Outcomes of Alzheimer's disease therapy with acetylcholinesterase inhibitors and memantine
Bibliographic record
Abstract
INTRODUCTION: Alzheimer's disease (AD) is a world-wide health problem with implications for an increasing number of people and countries. Populations suffering from AD financially strain the healthcare budgets of rich and poor countries alike. Moreover, no effective treatment is available and current drugs merely slow the progression of cognitive function deterioration and overall health status toward an inevitable end point. An increasing number of novel approaches have been tested in numerous clinical trials, but none of them has proved safe and effective for treating AD. AREAS COVERED: This review summarizes all currently available compounds (donepezil, rivastigmine, galantamine, memantine) for the management of AD, concentrating on clinical aspects such as the mechanisms of action, pharmacokinetics, pharmacodynamics and clinical trials. This review also considers the mechanisms and side effects to provide perspective on current treatment options. EXPERT OPINION: Novel approaches in the treatment of AD are being intensively tested, but so far without any major success. Patients diagnosed with AD still mostly benefit from four compounds to significantly improve cognition functions and overall health and help manage other symptoms or even prolong the symptom-free period.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".