title: Impact of acute and chronic risk factors on use of evidence-based treatments in patients in Australia with acute coronary syndromes.
abstract: OBJECTIVE
  To determine whether acute risk factors (ARF) and chronic risk factors (CRF) contribute differently to the use of evidence-based treatments (EBT) for patients with acute coronary syndromes (ACS).
  
  
  METHODS
  Data were collected through a prospective audit of patients with ACS. Management was analysed by the presence of acute myocardial risk factors and chronic comorbid risk factors at presentation.
  
  
  METHODS
  39 hospitals across Australia.
  
  
  METHODS
  2599 adults presenting with ACS.
  
  
  METHODS
  None.
  
  
  METHODS
  Use of EBT, in-hospital and 12-month death, recurrent myocardial infarction and bleeding.
  
  
  RESULTS
  The number of ARF and CRF at presentation predicted in-hospital and 12-month death, recurrent myocardial infarction and bleeding. Patients with higher numbers of ARF were more likely to receive EBT (aspirin at presentation, 81.1% for zero ARF to 85.7% for > or =3 ARF, p<0.001; angiography 45.9% to 67.5%, p<0.001; reperfusion for ST elevation 50% to 70%, p = 0.392; beta blocker at discharge 66.5% to 74.4%, p<0.001). Patients with higher numbers of CRF were less likely to receive EBT (aspirin at presentation 90.4% for zero CRF to 68.8% for > or =4 CRF, p<0.001; angiography 78.8% to 24.7%, p<0.001; reperfusion for ST elevation 73.4% to 30%; p<0.001, beta blocker at discharge 75.2% to 55.6%; p<0.001). In multivariate regression analysis, ARF and CRF were the strongest predictors of receiving or failing to receive EBT, respectively.
  
  
  CONCLUSIONS
  Patients presenting with many ARF are more likely to receive EBT, while patients presenting with many CRF are less likely to receive them. This has important implications for future quality-improvement efforts.
authors.affiliation: Duke University Medical Center/Brigham and Women's Hospital, Boston, MA 02215, USA.
authors.forename: K E
authors.initials: KE
authors.lastname: Joynt
authors.forename: L
authors.initials: L
authors.lastname: Huynh
authors.forename: J V
authors.initials: JV
authors.lastname: Amerena
authors.forename: D B
authors.initials: DB
authors.lastname: Brieger
authors.forename: S G
authors.initials: SG
authors.lastname: Coverdale
authors.forename: J M
authors.initials: JM
authors.lastname: Rankin
authors.forename: A
authors.initials: A
authors.lastname: Soman
authors.forename: D P
authors.initials: DP
authors.lastname: Chew
mesh_terms: D054058:Acute Coronary Syndrome / Q000401:mortality / Q000628:therapy*; D000368:Aged; D001315:Australia / Q000453:epidemiology; D019317:Evidence-Based Medicine; D005260:Female; D019983:Guideline Adherence / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000453:epidemiology / Q000209:etiology / Q000517:prevention & control; D017410:Practice Guidelines as Topic; D012307:Risk Factors; D055502:Secondary Prevention