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Combining Cognitive...
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Payton, Nicola M.Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
(author)
Combining Cognitive, Genetic, and Structural Neuroimaging Markers to Identify Individuals with Increased Dementia Risk
- Article/chapterEnglish2018
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LIBRIS-ID:oai:DiVA.org:su-158210
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https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-158210URI
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https://doi.org/10.3233/JAD-180199DOI
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http://kipublications.ki.se/Default.aspx?queryparsed=id:138564934URI
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Background: Cognitive and biological markers have shown varying degrees of success in identifying persons who will develop dementia. Objective: To evaluate different combinations of cognitive and biological markers and identify prediction models with the highest accuracy for identifying persons with increased dementia risk. Methods: Neuropsychological assessment, genetic testing (apolipoprotein E - APOE), and structural magnetic resonance imaging (MRI) were performed for 418 older individuals without dementia (60-97 years) from a population-based study (SNAC-K). Participants were followed for six years. Results: Cognitive, genetic, and MRI markers were systematically combined to create prediction models for dementia at six years. The most predictive individual markers were perceptual speed or carrying at least one APOE epsilon 4 allele (AUC = 0.875). The most predictive model (AUC = 0.924) included variables from all three modalities (category fluency, general knowledge, any epsilon 4 allele, hippocampal volume, white matter-hyperintensity volume). Conclusion: This study shows that combining markers within and between modalities leads to increased predictivity for future dementia. However, minor increases in predictive value should be weighed against the cost of additional tests in larger-scale screening.
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Kalpouzos, GregoriaKarolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
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Rizzuto, DeboraKarolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
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Fratiglioni, LauraKarolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI),Stockholm Gerontology Research Center, Sweden
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Kivipelto, MiiaKarolinska Institutet
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Bäckman, LarsKarolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
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Laukka, Erika J.Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI),Stockholm Gerontology Research Center, Sweden
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Stockholms universitetCentrum för forskning om äldre och åldrande (ARC), (tills m KI)
(creator_code:org_t)
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In:Journal of Alzheimer's Disease64:2, s. 533-5421387-28771875-8908
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