Systematic Review of Cholinesterase Inhibitors on Cognition and Behavioral Symptoms in Patients of Chinese Descent with Alzheimer’s Disease, Vascular Dementia, or Mixed Dementia
Bibliographic record
Abstract
Cholinesterase inhibitors (ChEIs) are the primary pharmacologic treatment for dementia. Their efficacy in patients of Chinese descent is not well described. We reviewed how ChEIs could affect cognition and behavioral and psychological symptoms (BPSD) in Chinese patients with Alzheimer's disease (AD), vascular dementia (VaD), or mixed (AD with vascular component) dementia. MEDLINE, PsycINFO, EMBASE and CINAHL were systematically searched for controlled trials of ChEIs, including donepezil, galantamine, and rivastigmine, for Chinese patients with AD, VaD, or mixed dementia. Outcomes for cognition and BPSD were extracted for discussion. Fifty-four studies were identified. While one larger study found that dementia patients of Chinese descent treated with ChEIs had significantly higher mean Mini-Mental State Examination (MMSE) score, other studies showed no significant difference. Evidence on BPSD after use of ChEIs was also conflicting. ChEIs may be effective in improving cognition among patients of Chinese descent with dementia. Further studies are needed to examine the possible effects of ChEIs on BPSD in Chinese patients with dementia in view of the small number of studies and limitations in their methodologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".