title: Metabolic syndrome-related conditions among people with and without gout: prevalence and resource use.
abstract: OBJECTIVE
  A cohort of employees with gout were compared to those without to evaluate the differences in prevalence of disorders associated with metabolic syndrome (both those considered underlying and those associated with end-stage morbidity and mortality) as well as the cost of annual medical services (AMS) required for treatment of these conditions.
  
  
  METHODS
  Employees with gout were identified by International Classification of Diseases-9 (ICD-9) code during the calendar years of 2001-2004 and compared to propensity-score matched employees without gout using the Human Capital Management Services Research Reference Database. T-tests were then used to compare prevalence and average AMS of comorbid disorders defined from Agency for Healthcare and Research Quality (AHRQ) diagnostic categories.
  
  
  RESULTS
  'Hyperlipidemia', 'essential hypertension', and 'diabetes mellitus without complications' ranked in the top 10 categories of mean number of AMS for employees with gout using AHRQ specific categories; the values were higher than found for those without gout (all p < 0.0001). 'Essential hypertension', 'hyperlipidemia', 'diabetes mellitus without complications', and 'coronary atherosclerosis' showed an approximate 2:1 prevalence ratio for employees with gout over those without (p < or = 0.05). Main study limitations include the small number of subjects with gout, retrospective study design, and possible miscoding and/or non-coding of individuals with the studied disorders.
  
  
  CONCLUSIONS
  These results support the continued need for patients with gout and their clinicians to be aware of the possibility of the increased risk of associated metabolic syndrome and related comorbidities in these individuals, emphasizing the need for prevention when possible and treatment when necessary.
authors.affiliation: Pharmacy Practice, University of Texas at Austin, Austin, TX, USA.
authors.forename: Suzanne
authors.initials: S
authors.lastname: Novak
authors.forename: Arthur K
authors.initials: AK
authors.lastname: Melkonian
authors.forename: Pankaj A
authors.initials: PA
authors.lastname: Patel
authors.forename: Nathan L
authors.initials: NL
authors.lastname: Kleinman
authors.forename: Nancy
authors.initials: N
authors.lastname: Joseph-Ridge
authors.forename: Richard A
authors.initials: RA
authors.lastname: Brook
mesh_terms: D000328:Adult; D017677:Age Distribution; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D015331:Cohort Studies; D015897:Comorbidity; D004651:Employment / Q000706:statistics & numerical data; D005260:Female; D006073:Gout / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology*; D006306:Health Surveys; D006801:Humans; D006949:Hyperlipidemias / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy; D006973:Hypertension / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy; D038801:International Classification of Diseases; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D008875:Middle Aged; D015995:Prevalence; D011379:Prognosis; D018570:Risk Assessment; D012720:Severity of Illness Index; D017678:Sex Distribution; D018582:Sick Leave / Q000191:economics; D014481:United States / Q000453:epidemiology