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P3–225: Quick and accessible: The highly correlated Cognitive Self‐Test (CST)
Author(s) -
Kuhn Tarah,
Dougherty John,
Crane Monica,
Yeager Jamie,
Missimer Cassie,
Heidel Eric
Publication year - 2013
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.2013.05.1298
Subject(s) - neurocognitive , boston naming test , verbal fluency test , clinical dementia rating , dementia , geriatric depression scale , psychology , cognition , montreal cognitive assessment , verbal learning , cognitive test , audiology , alzheimer's disease , clinical psychology , neuropsychology , psychiatry , disease , medicine , cognitive impairment , depressive symptoms
Background: The CogState brief battery consists of four card playing tasks, which assesses the cognitive domains of psychomotor function, attention, visual learning, and visual working memory. Previous studies have demonstrated the utility and sensitivity of the CogState brief battery for detection of cognitive impairment in Alzheimer’s disease (AD) and mild cognitive impairment (MCI), and for the measurement of cognitive change in the preclinical stages of AD. Thus, the CogState brief battery may be a useful screening tool to assist the management of cognitive function in clinical settings. This study aimed to determine the clinical utility of the CogState brief battery. Methods: Healthy older adults (n 1⁄4 653), adults with MCI (n 1⁄4 68), and adults with AD (n 1⁄4 44) who completed the CogState brief battery were recruited from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) Study of Ageing, and the AIBL-Rate of Change sub-study (AIBL-ROCS). The four performance measures of the CogState brief battery were reduced to two composites a psychomotor/attention composite and a learning/working memory composite. Sensitivity and specificity analyses were conducted on the two composites to determine their clinical utility. Results: Large impairments inMCI (d1⁄4 1.20) and AD (d1⁄4 2.20) were identified for the learning/working memory composite but not the psychomotor/attention composite (MCI d 1⁄4 0.40; AD d 1⁄4 0.50). Using a cutscore of -1.96, the learning/working memory composite showed 85.71% sensitivity and 96.81% specificity to a clinical classification of AD. Both composite scores showed high test-retest reliability (0.95) over four months. Performance on the memory composite was also related to performance on the MMSE, with worse scores on the MMSE associated with worse performance on the CogState memory composite. Additionally, increasing severity on the CDR, sum of boxes score was also associated with worse performance on the CogState memory composite. Conclusions: The results of this study suggest that the CogState memory composite is a useful tool for the identification of AD related memory impairment, and correlates well with traditional measures of disease classification.