title: A validated risk score to predict outcomes after carotid stenting.
abstract: BACKGROUND
  Periprocedural outcome has been extensively investigated in patients undergoing carotid artery stenting. However, risk factors contributing to long-term mortality have not been comprehensively assessed. We aimed to establish a validated clinical risk score for long-term mortality in patients after carotid artery stenting.
  
  
  RESULTS
  Two independent cohorts after successful carotid artery stenting (602 and 552 patients) were prospectively investigated. Multivariable Cox regression and bootstrap variable selection were used to select the best-fitting multivariable model. The mortality rate was 35% in the derivation and 39% in the validation cohort during a median follow-up of 6.5 and 7.4 years, respectively. The following variables were identified as most robust risk factors in the derivation cohort: age, heart failure, diabetes mellitus, relative lymphocyte count, prothrombin time, peripheral artery disease, and contralateral carotid occlusion. A weighted multimarker risk score yielded an area under the receiver operating characteristic curve of 0.79 in the derivation (P<0.001) and of 0.69 (P<0.001) in the validation cohort. In comparison, the best area under the receiver operating characteristic curves for single risk factors were 0.67 and 0.63, respectively. For optimal clinical use, a simplified risk score was also developed, which discriminated very well from very low to very high risk. The risk of all-cause mortality ranged from 8% for a score of 1 to 93% for a score of 7 (P<0.001) in the derivation and from 11% to 100% in the validation cohort (P<0.001).
  
  
  CONCLUSIONS
  A multimarker risk score outperformed the prognostic value of single risk factors for the prediction of long-term mortality.
authors.affiliation: Department of Internal Medicine II, Division of Angiology, Medical University of Vienna, Austria.
authors.forename: Matthias
authors.initials: M
authors.lastname: Hoke
authors.forename: Elmir
authors.initials: E
authors.lastname: Ljubuncic
authors.forename: Clemens
authors.initials: C
authors.lastname: Steinwender
authors.forename: Kurt
authors.initials: K
authors.lastname: Huber
authors.forename: Erich
authors.initials: E
authors.lastname: Minar
authors.forename: Renate
authors.initials: R
authors.lastname: Koppensteiner
authors.forename: Franz
authors.initials: F
authors.lastname: Leisch
authors.forename: Petra
authors.initials: P
authors.lastname: Dick
authors.forename: Klaus
authors.initials: K
authors.lastname: Kerschner
authors.forename: Martin
authors.initials: M
authors.lastname: Schillinger
authors.forename: Robert
authors.initials: R
authors.lastname: Hofmann
authors.forename: Alexander
authors.initials: A
authors.lastname: Niessner
mesh_terms: D000368:Aged; D017130:Angioplasty / Q000009:adverse effects / Q000295:instrumentation* / Q000401:mortality*; D019540:Area Under Curve; D016009:Chi-Square Distribution; D003324:Coronary Artery Disease / Q000401:mortality / Q000628:therapy*; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012372:ROC Curve; D012042:Registries; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D015607:Stents; D013997:Time Factors; D016896:Treatment Outcome