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Hyperuricemia and Risk of Stroke: A Systematic Review and Meta-analysis Seo Young Kim, MD 1,2 , James P Guevara, MD, MPH 2,3 , Kyoung Mi Kim, MD 4 , Hyon K Choi, MD, DrPH 5 , Daniel F. Heitjan, PhD 2,6 , and Daniel A Albert, MD 7 1 Division of Rheumatology, Department of Medicine, University of Pennsylvania 2 Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania 3 Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia 4 Pusan National University, Pusan, South Korea 5 Division of Rheumatology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada 6 Department of Biostatistics and Epidemiology, University of Pennsylvania 7 Division of Rheumatology, Dartmouth Hitchcock Medical Center, Lebanon, NH Abstract BACKGROUND—Hyperuricemia is hypothesized to be a risk factor for stroke and other cardiovascular disease, but to date results from observational studies are conflicting. METHODS—We conducted a systematic review and meta-analysis to assess the association between hyperuricemia and risk of stroke incidence and mortality. Studies were identified by searching major electronic databases using the Medical Subject Headings and keywords without restriction in languages. Only prospective cohort studies were included if they had data on stroke incidences or mortalities related to serum uric acid levels in adults. Pooled risk ratios (RRs) for the association of stroke incidence and mortality with serum uric acid levels were calculated. RESULTS—A total of 16 studies including 238,449 adults were eligible and abstracted. Hyperuricemia was associated with a significantly higher risk of both stroke incidence [N=6 studies, RR 1.41, 95% confidence interval (CI): 1.05–1.76] and mortality [N=6 studies, RR 1.36, 95% CI: 1.03–1.69] in our meta-analyses of unadjusted study estimates. Subgroup analyses of studies adjusting for known risk factors such as age, hypertension, diabetes, and cholesterol still showed that hyperuricemia was significantly associated with both stroke incidence [N=4 studies, RR 1.47, 95% CI: 1.19–1.76] and mortality [N=6 studies, RR 1.26, 95% CI: 1.12–1.39]. The pooled estimate of multivariate RRs did not differ much by gender. CONCLUSION—Our study suggests that hyperuricemia may modestly increase the risks of both stroke incidence and mortality. Future research is needed to determine whether lowering uric acid level has any beneficial effects on stroke. Corresponding author and Reprint requests: Seo Young Kim, M.D., Division of Rheumatology, University of Pennsylvania, 504 Maloney, 3600 Spruce Street, Philadelphia PA 19104, Tel) 215-662-2350, Fax) 215-615-4312, E-mail: [email protected]. Financial supports or conflicts disclosure S Kim - NIH T32 (AR07442) Training Program in Rheumatic Disease HK Choi - Holds the Mary Pack Arthritis Society of Canada Chair in Rheumatology, served on the advisory board for TAP and Savient Pharmaceuticals JP Guevara and DA Albert – None NIH Public Access Author Manuscript Arthritis Rheum. Author manuscript; available in PMC 2010 July 15. Published in final edited form as: Arthritis Rheum. 2009 July 15; 61(7): 885–892. doi:10.1002/art.24612. NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript

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Hyperuricemia and Risk of Stroke: A Systematic Review andMeta-analysis

Seo Young Kim, MD1,2, James P Guevara, MD, MPH2,3, Kyoung Mi Kim, MD4, Hyon K Choi,MD, DrPH5, Daniel F. Heitjan, PhD2,6, and Daniel A Albert, MD7

1Division of Rheumatology, Department of Medicine, University of Pennsylvania2Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania3Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia4Pusan National University, Pusan, South Korea5Division of Rheumatology, Department of Medicine, University of British Columbia, Vancouver,BC, Canada6Department of Biostatistics and Epidemiology, University of Pennsylvania7Division of Rheumatology, Dartmouth Hitchcock Medical Center, Lebanon, NH

AbstractBACKGROUND—Hyperuricemia is hypothesized to be a risk factor for stroke and othercardiovascular disease, but to date results from observational studies are conflicting.

