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July 13, 2004; 63 (1) Articles

Predicting the rate of cognitive decline in aging and early Alzheimer disease

S. Adak, K. Illouz, W. Gorman, R. Tandon, E. A. Zimmerman, R. Guariglia, M. M. Moore, J. A. Kaye
First published July 12, 2004, DOI: https://doi.org/10.1212/01.WNL.0000132520.69612.AB
S. Adak
PhD
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K. Illouz
MS
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W. Gorman
MS
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R. Tandon
MS
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E. A. Zimmerman
MD
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R. Guariglia
BSN
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M. M. Moore
BS
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J. A. Kaye
MD
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Citation
Predicting the rate of cognitive decline in aging and early Alzheimer disease
S. Adak, K. Illouz, W. Gorman, R. Tandon, E. A. Zimmerman, R. Guariglia, M. M. Moore, J. A. Kaye
Neurology Jul 2004, 63 (1) 108-114; DOI: 10.1212/01.WNL.0000132520.69612.AB

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Abstract

Objectives: To determine prognostic factors affecting the course of Alzheimer disease (AD) and to determine the role of region-specific brain volumes as predictors of cognitive decline.

Methods: Longitudinal data from 166 normal elderly individuals and 59 early AD patients were analyzed. Brain volumes were extracted from MRI scans using semiautomated recursive segmentation methods. Prognostic factors were considered significant if they had a significant effect on the rate of cognitive decline.

Results: In multivariate analysis, higher Clinical Dementia Rating Scale (CDR) score at entry was a significant prognostic factor for an increased rate of cognitive decline. Significant prognostic factors within the baseline CDR = 0 group were base rate of progression and percent total high signal intensity (HSI), percent ventricular, and percent CSF volumes. Base rate of progression, family history, and percent ventricular volume were significant prognostic factors within the CDR = 0.5 group and APOE had a marginally significant effect on the rate of cognitive decline in the CDR = 1 group.

Conclusions: Percent total HSI, ventricular, and total CSF volume measures can independently predict the rate of cognitive decline and improve the predictive power of statistical models that use only clinical data. Brain volumetric measures from MRI can be used to estimate the rate of cognitive decline even among normal elderly individuals and thus may aid in the prediction of time of onset of disease.

  • Received September 29, 2003.
  • Accepted March 4, 2004.
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