Vascular Cognitive ImpairmentView this Special Issue
Rebecca F. Gottesman, Jonathan T. Kleinman, Cameron Davis, Jennifer Heidler-Gary, Melissa Newhart, Argye E. Hillis, "The NIHSS-Plus: Improving Cognitive Assessment with the NIHSS", Behavioural Neurology, vol. 22, Article ID 123903, 5 pages, 2010. https://doi.org/10.3233/BEN-2009-0259
The NIHSS-Plus: Improving Cognitive Assessment with the NIHSS
Background: The National Institutes of Health Stroke Scale (NIHSS) has been criticized for limited representation of cognitive dysfunction and bias towards dominant hemisphere functions. Patients may therefore receive a low NIHSS score despite a fairly large stroke. A broader scale including simple cognitive tests would improve the clinical and research utility of the NIHSS.Methods: We studied 200 patients with acute non-dominant hemispheric stroke who underwent cognitive testing and had MRI with diffusion-weighted imaging (DWI) within 5 days of presentation. We measured DWI volumes and retrospectively calculated NIHSS scores. We used linear regression to determine the role of selected cognitive tests, when added to the NIHSS, in predicting DWI volume.Results: The NIHSS predicted DWI volume in a univariate analysis, as did total line cancellation and a visual perception task. In a multivariate model, using log-transformed variables, the NIHSS (p = 0.0002), line cancellation errors (p = 0.02) and visual perception (p = 0.004) each improved prediction of total infarct volume.Conclusion: The addition of line cancellation and visual perception tasks significantly adds to the model of NIHSS alone in predicting DWI volume. We propose that these two cognitive tests, which together can be completed in 2–3 minutes, could be combined with the NIHSS to create an “NIHSS-plus” that more accurately represents a patient’s ischemic tissue volume after a stroke. This scale requires further validation in a prospective study.
Copyright © 2010 Hindawi Publishing Corporation and the authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.