METHODS—We conducted a systematic review and meta-analysis to assess the associationbetween hyperuricemia and risk of stroke incidence and mortality. Studies were identified bysearching major electronic databases using the Medical Subject Headings and keywords withoutrestriction in languages. Only prospective cohort studies were included if they had data on strokeincidences or mortalities related to serum uric acid levels in adults. Pooled risk ratios (RRs) for theassociation of stroke incidence and mortality with serum uric acid levels were calculated.

RESULTS—A total of 16 studies including 238,449 adults were eligible and abstracted.Hyperuricemia was associated with a significantly higher risk of both stroke incidence [N=6studies, RR 1.41, 95% confidence interval (CI): 1.05–1.76] and mortality [N=6 studies, RR 1.36,95% CI: 1.03–1.69] in our meta-analyses of unadjusted study estimates. Subgroup analyses ofstudies adjusting for known risk factors such as age, hypertension, diabetes, and cholesterol stillshowed that hyperuricemia was significantly associated with both stroke incidence [N=4 studies,RR 1.47, 95% CI: 1.19–1.76] and mortality [N=6 studies, RR 1.26, 95% CI: 1.12–1.39]. Thepooled estimate of multivariate RRs did not differ much by gender.

CONCLUSION—Our study suggests that hyperuricemia may modestly increase the risks of bothstroke incidence and mortality. Future research is needed to determine whether lowering uric acidlevel has any beneficial effects on stroke.

Corresponding author and Reprint requests: Seo Young Kim, M.D., Division of Rheumatology, University of Pennsylvania, 504Maloney, 3600 Spruce Street, Philadelphia PA 19104, Tel) 215-662-2350, Fax) 215-615-4312, E-mail: [email protected] supports or conflicts disclosureS Kim - NIH T32 (AR07442) Training Program in Rheumatic DiseaseHK Choi - Holds the Mary Pack Arthritis Society of Canada Chair in Rheumatology, served on the advisory board for TAP andSavient PharmaceuticalsJP Guevara and DA Albert – None

NIH Public AccessAuthor ManuscriptArthritis Rheum. Author manuscript; available in PMC 2010 July 15.

Published in final edited form as:Arthritis Rheum. 2009 July 15; 61(7): 885–892. doi:10.1002/art.24612.

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Keywordshyperuricemia; stroke; systematic review; meta-analysis

INTRODUCTIONUric acid is the end-product of purine metabolism in humans. There is no universallyaccepted definition for hyperuricemia, but it is usually defined as serum urate concentrationin excess of 6.8 mg/dL, which is the limit of urate solubility in serum 1, 2. Currently, nourate-lowering therapy is indicated in asymptomatic hyperuricemia 3. High serum uric acidlevel with or without gout is associated with cardiovascular diseases such as hypertension,coronary heart disease, peripheral vascular disease, and stroke 4–10. However, the role ofhigh serum uric acid level as an independent risk factor for cardiovascular disease includingstroke has been controversial 11–16. Several patho-physiological mechanisms throughendothelial dysfunction, oxidative metabolism, platelet adhesiveness and aggregation,related to hyperuricemia in cardiovascular disease have been suggested 17–19. According toa recent report 20, about 780,000 Americans experience a new or recurrent stroke each year,on average, one stroke every 40 seconds. Preliminary data from 2005 indicate that strokeaccounted for about 1 of every 17 deaths in the United States 20. If asymptomatichyperuricemia has a deleterious effect on serious morbidity and mortality related to stroke,hyperuricemia may become a new target for more comprehensive risk factor management inthe primary prevention of stroke. Accordingly, we conducted a meta-analysis of prospectivecohort studies to determine the association between hyperuricemia and the risk of stroke.

METHODSData Sources

We searched three major electronic databases — MEDLINE (1950-July 2008), EMBASE(1980-July 2008), and the Cochrane library — for studies of the association between serumuric acid levels and stroke incidence and/or mortality. We also searched bibliographies ofidentified reports and review articles for additional references. Our search strategy isdescribed in Figure 1.

Study EligibilityTo be eligible for inclusion, we only considered (1) prospective cohort studies of adultpatients, (2) longer than one year of follow-up, (3) with sample size of at least fifty subjects,and (4) inception cohort free of stroke. We imposed no geographic or language restrictions.Studies reporting interventional and secondary prevention trials were excluded.

