title: An integer based risk score for predicting 30-day major adverse cardiac or cerebrovascular events after percutaneous coronary intervention with drug-eluting stents: results from a large prospective multicentre registry, the STENT Group.
abstract: OBJECTIVE
  Previous risk models predicting in-hospital major adverse cardiac or cerebrovascular events (MACCE) after percutaneous coronary interventions (PCI) may underestimate actual short-term post-procedure complications due to the trend toward early discharge of patients.
  
  
  RESULTS
  Using a subset (N=10,679) from the STENT Group registry, a logistic regression model was developed to predict 30-day MACCE which includes death, myocardial infarction, target vessel revascularisation and stroke. An integer-based risk score was created from the model and validated in another subset (N=3,099). In the study subset, there was significant difference between in-hospital and 30-day MACCE N=443 (2.0%) vs. 131 (4.2), p<0.01, respectively. A final risk model included nine variables; absence of pre-procedural statin (odds ratio=1.3, 95% confidence interval=1.0-1.5), haemoglobin level (0.9/1 gm increase, 0.8-0.9), cardiogenic shock (4.4, 3.1-6.3), acute congestive heart failure (1.6, 1.2-2.3), left main disease (2.2, 1.3-3.7), left anterior descending artery lesion (1.3, 1.0-1.5), ostial lesion (1.6, 1.2-2.1), coronary thrombosis (2.0, 1.4-2.9) and ACC/AHA type C lesion (1.3, 1.1-1.6). The c-statistics of the final model were 0.653 and 0.692 in the study and validation subset, respectively.
  
  
  CONCLUSIONS
  In this large real world registry of DES, in-hospital MACCE did not represent short-term post-procedure prognosis. The risk model consisting of nine variables predicted 30-day MACCE with modest discriminatory value.
authors.affiliation: St. Vincent Heart Center of Indiana, Indianapolis, IN 46260, USA. itohiroki@gmail.com
authors.forename: Hiroki
authors.initials: H
authors.lastname: Ito
authors.forename: Marcy
authors.initials: M
authors.lastname: Nussbaum
authors.forename: James B
authors.initials: JB
authors.lastname: Hermiller
authors.forename: Zachary
authors.initials: Z
authors.lastname: Hodes
authors.forename: Bruce
authors.initials: B
authors.lastname: Brodie
authors.forename: Barrett
authors.initials: B
authors.lastname: Cheek
authors.forename: Stanley
authors.initials: S
authors.lastname: Juk
authors.forename: Fred
authors.initials: F
authors.lastname: Krainin
authors.forename: Christopher
authors.initials: C
authors.lastname: Metzger
authors.forename: Peter
authors.initials: P
authors.lastname: Duffy
authors.forename: Angela
authors.initials: A
authors.lastname: Humphrey
authors.forename: Sherry
authors.initials: S
authors.lastname: Laurent
authors.forename: Charles A
authors.initials: CA
authors.lastname: Simonton
mesh_terms: D000368:Aged; D015906:Angioplasty, Balloon, Coronary / Q000009:adverse effects* / Q000401:mortality / Q000706:statistics & numerical data; D003324:Coronary Artery Disease / Q000401:mortality* / Q000628:therapy*; D054855:Drug-Eluting Stents / Q000009:adverse effects* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010351:Patient Discharge / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012042:Registries / Q000706:statistics & numerical data*; D018570:Risk Assessment; D012307:Risk Factors