OBJECTIVE: To evaluate the performance of nondemented subjects 85 years and older on the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery, and to assess its relationship with sociodemographic variables. METHODS: We studied 196 subjects enrolled in an Alzheimer's Disease Research Center study who had a complete CERAD neuropsychological assessment. We used multiple regression analysis to predict performance on the neuropsychological tests from age, education, and sex. Eight representative hypothetical individuals were created (for example, an 87-year-old man, with high education). For each test, estimates of performance at the 10th, 25th, 50th, and 75th percentiles were reported for the eight representative hypothetical individuals. RESULTS: Mean age was 89.2 years (SD = 3.2), mean years of education was 14.9 (SD = 3.2), and 66% of the sample were women. For 11 of the 14 neuropsychological tests, there was a significant multiple regression model using education, age, and sex as predictors. Neither the models nor the predictors used individually were significant for Delayed Recall, Savings, or correct Recognition. Among the significant results, seven had education as the strongest predictor. Lower age and higher education were associated with better performance. Women performed better than men in three of four tests with significant results for sex. CONCLUSIONS: In a sample of oldest old whose primary language is English, neuropsychological testing is influenced mainly by education and age. Cutoff scores based on younger populations and applied to the oldest old might lead to increased false-positive misclassifications.
OBJECTIVE: To evaluate the performance of nondemented subjects 85 years and older on the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery, and to assess its relationship with sociodemographic variables. METHODS: We studied 196 subjects enrolled in an Alzheimer's Disease Research Center study who had a complete CERAD neuropsychological assessment. We used multiple regression analysis to predict performance on the neuropsychological tests from age, education, and sex. Eight representative hypothetical individuals were created (for example, an 87-year-old man, with high education). For each test, estimates of performance at the 10th, 25th, 50th, and 75th percentiles were reported for the eight representative hypothetical individuals. RESULTS: Mean age was 89.2 years (SD = 3.2), mean years of education was 14.9 (SD = 3.2), and 66% of the sample were women. For 11 of the 14 neuropsychological tests, there was a significant multiple regression model using education, age, and sex as predictors. Neither the models nor the predictors used individually were significant for Delayed Recall, Savings, or correct Recognition. Among the significant results, seven had education as the strongest predictor. Lower age and higher education were associated with better performance. Women performed better than men in three of four tests with significant results for sex. CONCLUSIONS: In a sample of oldest old whose primary language is English, neuropsychological testing is influenced mainly by education and age. Cutoff scores based on younger populations and applied to the oldest old might lead to increased false-positive misclassifications.
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