title: Recursive partitioning-based preoperative risk stratification for atrial fibrillation after coronary artery bypass surgery.
abstract: BACKGROUND
  Knowledge of the risk of atrial fibrillation (AF) for patients undergoing coronary artery bypass graft surgery (CABG) can guide decisions about prophylactic therapy. Accordingly, we sought to use tree-based methods to stratify patients into groups that will have similar risk of AF after CABG and informed decision making regarding aggressive prophylaxis of AF.
  
  
  METHODS
  We studied 1209 consecutive patients with isolated CABG performed in 1998-1999 at Yale-New Haven Hospital. Patients with preoperative AF were excluded. Tree-based analysis was carried out to stratify patients into similar groups regarding the risk of AF. Relative risks (RRs) and 95% CIs were calculated at each level of stratification.
  
  
  RESULTS
  Age was the most important variable. The importance of other risk factors seemed to be different for younger and older patients. Although in the younger age group (< or =60 years) severity of coronary artery disease (RR 2.19, 95% CI 1.12-3.34) followed by hypertension (RR 1.82, 95% CI 1.23-2.68) were important predictors, in the older age subgroups (61-69 and > or =70 years), nothing or only ejection fraction <40% (RR 1.31, 95% CI 1.08-1.59) was important. In the highest-risk group, AF occurrence was 55% and, in the lowest-risk group, it was 10%. In the low-risk groups, aggressive prophylaxis may not be justified in light of the smaller number of events that would be prevented, possible adverse events, and costs.
  
  
  CONCLUSIONS
  Age and variables related to heart disease severity are predictors of AF. The tree-based method may be a useful tool for clinicians who seek to determine who is more or less likely to benefit from aggressive arrhythmia prophylaxis.
authors.affiliation: Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Artyom
authors.initials: A
authors.lastname: Sedrakyan
authors.forename: Heping
authors.initials: H
authors.lastname: Zhang
authors.forename: Tom
authors.initials: T
authors.lastname: Treasure
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D000368:Aged; D000465:Algorithms; D001281:Atrial Fibrillation / Q000453:epidemiology* / Q000209:etiology; D001026:Coronary Artery Bypass / Q000009:adverse effects; D003663:Decision Trees; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D018570:Risk Assessment; D012307:Risk Factors; D018709:Statistics, Nonparametric; D013318:Stroke Volume