title: Hierarchical cognitive and psychosocial predictors of amnestic mild cognitive impairment.
abstract: To identify neuropsychological and psychosocial factors predictive of amnestic Mild Cognitive Impairment (aMCI) among a group of 94 nondemented older adults, we employed a novel nonlinear multivariate classification statistical method called Optimal Data Analysis (ODA) in a dataset collected annually for 3 years. Performance on measures of memory and visuomotor processing speed or symptoms of depression in year 1 predicted aMCI status by year 2. Performance on a measure of learning at year 1 predicted aMCI status at year 3. No other measures significantly predicted incidence of aMCI at years 2 and 3. Results support the utility of multiple neuropsychological and psychosocial measures in the diagnosis of aMCI, and the present model may serve as a testable hypothesis for prospective investigations of the development of aMCI.
authors.affiliation: Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA. Duke_Han@rush.edu
authors.forename: S Duke
authors.initials: SD
authors.lastname: Han
authors.forename: Hideo
authors.initials: H
authors.lastname: Suzuki
authors.forename: Amy J
authors.initials: AJ
authors.lastname: Jak
authors.forename: Yu-Ling
authors.initials: YL
authors.lastname: Chang
authors.forename: David P
authors.initials: DP
authors.lastname: Salmon
authors.forename: Mark W
authors.initials: MW
authors.lastname: Bondi
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003072:Cognition Disorders / Q000145:classification / Q000175:diagnosis / Q000503:physiopathology / Q000523:psychology; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D012919:Social Behavior