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

Abstract:

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.

journal_name

Neurology

journal_title

Neurology

authors

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

doi

10.1212/wnl.54.6.1290

subject

Has Abstract

pub_date

2000-03-28 00:00:00

pages

1290-6

issue

6

eissn

0028-3878

issn

1526-632X

journal_volume

54

pub_type

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