title: Prevalence of atrial fibrillation and its predictors in nondialysis patients with chronic kidney disease.
abstract: OBJECTIVE
  Chronic kidney disease (CKD) increases systemic inflammation, which is implicated in development and maintenance of atrial fibrillation (AF); therefore, we hypothesized that the prevalence of AF would be increased among nondialysis patients with CKD. This study also reports independent predictors of the presence of AF in this population.
  
  
  METHODS
  A retrospective, cross-sectional analysis of 1010 consecutive nondialysis patients with CKD from two community-based hospitals was conducted. Estimated GFRs (eGFRs) were calculated using the Modification of Diet in Renal Disease (MDRD) equation. Multivariate logistic regression was used to determine independent predictors.
  
  
  RESULTS
  Of 1010 nondialysis patients with CKD, 214 (21.2%) had AF. Patients with AF were older than patients without AF (76 +/- 11 versus 63 +/- 15 yr). The prevalence of AF among white patients (42.7%) was higher than among black patients (12.7%) or other races (5.7%). In multivariate analyses, age, white race, increasing left atrial diameter, lower systolic BP, and congestive heart failure were identified as independent predictors of the presence of AF. Although serum high-sensitivity C-reactive protein levels were elevated in our population (5.2 +/- 7.4 mg/L), levels did not correlate with the presence of AF or with eGFR. Finally, eGFR did not correlate with the presence of AF in our population.
  
  
  CONCLUSIONS
  The prevalence of AF was increased in our population, and independent predictors were age, white race, increasing left atrial diameter, lower systolic BP, and congestive heart failure.
authors.affiliation: Department of Medicine, University of Illinois at Chicago, Advocate Christ Medical Center, Oak Lawn, Illinois 60453, USA.
authors.forename: Wanwarat
authors.initials: W
authors.lastname: Ananthapanyasut
authors.forename: Sirikarn
authors.initials: S
authors.lastname: Napan
authors.forename: Earl H
authors.initials: EH
authors.lastname: Rudolph
authors.forename: Tasma
authors.initials: T
authors.lastname: Harindhanavudhi
authors.forename: Husam
authors.initials: H
authors.lastname: Ayash
authors.forename: Kelly E
authors.initials: KE
authors.lastname: Guglielmi
authors.forename: Edgar V
authors.initials: EV
authors.lastname: Lerma
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001281:Atrial Fibrillation / Q000175:diagnosis / Q000453:epidemiology* / Q000208:ethnology / Q000209:etiology* / Q000503:physiopathology; D001794:Blood Pressure; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D005260:Female; D005919:Glomerular Filtration Rate; D006325:Heart Atria / Q000000981:diagnostic imaging; D006333:Heart Failure / Q000150:complications / Q000453:epidemiology; D006764:Hospitals, Community / Q000706:statistics & numerical data; D006801:Humans; D007087:Illinois / Q000453:epidemiology; D007674:Kidney Diseases / Q000150:complications* / Q000175:diagnosis / Q000453:epidemiology* / Q000208:ethnology / Q000503:physiopathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D015995:Prevalence; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D014463:Ultrasonography; D044465:White People / Q000706:statistics & numerical data