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Diagnosing mild cognitive impairment – a data-driven approach

Published online by Cambridge University Press:  24 June 2014

N Kochan ,
P Sachdev ,
J Trollor ,
H Brodaty  and
M Slavin
N Kochan
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
P Sachdev
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
J Trollor
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
H Brodaty
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
M Slavin
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
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Abstract

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Type
Abstracts from ‘Brainwaves’— The Australasian Society for Psychiatric Research Annual Meeting 2006, 6–8 December, Sydney, Australia
Information
Acta Neuropsychiatrica , Volume 18 , Issue 6 , December 2006 , pp. 257
Copyright
Copyright © 2006 Blackwell Munksgaard

Background:

There has been increasing research interest in the concept of mild cognitive impairment (MCI) as a prodrome to Alzheimer's disease and other dementias. Several diagnostic schemas have been proposed with a central feature being the presence of cognitive impairment in one or more domains. But how should cognitive impairment be determined? Which tests, how many and what cut-offs should be used? The current study uses a data-driven approach to determine patterns of healthy cognitive functioning and impairment in a community sample of older adults.

Methods:

Four hundred adults aged 70–90 years completed a comprehensive neuropsychological assessment as part of the Memory and Ageing Study, Sydney.

Results:

Prevalence of cognitive impairment across the domains of memory, language, psychomotor speed, visuospatial and frontal-executive functions varied considerably when different sources of normative data, demographic corrections, cut-scores and clusters of tests were applied.

Conclusions:

MCI is a very difficult construct to define at an individual and group level. This study provides much needed normative neuropsychological data in an Australian older adult sample. Longitudinal data will inform us about the most sensitive and specific neuropsychological profile that will predict those who progress to dementia.