Critical appraisal of the long-term impact of memantine in treatment of moderate to severe Alzheimer’s disease
Bibliographic record
Abstract
Critical appraisal of the long-term impact of memantine in treatment of moderate to severe Alzheimer’s disease Umamon Puangthong, Ging-Yuek Robin HsiungDivision of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, CanadaAbstract: Alzheimer’s disease is the most common cause of dementia in older adults. The clinical features include progressive memory decline as well as cognitive deficits with executive dysfunction, language, visual perceptual difficulties, apraxia and agnosia. During the moderate to severe stage of the disease, there is a major decline in memory and function, while neuropsychiatric disturbances often emerge and patients become difficult to manage. These distressing symptoms increase caregiver burden and add to the direct costs of care of the patients. Any improvements in patient function and behavioral symptoms can reduce caregiver burden. Memantine has been available for a number of years in Europe and in North America. In this article, we examine the pharmacological rationale for its use, and the current clinical evidence for its efficacy and long-term effectiveness in the management of cognitive and behavioral symptoms in moderate to severe stages of Alzheimer’s disease.Keywords: memantine, Alzheimer’s disease, dementia
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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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| 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".