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Factors and brain imaging features associated with cognition in oldest-old patients with Alzheimer-type dementia
Haruo Hanyu1, Yumi Koyama2, Kazuki Umekida2
1Dementia Research Center, Tokyo General Hospital, Tokyo, Japan; Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan.
Background:
The underlying pathophysiology of cognitive dysfunction in oldest-old patients with Alzheimer-type dementia (AD) has not been clarified to date. We aimed to determine the factors and brain imaging features associated with cognition in oldest-old patients with AD.
Methods:
We enrolled 456 consecutive outpatients with probable AD (145 men and 311 women, age range: 51-95 years). Demographic factors, such as education level, disease duration at initial visit, body mass index, comorbidities, frailty, and leisure activity, and brain imaging features, including severity of medial temporal lobe (MTL) atrophy, white matter lesions and infarcts, and frequency of posterior cerebral hypoperfusion were compared among pre-old (≤ 74 years), old (75 to 84 years), and oldest-old (≥ 85 years) subgroups.
Results:
The oldest-old subgroup showed significantly longer disease duration, lower education level, more severe frailty, less leisure activity, worse cognitive impairment, a tendency of slower progression of cognitive decline, greater MTL atrophy, more severe white matter hyperintensities and infarcts, and lower frequency of posterior hypoperfusion than the younger age subgroups. Regarding the brain imaging subtypes, there were significantly more patients with the limbic-predominant subtype and fewer patients with the hippocampal-sparing subtype in the oldest-old AD group than the pre-old AD group.
Conclusions:
Oldest-old patients with AD show different factors and brain imaging features associated with cognition from pre-old and old patients. Our results are expected to provide useful information towards understanding the pathophysiology of oldest-old patients with AD, and for determining their clinical diagnosis and appropriate management methods.
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