Diagnostic utility of the NAB List Learning test in Alzheimer's disease and amnestic mild cognitive impairment

被引:42
作者
Gavett, Brandon E.
Poon, Sabrina J.
Ozonoff, Al [2 ]
Jefferson, Angela L.
Nair, Anil K.
Green, Robert C. [3 ,4 ]
Stern, Robert A. [1 ]
机构
[1] Boston Univ, Sch Med, Alzheimers Dis Clin & Res Program, Dept Neurol, Boston, MA 02118 USA
[2] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02118 USA
[3] Boston Univ, Dept Med, Genet Program, Sch Med, Boston, MA 02118 USA
[4] Boston Univ, Sch Publ Hlth, Dept Epidemiol, Boston, MA 02118 USA
关键词
Dementia; Sensitivity and specificity; Differential diagnosis; Neuropsychology; Neuropsychological tests; Memory; DEMENTIA; CERAD; INDIVIDUALS; PERFORMANCE;
D O I
10.1017/S1355617708090176
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Measures of episodic memory are often used to identify Alzheimer's disease (AD) and mild cognitive impairment (MCI). The Neuropsychological Assessment Battery (NAB) List Learning test is a promising tool for the memory assessment of older adults due to its simplicity of administration, good psychometric properties, equivalent forms, and extensive normative data. This study examined the diagnostic utility of the NAB List Learning test for differentiating cognitively healthy, MCI, and AD groups. One hundred fifty-three participants (age: range, 57-94 years; M = 74 years SD, 8 years; sex: 61% women) were diagnosed by It multidisciplinary consensus team as cognitively normal, amnestic MCI (aMCI; single and multiple domain), or AD, independent of NAB List Learning performance. In univariate analyses, receiver operating characteristics Curve analyses were conducted for four demographically-corrected NAB List Learning variables. Additionally, multivariate ordinal logistic regression and fivefold cross-validation was used to create and validate a predictive model based on demographic variables and NAB List Learning test raw scores. At optimal cutoff scores, univariate sensitivity values ranged from .58 to .92 and univariate specificity Values ranged from .52 to .97. Multivariate ordinal regression produced a model that classified individuals with 80% accuracy and good predictive power. (JINS, 2009, 15, 121-129.)
引用
收藏
页码:121 / 129
页数:9
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