P728 - LONGITUDINAL BRAIN AGE GAP AND COGNITIVE DECLINE AFTER STROKE (ID 461)
Abstract
Aims
Advanced age is associated with poorer prognosis following stroke. Machine learning based on brain imaging can be used to estimate the age of a patient and compute the difference to chronological age; the brain age gap (BAG). Higher BAG has been found in a range of clinical conditions and has been associated with increased risk of dementia and mortality. Few studies have been conducted on its association with stroke, and the predictive value for post-stroke cognitive decline and dementia is unknown. To this end, using longitudinal data after stroke we tested the hypothesis that cognitive decline after stroke is associated with a higher BAG.
Methods
270 stroke survivors (age = 71.1 (11.0), women = 55.6%) were included from the ‘Norwegian Cognitive Impairment After Stroke (Nor-COAST) study. Clinical-, neuropsychological- and MRI data was collected shortly after the acute stroke and at 18- and 36 months follow-up. Freesurfer anatomical segmentation was conducted, and BAG computed.
Results
Mean (SD) Montreal Cognitive Assessment (MoCA) scores were 24.0 (4.6) at baseline, 24.9 (4.3) at 18 months and 24.6 (5.7) at 36 months. A significant relationship was found with global BAG at baseline and 18 months, and with right hemisphere BAG at 18 months.
Conclusions
We found that a higher global BAG was associated with worse cognition at baseline and 18 months. Higher right hemisphere BAG was also found to be associated with worse cognitive outcome 18 months after a right-sided stroke. These findings suggests that BAG may be used as a predictive marker for cognitive decline after stroke.
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