Dementia diagnoses from clinical and neuropsychological data compared: the Cache County study.

Journal Article (Journal Article)

OBJECTIVE: To validate a neuropsychological algorithm for dementia diagnosis. METHODS: We developed a neuropsychological algorithm in a sample of 1,023 elderly residents of Cache County, UT. We compared algorithmic and clinical dementia diagnoses both based on DSM-III-R criteria. The algorithm diagnosed dementia when there was impairment in memory and at least one other cognitive domain. We also tested a variant of the algorithm that incorporated functional measures that were based on structured informant reports. RESULTS: Of 1,023 participants, 87% could be classified by the basic algorithm, 94% when functional measures were considered. There was good concordance between basic psychometric and clinical diagnoses (79% agreement, kappa = 0.57). This improved after incorporating functional measures (90% agreement, kappa = 0.76). CONCLUSIONS: Neuropsychological algorithms may reasonably classify individuals on dementia status across a range of severity levels and ages and may provide a useful adjunct to clinical diagnoses in population studies.

Full Text

Duke Authors

Cited Authors

  • Tschanz, JT; Welsh-Bohmer, KA; Skoog, I; West, N; Norton, MC; Wyse, BW; Nickles, R; Breitner, JC

Published Date

  • March 28, 2000

Published In

Volume / Issue

  • 54 / 6

Start / End Page

  • 1290 - 1296

PubMed ID

  • 10746600

International Standard Serial Number (ISSN)

  • 0028-3878

Digital Object Identifier (DOI)

  • 10.1212/wnl.54.6.1290


  • eng

Conference Location

  • United States