Mild Cognitive impairment Healthy adult volunteers
Conditions
Interventions
None listed
Sponsors
Oita University
Eisai Co., Ltd.
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: Subjects of this study are participants in Usuki Cohort (the cohort of local elderly residents in Usuki City, Oita Prefecture) and those who visited Oita University Hospital, and they meet all the following inclusion criteria. 1. MCI who fulfilled the diagnostic criteria of Petersen (CDR 0.5), or healthy adult volunteers who did not fulfill the diagnostic criteria of Petersen (CDR 0). 2. Subjects undergone amyloid PET ([11C]PiB: Pittsburgh compound-B) testing.
Exclusion criteria
Exclusion criteria: Subjects of this study are participants in Usuki Cohort (the cohort of local elderly residents in Usuki City, Oita Prefecture) and those who visited Oita University Hospital, and they meet all the following inclusion criteria. 1. Subjects with some missing data. 2. Subjects who have stated their willingness to participate in the research. 3. Any other subjects who are judged to be ineligible by the principal investigator or sub-investigator.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| To construct a prediction model for the presence or absence of Amyloid-beta accumulation in the brain using machine learning based on clinical information (variables) collected retrospectively, and to evaluate its prediction accuracy. | — |
Countries
Japan
Contacts
Public ContactNoriyuki Kimura
Oita University Faculty of Medicine Department of Neurology
Outcome results
None listed