PUMCH Dementia Longitudinal Cohort Study

In China, the burden of dementia is increasing, which has a major impact on medical care, society, and the economy. In order to solve this important public health problem, a cohort study of cognitive impairment in the elderly should be carried out. We designed an age stratified dementia cohort and tried to to clarify the risk and prognostic factors, disease characteristics, cognitive evaluation, biomarkers, diagnosis, treatment of dementia and its subtypes in China. It is of great significance to establish a relatively comprehensive dementia database, improve the level of clinical diagnosis and treatment of cognitive impairment, and formulate prevention and treatment strategies for dementia. Baseline data collection and cohort establishing: Detailed clinical information including demographic data, clinical history, past history and physical examination are collected. Formatted neuropsychological battery is used in all patients, including screening tests (MMSE, MoCA-PUMCH, ADL, HAD) and domain specific evaluation (Memory, executive function, visual spatial, calculation, language). Samples including serum, CSF, urine, skin, saliva are stored. Every patient is followed up every 6 months. Autopsy brain tissue will be collected if patients died. The main contents of this study are following: 1. Explore the relationship between lifestyles, stress and dementia. 2. Assess risk factors for dementia. 3. Evaluating behavioral and psychological symptoms of dementia. 4. Improve the long-term follow-up cohort stratified by age and dementia type and construct the high standard information and sample bank. 5. Explore biomarkers of different groups of dementia, incorporating neuropsychology, multi-model neuroimaging, metabolics and proteomics based fluid biomarkers as well as genetic biomarkers. Autopsy after clinical follow up help to verify the biomarkers. 6. Establish and promote standardized and consistent biomarker detection methods. 7. Dementia education and training. 8. Use machine learning methods to establish computer-assisted dementia diagnosis system and evaluation system. Establish prediction models for the progression of dementia.