Prazosin for the management of behavioural and psychological symptoms of dementia
Bibliographic record
Abstract
Prazosin, a centrally acting α1 adrenoceptor antagonist, has been included in two published algorithms amongst the list of medications that may be used in the management of behavioural and psychological symptoms of dementia (BPSD). However, a review of PubMed, Ovid and Cochrane Collaboration found that there was only one small published randomized controlled trial (RCT) that evaluated the use of prazosin amongst individuals with BPSD. Evidence from this good quality RCT indicates that prazosin appears to benefit individuals with agitation and aggression amongst individuals with BPSD and this medication is well tolerated. When compared to other treatments for BPSD, including atypical antipsychotics, antidepressants, acetylcholinesterase inhibitors, memantine, repetitive transcranial magnetic stimulation and electroconvulsive therapy, where there are multiple studies for each of these treatment modalities, the data for the use of prazosin for BPSD are limited to just one good quality RCT. Given the limitations in available data, the routine use of prazosin for the treatment of BPSD cannot be recommended at this time. However, prazosin may be used for the management of agitation and aggression amongst individuals with dementia when other medication classes, like acetylcholinesterase inhibitors, memantine, antidepressants and/or atypical antipsychotics, have been ineffective or not tolerated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".