Selection of StudiesTwo authors (S. Kim and K. Kim) independently screened each of the potential titles,abstracts, and/or full-texts to determine inclusion. Areas of disagreement or uncertainty wereresolved by consensus. When multiple articles were published from a single study, weselected the report that contained the most complete and relevant data on the associationbetween hyperuricemia and stroke. The electronic search retrieved 566 potentially relevantstudies. Non-electronic search identified 3 additional studies. On initial screening, 504 wereexcluded based on title. Of the 65 screened abstracts, 22 studies were retrieved for detailedevaluation. Of those, two studies were based on the same patient population, so they wereconsidered as one study in the meta-analysis 21, 22. One study was excluded because itreported insufficient data on stroke outcome 23. Four studies that reported data on carotid

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intima-media thickness only were excluded 24–27. Eventually 16 studies were included inthis meta-analysis (Figure 2).

Data Abstraction and Quality AssessmentAll data were independently abstracted in duplicate by two authors (S. Kim and K. Kim)using a data abstraction form. Discrepancies were resolved by consensus. When necessary,the original authors were contacted for additional information. Data on the studycharacteristics such as author name, year of publication, language, sample size, mean age,uric acid level and number of outcome were collected. The Newcastle–Ottawa Scale wasused to assess the quality of studies 28 (Table 1). A quality score was calculated on the basisof three major components: selection of the study groups (0–4 points), quality of theadjustment for confounding (0–2 points) and ascertainment of the outcome of interest in thecohorts (0–3 points). A higher score represents better methodological quality. Adjustmentfor known stroke risk factors, duration of follow-up of at least 5 years, and adequate follow-up rate were criteria of higher quality.

Statistical AnalysisSome studies included in our meta-analysis used the International system (SI) of units (µmolper liter) to report levels of serum uric acid. We therefore converted those to theconventional units (milligram per deciliter), using a conversion rate of 16.81 (1 mg/dL =59.48 µmol/L) 29. Pooled estimates of risk ratios (RRs) were calculated using theDerSimonian and Laird random effects model 30, 31 for stroke incidence and mortality.This statistical technique weighs individual studies by sample size and variance (bothwithin- and between-study variance) and yields a pooled point estimate and a 95%confidence interval. The DerSimonian and Laird technique was considered an appropriatepooling technique because of the relative heterogeneity of the source population in eachstudy. We also evaluated the presence of heterogeneity across trials by using the I2 statistic,which quantifies the percentage of variability that can be attributed to between-studydifferences 32. To assess the potential for publication bias, we performed the Begg’s testand the Egger’s test and constructed funnel plots to visualize a possible asymmetry 33. Allthe statistical analyses were done in Stata 10 (Stata Corp, College Station, TX). We followedthe Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines 34 in thereport of this meta-analysis.

RESULTSStudy Characteristics

Sixteen prospective cohort studies representing data from 238,449 participants wereincluded in the meta-analysis. The characteristics of the studies and of their participants arepresented in Table 2. Of the 16 trials, 2 were conducted primarily in the United Statesalthough the study by Kagan et al 35 was based on a Hawaiian Japanese cohort. Eightstudies were done in Asian countries and six studies were from European countries. Thenumber of participants ranged from 153 in a study by Tofuku et al 36 to 83,683 in theVorarlberg Health Monitoring and Promotion Program cohort study by Strasak et al 37.Nine studies 14, 15, 21, 22, 36, 38–42 included both men and women. Four studies used alower cut-off value to define hyperuricemia for women compared to men 39, 40, 42, 43. Sixstudies 35, 37, 44–47 included only men, and one study 43 only women. Seven studies 35,37, 39, 41, 43–45 reported gender-specific outcome for ischemic stroke. Six studies 15, 35,37, 39, 41, 43 provided only adjusted risk estimates.

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Hyperuricemia and Stroke IncidenceThe pooled estimate of unadjusted RRs for stroke based on six studies 14, 36, 38–40, 46 was1.41 (95% CI: 1.05–1.76) among subjects with hyperuricemia, compared with those withnormouricemia. The heterogeneity test was not significant (I2 =23.8%, p=0.25). The pooledmultivariate RR based on four studies14, 39–41 fully adjusting for known risk factors ofstroke was 1.47 (95% CI: 1.19–1.76). The heterogeneity test for this analysis was notsignificant (I2=0.0%, p=0.96).

