title: Comparison of cardiovascular risk calculation tools in pharmacy practice.
abstract: OBJECTIVE
  To examine the use of various cardiovascular disease (CVD) risk estimation calculators in pharmacy practice.
  
  
  METHODS
  Longitudinal cohort study.
  
  
  METHODS
  Midwestern university worksite from August 2008 through May 2012.
  
  
  METHODS
  University employees with hypertension, dyslipidemia, and diabetes.
  
  
  METHODS
  Risk estimation calculators were applied to data from a pharmacist-run chronic disease management program.
  
  
  METHODS
  Difference in estimated CVD risk from multiple estimation calculators.
  
  
  RESULTS
  At baseline and 12 months, non-lab-based tools reported significantly higher 10-year CVD risk percentages compared with lab-based tools among the same cohort of patients (10.63% vs. 8.71% at baseline, P < 0.001; 9.34% vs. 7.31% at 12 months, P < 0.001). In addition, the electronic version of 10-year CVD risk reported significantly higher values than the paper version when applied to the same patient cohort (7.31% vs. 6.60% at 12 months, P = 0.018).
  
  
  CONCLUSIONS
  CVD risk estimation tools report significantly different values and are not interchangeable. Pharmacists using non-lab-based tools should expect significantly higher risk estimates than estimates derived from lab-based tools and therefore should use the same version of the estimation tool over the long term.
authors.affiliation: School of Pharmacy and Health Professions, Creighton University, Omaha, NE 68178, USA. nicolewhite@creighton.edu
authors.forename: Nicole D
authors.initials: ND
authors.lastname: White
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Lenz
authors.forename: Maryann Z
authors.initials: MZ
authors.lastname: Skrabal
authors.forename: Michele A
authors.initials: MA
authors.lastname: Faulkner
authors.forename: Jessica J
authors.initials: JJ
authors.lastname: Skradski
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Southard
authors.forename: Derek E
authors.initials: DE
authors.lastname: Popken
mesh_terms: D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000209:etiology / Q000517:prevention & control*; D002908:Chronic Disease; D003661:Decision Support Techniques; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000628:therapy*; D019468:Disease Management; D050171:Dyslipidemias / Q000150:complications / Q000175:diagnosis / Q000628:therapy*; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000175:diagnosis / Q000628:therapy*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015146:Midwestern United States; D009786:Occupational Health Services; D010593:Pharmaceutical Services; D011379:Prognosis; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014495:Universities