title: Itemized NIHSS subsets predict positive MRI strokes in patients with mild deficits.
abstract: BACKGROUND
  While imaging is useful in confirming the diagnosis of ischemic stroke, negative diffusion weighted imaging (DWI) is reported in up to 25% of patients. Our aim was to identify predictors of MRI-positive stroke from the itemized NIHSS.
  
  
  METHODS
  Data were derived from the Stroke Warning Information and Faster Treatment study from February 2006 to February 2010 among patients with mild deficits (NIHSS 0-5) and a final diagnosis of stroke by a vascular neurologist. All MRI sequences were reviewed for the presence or absence of an acute infarct on DWI. Multivariate logistic regression assessed factors predicting DWI-positive strokes; p<0.05 was considered significant.
  
  
  RESULTS
  894 patients had a discharge diagnosis of stroke; 709 underwent MRI and 28.0% were DWI negative. All patients with visual field deficits or neglect were DWI positive. On multivariate analysis including total NIHSS (0-2 vs. 3-5) and itemized NIHSS score subsets, predictors of a positive DWI were NIHSS score of 3-5 (OR=3.3, 95% CI: 1.8-6.1), motor deficits (OR=1.7, 95% CI: 1.1-2.8), ataxia (OR=1.9, 95% CI: 1.0-3.5), and absence of sensory deficits (OR=1.7, 95% CI: 1.0-2.7). We developed the NIHSS-m score that predicts DWI positivity in patients with mild deficits in the absence of neglect or visual field deficits.
  
  
  CONCLUSIONS
  NIHSS score subsets predict DWI positivity in mild strokes. The presence of neglect or visual field deficits on the NIHSS subsets is most likely to have an MRI correlate even in patients with low NIHSS.
authors.affiliation: Columbia University Medical Center, United States. Electronic address: sy2528@cumc.columbia.edu.
authors.forename: Shadi
authors.initials: S
authors.lastname: Yaghi
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Herber
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Joshua Z
authors.initials: JZ
authors.lastname: Willey
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Howard F
authors.initials: HF
authors.lastname: Andrews
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Amelia K
authors.initials: AK
authors.lastname: Boehme
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Randolph S
authors.initials: RS
authors.lastname: Marshall
authors.affiliation: Columbia University Medical Center, United States.
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Lazar
authors.affiliation: Division of Social Epidemiology, Global Institute of Public Health, Department of Neurology, NYU Langone Medical Center, New York University, New York, NY 10003, United States; Department of Epidemiology, College of Dentistry, New York University, New York, NY 10003, United States.
authors.forename: Bernadette
authors.initials: B
authors.lastname: Boden-Albala
mesh_terms: D000368:Aged; D001921:Brain / Q000473:pathology*; D002545:Brain Ischemia / Q000175:diagnosis* / Q000473:pathology; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis* / Q000473:pathology; D013997:Time Factors
keywords: DWI negative stroke; Diffusion weighted imaging; MRI; Mild deficits; NIHSS; Stroke