title: Paradigm of pretest risk stratification before coronary computed tomography.
abstract: BACKGROUND
  The optimal method of determining the pretest risk of coronary artery disease as a patient selection tool before coronary multidetector computed tomography (MDCT) is unknown.
  
  
  OBJECTIVE
  We investigated the ability of 3 different clinical risk scores to predict the outcome of coronary MDCT.
  
  
  METHODS
  This was a retrospective study of 551 patients consecutively referred for coronary MDCT on a suspicion of coronary artery disease. Diamond-Forrester, Duke, and Morise risk models were used to predict coronary artery stenosis (>50%) as assessed by coronary MDCT. The models were compared by receiver operating characteristic analysis. The distribution of low-, intermediate-, and high-risk persons, respectively, was established and compared for each of the 3 risk models.
  
  
  RESULTS
  Overall, all risk prediction models performed equally well. However, the Duke risk model classified the low-risk patients more correctly than did the other models (P < 0.01). In patients without coronary artery calcification (CAC), the predictive value of the Duke risk model was superior to the other risk models (P < 0.05). Currently available risk prediction models seem to perform better in patients without CAC. Between the risk prediction models, there was a significant discrepancy in the distribution of patients at low, intermediate, or high risk (P < 0.01).
  
  
  CONCLUSIONS
  The 3 risk prediction models perform equally well, although the Duke risk score may have advantages in subsets of patients. The choice of risk prediction model affects the referral pattern to MDCT.
authors.affiliation: Department of Cardiology, Vejle Sygehus, Kabbeltoft 25, DK-7100 Vejle, Denmark. jesper.moeller.jensen@slb.regionsyddanmark.dk
authors.forename: Jesper Møller
authors.initials: JM
authors.lastname: Jensen
authors.forename: Kristian A
authors.initials: KA
authors.lastname: Ovrehus
authors.forename: Lene H
authors.initials: LH
authors.lastname: Nielsen
authors.forename: Jesper K
authors.initials: JK
authors.lastname: Jensen
authors.forename: Henrik M
authors.initials: HM
authors.lastname: Larsen
authors.forename: Bjarne L
authors.initials: BL
authors.lastname: Nørgaard
mesh_terms: D000368:Aged; D002114:Calcinosis / Q000000981:diagnostic imaging; D016009:Chi-Square Distribution; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000000981:diagnostic imaging* / Q000209:etiology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D018579:Patient Selection; D011237:Predictive Value of Tests; D012372:ROC Curve; D012017:Referral and Consultation; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D036542:Tomography, Spiral Computed