The pooled estimate of unadjusted RRs among men based on two studies 40, 46 was 1.82,(95% CI: 0.84–2.80), whereas only one study reported unadjusted RR of 2.55 among women(95% CI: 0.84–4.27)40. The pooled estimate of multivariate RRs based on three studies39–41 was 1.42 (95% CI: 1.03–1.80) among women and 1.42 among men (95% CI: 0.94–1.90).The forest plot of multivariate RRs and 95% CIs for stroke incidence and hyperuricemia areshown in Figure 3 (top).

Hyperuricemia and Stroke MortalityThe pooled estimate of unadjusted RR based on 6 studies 21, 22, 36, 42, 44, 45, 47 was 1.36(95% CI: 1.03–1.69) for patients with hyperuricemia, compared with those withnormouricemia. There was no statistically significant heterogeneity among the studies (I2=0.0%, p=0.62). The pooled multivariate RR based on six studies 15, 37, 42–44 fullyadjusting for known risk factors of stroke was 1.26 (95% CI: 1.12–1.39) with a non-significant heterogeneity test (I2= 0.0%, p=0.50).

The pooled estimate of unadjusted RRs among men based on 5 studies 21, 42, 44, 45, 47was 1.34 (95% CI: 1.01–1.67). The pooled unadjusted RR among women based on only twostudies 21, 42 was 4.75, but it was not statistically significant (95% CI: 0.53–8.98).

The pooled multivariate RRs were significantly higher for both men [N=4 studies 37, 42, 44,45, RR 1.20, 95% CI: 1.05–1.35] and women [N=2 studies 42, 43, RR 1.35, 95% CI: 1.04–1.66], compared to those with normouricemia. The forest plot of multivariate RRs and 95%CIs for stroke mortality and hyperuricemia are shown in Figure 3 (bottom).

Publication Bias AssessmentThe funnel plots for both stroke incidence and mortality were visually examined (Figure 4).There was no statistical evidence of publication bias among studies for stroke incidence ormortality by using Egger’s (p=0.80; 0.25 respectively) and Begg’s (p=0.70; 0.48respectively) tests.

Sensitivity AnalysesMeta-regression was performed to further investigate the effect of three study-levelcharacteristics (year of publication, race, and gender) on the risk of stroke. None of theregression coefficients was statistically significant (Appendix 1). A linear regression model(Appendix 2) showed that studies that adjusted for more confounding variables had lowerrisk estimates than studies that adjusted for fewer or no potentially confounding variables.For both stroke outcomes, the risk estimates remained above 1 even after adjusting for morethan ten potential risk factors although the confidence intervals crossed 1.

DISCUSSIONOur systematic review and meta-analysis of 16 prospective cohort studies finds that theelevated serum uric acid level in adults is associated with a modest but statisticallysignificant increased risk of stroke incidence and mortality.

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There has been considerable debate whether uric acid is neuro-protective as an antioxidantor neuro-toxic as a pro-oxidant 12, 48, 49. A pathogenetic role for uric acid incardiovascular disease also remains to be elucidated, although recent experimental studieshave shown that hyperuricemia is associated with endothelial dysfunction, local oxidantgeneration, elevated circulating levels of systemic inflammatory mediators such asmonocyte chemoattractant protein-1, NF-κB, interleukin-1β, interleukin-6, and tumornecrosis factor-α, and vascular smooth muscle proliferation 18, 19, 50–53. Hypertension,one of the most common causes of stroke, is closely related to hyperuricemia 19. Severalexperimental animal models showed the development of systemic hypertension inhyperuricemic rats 54–57. In a recent randomized, placebo-controlled, crossover trial 58involving 30 hyperuricemic adolescents with newly diagnosed hypertension, allopurinoltreatment was associated with significant reductions in casual and 24-hour ambulatory bloodpressure compared to placebo. More clinical trials with longer follow-up periods are neededto determine the safety and the generalizability of urate-lowering therapy such as allopurinolin hypertension.

