Title:Predicting Stability of Mild Cognitive Impairment (MCI): Findings of a Community Based Sample
Volume: 14
Issue: 6
Author(s): Sinika Ellendt, Bianca Voβ, Nils Kohn, Lisa Wagels, Katharina S. Goerlich, Eva Drexler, Frank Schneider and Ute Habel*
Affiliation:
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen,Germany
Keywords:
Mild cognitive impairment (MCI), Alzheimer dementia (AD), cognitive functions, memory, longitudinal survey,
neuropsychology.
Abstract: Background: Mild Cognitive Impairment (MCI) is a risk factor for Alzheimer’s disease (AD)
and other forms of dementia. However, much heterogeneity concerning neuropsychological measures,
prevalence and progression rates impedes distinct diagnosis and treatment implications.
Objective: Aim of the present study was the identification of specific tests providing a high certainty for
stable MCI and factors that precipitate instability of MCI in a community based sample examined at three
measurement points.
Method: 130 participants were tested annually with an extensive test battery including measures of
memory, language, executive functions, intelligence and dementia screening tests. Exclusion criteria at
baseline comprised, severe cognitive deficits (e.g. diagnosis of dementia, psychiatric or neurological
disease). Possible predictors for stability or instability of MCI-diagnosis were analyzed using Regression
and Receiver Operating Characteristic (ROC) curve analysis. Age, IQ and APOE status were tested for
moderating effects on the interaction of test performances and group membership.
Results: A high prevalence of MCI (49%) was observed at baseline with a reversion rate of 18% after
two years. Stability of MCI was related to performances in four measures (VLMT: delayed recall,
CERAD: recall drawings, CERAD: Boston Naming Test, Benton Visual Retention Test: number of mistakes).
Conversion to MCI is associated with language functions. Reversion to ‘normal’ was primarily
predicted by single domain impairment. There was no significant influence of demographic, medical or
genetic variables.
Conclusion: The results highlight the role of repeated measurements for a reliable identification of functional
neuropsychological predictors and better diagnostic reliability. In cases of high uncertainty close
monitoring over time is needed in order of estimating outcome.
