title: Early clinical differentiation of cerebral infarction from severe atherosclerotic stenosis and cardioembolism.
abstract: OBJECTIVE
  Hyperacute cerebral infarction trials require early differentiation of infarction subtype. Our aim was to determine clinical factors predictive of infarction subtype from data collected in the early hours of admission.
  
  
  METHODS
  Using the 1,273 patients enrolled in the Stroke Data Bank, stroke risk factors and demographic, clinical, and radiological features were compared between the 246 cardioembolic and 113 large-vessel atherosclerotic cerebral infarcts.
  
  
  RESULTS
  Stroke Data Bank definitions ensured more transient ischemic attacks in atherosclerotic infarcts and more cardiac disease in cardioembolic infarcts, but the diagnosis was distinguished further using a logistic regression model. Fractional arm weakness (shoulder different from hand) (odds ratio 3.1, 95% confidence interval [CI] 1.6-5.8), hypertension (odds ratio 2.8, CI 1.4-5.3), diabetes (odds ratio 2.5, CI 1.2-5.1) and male gender (odds ratio = 2.2, CI 1.2-4.1) occurred more frequently in patients with atherosclerotic than cardioembolic infarcts. Reduced consciousness (odds ratio = 3.2, CI 1.4-7.3) was more frequent in cardioembolism. For a male patient with hypertension, diabetes, and fractional arm weakness, the estimated odds of an atherosclerotic infarction were 47-fold that of a cardioembolic infarction. Patients with atherosclerotic infarcts were more likely to have a fractional arm weakness regardless of infarct size, whereas, for those with cardioembolic infarctions, fractional weakness was more frequent in infarcts less than 20 cc in volume.
  
  
  CONCLUSIONS
  Clinical features that are observed at stroke onset can help distinguish cerebral infarction subtypes and may allow for early stratification in therapeutic trials.
authors.affiliation: Neurological Institute, Columbia-Presbyterian Medical Center, New York 10032.
authors.forename: S G
authors.initials: SG
authors.lastname: Timsit
authors.forename: R L
authors.initials: RL
authors.lastname: Sacco
authors.forename: J P
authors.initials: JP
authors.lastname: Mohr
authors.forename: M A
authors.initials: MA
authors.lastname: Foulkes
authors.forename: T K
authors.initials: TK
authors.lastname: Tatemichi
authors.forename: P A
authors.initials: PA
authors.lastname: Wolf
authors.forename: T R
authors.initials: TR
authors.lastname: Price
authors.forename: D B
authors.initials: DB
authors.lastname: Hier
mesh_terms: D000368:Aged; D002533:Cerebral Angiography; D002544:Cerebral Infarction / Q000150:complications / Q000000981:diagnostic imaging / Q000209:etiology*; D003251:Constriction, Pathologic / Q000150:complications; D003327:Coronary Disease / Q000150:complications*; D004617:Embolism / Q000150:complications*; D005260:Female; D005544:Forecasting; D006801:Humans; D002537:Intracranial Arteriosclerosis / Q000150:complications*; D002546:Ischemic Attack, Transient / Q000150:complications; D007806:Language Disorders / Q000209:etiology; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009069:Movement Disorders / Q000209:etiology; D012044:Regression Analysis; D014057:Tomography, X-Ray Computed