Bibliographic record
Abstract
OBJECTIVE: The objective of this paper is to review the randomized controlled trials (RCTs) on the pharmacotherapy of Alzheimer's disease and other dementias and to provide evidence-based recommendations for treatment of the cognitive impairment associated with these disorders. METHOD: A Medline search was conducted for RCTs, using the following key words: Alzheimer's disease, dementia, therapy, cholinesterase inhibitor, donepezil, rivastigmine, and galantamine. Studies were critically appraised, followed by a review of published major clinical practice guidelines. Recommendations for treatment were made based on best available evidence. RESULTS: The pharmacotherapy of Alzheimer's disease should include the meticulous management of vascular risk factors (for example, hypertension, diabetes, cholesterol, and stroke prophylaxis) and consideration for supplementation with folate, vitamin B complex, and vitamin E. Patients should be offered at least 1 trial of a cholinesterase inhibitor, with the possibility of another trial if the first is poorly tolerated or ineffective. Patients with vascular dementia and dementia with Lewy bodies should also be offered treatment with cholinesterase inhibitors. At this time, we lack sufficient data to recommend the use of hormone replacement or antiinflammatory therapy for treatment of dementia as the primary indication. CONCLUSION: Reasonable evidence exists to provide recommendations for the pharmacotherapy of dementia. Treatment will likely result in modest but important benefits to patients, caregivers, and society.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".