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Predicting progression to dementia in persons with mild cognitive impairment using cerebrospinal fluid markers
Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg, School for Mental Health and Neurosciences, Maastricht University, Maastricht, The Netherlands.
Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg, School for Mental Health and Neurosciences, Maastricht University, Maastricht, The Netherlands.
Department of Neurology, Ljubljana University Medical Centre, Ljubljana, Slovenia.
Division of Clinical Geriatrics, Department of NVS, Karolinska Institutet, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden.
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2017 (English)In: Alzheimer's & Dementia: Journal of the Alzheimer's Association, ISSN 1552-5260, E-ISSN 1552-5279, Vol. 13, no 8, p. 903-912Article in journal (Refereed) Published
Abstract [en]

INTRODUCTION: We aimed to determine the added value of cerebrospinal fluid (CSF) to clinical and imaging tests to predict progression from mild cognitive impairment (MCI) to any type of dementia.

METHODS: The risk of progression to dementia was estimated using two logistic regression models based on 250 MCI participants: the first included standard clinical measures (demographic, clinical, and imaging test information) without CSF biomarkers, and the second included standard clinical measures with CSF biomarkers.

RESULTS: Adding CSF improved predictive accuracy with 0.11 (scale from 0-1). Of all participants, 136 (54%) had a change in risk score of 0.10 or higher (which was considered clinically relevant), of whom in 101, it was in agreement with their dementia status at follow-up.

DISCUSSION: An individual person's risk of progression from MCI to dementia can be improved by relying on CSF biomarkers in addition to recommended clinical and imaging tests for usual care.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 13, no 8, p. 903-912
Keywords [en]
Alzheimer's disease, Conversion, Dementia, Mild cognitive impairment, Predict, Prognosis, Progression, Reclassification, Risk, Risk prediction model
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Neurology
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URN: urn:nbn:se:oru:diva-74059DOI: 10.1016/j.jalz.2016.12.015ISI: 000407041800007PubMedID: 28216393Scopus ID: 2-s2.0-85014793039OAI: oai:DiVA.org:oru-74059DiVA, id: diva2:1313971
Available from: 2019-05-07 Created: 2019-05-07 Last updated: 2023-03-28Bibliographically approved

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Freund-Levi, Yvonne

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