Interestingly, many previous studies that investigated the role of the uric acid level on eithercardiovascular disease or all-cause mortality observed a J-curve relationship 11, 16, 59–61.Similar results were noted in some of the studies included in our analysis 14, 15, 35, 42, 44.It has been postulated that a low uric acid level is associated with a higher mortality becauseuric acid may play an antioxidant role 19.

The limitations of this meta-analysis fall into two categories: those attributable to the dataavailable for analysis and those attributable to the techniques generally used to perform themeta-analysis. Our analysis is based on observational studies which are subject toconfounding and other biases and cannot prove causality. Randomized clinical trials were,however, neither generally useful to evaluate etiological hypotheses over a long period offollow-up 31, nor available in the literature to examine our study questions. We selectedonly large prospective studies with inception cohort free of disease, which helped increaseprecision of estimates while minimizing heterogeneity. There were different definitions ofhyperuricemia across the studies; therefore, we chose the category nearest to 6.8 mg/dl ineach study for the hyperuricemia group. Although studies differed by geographic location,age, race, sex distribution and size, meta-regression analysis did not reveal any significantassociation with these factors. Nonetheless, we cannot rule out other potential sources forheterogeneity such as clinical features.

All meta-analyses are inherently vulnerable to publication bias. We attempted to minimizethis bias by searching three major electronic databases with no language restriction. Threedifferent statistical tests to examine the issue of publication bias were performed revealingno statistical evidence for significant publication bias. Lastly, because we did not haveaccess to the raw data on adjustments in each study, we utilized the best adjusted RRs perindividual study. The use of medications such as diuretics was adjusted for in only a fewstudies 14, 39, 41, 42. For the stroke outcome data, there is a possibility of misclassificationbias because most of the papers we included used death certificates or diagnostic codes todefine their outcomes.

Our study has several important strengths. This meta-analysis is based on large prospectivecohort studies over a long follow-up period in many different countries. To our knowledge,this is the first systematic review and meta-analysis on hyperuricemia and the risk of stroke.We assessed the quality of individual studies using the Newcastle–Ottawa Scale 28. Themajority of the included studies had adequate sizes, follow-up lengths, and adjustments forother risk factors. We furthermore performed subgroup analyses of the studies with full

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adjustments for known stroke risk factors as the degree of adjustments for potentialconfounders was still different in each study.

In conclusion, our meta-analysis of published prospective studies suggests that high serumuric acid levels may modestly increase the risk of stroke incidence and mortality. Futureresearch should focus on confirming the pathogenetic mechanisms of hyperuricemia as wellas examining the role of urate-lowering therapy in stroke.

AcknowledgmentsSeo Young Kim is funded, in part, by a National Institutes of Health T32 training grant for training program inrheumatic disease.

Appendix 1

Effect of study variables by meta-regression

Stroke Incidence Stroke Mortality

Coefficient 95 % CI Coefficient 95 % CI

Gender −0.09 −0.33-0.14 0.21 −0.11-0.53

Year 0.003 −0.02-0.03 −0.06 −0.12-0.01

Race 0.25 −0.14-0.65 0.27 −0.14-0.69

CI; confidence interval

Appendix 2Linear regression plot for the relative risks (RR) of stroke against the number of adjustedrisk factors in each study

CI: confidence interval

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48. Cutler R. Urate and ascorbate: their possible roles as antioxidants in determining longevity ofmammalian species. Arch Gerontol Geriatr. 1984; 3:321–348. [PubMed: 6532339]

49. Proctor P. Uric acid: neuroprotective or neurotoxic? Stroke. 2008; 39:e88. [PubMed: 18369163]

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50. Kanellis J, Feig D, Johnson R. Does asymptomatic hyperuricaemia contribute to the developmentof renal and cardiovascular disease? An old controversy renewed. Nephrology (Carlton). 2004;9(6):394–399. [PubMed: 15663643]

51. Kanellis J, Watanabe S, Li J, et al. Uric acid stimulates monocyte chemoattractant protein-1production in vascular smooth muscle cells via mitogen-activated protein kinase andcyclooxygenase-2. Hypertension. 2003; 41(6):1287–1293. [PubMed: 12743010]

52. Kang D, Han L, Ouyang X, et al. Uric acid causes vascular smooth muscle cell proliferation byentering cells via a functional urate transporter. Am J Nephrol. 2005; 25(5):425–433. [PubMed:16113518]

