Itemized NIHSS subsets predict positive MRI strokes in patients with mild deficits
Shadi Yaghi1, Charlotte Herber1, Joshua Z Willey1
1Columbia University Medical Center, United States.
Journal of the Neurological Sciences
|September 17, 2015
Summary
Certain National Institutes of Health Stroke Scale (NIHSS) score subsets can predict diffusion-weighted imaging (DWI) positive strokes in mild cases. Neglect or visual field deficits strongly indicate an MRI-visible stroke, even with low NIHSS scores.
Area of Science:
- Neurology
- Medical Imaging
- Stroke Diagnosis
Background:
- Diffusion-weighted imaging (DWI) is crucial for ischemic stroke diagnosis but can be negative in up to 25% of patients.
- Identifying predictors of MRI-positive stroke from the National Institutes of Health Stroke Scale (NIHSS) is essential for accurate diagnosis.
Purpose of the Study:
- To identify predictors of MRI-positive stroke using itemized NIHSS scores in patients with mild neurological deficits.
- To develop a predictive score for DWI positivity in mild stroke cases.
Main Methods:
- Analysis of data from the Stroke Warning Information and Faster Treatment study (2006-2010).
- Inclusion of patients with mild deficits (NIHSS 0-5) and confirmed stroke diagnosis.
- Multivariate logistic regression to assess factors predicting DWI-positive strokes.
Main Results:
- 28.0% of patients with stroke undergoing MRI were DWI negative.
- Predictors of DWI positivity included NIHSS scores of 3-5, motor deficits, ataxia, and absence of sensory deficits.
- A novel NIHSS-m score was developed to predict DWI positivity in mild strokes without neglect or visual field deficits.
Conclusions:
- Itemized NIHSS score subsets effectively predict DWI positivity in mild ischemic strokes.
- The presence of neglect or visual field deficits on NIHSS is highly indicative of an MRI-positive stroke, even with low NIHSS scores.
More Related Videos
11:25Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Published on: July 26, 2013
44.3K
12:41Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat
Published on: August 28, 2021
5.0K
