Robust and Conventional Neuropsychological Norms: Diagnosis and Prediction of Age-Related Cognitive Decline Academic Article Article uri icon

Overview

MeSH Major

  • Alzheimer Disease
  • Amyloid
  • Brain
  • Cognition Disorders
  • Positron-Emission Tomography

abstract

  • The aim of the study was to compare the performance of Robust and Conventional neuropsychological norms in predicting clinical decline among healthy adults and in mild cognitive impairment (MCI). The authors developed Robust baseline cross sectional and longitudinal change norms from 113 healthy participants retaining a normal diagnosis for at least 4 years. Baseline Conventional norms were separately created for 256 similar healthy participants without follow-up. Conventional and Robust norms were tested in an independent cohort of longitudinally studied healthy (n = 223), MCI (n = 136), and Alzheimer's disease (AD, n = 162) participants; 84 healthy participants declined to MCI or AD (NL→DEC), and 44 MCI declined to AD (MCI→AD). Compared to Conventional norms, baseline Robust norms correctly identified a higher proportion of NL→DEC with impairment in delayed memory and attention-language domains. Both norms predicted decline from MCI→AD. Change norms for delayed memory and attention-language significantly incremented baseline classification accuracies. These findings indicate that Robust norms improve identification of healthy individuals who will decline and may be useful for selecting at-risk participants for research studies and early interventions. © 2008 American Psychological Association.

publication date

  • July 2008

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1037/0894-4105.22.4.469

PubMed ID

  • 18590359

Additional Document Info

start page

  • 469

end page

  • 484

volume

  • 22

number

  • 4