Distinctive Clinical Features of Mild Cognitive Impairment with Subcortical Cerebrovascular Disease

Background and Purpose: Patients with mild cognitive impairment and subcortical cerebrovascular disease (svMCI) can be isolated using criteria modified from those of Erkinjuntti et al. for subcortical vascular dementia and have poorer outcomes (cognitive deterioration, disability, institutionalizati...

Full description

Saved in:
Bibliographic Details
Published inDementia and geriatric cognitive disorders Vol. 19; no. 4; pp. 196 - 203
Main Authors Galluzzi, Samantha, Sheu, Ching-Fan, Zanetti, Orazio, Frisoni, Giovanni B.
Format Journal Article
LanguageEnglish
Published Basel, Switzerland Karger 01.01.2005
S. Karger AG
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Background and Purpose: Patients with mild cognitive impairment and subcortical cerebrovascular disease (svMCI) can be isolated using criteria modified from those of Erkinjuntti et al. for subcortical vascular dementia and have poorer outcomes (cognitive deterioration, disability, institutionalization, and mortality). The aim of this study was to test which of the core (dysexecutive syndrome with relative sparing of memory, gait disorders and extrapyramidal signs) and supporting (urinary and behavioral symptoms) clinical features are most useful to recognize patients with svMCI and discriminate them from those with amnestic MCI (aMCI). Methods: Twenty-nine svMCI and 14 aMCI patients were seen in a memory clinic. Tests and scales assessing core and supporting features that independently contributed to the discrimination between svMCI and aMCI were identified with stepwise logistic regression analysis. The accuracy of the discrimination was estimated with area under the receiver operating characteristic curve and 95% confidence intervals (CIs). Results: The most accurate scales were the extrapyramidal sign scale by Richards et al. (0.75, 95% CI 0.61–0.89), letter fluency (0.75, 95% CI 0.61–0.90), irritability of the Neuropsychiatric Inventory and urinary dependence (0.66, 95% CI 0.49–0.82 for both), and digit span forward (0.59, 95% CI 0.41–0.77). The overall accuracy of a model compounding information from main and supporting features was 0.98, 95% CI 0.94–1.0. Conclusions: All the domains that are included in the clinical criteria for svMCI independently contribute to the identification of the condition. These criteria can be useful to recognize svMCI patients in clinical settings.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1420-8008
1421-9824
DOI:10.1159/000083499