Effectiveness of Cholinesterase Inhibitors and Memantine for Treating Dementia: Evidence Review for a Clinical Practice Guideline
Bibliographic record
Abstract
BACKGROUND: The effectiveness of the 5 U.S. Food and Drug Administration-approved pharmacologic therapies for dementias in achieving clinically relevant improvements is unclear. PURPOSE: To review the evidence for the effectiveness of cholinesterase inhibitors (donepezil, galantamine, rivastigmine, and tacrine) and the neuropeptide-modifying agent memantine in achieving clinically relevant improvements, primarily in cognition, global function, behavior, and quality of life, for patients with dementia. DATA SOURCES: Cochrane Central Register of Controlled Trials, MEDLINE, PREMEDLINE, EMBASE, Allied and Complementary Medicine Database, CINAHL, AgeLine, and PsycINFO from January 1986 through November 2006. STUDY SELECTION: English-language randomized, controlled trials were included in the review if they evaluated pharmacologic agents for adults with a diagnosis of dementia, did not use a crossover design, and had a quality score of at least 3 on the Jadad scale. DATA EXTRACTION: Data were extracted on study characteristics and outcomes, including adverse events. Effect sizes were calculated and data were combined when appropriate. DATA SYNTHESIS: 96 publications representing 59 unique studies were eligible for this review. Both cholinesterase inhibitors and memantine had consistent effects in the domains of cognition and global assessment, but summary estimates showed small effect sizes. Outcomes in the domains of behavior and quality of life were evaluated less frequently and showed less consistent effects. Most studies were of short duration (6 months), which limited their ability to detect delay in onset or progression of dementia. Three studies directly compared different cholinesterase inhibitors and found no differences in cognition and behavior. LIMITATIONS: Limitations of available studies included short duration, inclusion of only patients with mild to moderate Alzheimer disease, poor reporting of adverse events, lack of clear definitions for statistical significance, limited evaluation of behavior and quality-of-life outcomes, and limited direct comparison of different treatments. CONCLUSIONS: Treatment of dementia with cholinesterase inhibitors and memantine can result in statistically significant but clinically marginal improvement in measures of cognition and global assessment of 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 | 0.027 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".