title: A clinical prediction model to estimate risk for 30-day adverse events in emergency department patients with symptomatic atrial fibrillation.
abstract: OBJECTIVE
  Atrial fibrillation affects more than 2 million people in the United States and accounts for nearly 1% of emergency department (ED) visits. Physicians have little information to guide risk stratification of patients with symptomatic atrial fibrillation and admit more than 65%. Our aim is to assess whether data available in the ED management of symptomatic atrial fibrillation can estimate a patient's risk of experiencing a 30-day adverse event.
  
  
  METHODS
  We systematically reviewed the electronic medical records of all ED patients presenting with symptomatic atrial fibrillation between August 2005 and July 2008. Predefined adverse outcomes included 30-day ED return visit, unscheduled hospitalization, cardiovascular complication, or death. We performed multivariable logistic regression to identify predictors of 30-day adverse events. The model was validated with 300 bootstrap replications.
  
  
  RESULTS
  During the 3-year study period, 914 patients accounted for 1,228 ED visits. Eighty patients were excluded for non-atrial-fibrillation-related complaints and 2 patients had no follow-up recorded. Of 832 eligible patients, 216 (25.9%) experienced at least 1 of the 30-day adverse events. Increasing age (odds ratio [OR] 1.20 per decade; 95% confidence interval [CI] 1.06 to 1.36 per decade), complaint of dyspnea (OR 1.57; 95% CI 1.12 to 2.20), smokers (OR 2.35; 95% CI 1.47 to 3.76), inadequate ventricular rate control (OR 1.58; 95% CI 1.13 to 2.21), and patients receiving β-blockers (OR 1.44; 95% CI 1.02 to 2.04) were independently associated with higher risk for adverse events. C-index was 0.67.
  
  
  CONCLUSIONS
  In ED patients with symptomatic atrial fibrillation, increased age, inadequate ED ventricular rate control, dyspnea, smoking, and β-blocker treatment were associated with an increased risk of a 30-day adverse event.
authors: Department of Emergency Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA. tyler.barrett@vanderbilt.edu
authors: Tyler W
authors: TW
authors: Barrett
authors: Amy R
authors: AR
authors: Martin
authors: Alan B
authors: AB
authors: Storrow
authors: Cathy A
authors: CA
authors: Jenkins
authors: Frank E
authors: FE
authors: Harrell
authors: Stephan
authors: S
authors: Russ
authors: Dan M
authors: DM
authors: Roden
authors: Dawood
authors: D
authors: Darbar
mesh_terms: D000367:Age Factors; D000368:Aged; D001281:Atrial Fibrillation / Q000150:complications* / Q000175:diagnosis / Q000628:therapy; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011336:Probability; D012189:Retrospective Studies; D012307:Risk Factors; D012737:Sex Factors; D013997:Time Factors