Itemized NIHSS subsets predict positive MRI strokes in patients with mild deficits

J Neurol Sci. 2015 Nov 15;358(1-2):221-5. doi: 10.1016/j.jns.2015.08.1548. Epub 2015 Sep 2.

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.

Conclusion: 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.

Keywords: DWI negative stroke; Diffusion weighted imaging; MRI; Mild deficits; NIHSS; Stroke.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Brain / pathology*
  • Brain Ischemia / diagnosis*
  • Brain Ischemia / pathology
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Severity of Illness Index
  • Stroke / diagnosis*
  • Stroke / pathology
  • Time Factors