53. Rao G, Corson M, Berk B. Uric acid stimulates vascular smooth muscle cell proliferation byincreasing platelet-derived growth factor A-chain expression. J Bio Chem. 1991; 266(13):8604–8608. [PubMed: 2022672]

54. Mazzali M, Kanellis J, Han L, et al. Hyperuricemia induces a primary arteriolopathy in rats by ablood pressure-independent mechanism. Am J Physiol Renal Physiol. 2002; 282:F991–F997.[PubMed: 11997315]

55. Watanabe S, Kang D, Feng L, et al. Uric acid, hominoid evolution, and the pathogenesis salt-sensitivity. Hypertension. 2002; 40:355–356. [PubMed: 12215479]

56. Mazzali M, Hughes J, Kim Y, et al. Elevated uric acid increases blood pressure in the rat by anovel crystal-independent mechanism. Hypertension. 2001; 38:1101–1106. [PubMed: 11711505]

57. Sanchez-Lozada L, Tapia E, Avila-Casado C, et al. Mild hyperuricemia induces glomerularhypertension in normal rats. Am J Physiol Renal Physiol. 2002; 283:F1105–F1110. [PubMed:12372787]

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59. Hsu S-P, Pai M-F, Peng Y-S, et al. Serum uric acid levels show a ‘J-shaped’ association with all-cause mortality in haemodialysis patients. Nephrol Dial Transplant. 2004; 19(2):457–462.[PubMed: 14736974]

60. Mazza A, Zamboni S, Rizzato E, et al. Serum uric acid shows a J-shaped trend with coronarymortality in non-insulin-dependent diabetic elderly people. The CArdiovascular STudy in theELderly (CASTEL). Acta Diabetol. 2007; 44(3):99–105. [PubMed: 17721747]

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Figure 1.Search strategy

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Figure 2.Selection of studies included in the analysis.

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Figure 3.Random effects analysis of fully adjusted studies for the association between hyperuricemiaand strokePoints (dot) and overall (diamond) estimates are given as risk ratios (RR) with 95% CI. Thesize of each box represents the weight of the corresponding study in our meta-analysis;Combined: studies which did not have gender specific data, ES: effect size, CI: confidenceinterval.

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Figure 4.Begg’s funnel plot for publication bias in studies for stroke incidence and mortalityRR; risk ratio, s.e.; standard error

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Table 1

Quality assessment of included studies based on Newcastle-Ottawa Scale

Author Selection Comparability Outcome

Tofuku 36 3 0 2

Takagi 46 4 0 3

Kagan 35 4 1 3

Lehto 14 3 2 3

Chien 40 4 2 3

Bos 39 4 2 3

Hozawa 41 4 2 3

Baba 38 3 0 3

Tomita 47 4 1 3

Sakata 42 4 2 3

Mazza 15 4 2 3

Jee 45 4 2 3

Gerber 44 4 2 3

Bae/Hyun 21, 22 3 0 2

Strasak 37 4 2 3

Strasak 43 4 2 3

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Tabl

e 2

Cha

ract

eris

tics o

f inc

lude

d co

hort

stud

ies.

Aut

hor,

yea

r of

publ

icat

ion,

cou

ntry

Part

icip

ants

(% m

ale)

Age

rang

eor m

ean

(yr)

Follo

w-u

p (y

r)H

yper

uric

emia

defin

ition

(mg/

dl)

No.

of t

otal

outc

omes

Out

com

e de

finiti

onV

aria

bles

con

trol

led

STR

OK

E IN

IDEN

CE

Tofu

ku* 3

6 19

78 Ja

pan

153

hype

rtens

ive

patie

nts (

75)

16–7

73.

7≥

7 (C

)4

Any

stro

ke--

Taka

gi 4

6 19

82 Ja

pan

314

men

in th

e fis

hing

vill

age

(100

)50

–79

8≥

7.5

(C)

30A

ny st

roke

--

Kag

an 3

5 19

85 U

SA7,

895

Japa

nese

Haw

aiia

n m

en(1

00)

45–6

810

≥ 7

.2 (M

)16

3 (7

9is

chem

ic, 6

5he

mor

rhag

ic a

nd19

unk

now

n)

All

stro

ke, i

sche

mic

, and

hem

orrh

agic

stro

ke b

ased

on

hosp

ital r

ecor

ds

Age

Leht

o 14

199

8 Fi

nlan

d1,

017

subj

ects

with

NID

DM

(54)

45–6

47.

2≥

5 (C

)11

4A

ny st

roke

exc

ept

suba

rach

noid

hem

orrh

age

base

d on

ICD

-9 c

odes

and

hosp

ital r

ecor

ds

Age

, gen

der,

smok

ing,

chol

este

rol,

HTN

, BM

I, to

tal

trigl

ycer

ides

, HD

L, g

luco

se,

use

of d

iure

tics,

dura

tion

ofD

M, a

nd h

isto

rical

stro

ke †

Chi

en 4

0 20

05 T

aiw

an3,

602

subj

ects

in th

e C

hin-

Shan

Com

mun

ity (4

7)35

+11

≥ 7

.7 (M

)≥

6.6

(W)

155

Any

type

of s

troke

bas

ed o

ncl

inic

al m

anife

stat

ion,

hos

pita

lre

cord

s, an

d de

ath

certi

ficat

es

Age

, SB

P, B

MI,

LDL,

HD

L,sm

okin

g, a

lcoh

ol in

take

, LV

H,

and

AF

Bos

39

2006

Net

herla

nds

4,38

5 su

bjec

ts in

the

Rot

terd

am st

udy

(35)

63–7

68.

4≥

6.4

(M)

≥ 5

.4 (W

)38

1 (2

05is

chem

ic, 4

6he

mor

rhag

ic,

and

130

unkn

own)

All

stro

ke, i

sche

mic

and

hem

orrh

agic

stro

ke b

ased

on

hosp

ital r

ecor

ds a

nd C

T/M

RI

Age

, sex

, SB

P, c

hole

ster

ol,

HD

L, D

M, s

mok

ing,

use

of

diur

etic

s, an

d w

aist

/hip

ratio

Hoz

awa

4120

06 U

SA13

,413

subj

ects

in th

e A

RIC

stud

y (4

6)45

–64

12.6

≥ 6

.9 (M

)≥

6.9

(W)

381

Isch

emic

stro

ke b

ased

on

ICD

-9 c

odes

and

CT/

MR

IA

ge, s

ex, r

ace,

edu

catio

n, S

BP,

DM

, ant

i-HTN

med

s, sm

okin

g,al

coho

l int

ake,

seru

m a

lbum

in,

vWF,

and

HD

L

Bab

a 38

200

7 Ja

pan

2,02

4 at

omic

bom

b su

rviv

ors

(39)

638

≥ 7

(C)

84 (6

3 is

chem

ican

d 21

hem

orrh

agic

)

Any

type

of s

troke

bas

ed o

ncl

inic

al p

rese

ntat

ion

and

CT/

MR

I

--

STR

OK

E M

OR

TALI

TY

Tom

ita 4

7 20

00 Ja

pan

49,4

13 m

ale

railr

oad

wor

kers

(100

)25

–60

5.4

≥ 8

.5 (M

)12

7A

ny ty

pe o

f stro

ke b

ased

on

ICD

-9 c

odes

Age

Saka

ta 4

2 20

01 Ja

pan

8,17

2 su

bjec

ts in

the

Nat

iona

lC

ardi

ovas

cula

r stu

dy (4

4)50

13.3

≥ 6

.5 (M

)≥

5.0

(W)

174

Any

type

of s

troke

bas

ed o

nIC

D-9

cod

esA

ge, B

MI,

SBP,

ant

i- H

TNm

eds,

chol

este

rol,

seru

mcr

eatin

ine,

glu

cose

, sm

okin

g,al

coho

l int

ake,

LV

H

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Aut

hor,

yea

r of

publ

icat

ion,

cou

ntry

Part

icip

ants

(% m

ale)

Age

rang

eor m

ean

(yr)

Follo

w-u

p (y

r)H

yper

uric

emia

defin

ition

(mg/

dl)

No.

of t

otal

outc

omes

Out

com

e de

finiti

onV

aria

bles

con

trol

led

Maz

za 1

5 20

02 It

aly

3,28

2 el

derly

subj

ects

(39)

