Dementia diagnoses from clinical and neuropsychological data compared: the Cache County study.
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.
Tschanz
J T
JT
Department of Psychology, College of Family Life, Utah State University, Logan 84322-4440, USA. joannt@cc.usu.edu
Welsh-Bohmer
K A
KA
Skoog
I
I
West
N
N
Norton
M C
MC
Wyse
B W
BW
Nickles
R
R
Breitner
J C
JC
D000368:Aged; D000369:Aged, 80 and over; D003704:Dementia / Q000523:psychology*; D005260:Female; D006801:Humans; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D011569:Psychiatric Status Rating Scales; D012680:Sensitivity and Specificity; D014589:Utah