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
Neurologyjournal_title
Neurologyauthors
Tschanz JT,Welsh-Bohmer KA,Skoog I,West N,Norton MC,Wyse BW,Nickles R,Breitner JCdoi
10.1212/wnl.54.6.1290subject
Has Abstractpub_date
2000-03-28 00:00:00pages
1290-6issue
6eissn
0028-3878issn
1526-632Xjournal_volume
54pub_type
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