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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Development of screening guidelines and clinical criteria for predementia Alzheimer's disease. The DESCRIPA Study
P J Visser1, F R J Verhey, M Boada
1Department of Psychiatry and Neuropsychology, University of Maastricht, Maastricht, The Netherlands. pj.visser@np.unimaas.nl
Background:
There is an urgent need to identify subjects with Alzheimer's disease (AD) in the predementia phase, but validated diagnostic approaches are currently lacking. In this paper, we present the background, design and methods of a study, which aims to develop clinical criteria for predementia AD. We also present baseline characteristics of the subjects included. The study was part of the multicentre DESCRIPA project, which is being conducted within the network of the European Alzheimer's Disease Consortium.
Methods:
Clinical criteria will be based on a prospective cohort study of non-demented subjects older than 55 years and referred to a memory clinic. At baseline, a number of markers and risk factors for AD were collected, including demographic variables, measures of performance in activities of daily living, cognitive, neuroimaging and genetic markers, and serum and cerebrospinal fluid markers. Subjects will be reassessed annually for 2-3 years, and we will evaluate which combination of variables best predicts AD-type dementia at follow-up.
Results:
Between 2003 and 2005, 881 subjects were included from 20 memory clinics. Subjects were on average 70.3 years old, and had 10.4 years of education. The average score on the Mini-Mental State Examination was 27.4.
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