Progress in Clinical Neurosciences: Treatment of Alzheimer’s Disease and Other Dementias - Review and Comparison of the Cholinesterase Inhibitors
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in older adults. Acceptance of the cholinergic hypothesis led to a search for medications which could enhance central cholinergic activity in this condition. There are now three cholinesterase inhibitors available for the treatment of AD in Canada. OBJECTIVES: To review the currently available cholinesterase inhibitors approved for the treatment of AD in Canada and to provide guidance on who and how to treat with these agents. RESULTS: Donepezil, rivastigmine, and galantamine are approved for the treatment of AD in Canada. In clinical trails, patients with mild to moderate AD treated with these agents experienced modest improvements in cognition, function, behaviour, and/or global clinical state. The magnitude of benefits seen with each agent appeared to be similar. While to date, there is no convincing evidence that one is more efficacious or effective, they do differ in their pharmacokinetics, additional mechanisms of action, and side effect profiles. Therefore, the selection of agent will be based on considerations such as side effect profiles, ease of administration, personal familiarity/experience, and beliefs about the importance of the noted differences in their pharmacokinetics and additional mechanisms of action. CONCLUSION: We believe that these agents should be offered to all individuals with a mild to moderate dementia where Alzheimer's pathology is felt to be a contributing factor. We view all three available cholinesterase inhibitors as first-line drugs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".