dc.date.accessioned | 2023-02-17T19:00:36Z | |
dc.date.available | 2023-02-17T19:00:36Z | |
dc.date.created | 2023-01-31T12:03:07Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Aamodt, 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.uri | http://hdl.handle.net/10852/100135 | |
dc.description.abstract | Advanced 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.language | EN | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | Longitudinal brain age prediction and cognitive function after stroke | |
dc.title.alternative | ENEngelskEnglishLongitudinal brain age prediction and cognitive function after stroke | |
dc.type | Journal article | |
dc.creator.author | Aamodt, Eva Birgitte | |
dc.creator.author | Alnæs, Dag | |
dc.creator.author | de Lange, Ann-Marie Glasø | |
dc.creator.author | Aam, Stina | |
dc.creator.author | Schellhorn, Till | |
dc.creator.author | Saltvedt, Ingvild Tina | |
dc.creator.author | Beyer, Mona Kristiansen | |
dc.creator.author | Westlye, Lars Tjelta | |
cristin.unitcode | 185,53,0,0 | |
cristin.unitname | Institutt for klinisk medisin | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 2119841 | |
dc.identifier.bibliographiccitation | info: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.jtitle | Neurobiology of Aging | |
dc.identifier.volume | 122 | |
dc.identifier.startpage | 55 | |
dc.identifier.endpage | 64 | |
dc.identifier.doi | https://doi.org/10.1016/j.neurobiolaging.2022.10.007 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 0197-4580 | |
dc.type.version | PublishedVersion | |