title: Association between the CHADS2 score and an ankle-brachial index of ＜0.9 in patients without atrial fibrillation.
abstract: OBJECTIVE
  The ankle-brachial index(ABI) is an easy-to-use, non-invasive and reliable diagnostic tool for assessing peripheral arterial occlusive disease(PAOD). The CHADS2(congestive heart failure, hypertension, age ≧75 years, diabetes, prior stroke) score is a simple and popular clinical parameter that is used to assess the risk of stroke in patients with atrial fibrillation (AF). Because all five components of the CHADS2 score are risk factors for PAOD, the score should have a strong correlation with the presence of PAOD. However, there are limited studies regarding the association between the CHADS2 score and PAOD in patients without AF. Therefore, the aim of the present study was to investigate whether the CHADS2 score is positively associated with PAOD in patients without AF.
  
  
  METHODS
  A total of 1,320 patients without AF were included in this study. The ABI was measured using an ABI-form device. PAOD was defined as an ABI of ＜0.9 in either leg.
  
  
  RESULTS
  Among the 1,320 subjects (mean age: 60.3±13.4 years), the prevalence of an ABI of ＜0.9 was 5.7%. A multivariate analysis showed that an increased age(odds ratio [OR], 1.054; p＜0.001), decreased estimated glomerular filtration rate (OR, 0.971; p＜0.001) and increased CHADS2 score (OR, 1.861; p＜0.001) were independently associated with an ABI of ＜0.9.
  
  
  CONCLUSIONS
  Our study demonstrated that the CHADS2 score is significantly associated with an ABI of ＜0.9 in non-AF patients. Further prospective studies are needed to examine the ability of the CHADS2 score to predict the incidence of PAOD.
authors.affiliation: Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University.
authors.forename: Po-Chao
authors.initials: PC
authors.lastname: Hsu
authors.forename: Tsung-Hsien
authors.initials: TH
authors.lastname: Lin
authors.forename: Wen-Hsien
authors.initials: WH
authors.lastname: Lee
authors.forename: Chun-Yuan
authors.initials: CY
authors.lastname: Chu
authors.forename: Cheng-An
authors.initials: CA
authors.lastname: Chiu
authors.forename: Hung-Hao
authors.initials: HH
authors.lastname: Lee
authors.forename: Ho-Ming
authors.initials: HM
authors.lastname: Su
authors.forename: Wen-Chol
authors.initials: WC
authors.lastname: Voon
authors.forename: Wen-Ter
authors.initials: WT
authors.lastname: Lai
authors.forename: Sheng-Hsiung
authors.initials: SH
authors.lastname: Sheu
mesh_terms: D000368:Aged; D055109:Ankle Brachial Index; D001281:Atrial Fibrillation / Q000175:diagnosis*; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D003430:Cross-Sectional Studies; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D015995:Prevalence; D012307:Risk Factors; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis*