title: Gout after living kidney donation: correlations with demographic traits and renal complications.
abstract: BACKGROUND
  The demographic and clinical correlates of gout after living kidney donation are not well described.
  
  
  METHODS
  Using a unique database that integrates national registry identifiers of U.S. living kidney donors (1987-2007) with billing claims from a private health insurer (2000-2007), we identified post-donation gout based on medical diagnosis codes or pharmacy fills for gout therapies. The frequencies and demographic correlates of gout after donation were estimated by Cox regression with left- and right-censoring. We also compared the rates of renal diagnoses among donors with and without gout, matched in the ratio 1:3 by age, sex, and race.
  
  
  RESULTS
  The study sample of 4,650 donors included 13.1% African Americans. By seven years, African Americans were almost twice as likely to develop gout as Caucasian donors (4.4 vs. 2.4%; adjusted hazard ratio, aHR, 1.8; 95% confidence interval (CI) 1.0-3.2). Post-donation gout risk also increased with older age at donation (aHR per year 1.05) and was higher in men (aHR 2.80). Gout rates were similar in donors and age- and sex-matched general non-donors (rate ratio 0.86; 95% CI 0.66-1.13). Compared to matched donors without gout, donors with gout had more frequent renal diagnoses, reaching significance for acute kidney failure (rate ratio 12.5; 95% CI 1.5-107.0), chronic kidney disease (rate ratio 5.0; 95% CI 2.1-11.7), and other disorders of the kidney (rate ratio 2.2; 95% CI 1.2-4.2).
  
  
  CONCLUSIONS
  Donor subgroups at increased risk of gout include African Americans, older donors, and men. Donors with gout have a higher burden of renal complications after demographic adjustment.
authors.affiliation: Division of Nephrology, Western University, London, Ont., Canada.
authors.forename: Ngan N
authors.initials: NN
authors.lastname: Lam
authors.forename: Amit X
authors.initials: AX
authors.lastname: Garg
authors.forename: Dorry L
authors.initials: DL
authors.lastname: Segev
authors.forename: Mark A
authors.initials: MA
authors.lastname: Schnitzler
authors.forename: Huiling
authors.initials: H
authors.lastname: Xiao
authors.forename: David
authors.initials: D
authors.lastname: Axelrod
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Brennan
authors.forename: Bertram L
authors.initials: BL
authors.lastname: Kasiske
authors.forename: Janet E
authors.initials: JE
authors.lastname: Tuttle-Newhall
authors.forename: Krista L
authors.initials: KL
authors.lastname: Lentine
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000367:Age Factors; D005260:Female; D006073:Gout / Q000453:epidemiology* / Q000208:ethnology; D006801:Humans; D015994:Incidence; D007674:Kidney Diseases / Q000453:epidemiology* / Q000208:ethnology; D016030:Kidney Transplantation / Q000009:adverse effects*; D019520:Living Donors / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009392:Nephrectomy / Q000009:adverse effects*; D012042:Registries / Q000706:statistics & numerical data; D012307:Risk Factors; D012737:Sex Factors; D013997:Time Factors; D014481:United States / Q000453:epidemiology / Q000208:ethnology; D044465:White People / Q000706:statistics & numerical data