASc score of 0 was small, and the usefulness of hyperuricemia for further risk stratifications among these low-risk patients may not be conclusive based on the results presented here. Lastly, we were not able to clearly confirm the cause of ischemic stroke since it can be due to thrombosis of the cerebral artery or AF-related thromboembolism. However, it was also a common limitation in previous randomized trials [30–32].
Hyperuricemia could potentially refine the clinical risk stratification for AF patients, and thus deserves a further prospective and largescale clinical trial to investigate whether it would change the current strategy for the use of OACs in stroke prevention. Acknowledgments This work was supported in part by grants from the National Science Council (NSC98-2410-H-010-003-MY2), and the Taipei Veterans General Hospital (V99C1-140, V99A-153, V100D-002-3, and V101D-001-2). References
5. Conclusion In this AF cohort study, hyperuricemia was a significant risk factor of ischemic stroke after adjusting for the CHA2DS2-VASc score.
[1] Potpara TS, Lip GY. Lone atrial fibrillation: what is known and what is to come. Int J Clin Pract 2011;65:446–57. [2] Chugh SS, Blackshear JL, Shen WK, Hammill SC, Gersh BJ. Epidemiology and natural history of atrial fibrillation: clinical implications. J Am Coll Cardiol 2001;37:371–8. [3] Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke 1991;22:983–8. [4] Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation. Chest 2010;137:263–72. [5] Camm AJ, Kirchhof P, Lip GY, 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. [6] Camm AJ, Lip GY, De Caterina R, et al. 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC guidelines for the management of atrial fibrillation developed with the special contribution of the European Heart Rhythm Association. Eur Heart J 2012;33:2719–47.
Table 4 Summary of the cohort studies showing hyperuricemia as a risk factor of stroke. Author (year) Lehto et al. (1998)13 Chien et al. (2005)14 Bos et al. (2006)15 Hozawa et al. (2006)16
Patient number
Age
Outcome
Risk of outcome HR (95% CI)
p value
% AF in the study group
1017 3602
45–64 N35
Any stroke except SAH Any type of stroke
63–76 45–64
Ischemic stroke Ischemic stroke
0.008 0.054 0.021 N.R. 0.02
N.R. N.R.
4385 13,413
1.74 (1.16–2.61)a Male: 1.23 (1.00–1.53)b Female: 1.36 (1.05–1.75)b 1.77 (1.10–2.83)c 1.49 (1.00–2.23)d
N.R. N.R.
AF = atrial fibrillation; CI = confidence interval; HR = hazard ratio; N.R. = not reported; SAH = subarachnoid hemorrhage. a Adjusted for age, gender, smoking, cholesterol and hypertension. b Adjusted for age. Uric acid was regarded as a continuous variable. c Age- and sex-adjusted HR for the highest versus the lowest quintile of uric acid for ischemic stroke. d Adjusted HR for the highest versus the lowest quartile of uric acid for ischemic stroke. The regression model included age, sex, race, education, systolic blood pressure, diabetes mellitus, anti-hypertensive medication, cigarette smoking status, ethanol intake, serum albumin, von Willebrand factor, body mass index, waist-to-hip ratio, and low HDL cholesterol.
T.-F. Chao et al. / International Journal of Cardiology 170 (2014) 344–349 [7] Olesen JB, Lip GY, Hansen ML, et al. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study. BMJ 2011;342:d124. [8] Chao TF, Lin YJ, Tsao HM, et al. CHADS(2) and CHA(2)DS(2)-VASc scores in the prediction of clinical outcomes in patients with atrial fibrillation after catheter ablation. J Am Coll Cardiol 2011;58:2380–5. [9] Potpara TS, Polovina MM, Licina MM, Marinkovic JM, Prostran MS, Lip GY. Reliable identification of “truly low” thromboembolic risk in patients initially diagnosed with “lone” atrial fibrillation: the Belgrade Atrial Fibrillation Study. Circ Arrhythm Electrophysiol 2012;5:319–26. [10] Olesen JB, Torp-Pedersen C, Hansen ML, Lip GY. The value of the CHA 2DS2-VASc score for refining stroke risk stratification in patients with atrial fibrillation with a CHADS 2 score 0–1: a nationwide cohort study. Thromb Haemost 2012;107:1172–9. [11] Chao TF, Liu CJ, Chen SJ, et al. Atrial fibrillation and the risk of ischemic stroke: does it still matter in patients with a CHA2DS2-VASc score of 0 or 1? Stroke 2012;43:2551–5. [12] Zhu Y, Pandya BJ, Choi HK. Prevalence of gout and hyperuricemia in the US general population: the National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 2011;63:3136–41. [13] Lehto S, Niskanen L, Ronnemaa T, Laakso M. Serum uric acid is a strong predictor of stroke in patients with non-insulin-dependent diabetes mellitus. Stroke 1998;29:635–9. [14] Chien KL, Hsu HC, Sung FC, Su TC, Chen MF, Lee YT. Hyperuricemia as a risk factor on cardiovascular events in Taiwan: the Chin-Shan Community Cardiovascular Cohort Study. Atherosclerosis 2005;183:147–55. [15] Bos MJ, Koudstaal PJ, Hofman A, Witteman JC, Breteler MM. Uric acid is a risk factor for myocardial infarction and stroke: the Rotterdam Study. Stroke 2006;37:1503–7. [16] Hozawa A, Folsom AR, Ibrahim H, Javier Nieto F, Rosamond WD, Shahar E. Serum uric acid and risk of ischemic stroke: the ARIC Study. Atherosclerosis 2006;187:401–7. [17] Kim SY, Guevara JP, Kim KM, Choi HK, Heitjan DF, Albert DA. Hyperuricemia and risk of stroke: a systematic review and meta-analysis. Arthritis Rheum 2009;61:885–92. [18] von Elm E, Altman DG, Egger M, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007;335:806–8. [19] Ruggiero C, Cherubini A, Ble A, et al. Uric acid and inflammatory markers. Eur Heart J 2006;27:1174–81.
349
[20] Krishnan E, Pandya BJ, Chung L, Hariri A, Dabbous O. Hyperuricemia in young adults and risk of insulin resistance, prediabetes, and diabetes: a 15-year follow-up study. Am J Epidemiol 2012;176:108–16. [21] Papezikova I, Pekarova M, Kolarova H, et al. Uric acid modulates vascular endothelial function through the down regulation of nitric oxide production. Free Radic Res 2013;47:82–8. [22] Heo SH, Lee SH. High levels of serum uric acid are associated with silent brain infarction. J Neurol Sci 2010;297:6–10. [23] Ishizaka N, Ishizaka Y, Toda E, Nagai R, Yamakado M. Association between serum uric acid, metabolic syndrome, and carotid atherosclerosis in Japanese individuals. Arterioscler Thromb Vasc Biol 2005;25:1038–44. [24] Ishizaka N, Ishizaka Y, Toda E, Hashimoto H, Nagai R, Yamakado M. Higher serum uric acid is associated with increased arterial stiffness in Japanese individuals. Atherosclerosis 2007;192:131–7. [25] 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. [26] Lip GY, Halperin JL. Improving stroke risk stratification in atrial fibrillation. Am J Med 2010;123:484–8. [27] Lip GY. Stroke in atrial fibrillation: epidemiology and thromboprophylaxis. J Thromb Haemost 2011;9(Suppl. 1):344–51. [28] Van Staa TP, Setakis E, Di Tanna GL, Lane DA, Lip GY. A comparison of risk stratification schemes for stroke in 79,884 atrial fibrillation patients in general practice. J Thromb Haemost 2011;9:39–48. [29] Abu-Assi E, Otero-Ravina F, Allut Vidal G, et al. Comparison of the reliability and validity of four contemporary risk stratification schemes to predict thromboembolism in non-anticoagulated patients with atrial fibrillation. Int J Cardiol 2013;166:205–9. [30] Connolly SJ, Ezekowitz MD, Yusuf S, et al. Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med 2009;361:1139–51. [31] Patel MR, Mahaffey KW, Garg J, et al. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med 2011;365:883–91. [32] Granger CB, Alexander JH, McMurray JJ, et al. Apixaban versus warfarin in patients with atrial fibrillation. N Engl J Med 2011;365:981–92. [33] Hart RG, Pearce LA, Rothbart RM, McAnulty JH, Asinger RW, Halperin JL. Stroke with intermittent atrial fibrillation: incidence and predictors during aspirin therapy. Prevention in Atrial Fibrillation Investigators. Stroke J Am Coll Cardiol 2000;35:183–7. [34] Hohnloser SH, Pajitnev D, Pogue J, et al. Incidence of stroke in paroxysmal versus sustained atrial fibrillation in patients taking oral anticoagulation or combined antiplatelet therapy: an ACTIVE W Substudy. J Am Coll Cardiol 2007;50:2156–61.
