Review: donepezil improves cognitive and global function in people with mild to moderate Alzheimer’s disease
Bibliographic record
Abstract
Whitehead A, Perdomo C, Pratt RD, et al . Donepezil for the symptomatic treatment of patients with mild to moderate Alzheimer’s disease: a meta-analysis of individual patient data from randomised controlled trials. Int J Geriatr Psychiatry 2004;19:624–33.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Does donepezil improve cognitive and global function in people with mild to moderate Alzheimer’s disease? ### ![Graphic][5]</img>Design: Systematic review with meta-analysis. ### ![Graphic][6]</img>Data sources: Studies were identified using the Eisai Inc database and from scientific literature searches (search dates not stated). ### ![Graphic][7]</img>Study selection and analysis: Eligible studies were randomised controlled trials comparing donepezil versus placebo in people with mild to moderate Alzheimer’s disease (MMSE criteria). Trials were undertaken and completed by 20 December 1999. Exclusions: not stated. Data were extracted for each individual study on the efficacy and safety of donepezil. Meta-analysis was carried out using fixed and random effects models, and results were tested for statistical heterogeneity. ### ![Graphic][8]</img>Outcomes: Change in cognitive status (Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog)); improvement in global function (Clinician’s … [1]: {openurl}?query=rft.jtitle%253DInternational%2Bjournal%2Bof%2Bgeriatric%2Bpsychiatry%26rft.stitle%253DInt%2BJ%2BGeriatr%2BPsychiatry%26rft.aulast%253DWhitehead%26rft.auinit1%253DA.%26rft.volume%253D19%26rft.issue%253D7%26rft.spage%253D624%26rft.epage%253D633%26rft.atitle%253DDonepezil%2Bfor%2Bthe%2Bsymptomatic%2Btreatment%2Bof%2Bpatients%2Bwith%2Bmild%2Bto%2Bmoderate%2BAlzheimer%2527s%2Bdisease%253A%2Ba%2Bmeta-analysis%2Bof%2Bindividual%2Bpatient%2Bdata%2Bfrom%2Brandomised%2Bcontrolled%2Btrials.%26rft_id%253Dinfo%253Adoi%252F10.1002%252Fgps.1133%26rft_id%253Dinfo%253Apmid%252F15254918%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1002/gps.1133&link_type=DOI [3]: /lookup/external-ref?access_num=15254918&link_type=MED&atom=%2Febmental%2F8%2F1%2F15.atom [4]: /lookup/external-ref?access_num=000222516600002&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".