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- W2538272283 abstract "As the older adult population increases, medical conditions will become more prevalent, including neurodegenerative diseases. Early detection, including at the mild cognitive impairment (MCI) level, will become increasingly necessary for prevention and treatment of Alzheimer’s disease and related dementias. We investigated the use of computerized neuropsychological batteries in the identification of amnestic MCI (aMCI) and non-amnestic MCI (naMCI) compared to cognitively healthy older adults. Volunteers were 114 persons (69% female, 45% African-American) recruited from the University of Michigan Alzheimer’s Disease Center (MADC) and the Wayne State University Institute of Gerontology’s Healthy Black Elders Center (HBEC). All were enrolled in the longitudinal cohort of the MADC and underwent complete NACC Uniform Data Set (UDS) assessment, being diagnosed via consensus conference as aMCI (n=13, 72.5±7.6 years), naMCI (n=10, 72±5.9 years) or cognitively healthy older adults (n=91, 72.1±7.6 years). No significant differences were noted across the groups in MMSE, age, or education). The computerized tests were not used for consensus. ANOVA results showed healthy older adults' performance to significantly differ (p < 0.05 or better) from both aMCI and naMCI participants on three of the four subtests of the CogState measure used in our study (Identification, One Card Learning, One Back), though no significant difference was found for the simple reaction time measure (Detection). For the Toolbox, similar results were found for all subtests, not just memory-related, within the “fluid” cognitive dimension, though no significant differences were found for “crystalized” (premorbid, well learned material) subscales. Of all the measures, only one NIH Toolbox subtest, the Dimensional Change Card Sorting Task, showed a difference between aMCI and naMCI performance (p = 0.05), with naMCI (92.4±12.5) scoring below the aMCI group (102.7±13.7), and healthy older above both (108.3±11.3). Overall, both of these computer-based neuropsychological batteries accurately differentiate healthy older adults from those with MCI in a relatively mildly affected community sample. Additionally, on the more extended Toolbox assessment of multiple domains, one subtest was able to identify select executive-based deficits in the naMCI group. For both clinical and pharmacological outcomes, both of these approaches hold great promise in identification of potential MCI participants." @default.
- W2538272283 created "2016-10-28" @default.
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- W2538272283 date "2016-07-01" @default.
- W2538272283 modified "2023-10-16" @default.
- W2538272283 title "P1-026: NIH Toolbox-Cognitive and Cogstate Computer-Based Assessment in the Identification of MCI Subtypes" @default.
- W2538272283 doi "https://doi.org/10.1016/j.jalz.2016.06.773" @default.
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