메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Objective: The Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (KBASE) aimed to recruit 650 individuals, aged from 20 to 90 years, to search for new biomarkers of Alzheimer’s disease (AD) and to investigate how multi-faceted lifetime experiences and bodily changes contribute to the brain changes or brain pathologies related to the AD process. Methods: All participants received comprehensive clinical and neuropsychological evaluations, multi-modal brain imaging, including magnetic resonance imaging, magnetic resonance angiography, [11C]Pittsburgh compound B-positron emission tomography (PET), and [18F]fluorodeoxyglucose-PET, blood and genetic marker analyses at baseline, and a subset of participants underwent actigraph monitoring and completed a sleep diary. Participants are to be followed annually with clinical and neuropsychological assessments, and biannually with the full KBASE assessment, including neuroimaging and laboratory tests. Results: As of March 2017, in total, 758 individuals had volunteered for this study. Among them, in total, 591 participants–291 cognitively normal (CN) old-aged individuals, 74 CN young- and middle-aged individuals, 139 individuals with mild cognitive impairment (MCI), and 87 individuals with AD dementia (ADD)–were enrolled at baseline, after excluding 162 individuals. A subset of participants (n=275) underwent actigraph monitoring. Conclusion: The KBASE cohort is a prospective, longitudinal cohort study that recruited participants with a wide age range and a wide distribution of cognitive status (CN, MCI, and ADD) and it has several strengths in its design and methodologies. Details of the recruitment, study methodology, and baseline sample characteristics are described in this paper.

목차

등록된 정보가 없습니다.

참고문헌 (26)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0