Efficacy and safety of cognitive enhancers for patients with mild cognitive impairment: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Cognitive enhancers, including cholinesterase inhibitors and memantine, are used to treat dementia, but their effectiveness for mild cognitive impairment is unclear. We conducted a systematic review to examine the efficacy and safety of cognitive enhancers for mild cognitive impairment. METHODS: Our eligibility criteria were studies of the effects of donepezil, rivastigmine, galantamine or memantine on mild cognitive impairment reporting cognition, function, behaviour, global status, and mortality or harms. We identified relevant material by searching electronic databases (e.g., MEDLINE, Embase), the references of included studies, trial registries and conference proceedings, and by contacting experts. Two reviewers independently screened the results of the literature search, abstracted data and appraised risk of bias using the Cochrane risk-of-bias tool. RESULTS: We screened 15,554 titles and abstracts and 1384 full-text articles. Eight randomized clinical trials and 3 companion reports met our inclusion criteria. We found no significant effects of cognitive enhancers on cognition (Mini-Mental State Examination: 3 randomized clinical trials [RCTs], mean difference [MD] 0.14, 95% confidence interval [CI] -0.22 to 0.50; Alzheimer's Disease Assessment Scale - cognition subscale: 3 RCTs, standardized MD -0.07, 95% CI-0.16 to 0.01]) or function (Alzheimer's Disease Cooperative Study activities of daily living inventory: 2 RCTs, MD 0.30, 95% CI -0.26 to 0.86). Cognitive enhancers were associated with higher risks of nausea, diarrhea and vomiting than placebo. INTERPRETATION: Cognitive enhancers did not improve cognition or function among patients with mild cognitive impairment and were associated with a greater risk of gastrointestinal harms. Our findings do not support the use of cognitive enhancers for mild cognitive impairment.
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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".