title: Risk Prediction for Ischemic Stroke and Transient Ischemic Attack in Patients Without Atrial Fibrillation: A Retrospective Cohort Study.
abstract: BACKGROUND
  Stroke mainly occurs in patients without atrial fibrillation (AF). This study explored risk prediction models for ischemic stroke and transient ischemic attack (TIA) in patients without AF.
  
  
  METHODS
  Three US-based healthcare databases (Truven MarketScan Commercial Claims and Encounters [CCAE], Medicare Supplemental [MDCR], and Optum Clinformatics [Optum]) were used to establish patient cohorts without AF during the index period of 2008-2012. The performance of 2 existing models (CHADS2and CHA2DS2-VASc) for predicting stroke and TIA was examined by fitting a logistic regression to a training dataset and evaluating predictive accuracy in a validation dataset (area under the curve, AUC) using patients with complete follow-up of 1 or 3 years, separately.
  
  
  RESULTS
  The commercial populations were younger and had fewer comorbidities than Medicare-eligible population. The incidence proportions of ischemic stroke and TIA during 1 and 3 years of follow-up were .5% and 1.9% (CCAE), .6% and 2.2% (Optum), and 4.6% and 13.1% (MDCR), respectively. The models performed consistently across all 3 databases, with the AUC ranging from .69 to .77 and from .68 to .73 for 1- and 3-year prediction, respectively. Predictive accuracy was lower than the initial work of CHADS2evaluation in patients with AF (AUC: .82), but consistent with a subsequent meta-analysis of CHADS2(.60-.80) and CHA2DS2-VASc performance (.64-.79).
  
  
  CONCLUSIONS
  Although the existing schemes for predicting ischemic stroke and TIA in patients with AF can be applied to patients without AF with comparable predictive accuracy, the evidence suggests that there is room for improvement in these models' performance.
authors.affiliation: Janssen Research & Development, LLC, Titusville, New Jersey. Electronic address: zyuan6@its.jnj.com.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Yuan
authors.affiliation: Janssen Research & Development, LLC, Raritan, New Jersey.
authors.forename: Erica A
authors.initials: EA
authors.lastname: Voss
authors.affiliation: Janssen Research & Development, LLC, Raritan, New Jersey.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: DeFalco
authors.affiliation: Janssen Research & Development, LLC, Raritan, New Jersey.
authors.forename: Guohua
authors.initials: G
authors.lastname: Pan
authors.affiliation: Janssen Research & Development, LLC, Titusville, New Jersey.
authors.forename: Patrick B
authors.initials: PB
authors.lastname: Ryan
authors.affiliation: Janssen Scientific Affairs, LLC, Titusville, New Jersey.
authors.forename: Daniel
authors.initials: D
authors.lastname: Yannicelli
authors.affiliation: Janssen Research & Development, LLC, Raritan, New Jersey.
authors.forename: Christopher
authors.initials: C
authors.lastname: Nessel
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D002545:Brain Ischemia / Q000175:diagnosis / Q000453:epidemiology*; D015897:Comorbidity; D016208:Databases, Factual; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D015994:Incidence; D002546:Ischemic Attack, Transient / Q000175:diagnosis / Q000453:epidemiology*; D016015:Logistic Models; D008297:Male; D016345:Medicare Part B; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D020521:Stroke / Q000175:diagnosis / Q000453:epidemiology*; D013997:Time Factors; D014481:United States / Q000453:epidemiology
keywords: Stroke; risk prediction; stroke prevention; transient ischemic attack