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P2‐430: Screening performance of the Healthy Brain Checklist in a community setting
Author(s) -
Shankle William,
Fortier Dennis,
Hara Junko,
Keeble Celine,
Macias Denise,
Holnagel Dori,
BrantZawadzki Michael,
Reisberg Barry
Publication year - 2012
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2012.05.2055
Subject(s) - dementia , cognition , checklist , medicine , cognitive impairment , montreal cognitive assessment , disease , clinical psychology , audiology , gerontology , psychology , psychiatry , cognitive psychology
Background: Despite its utility, the Mini-Mental State Examination (MMSE) has proven to be relatively insensitive to conditions associated with frontal-executive and subcortical dysfunction, and to milder forms of cognitive impairment. The Alzheimer’s Disease Assessment Scale (ADAS Cog) is both convenient for screening of probable AD and as a measure of cognitive functioning during drug intervention. The aim of the present study was to assess the ADAS-Cog’s ability as a cognitive screening tool through examination of standard threshold scores, for patients with higher dementia (MMSE < 12; n 1⁄4 92), AD (MMSE 13 to 25; n 1⁄4 2263) or probable MCI (MMSE 26; n1⁄4 422), and to assess cognitive symptom profiles among groups. Methods: AD data was obtained from the Critical Path Institute Online Data Repository (CODR). The diagnostic accuracy of the ADAS-Cog for clinical screening of Higher Dementia, AD and probable MCI, was assessed through receiver operating characteristics (ROC) curve analysis. For the predictive value of the ADAS-Cog, for each cut-off point, sensitivity and specificity were computed. An exploratory factory analysis using promax rotation was also carried out on the ADAS-Cog, to assess factor structures.Results: The discriminant potential of the ADAS-Cog for AD was excellent, with an AUC of 0.906 [95% confidence interval (CI), 0.8010.918], and that for Higher Dementia was high, with an AUC of 0.884 (95% CI, 0.745-0.907). The discriminant potential for MCI was moderate with 0.756 (75%CI, 0.705-0.843) possibly indicating different classification accuracies of the ADAS-Cog for milder cognitive impairment. The optimal cut-off point for maximum accuracy and the respective values of sensitivity, specificity, PPV, NPV, and classification accuracy was < 87 for Higher Dementia,< 79 for AD and< 51 for probableMCI. The three groups displayed different factor loadings that could also help discriminate severity alongside total score. Conclusions: The ADAS-Cog is valuable for early detection of the illness and staging. ADAS Cog plays an important role in the diagnostic makeup of AD. The cognitive profile in Higher Dementia and probableMCI groups differs significantly from that in AD. Performance on tests of Language performance and praxis attitudes are best in differentiating the groups.