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Journal of Korean Geriatric Psychiatry ; : 68-74, 2016.
Artigo em Coreano | WPRIM | ID: wpr-67359

RESUMO

OBJECTIVE: The present study investigated the clinical characteristics of Alzheimer's disease (AD) dementia with low brain amyloid-beta (Aβ-AD) burden comparing with AD dementia with high amyloid-beta burden (Aβ+AD). We also developed a prediction model for the amyloid positivity on ¹¹C-labelled Pittsburgh Compound B (PiB) positron emission tomography (PET) with distinct clinical variables in AD dementia patients. METHODS: Fifty-nine clinically defined AD dementia individuals, who participated in the Korean Brain Aging Study for Early diagnosis and prediction of AD (KBASE) study, were included. All the subjects received comprehensive clinical evaluations and PiB-PET. Based on cerebral PiB retention, all subjects were divided into Aβ+AD (n=47) and Aβ-AD (n=12) subgroups. To develop a prediction model for amyloid positivity, stepwise multiple logistic regression analysis was conducted. RESULTS: When compared to Aβ+AD, Aβ-AD showed older age, later age-at-onset, and lower education. In regard of risk factors for dementia, Aβ-AD had higher frequency of hypertension and diabetes mellitus as well as lower frequency of apolipoprotein E (APOE) ε4 allele. Although there was no between group difference in Clinical Dementia Rating (CDR) or CDR sum-of-boxes scores, mini-mental state examination and constructional recall scores were higher for Aβ-AD than Aβ+AD. The final amyloid positivity prediction model included APOE4 genotype, hypertension, and diabetes mellitus. CONCLUSION: The findings from this study indicated that clinically diagnosed AD dementia may have high possibility of not being pathological AD if they have older age and higher vascular risks, and did not have APOE4 genotype.


Assuntos
Humanos , Idade de Início , Envelhecimento , Alelos , Doença de Alzheimer , Amiloide , Apolipoproteína E4 , Apolipoproteínas , Encéfalo , Demência , Diabetes Mellitus , Diagnóstico Precoce , Educação , Genótipo , Hipertensão , Modelos Logísticos , Tomografia por Emissão de Pósitrons , Fatores de Risco
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