65+

14≥

6.4

(C)

170

Any

type

of s

troke

bas

ed o

nIC

D-9

cod

esA

ge, h

isto

rical

stro

ke †

, CA

D,

HTN

, SB

P, p

ulse

pre

ssur

e, A

F,LV

H, s

mok

ing,

seru

mpo

tass

ium

and

sodi

um

Jee

45 2

004

Kor

ea22

,698

subj

ects

in th

e K

MIC

(100

)30

–77

6.5

≥ 7

.01(

M)

192

Any

type

of s

troke

bas

ed o

nho

spita

l rec

ords

and

ICD

-9co

des

Age

, DM

, HTN

, cho

lest

erol

,an

d sm

okin

g

Ger

ber 4

4 20

06 Is

rael

9,12

5 m

iddl

e-ag

ed m

ale

wor

kers

(100

)49

23≥

5.6

(M)

292

Any

type

of s

troke

bas

ed o

nIC

D-9

cod

esA

ge, B

MI,

SBP,

DM

,ch

oles

tero

l, sm

okin

g, a

nd L

VH

Bae

/Hyu

n 21

, 22

2007

Kor

ea66

0 su

bjec

ts w

ith c

oron

ary

arte

ry d

isea

se (5

7)59

2.3

≥ 6

.1 (M

)≥

5.1

(W)

12A

ny ty

pe o

f stro

ke b

ased

on

hosp

ital r

ecor

ds-

Stra

sak

37 2

008

Aus

tria

83,6

83 m

en in

the

risk

fact

orsu

rvei

llanc

e pr

ogra

m (1

00)

41.6

12.4

≥ 6

.7 (M

)64

5 (1

47is

chem

ic, 1

47he

mor

rhag

ic,

and

351

unkn

own)

All

stro

ke, i

sche

mic

, and

hem

orrh

agic

stro

ke b

ased

on

ICD

-9 c

odes

and

aut

opsy

Age

, BM

I, SB

P, D

BP,

chol

este

rol,

trigl

ycer

ides

, GG

T,gl

ucos

e, sm

okin

g, a

nd y

ear o

fex

amin

atio

n

Stra

sak

43 2

008

Aus

tria

28,6

13 w

omen

in th

e ris

kfa

ctor

surv

eilla

nce

prog

ram

(0)

62.3

13.6

≥ 5

.4 (W

)77

6 (2

11is

chem

ic, 1

14he

mor

rhag

ic,

and

451

unkn

own)

All

stro

ke, i

sche

mic

, and

hem

orrh

agic

stro

ke b

ased

on

ICD

-9 c

odes

and

aut

opsy

Age

, BM

I, SB

P, D

BP,

chol

este

rol,

trigl

ycer

ides

, GG

T,gl

ucos

e, sm

okin

g, o

ccup

atio

n,an

d ye

ar o

f exa

min

atio

n

* Incl

uded

for b

oth

stro

ke m

orta

lity

and

inci

denc

e; C

: com

bine

d; M

: men

; W: w

omen

; -- :

una

djus

ted;

SB

P: sy

stol

ic b

lood

pre

ssur

e; D

BP:

dia

stol

ic b

lood

pre

ssur

e; D

M: d

iabe

tes m

ellit

us; H

TN:

hype

rtens

ion;

vW

F, v

on W

illeb

rand

fact

or; H

DL:

hig

h de

nsity

lipo

prot

ein;

LD

L: lo

w d

ensi

ty li

popr

otei

n;

† prev

ious

stro

ke in

less

than

10

% o

f the

stud

y po

pula

tion;

CA

D: c

oron

ary

arte

ry d

isea

se; A

F: a

trial

fibr

illat

ion;

LV

H: l

eft v

entri

cula

r hyp

ertro

phy;

BM

I: bo

dy m

ass i

ndex

; NID

DD

M: n

on-in

sulin

dep

ende

ntdi

abet

es m

ellit

us; A

RIC

: Ath

eros

cler

osis

Ris

k in

Com

mun

ities

stud

y; K

MIC

: Kor

ea M

edic

al In

sura

nce

Cor

pora

tion

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