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Combining Cognitive Markers to Identify Individuals at Increased Dementia Risk : Influence of Modifying Factors and Time to Diagnosis

Payton, Nicola M. (author)
Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
Rizzuto, Debora (author)
Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
Fratiglioni, Laura (author)
Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
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Kivipelto, Miia (author)
Karolinska Institutet
Bäckman, Lars (author)
Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
Laukka, Erika J. (author)
Karolinska Institutet,Stockholms universitet,Centrum för forskning om äldre och åldrande (ARC), (tills m KI)
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 (creator_code:org_t)
2020
2020
English.
In: Journal of the International Neuropsychological Society. - 1355-6177 .- 1469-7661. ; 26:8, s. 785-797
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Objective: We investigated the extent to which combining cognitive markers increases the predictive value for future dementia, when compared to individual markers. Furthermore, we examined whether predictivity of markers differed depending on a range of modifying factors and time to diagnosis. Method: Neuropsychological assessment was performed for 2357 participants (60þ years) without dementia from the population-based Swedish National Study on Aging and Care in Kungsholmen. In the main sample analyses, the outcome was dementia at 6 years. In the time-todiagnosis analyses, a subsample of 407 participants underwent cognitive testing 12, 6, and 3 years before diagnosis, with dementia diagnosis at the 12-year follow-up. Results: Category fluency was the strongest individual predictor of dementia 6 years before diagnosis [area under the curve (AUC) = .903]. The final model included tests of verbal fluency, episodic memory, and perceptual speed (AUC = .913); these three domains were found to be the most predictive across a range of different subgroups. Twelve years before diagnosis, pattern comparison (perceptual speed) was the strongest individual predictor (AUC = .686). However, models 12 years before diagnosis did not show significantly increased predictivity above that of the covariates. Conclusions: This study shows that combining markers from different cognitive domains leads to increased accuracy in predicting future dementia 6 years later. Markers from the verbal fluency, episodic memory, and perceptual speed domains consistently showed high predictivity across subgroups stratified by age, sex, education, apolipoprotein E ϵ4 status, and dementia type. Predictivity increased closer to diagnosis and showed highest accuracy up to 6 years before a dementia diagnosis.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Neurosciences (hsv//eng)

Keyword

Prediction
Preclinical dementia
Alzheimer's disease
Cognition
Population-based
Longitudinal

Publication and Content Type

ref (subject category)
art (subject category)

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