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Dual-Task Tests Predict Conversion to Dementia-A Prospective Memory-Clinic-Based Cohort Study
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2020 (English)In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 17, no 21, article id E8129Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to investigate whether Timed Up-and-Go (TUG) dual-task (TUGdt) tests predict dementia incidence among patients with subjective or mild cognitive impairment (SCI; MCI). Other study objectives were to determine whether TUGdt improves dementia prediction compared to a) demographic characteristics and standard cognitive tests alone; and b) TUG and Verbal Fluency performed separately. Patients (n = 172, age range 39-91 years, 78 women) with SCI or MCI performed TUGdt tests, including 1) naming animals and 2) reciting months backwards, and clinical cognitive tests at baseline. Diagnoses were identified at follow-up after 2.5 years. Logistic regression was used to predict dementia incidence, receiver operating characteristic (ROC) curves and c-statistics for predictive capacity. Analyses were stratified by age and gender. At follow-up, 51 patients had developed dementia. The TUGdt result "animals/10 s" was associated with dementia incidence (standardized odds ratio (OR) = 4.06, 95% confidence interval (CI) 2.28-7.23, p < 0.001), more so among patients under the median age of 72 years (standardized OR = 19.4, 95% CI 3.53-106.17, p < 0.001). TUGdt "animals/10 s" improved dementia prediction compared to demographic characteristics and standard tests alone (c-statistics 0.88 to 0.94) and single-task tests (c-statistics 0.86 to 0.89), but only in the younger patient group. TUGdt has the potential to become a useful tool for dementia prediction.

Place, publisher, year, edition, pages
2020. Vol. 17, no 21, article id E8129
Keywords [en]
dementia, dual-task, gait, mild cognitive impairment, subjective cognitive impairment
National Category
Health Sciences
Research subject
Research Profiles 2009-2020, Health and Welfare
Identifiers
URN: urn:nbn:se:du-35496DOI: 10.3390/ijerph17218129ISI: 000588987600001PubMedID: 33153203Scopus ID: 2-s2.0-85095567633OAI: oai:DiVA.org:du-35496DiVA, id: diva2:1503825
Available from: 2020-11-25 Created: 2020-11-25 Last updated: 2025-03-12Bibliographically approved

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McKee, KevinÅberg, Anna Cristina

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf