Treatment of Delusions in Alzheimer’s Disease – Response to Pharmacotherapy
Bibliographic record
Abstract
Delusions are commonly encountered symptoms in patients with Alzheimer's disease and may lead to significant morbidity. The purpose of this article is to review all clinical trials to date focusing on the management of delusions in patients with Alzheimer's disease to determine the level of evidence for treatment. To achieve this objective, Medline was searched using the key words delusions, dementia, Alzheimer's disease and psychosis. Three main categories of treatment were identified: atypical antipsychotics, cholinesterase inhibitors, and other miscellaneous treatments. It was concluded that all forms of treatment were effective although the greatest burden of evidence existed for risperidone and donepezil. Side effects were noted in all forms of treatment and included somnolence and extrapyramidal effects for antipsychotic medications, whereas gastrointestinal effects were more prevalent in studies involving cholinesterase inhibitors. Further large scale, double-blind, randomized, controlled studies are required before a definitive conclusion can be reached. To our knowledge this is the only systematic review of this area.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".