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dc.date.accessioned2023-02-17T19:00:36Z
dc.date.available2023-02-17T19:00:36Z
dc.date.created2023-01-31T12:03:07Z
dc.date.issued2022
dc.identifier.citationAamodt, Eva Birgitte Alnæs, Dag de Lange, Ann-Marie Glasø Aam, Stina Schellhorn, Till Saltvedt, Ingvild Tina Beyer, Mona Kristiansen Westlye, Lars Tjelta . Longitudinal brain age prediction and cognitive function after stroke. Neurobiology of Aging. 2022, 122, 55-64
dc.identifier.urihttp://hdl.handle.net/10852/100135
dc.description.abstractAdvanced age is associated with post-stroke cognitive decline. Machine learning based on brain scans can be used to estimate brain age of patients, and the corresponding difference from chronological age, the brain age gap (BAG), has been investigated in a range of clinical conditions, yet not thoroughly in post-stroke neurocognitive disorder (NCD). We aimed to investigate the association between BAG and post-stroke NCD over time. Lower BAG (younger appearing brain compared to chronological age) was found associated with lower risk of post-stroke NCD up to 36 months after stroke, even among those showing no evidence of impairments 3 months after hospital admission. For patients with no NCD at baseline, survival analysis suggested that higher baseline BAG was associated with higher risk of post-stroke NCD at 18 and 36 months. In conclusion, a younger appearing brain is associated with a lower risk of post-stroke NCD.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleLongitudinal brain age prediction and cognitive function after stroke
dc.title.alternativeENEngelskEnglishLongitudinal brain age prediction and cognitive function after stroke
dc.typeJournal article
dc.creator.authorAamodt, Eva Birgitte
dc.creator.authorAlnæs, Dag
dc.creator.authorde Lange, Ann-Marie Glasø
dc.creator.authorAam, Stina
dc.creator.authorSchellhorn, Till
dc.creator.authorSaltvedt, Ingvild Tina
dc.creator.authorBeyer, Mona Kristiansen
dc.creator.authorWestlye, Lars Tjelta
cristin.unitcode185,53,0,0
cristin.unitnameInstitutt for klinisk medisin
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin2119841
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Neurobiology of Aging&rft.volume=122&rft.spage=55&rft.date=2022
dc.identifier.jtitleNeurobiology of Aging
dc.identifier.volume122
dc.identifier.startpage55
dc.identifier.endpage64
dc.identifier.doihttps://doi.org/10.1016/j.neurobiolaging.2022.10.007
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0197-4580
dc.type.versionPublishedVersion


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